%0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e66321 %T Online Safety When Considering Self-Harm and Suicide-Related Content: Qualitative Focus Group Study With Young People, Policy Makers, and Social Media Industry Professionals %A La Sala,Louise %A Sabo,Amanda %A Michail,Maria %A Thorn,Pinar %A Lamblin,Michelle %A Browne,Vivienne %A Robinson,Jo %+ Orygen, 35 Poplar Road, Parkville, 3052, Australia, 61 3 9966 9512, louise.lasala@orygen.org.au %K young people %K suicide prevention %K self-harm %K social media %K online safety %K policy %D 2025 %7 10.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Young people are disproportionately impacted by self-harm and suicide, and concerns exist regarding the role of social media and exposure to unsafe content. Governments and social media companies have taken various approaches to address online safety for young people when it comes to self-harm and suicide; however, little is known about whether key stakeholders believe current approaches are fit-for-purpose. Objective: From the perspective of young people, policy makers and professionals who work within the social media industry, this study aimed to explore (1) the perceived challenges and views regarding young people communicating on social media about self-harm and suicide, and (2) what more social media companies and governments could be doing to address these issues and keep young people safe online. Methods: This qualitative study involved 6 focus groups with Australian young people aged 12-25 years (n=7), Australian policy makers (n=14), and professionals from the global social media industry (n=7). Framework analysis was used to summarize and chart the data for each stakeholder group. Results: In total, 3 primary themes and six subthemes are presented: (1) challenges and concerns, including the reasons for, and challenges related to, online communication about self-harm and suicide as well as reasoning with a deterministic narrative of harm; (2) roles and responsibilities regarding online safety and suicide prevention, including who is responsible and where responsibility starts and stops, as well as the need for better collaborations; and (3) future approaches and potential solutions, acknowledging the limitations of current safety tools and policies, and calling for innovation and new ideas. Conclusions: Our findings highlight tensions surrounding roles and responsibilities in ensuring youth online safety and offer perspectives on how social media companies can support young people discussing self-harm and suicide online. They also support the importance of cross-industry collaborations and consideration of social media in future suicide prevention solutions intended to support young people. %M 40063940 %R 10.2196/66321 %U https://www.jmir.org/2025/1/e66321 %U https://doi.org/10.2196/66321 %U http://www.ncbi.nlm.nih.gov/pubmed/40063940 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e64672 %T Health Information Scanning and Seeking in Diverse Language, Cultural and Technological Media Among Latinx Adolescents: Cross-Sectional Study %A DuPont-Reyes,Melissa J %A Villatoro,Alice P %A Tang,Lu %+ , Departments of Sociomedical Sciences and Epidemiology, Columbia University Irving Medical Center, 722 West 168th Street, Room 942, New York, NY, 10032, United States, 1 212 305 0120, md3027@cumc.columbia.edu %K adolescent behaviors %K mental health %K Latino %K social media %K adolescent %K media use %K internet use %K health information seeking %K health information scanning %K mobile phone %D 2025 %7 5.3.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: Continuous scientific and policy debate regarding the potential harm and/or benefit of media and social media on adolescent health has resulted, in part, from a deficiency in robust scientific evidence. Even with a lack of scientific consensus, public attitudes, and sweeping social media prohibitions have swiftly ensued. A focus on the diversity of adolescents around the world and their diverse use of language, culture, and social media is absent from these discussions. Objective: This study aims to guide communication policy and practice, including those addressing access to social media by adolescent populations. This study assesses physical and mental health information scanning and seeking behaviors across diverse language, cultural, and technological media and social media among Latinx adolescent residents in the United States. This study also explores how Latinx adolescents with mental health concerns use media and social media for support. Methods: In 2021, a cross-sectional survey was conducted among 701 US-based Latinx adolescents aged 13-20 years to assess their health-related media use. Assessments ascertained the frequency of media use and mental and physical health information scanning and seeking across various media technologies (eg, TV, podcasts, and social media) and language and cultural types (ie, Spanish, Latinx-tailored English, and general English). Linear regression models were used to estimate adjusted predicted means of mental and physical health information scanning and seeking across diverse language and cultural media types, net personal and family factors, in the full sample and by subsamples of mental health symptoms (moderate-high vs none-mild). Results: Among Latinx adolescents, media and social media use was similar across mental health symptoms. However, Latinx adolescents with moderate-high versus none-mild symptoms more often scanned general English media and social media for mental health information (P<.05), although not for physical health information. Also, Latinx adolescents with moderate-high versus none-mild symptoms more often sought mental health information on Latinx-tailored and general English media, and social media (P<.05); a similar pattern was found for physical health information seeking. In addition, Latinx adolescents with moderate-high versus none-mild symptoms often sought help from family and friends for mental and physical health problems and health care providers for mental health only (P<.05). Conclusions: While media and social media usage was similar across mental health, Latinx adolescents with moderate-high symptoms more often encountered mental health content in general English media and social media and turned to general English- and Latinx-tailored media and social media more often for their health concerns. Together these study findings suggest more prevalent and available mental health content in general English versus Spanish language and Latinx-tailored media and underscore the importance of providing accessible, quality health information across diverse language, cultural, and technological media and social networks as a viable opportunity to help improve adolescent health. %M 40053766 %R 10.2196/64672 %U https://www.jmir.org/2025/1/e64672 %U https://doi.org/10.2196/64672 %U http://www.ncbi.nlm.nih.gov/pubmed/40053766 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e62805 %T Machine Learning–Based Prediction of Substance Use in Adolescents in Three Independent Worldwide Cohorts: Algorithm Development and Validation Study %A Kim,Soeun %A Kim,Hyejun %A Kim,Seokjun %A Lee,Hojae %A Hammoodi,Ahmed %A Choi,Yujin %A Kim,Hyeon Jin %A Smith,Lee %A Kim,Min Seo %A Fond,Guillaume %A Boyer,Laurent %A Baik,Sung Wook %A Lee,Hayeon %A Park,Jaeyu %A Kwon,Rosie %A Woo,Selin %A Yon,Dong Keon %+ Department of Pediatrics, Kyung Hee University Medical Center, Kyung Hee University College of Medicine, 23 Kyungheedae-ro, Dongdaemun-gu, Seoul, 02447, Republic of Korea, 82 269352476, yonkkang@gmail.com %K adolescents %K machine learning %K substance %K prediction %K XGBoost %K random forest %K ML %K substance use %K adolescents %K adolescent %K South Korea %K United States %K Norway %K web-based survey %K survey %K risk behavior %K smoking %K alcohol %K intervention %K interventions %D 2025 %7 24.2.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: To address gaps in global understanding of cultural and social variations, this study used a high-performance machine learning (ML) model to predict adolescent substance use across three national datasets. Objective: This study aims to develop a generalizable predictive model for adolescent substance use using multinational datasets and ML. Methods: The study used the Korea Youth Risk Behavior Web-Based Survey (KYRBS) from South Korea (n=1,098,641) to train ML models. For external validation, we used the Youth Risk Behavior Survey (YRBS) from the United States (n=2,511,916) and Norwegian nationwide Ungdata surveys (Ungdata) from Norway (n=700,660). After developing various ML models, we evaluated the final model’s performance using multiple metrics. We also assessed feature importance using traditional methods and further analyzed variable contributions through SHapley Additive exPlanation values. Results: The study used nationwide adolescent datasets for ML model development and validation, analyzing data from 1,098,641 KYRBS adolescents, 2,511,916 YRBS participants, and 700,660 from Ungdata. The XGBoost model was the top performer on the KYRBS, achieving an area under receiver operating characteristic curve (AUROC) score of 80.61% (95% CI 79.63-81.59) and precision of 30.42 (95% CI 28.65-32.16) with detailed analysis on sensitivity of 31.30 (95% CI 29.47-33.20), specificity of 99.16 (95% CI 99.12-99.20), accuracy of 98.36 (95% CI 98.31-98.42), balanced accuracy of 65.23 (95% CI 64.31-66.17), F1-score of 30.85 (95% CI 29.25-32.51), and area under precision-recall curve of 32.14 (95% CI 30.34-33.95). The model achieved an AUROC score of 79.30% and a precision of 68.37% on the YRBS dataset, while in external validation using the Ungdata dataset, it recorded an AUROC score of 76.39% and a precision of 12.74%. Feature importance and SHapley Additive exPlanation value analyses identified smoking status, BMI, suicidal ideation, alcohol consumption, and feelings of sadness and despair as key contributors to the risk of substance use, with smoking status emerging as the most influential factor. Conclusions: Based on multinational datasets from South Korea, the United States, and Norway, this study shows the potential of ML models, particularly the XGBoost model, in predicting adolescent substance use. These findings provide a solid basis for future research exploring additional influencing factors or developing targeted intervention strategies. %M 39993291 %R 10.2196/62805 %U https://www.jmir.org/2025/1/e62805 %U https://doi.org/10.2196/62805 %U http://www.ncbi.nlm.nih.gov/pubmed/39993291 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 11 %N %P e52928 %T Association Among BMI, Self-Esteem, and Nonsuicidal Self-Injury in Young Adults to Understand the Influence of Socioenvironmental Factors: Longitudinal Study %A Zhang,Yi %A Ying,Ruixue %A Lu,Wan %A Liu,Xuemeng %A Hu,Keyan %A Feng,Qing %A Yu,Zixiang %A Wang,Zhen %A Lu,Fangting %A Miao,Yahu %A Ma,Nanzhen %A Tao,Fangbiao %A Jiang,Tian %A Zhang,Qiu %K nonsuicidal self-injury %K chronotype %K BMI %K self-esteem %K body mass index %K adolescent %K young adult %K teenager %K social environmental factor %K self-injury %K sampling method %K undergraduate %K college student %K linear regression %K regression %K regression model %D 2025 %7 21.2.2025 %9 %J JMIR Public Health Surveill %G English %X Background: Nonsuicidal self-injury (NSSI) is a major public health problem leading to psychological problems in adolescents and young adults, similar to disorders such as depression and anxiety. Objective: The aims of this study were to investigate (1) the interaction between BMI and socioenvironmental factors (including chronotype and mental health) that contribute to NSSI, and (2) whether self-esteem plays a mediating role in this association. Methods: From May to June 2022, the multistage cluster sampling method was used to sample college students in four grades, including freshmen and seniors. The baseline participants were followed up 6 months later, excluding those who did not qualify, and the participants included 1772 college students. Socioenvironmental factors (chronotype/mental health), self-esteem, and NSSI were measured using a questionnaire. Multivariate linear regression models and chi-square analysis were used to evaluate the linear relationship between BMI, socioenvironmental factors, and self-esteem and the NSSI status. We use a process approach (mediation-moderation analysis) to explore the complex relationships between these variables. Results: The mean age of the participants was 20.53 (SD 1.65) years at baseline. A significant association was revealed, suggesting that a high BMI (β=.056, 95% CI 0.008‐0.086, P=.018) was associated with a higher NSSI. There was also an interaction among BMI, socioenvironmental factors, and NSSI. Socioenvironmental factors played both moderating and mediating roles in the relationship between BMI and NSSI, whereas self-esteem only played a mediating role. Conclusions: Paying attention to factors such as overweight and obesity is important for early BMI control to identify other potential risk factors for NSSI and to evaluate how self-esteem can be improved considering multiple perspectives to improve the effect of BMI on NSSI in adolescents. %R 10.2196/52928 %U https://publichealth.jmir.org/2025/1/e52928 %U https://doi.org/10.2196/52928 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 12 %N %P e66665 %T Identifying Adolescent Depression and Anxiety Through Real-World Data and Social Determinants of Health: Machine Learning Model Development and Validation %A Mardini,Mamoun T %A Khalil,Georges E %A Bai,Chen %A DivaKaran,Aparna Menon %A Ray,Jessica M %K social determinants of health %K adolescents %K anxiety %K depression %K machine learning %K real-world data %K teenagers %K youth %K XGBoost %K cross-validation technique %K SHapley Additive exPlanation %K mental health %K mental disorder %K mental illness %K health outcomes %K clinical data %D 2025 %7 12.2.2025 %9 %J JMIR Ment Health %G English %X Background: The prevalence of adolescent mental health conditions such as depression and anxiety has significantly increased. Despite the potential of machine learning (ML), there is a shortage of models that use real-world data (RWD) to enhance early detection and intervention for these conditions. Objective: This study aimed to identify depression and anxiety in adolescents using ML techniques on RWD and social determinants of health (SDoH). Methods: We analyzed RWD of adolescents aged 10‐17 years, considering various factors such as demographics, prior diagnoses, prescribed medications, medical procedures, and laboratory measurements recorded before the onset of anxiety or depression. Clinical data were linked with SDoH at the block-level. Three separate models were developed to predict anxiety, depression, and both conditions. Our ML model of choice was Extreme Gradient Boosting (XGBoost) and we evaluated its performance using the nested cross-validation technique. To interpret the model predictions, we used the Shapley additive explanation method. Results: Our cohort included 52,054 adolescents, identifying 12,572 with anxiety, 7812 with depression, and 14,019 with either condition. The models achieved area under the curve values of 0.80 for anxiety, 0.81 for depression, and 0.78 for both combined. Excluding SDoH data had a minimal impact on model performance. Shapley additive explanation analysis identified gender, race, educational attainment, and various medical factors as key predictors of anxiety and depression. Conclusions: This study highlights the potential of ML in early identification of depression and anxiety in adolescents using RWD. By leveraging RWD, health care providers may more precisely identify at-risk adolescents and intervene earlier, potentially leading to improved mental health outcomes. %R 10.2196/66665 %U https://mental.jmir.org/2025/1/e66665 %U https://doi.org/10.2196/66665 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 9 %N %P e66330 %T Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey %A Choomung,Pichsinee %A He,Yupeng %A Matsunaga,Masaaki %A Sakuma,Kenji %A Kishi,Taro %A Li,Yuanying %A Tanihara,Shinichi %A Iwata,Nakao %A Ota,Atsuhiko %K schizophrenia %K schizophrenic %K prevalence %K artificial neural network %K neural network %K neural networks %K ANN %K deep learning %K machine learning %K SZ classifier %K web-based survey %K epidemiology %K epidemiological %K Japan %K classifiers %K mental illness %K mental disorder %K mental health %D 2025 %7 29.1.2025 %9 %J JMIR Form Res %G English %X Background: Estimating the prevalence of schizophrenia in the general population remains a challenge worldwide, as well as in Japan. Few studies have estimated schizophrenia prevalence in the Japanese population and have often relied on reports from hospitals and self-reported physician diagnoses or typical schizophrenia symptoms. These approaches are likely to underestimate the true prevalence owing to stigma, poor insight, or lack of access to health care among respondents. To address these issues, we previously developed an artificial neural network (ANN)–based schizophrenia classification model (SZ classifier) using data from a large-scale Japanese web-based survey to enhance the comprehensiveness of schizophrenia case identification in the general population. In addition, we also plan to introduce a population-based survey to collect general information and sample participants matching the population’s demographic structure, thereby achieving a precise estimate of the prevalence of schizophrenia in Japan. Objective: This study aimed to estimate the prevalence of schizophrenia by applying the SZ classifier to random samples from the Japanese population. Methods: We randomly selected a sample of 750 participants where the age, sex, and regional distributions were similar to Japan’s demographic structure from a large-scale Japanese web-based survey. Demographic data, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities were collected and applied to the SZ classifier, as this information was also used for developing the SZ classifier. The crude prevalence of schizophrenia was calculated through the proportion of positive cases detected by the SZ classifier. The crude estimate was further refined by excluding false-positive cases and including false-negative cases to determine the actual prevalence of schizophrenia. Results: Out of 750 participants, 62 were classified as schizophrenia cases by the SZ classifier, resulting in a crude prevalence of schizophrenia in the general population of Japan of 8.3% (95% CI 6.6%-10.1%). Among these 62 cases, 53 were presumed to be false positives, and 3 were presumed to be false negatives. After adjustment, the actual prevalence of schizophrenia in the general population was estimated to be 1.6% (95% CI 0.7%-2.5%). Conclusions: This estimated prevalence was slightly higher than that reported in previous studies, possibly due to a more comprehensive disease classification methodology or, conversely, model limitations. This study demonstrates the capability of an ANN-based model to improve the estimation of schizophrenia prevalence in the general population, offering a novel approach to public health analysis. %R 10.2196/66330 %U https://formative.jmir.org/2025/1/e66330 %U https://doi.org/10.2196/66330 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 11 %N %P e63809 %T An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study %A Thomas,Julia %A Lucht,Antonia %A Segler,Jacob %A Wundrack,Richard %A Miché,Marcel %A Lieb,Roselind %A Kuchinke,Lars %A Meinlschmidt,Gunther %+ Division of Clinical Psychology and Epidemiology, Faculty of Psychology, University of Basel, Missionsstrasse 60/62, Basel, 4055, Switzerland, 49 30 57714627, julia.thomas@krisenchat.de %K deep learning %K explainable artificial intelligence (XAI) %K large language model (LLM) %K machine learning %K neural network %K prevention %K risk monitoring %K suicide %K transformer model %K suicidality %K suicidal ideation %K self-murder %K self-harm %K youth %K adolescent %K adolescents %K public health %K language model %K language models %K chat protocols %K crisis helpline %K help-seeking behaviors %K German %K Shapley %K decision-making %K mental health %K health informatics %K mobile phone %D 2025 %7 29.1.2025 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Suicide represents a critical public health concern, and machine learning (ML) models offer the potential for identifying at-risk individuals. Recent studies using benchmark datasets and real-world social media data have demonstrated the capability of pretrained large language models in predicting suicidal ideation and behaviors (SIB) in speech and text. Objective: This study aimed to (1) develop and implement ML methods for predicting SIBs in a real-world crisis helpline dataset, using transformer-based pretrained models as a foundation; (2) evaluate, cross-validate, and benchmark the model against traditional text classification approaches; and (3) train an explainable model to highlight relevant risk-associated features. Methods: We analyzed chat protocols from adolescents and young adults (aged 14-25 years) seeking assistance from a German crisis helpline. An ML model was developed using a transformer-based language model architecture with pretrained weights and long short-term memory layers. The model predicted suicidal ideation (SI) and advanced suicidal engagement (ASE), as indicated by composite Columbia-Suicide Severity Rating Scale scores. We compared model performance against a classical word-vector-based ML model. We subsequently computed discrimination, calibration, clinical utility, and explainability information using a Shapley Additive Explanations value-based post hoc estimation model. Results: The dataset comprised 1348 help-seeking encounters (1011 for training and 337 for testing). The transformer-based classifier achieved a macroaveraged area under the curve (AUC) receiver operating characteristic (ROC) of 0.89 (95% CI 0.81-0.91) and an overall accuracy of 0.79 (95% CI 0.73-0.99). This performance surpassed the word-vector-based baseline model (AUC-ROC=0.77, 95% CI 0.64-0.90; accuracy=0.61, 95% CI 0.61-0.80). The transformer model demonstrated excellent prediction for nonsuicidal sessions (AUC-ROC=0.96, 95% CI 0.96-0.99) and good prediction for SI and ASE, with AUC-ROCs of 0.85 (95% CI 0.97-0.86) and 0.87 (95% CI 0.81-0.88), respectively. The Brier Skill Score indicated a 44% improvement in classification performance over the baseline model. The Shapley Additive Explanations model identified language features predictive of SIBs, including self-reference, negation, expressions of low self-esteem, and absolutist language. Conclusions: Neural networks using large language model–based transfer learning can accurately identify SI and ASE. The post hoc explainer model revealed language features associated with SI and ASE. Such models may potentially support clinical decision-making in suicide prevention services. Future research should explore multimodal input features and temporal aspects of suicide risk. %M 39879608 %R 10.2196/63809 %U https://publichealth.jmir.org/2025/1/e63809 %U https://doi.org/10.2196/63809 %U http://www.ncbi.nlm.nih.gov/pubmed/39879608 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e58656 %T Cross-Cultural Sense-Making of Global Health Crises: A Text Mining Study of Public Opinions on Social Media Related to the COVID-19 Pandemic in Developed and Developing Economies %A Kahlawi,Adham %A Masri,Firas %A Ahmed,Wasim %A Vidal-Alaball,Josep %+ Unitat de Recerca i Innovació, Gerència d'Atenció Primària i a la Comunitat de la Catalunya Central, Institut Català de la Salut, Carrer Pica d'Estats, 36, Sant Fruitós de Bages, 08272, Spain, 34 936930040, jvidal.cc.ics@gencat.cat %K COVID-19 %K SARS-CoV-2 %K pandemic %K citizen opinion %K text mining %K LDA %K health crisis %K developing economies %K Italy %K Egypt %K UK %K dataset %K content analysis %K social media %K twitter %K tweet %K sentiment %K attitude %K perception %K perspective %K machine learning %K latent Dirichlet allocation %K vaccine %K vaccination %K public health %K infectious %D 2025 %7 27.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: The COVID-19 pandemic reshaped social dynamics, fostering reliance on social media for information, connection, and collective sense-making. Understanding how citizens navigate a global health crisis in varying cultural and economic contexts is crucial for effective crisis communication. Objective: This study examines the evolution of citizen collective sense-making during the COVID-19 pandemic by analyzing social media discourse across Italy, the United Kingdom, and Egypt, representing diverse economic and cultural contexts. Methods: A total of 755,215 social media posts from X (formerly Twitter) were collected across 3 time periods: the virus' emergence (February 15 to March 31, 2020), strict lockdown (April 1 to May 30, 2020), and the vaccine rollout (December 1, 2020 to January 15, 2021). In total, 284,512 posts from Italy, 261,978 posts from the United Kingdom, and 209,725 posts from Egypt were analyzed using the latent Dirichlet allocation algorithm to identify key thematic topics and track shifts in discourse across time and regions. Results: The analysis revealed significant regional and temporal differences in collective sense-making during the pandemic. In Italy and the United Kingdom, public discourse prominently addressed pragmatic health care measures and government interventions, reflecting higher institutional trust. By contrast, discussions in Egypt were more focused on religious and political themes, highlighting skepticism toward governmental capacity and reliance on alternative frameworks for understanding the crisis. Over time, all 3 countries displayed a shift in discourse toward vaccine-related topics during the later phase of the pandemic, highlighting its global significance. Misinformation emerged as a recurrent theme across regions, demonstrating the need for proactive measures to ensure accurate information dissemination. These findings emphasize the role of cultural, economic, and institutional factors in shaping public responses during health crises. Conclusions: Crisis communication is influenced by cultural, economic, and institutional contexts, as evidenced by regional variations in citizen engagement. Transparent and culturally adaptive communication strategies are essential to combat misinformation and build public trust. This study highlights the importance of tailoring crisis responses to local contexts to improve compliance and collective resilience. %M 39869893 %R 10.2196/58656 %U https://www.jmir.org/2025/1/e58656 %U https://doi.org/10.2196/58656 %U http://www.ncbi.nlm.nih.gov/pubmed/39869893 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 13 %N %P e59740 %T Scrutinizing the Gateway Relationship Between Gaming and Gambling Disorder: Scoping Review With a Focus on the Southeast Asian Region %A Siste,Kristiana %A King,Daniel L %A Hanafi,Enjeline %A Sen,Lee Thung %A Adrian,Adrian %A Murtani,Belinda Julivia %K behavioral addiction %K convergence %K gateway effect %K gambling advertisement %K gamblification %K monetized gaming %D 2025 %7 15.1.2025 %9 %J JMIR Serious Games %G English %X Background: The gaming and gambling overlap has intensified with new evidence emerging. However, the relationship between gaming and gambling in the digital space is still inconclusive, especially in resource-limited Asian countries. Objective: This study aims to review available evidence on the possible interaction and focuses specifically on the gateway interaction between gambling and gaming. Additionally, this review delves into the state of evidence from the Southeast Asian region, providing an in-depth analysis of this underexplored area. Methods: We performed a scoping review by sifting through the publications in five databases. We focused on the gateway interaction and provided a possible pathway model, while two other convergence relationships were provided for comparison. Results: The scoping review identified a total of 289 publications, with the majority being empirical (n=181), although only 12 studies used longitudinal designs. A significant proportion of the publications (n=152) concentrated on the correlation or comorbidity between gaming and gambling. Most of the evidence has originated from Global North countries, with very limited research emerging from Southeast Asia (n=8). The most commonly studied gambling-like element in video games was loot boxes (n=105). Other elements investigated included esports betting, skin betting, token wagering, gambling advertisements, and gambling-like features. Several longitudinal studies have highlighted the risk of the gateway effect associated with gamblification involvement. However, emerging evidence suggests more nuanced underlying mechanisms that drive the transition from gaming to gambling. Conclusions: Overall, there is early evidence of linkage between gambling and gaming, through shared structural and biopsychosocial characteristics. This association possibly extends beyond disparate comorbidity, as such engagement in one activity might influence the risk of partaking in the other behavior. The field requires further longitudinal data to determine the directionality and significant precipitating factors of the gateway effect, particularly evidence from Asia. %R 10.2196/59740 %U https://games.jmir.org/2025/1/e59740 %U https://doi.org/10.2196/59740 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 11 %N %P e62730 %T The Association Between Posting WeChat Moments and the Risk of Depressive Symptoms Among Middle-Aged and Older Chinese Adults: Prospective National Cohort Study %A Wang,Wei %A Wang,Hui %A Hu,Xinru %A Yu,Qian %A Chen,Fangyi %A Qiu,Xirui %A Wang,Xiaoxiao %K cohort study %K depression %K depressive symptoms %K mental health %K middle-aged adults %K modified Poisson regression %K older adults %K WeChat %D 2025 %7 13.1.2025 %9 %J JMIR Public Health Surveill %G English %X Background: The association between social media usage and the risk of depressive symptoms has attracted increasing attention. WeChat is a popular social media software in China. The impact of using WeChat and posting WeChat moments on the risk of developing depressive symptoms among community-based middle-aged and older adults in China is unknown. Objective: The objective was to assess the association between using WeChat and posting WeChat moments and the risk of depressive symptoms among middle-aged and older adults in China. Methods: A prospective national cohort study was designed based on the data obtained from the fourth and fifth waves of the China Health and Retirement Longitudinal Study (CHARLS). The strength of association between using WeChat and posting WeChat moments and the risk of depressive symptoms was estimated by modified Poisson regressions. Depressive symptoms were determined using the 10-item Center for Epidemiologic Studies Depression Scale. Meanwhile, the heterogeneity of the associations was explored through multiple subgroup analyses. Moreover, multiple sensitivity analyses were performed to verify the robustness of the associations between the exposures and depressive symptoms. Results: A total of 9670 eligible participants were included in the cohort study, and the incidence rate of depressive symptoms was 19.08% (1845/9670, 95% CI 19.07%‐19.09%) from the fourth to fifth waves of the CHARLS. Using WeChat (adjusted relative risk [aRR] 0.691, 95% CI 0.582‐0.520) and posting WeChat moments (aRR 0.673, 95% CI 0.552‐0.821) reduced the risk of depressive symptoms among middle-aged and older Chinese adults. The association between the exposures and depressive symptoms was robust, proved through multiple sensitivity analyses (all P<.05). However, the associations were heterogeneous in certain subgroup catagories, such as solitude, duration of sleep at night, nap after lunch, physical activity, and having multiple chronic conditions. Conclusions: Using WeChat and especially posting WeChat moments can mitigate the risk of depressive symptoms among community-based middle-aged and older Chinese adults. However, there is likely a need for a longer follow-up period to explore the impact of the exposures on the risk of long-term depressive outcomes. %R 10.2196/62730 %U https://publichealth.jmir.org/2025/1/e62730 %U https://doi.org/10.2196/62730 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 27 %N %P e62824 %T The Impact of the COVID-19 Pandemic on Oldest-Old Social Capital and Health and the Role of Digital Inequalities: Longitudinal Cohort Study %A Valla,Luca Guido %A Rossi,Michele %A Gaia,Alessandra %A Guaita,Antonio %A Rolandi,Elena %+ Centre for Longitudinal Studies, UCL Social Research Institute, University College London, Room 101, 55-59 Gordon Square, London, WC1H 0AL, United Kingdom, 44 02076792000, a.gaia@ucl.ac.uk %K older adults %K information and communication technology %K ICT %K ICT use %K COVID-19 %K social capital %K health %K mental health %K digital divide %D 2025 %7 9.1.2025 %9 Original Paper %J J Med Internet Res %G English %X Background: During the COVID-19 pandemic, information and communication technology (ICT) became crucial for staying connected with loved ones and accessing health services. In this scenario, disparities in ICT use may have exacerbated other forms of inequality, especially among older adults who were less familiar with technology and more vulnerable to severe COVID-19 health consequences. Objective: This study investigated changes in ICT use, psychological and physical health, and social capital before and after the pandemic among the oldest old population (aged 80 years or older after the pandemic) and explored how internet use influenced these changes. Methods: We leveraged data from the InveCe.Ab study, a population-based longitudinal cohort of people born between 1935 and 1939 and living in Abbiategrasso, a municipality on the outskirts of Milan, Italy. Participants underwent multidimensional assessment at baseline (2010) and after 2, 4, 8, and 12 years. We restricted our analysis to cohort members who participated in the last wave (ie, 2022) and who did not have a diagnosis of dementia (n=391). We used linear mixed models to assess the impact of COVID-19 and time on changes in social capital, physical and psychological health, and ICT use in a discontinuity regression design while controlling for age, sex, education, and income satisfaction. Then, we assessed the influence of internet use and its interaction with COVID-19 on these changes. Results: COVID-19 had a significant impact on social relationships (β=–4.35, 95% CI 6.38 to –2.32; P<.001), cultural activities (β=–.55, 95% CI –0.75 to –0.35; P<.001), cognitive functioning (β=–1.00, 95% CI –1.28 to –0.72; P<.001), depressive symptoms (β=.42, 95% CI 0.10-0.74; P=.009), physical health (β=.07, 95% CI 0.04-0.10; P<.001), and ICT use (β=–.11, 95% CI –0.18 to –0.03; P=.008). Internet use predicts reduced depressive symptoms (β=–.56, 95% CI –1.07 to –0.06; P=.03) over time. The interaction between internet use and COVID-19 was significant for cultural activities (β=–.73, 95% CI –1.22 to –0.24; P=.003) and cognitive functioning (β=1.36, 95% CI 0.67-2.05; P<.001). Conclusions: The pandemic had adverse effects on older adults’ health and social capital. Contrary to expectations, even ICT use dropped significantly after the pandemic. Internet users maintained higher psychological health regardless of time and COVID-19 status. However, COVID-19 was associated with a steeper decline in cognitive functioning among internet nonusers. Policy makers may develop initiatives to encourage ICT adoption among older adults or strengthen their digital skills. Trial Registration: ClinicalTrials.gov NCT01345110; https://clinicaltrials.gov/study/NCT01345110 %M 39784108 %R 10.2196/62824 %U https://www.jmir.org/2025/1/e62824 %U https://doi.org/10.2196/62824 %U http://www.ncbi.nlm.nih.gov/pubmed/39784108 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e49927 %T Machine Learning–Based Suicide Risk Prediction Model for Suicidal Trajectory on Social Media Following Suicidal Mentions: Independent Algorithm Validation %A Kaminsky,Zachary %A McQuaid,Robyn J %A Hellemans,Kim GC %A Patterson,Zachary R %A Saad,Mysa %A Gabrys,Robert L %A Kendzerska,Tetyana %A Abizaid,Alfonso %A Robillard,Rebecca %+ University of Ottawa Institute of Mental Health Research at The Royal, 1145 Carling Avenue, Ottawa, ON, K1Z 7K4, Canada, 1 6137226521 ext 7003, Zachary.Kaminsky@theroyal.ca %K suicide %K prediction %K social media %K machine learning %K suicide risk model %K validation %K prediction %K natural language processing %K suicide risk %K Twitter %K suicidal ideation %K suicidal mention %D 2024 %7 5.12.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Previous efforts to apply machine learning–based natural language processing to longitudinally collected social media data have shown promise in predicting suicide risk. Objective: Our primary objective was to externally validate our previous machine learning algorithm, the Suicide Artificial Intelligence Prediction Heuristic (SAIPH), against external survey data in 2 independent cohorts. A second objective was to evaluate the efficacy of SAIPH as an indicator of changing suicidal ideation (SI) over time. The tertiary objective was to use SAIPH to evaluate factors important for improving or worsening suicidal trajectory on social media following suicidal mention. Methods: Twitter (subsequently rebranded as X) timeline data from a student survey cohort and COVID-19 survey cohort were scored using SAIPH and compared to SI questions on the Beck Depression Inventory and the Self-Report version of the Quick Inventory of Depressive Symptomatology in 159 and 307 individuals, respectively. SAIPH was used to evaluate changing SI trajectory following suicidal mentions in 2 cohorts collected using the Twitter application programming interface. Results: An interaction of the mean SAIPH score derived from 12 days of Twitter data before survey completion and the average number of posts per day was associated with quantitative SI metrics in each cohort (student survey cohort interaction β=.038, SD 0.014; F4,94=3.3, P=.01; and COVID-19 survey cohort interaction β=.0035, SD 0.0016; F4,493=2.9, P=.03). The slope of average daily SAIPH scores was associated with the change in SI scores within longitudinally followed individuals when evaluating periods of 2 weeks or less (ρ=0.27, P=.04). Using SAIPH as an indicator of changing SI, we evaluated SI trajectory in 2 cohorts with suicidal mentions, which identified that those with responses within 72 hours exhibit a significant negative association of the SAIPH score with time in the 3 weeks following suicidal mention (ρ=–0.52, P=.02). Conclusions: Taken together, our results not only validate the association of SAIPH with perceived stress, SI, and changing SI over time but also generate novel methods to evaluate the effects of social media interactions on changing suicidal trajectory. %M 39637380 %R 10.2196/49927 %U https://www.jmir.org/2024/1/e49927 %U https://doi.org/10.2196/49927 %U http://www.ncbi.nlm.nih.gov/pubmed/39637380 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e63195 %T Dynamic Simulation Models of Suicide and Suicide-Related Behaviors: Systematic Review %A Gariepy,Genevieve %A Zahan,Rifat %A Osgood,Nathaniel D %A Yeoh,Benjamin %A Graham,Eva %A Orpana,Heather %+ Centre for Surveillance and Applied Research, Public Health Agency of Canada, 785 Carling Avenue, Ottawa, ON, K1A 0K9, Canada, 1 6139527608, genevieve.gariepy@phac-aspc.gc.ca %K suicide %K agent-based modeling %K complex system %K complexity science %K discrete-event simulation %K dynamic modeling %K microsimulation %K system dynamics %K systems science %K qualitative study %K dynamic simulation %K database %K depression %K mental state %K systematic review %K stress %D 2024 %7 2.12.2024 %9 Review %J JMIR Public Health Surveill %G English %X Background: Suicide remains a public health priority worldwide with over 700,000 deaths annually, ranking as a leading cause of death among young adults. Traditional research methodologies have often fallen short in capturing the multifaceted nature of suicide, focusing on isolated risk factors rather than the complex interplay of individual, social, and environmental influences. Recognizing these limitations, there is a growing recognition of the value of dynamic simulation modeling to inform suicide prevention planning. Objective: This systematic review aims to provide a comprehensive overview of existing dynamic models of population-level suicide and suicide-related behaviors, and to summarize their methodologies, applications, and outcomes. Methods: Eight databases were searched, including MEDLINE, Embase, PsycINFO, Scopus, Compendex, ACM Digital Library, IEEE Xplore, and medRxiv, from inception to July 2023. We developed a search strategy in consultation with a research librarian. Two reviewers independently conducted the title and abstract and full-text screenings including studies using dynamic modeling methods (eg, System Dynamics and agent-based modeling) for suicide or suicide-related behaviors at the population level, and excluding studies on microbiology, bioinformatics, pharmacology, nondynamic modeling methods, and nonprimary modeling reports (eg, editorials and reviews). Reviewers extracted the data using a standardized form and assessed the quality of reporting using the STRESS (Strengthening the Reporting of Empirical Simulation Studies) guidelines. A narrative synthesis was conducted for the included studies. Results: The search identified 1574 studies, with 22 studies meeting the inclusion criteria, including 15 System Dynamics models, 6 agent-based models, and 1 microsimulation model. The studies primarily targeted populations in Australia and the United States, with some focusing on hypothetical scenarios. The models addressed various interventions ranging from specific clinical and health service interventions, such as mental health service capacity increases, to broader social determinants, including employment programs and reduction in access to means of suicide. The studies demonstrated the utility of dynamic models in identifying the synergistic effects of combined interventions and understanding the temporal dynamics of intervention impacts. Conclusions: Dynamic modeling of suicide and suicide-related behaviors, though still an emerging area, is expanding rapidly, adapting to a range of questions, settings, and contexts. While the quality of reporting was overall adequate, some studies lacked detailed reporting on model transparency and reproducibility. This review highlights the potential of dynamic modeling as a tool to support decision-making and to further our understanding of the complex dynamics of suicide and its related behaviors. Trial Registration: PROSPERO CRD42022346617; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=346617 %M 39622024 %R 10.2196/63195 %U https://publichealth.jmir.org/2024/1/e63195 %U https://doi.org/10.2196/63195 %U http://www.ncbi.nlm.nih.gov/pubmed/39622024 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e56166 %T Online Depression Communities as a Complementary Approach to Improving the Attitudes of Patients With Depression Toward Medication Adherence: Cross-Sectional Survey Study %A Chen,Runnan %A Fu,Xiaorong %A Liu,Mochi %A Liao,Ke %A Bai,Lifei %+ Department of Marketing, School of Business Administration, Southwestern University of Finance and Economics, 555 Liutai Road, Chengdu, 611130, China, 86 13981916682, fuxr@swufe.edu.cn %K online depression communities %K attitudes %K institution-generated content %K user-generated content %K perceived social support %K antidepressants %K hopelessness %K cross-sectional study %K China %K health care system %K online health community %K depression %K medication adherence %K social support %K health care practitioner %K peer support %D 2024 %7 19.11.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Lack of adherence to prescribed medication is common among patients with depression in China, posing serious challenges to the health care system. Online health communities have been found to be effective in enhancing patient compliance. However, empirical evidence supporting this effect in the context of depression treatment is absent, and the influence of online health community content on patients’ attitudes toward medication adherence is also underexplored. Objective: This study aims to explore whether online depression communities (ODCs) can help ameliorate the problem of poor medication taking among patients with depression. Drawing on the stimulus-organism-response and feelings-as-information theories, we established a research model to examine the influence of useful institution-generated content (IGC) and positive user-generated content (UGC) on attitudes toward medication adherence when combined with the mediating role of perceived social support, perceived value of antidepressants, and the moderating role of hopelessness. Methods: A cross-sectional questionnaire survey method was used in this research. Participants were recruited from various Chinese ODCs, generating data for a main study and 2 robustness checks. Hierarchical multiple regression analyses and bootstrapping analyses were adopted as the primary methods to test the hypotheses. Results: We received 1515 valid responses in total, contributing to 5 different datasets: model IGC (n=353, 23.3%), model UGC (n=358, 23.63%), model IGC+UGC (n=270, 17.82%), model IGC-B (n=266, 17.56%), and model UGC-B (n=268, 17.69%). Models IGC and UGC were used for the main study. Model IGC+UGC was used for robustness check A. Models IGC-B and UGC-B were used for robustness check B. Useful IGC and positive UGC were proven to have positive impact on the attitudes of patients with depression toward medication adherence through the mediations of perceived social support and perceived value of antidepressants. The findings corroborated the role of hopelessness in weakening or even negating the positive effects of ODC content on the attitudes of patients with depression toward medication adherence. Conclusions: This study provides the first empirical evidence demonstrating the relationship between ODC content and attitudes toward medication adherence, through which we offer a novel solution to the problem of poor medication adherence among patients with depression in China. Our findings also provide suggestions about how to optimize this new approach—health care practitioners should generate online content that precisely matches the informational needs of patients with depression, and ODC service providers should endeavor to regulate the community atmosphere. Nonetheless, we warn that ODC interventions cannot be used as the only approach to addressing the problem of poor medication taking among patients with severe depressive symptoms. %M 39561355 %R 10.2196/56166 %U https://www.jmir.org/2024/1/e56166 %U https://doi.org/10.2196/56166 %U http://www.ncbi.nlm.nih.gov/pubmed/39561355 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e49761 %T #TraumaTok—TikTok Videos Relating to Trauma: Content Analysis %A Woolard,Alix %A Paciente,Rigel %A Munro,Emily %A Wickens,Nicole %A Wells,Gabriella %A Ta,Daniel %A Mandzufas,Joelie %A Lombardi,Karen %+ The Kids Research Institute Australia, 15 Hospital Avenue, Nedlands, 6009, Australia, 61 63191823, alix.woolard@thekids.org.au %K trauma %K traumatic events %K traumatic stress %K TikTok %K public health %K social media %K content analysis %D 2024 %7 7.11.2024 %9 Short Paper %J JMIR Form Res %G English %X Background: Experiencing a traumatic event can significantly impact mental and emotional well-being. Social media platforms offer spaces for sharing stories, seeking support, and accessing psychoeducation. TikTok (ByteDance), a rapidly growing social media platform, is increasingly used for advice, validation, and information, although the content of this requires further study. Research is particularly needed to better understand TikTok content relating to trauma and the potential implications for young viewers, considering the distressing nature of the subject and the possibility of users experiencing vicarious trauma through exposure to these videos. Objective: This study aims to explore the content of trauma-related videos on TikTok, focusing on hashtags related to trauma. Specifically, this study analyzes how TikTok videos present information, advice, stories, and support relating to trauma. Methods: A quantitative cross-sectional descriptive content analysis was performed on TikTok in December 2022. A total of 5 hashtags related to trauma were selected: #trauma, #traumatized, #traumatok, #traumatic, and #traumabond, with the top 50 videos from each hashtag analyzed (total N=250 videos). A standardized codebook was developed inductively to analyze the content of the videos, while an existing generic codebook was used to collect the video features (eg, age of people in the video) and metadata (likes, comments, and shares) for each video. Results: A total of 2 major content themes were identified, which were instructional videos (54/250, 21.6%) and videos disclosing personal stories (168/250, 67.3%). The videos garnered significant engagement, with a total of 296.6 million likes, 2.3 million comments, and 4.6 million shares, indicating that users find this content engaging and useful. Alarmingly, only 3.7% (9/250) of videos included a trigger warning, despite many featuring highly distressing stories that young people and those with trauma may be exposed to. Conclusions: The study highlights the potential risks of vicarious trauma due to trauma dumping without trigger warnings on TikTok, and the need for further research to assess the accuracy of advice and information in these videos. However, it also underscores the platform’s potential to foster social connections, provide validation, and reduce stigma around mental health issues. Public health professionals should leverage social media to disseminate accurate mental health information, while promoting user education and content moderation to mitigate potential harms. People often use social media, such as TikTok to share advice, stories, and support around mental health, including their experiences with trauma. Out of 250 videos, most were either giving advice (54/250, 21.6%) or sharing personal experiences (168/250, 67.3%). The study found many videos lacked warnings about upsetting content, which could potentially harm young viewers or people suffering from trauma. While TikTok can help people feel connected and reduce the stigma around mental health, it is important to seek support from professionals when needed. %M 39509697 %R 10.2196/49761 %U https://formative.jmir.org/2024/1/e49761 %U https://doi.org/10.2196/49761 %U http://www.ncbi.nlm.nih.gov/pubmed/39509697 %0 Journal Article %@ 2563-3570 %I JMIR Publications %V 5 %N %P e58357 %T Enhancing Suicide Risk Prediction With Polygenic Scores in Psychiatric Emergency Settings: Prospective Study %A Lee,Younga Heather %A Zhang,Yingzhe %A Kennedy,Chris J %A Mallard,Travis T %A Liu,Zhaowen %A Vu,Phuong Linh %A Feng,Yen-Chen Anne %A Ge,Tian %A Petukhova,Maria V %A Kessler,Ronald C %A Nock,Matthew K %A Smoller,Jordan W %+ Psychiatric & Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, 185 Cambridge St, 6th Floor, Boston, MA, 02114, United States, 1 617 724 0835, jsmoller@mgh.harvard.edu %K polygenic risk score %K suicide risk prediction %K suicide attempt %K predictive algorithms %K genomics %K genotypes %K electronic health record %K machine learning %D 2024 %7 23.10.2024 %9 Original Paper %J JMIR Bioinform Biotech %G English %X Background: Despite growing interest in the clinical translation of polygenic risk scores (PRSs), it remains uncertain to what extent genomic information can enhance the prediction of psychiatric outcomes beyond the data collected during clinical visits alone. Objective: This study aimed to assess the clinical utility of incorporating PRSs into a suicide risk prediction model trained on electronic health records (EHRs) and patient-reported surveys among patients admitted to the emergency department. Methods: Study participants were recruited from the psychiatric emergency department at Massachusetts General Hospital. There were 333 adult patients of European ancestry who had high-quality genotype data available through their participation in the Mass General Brigham Biobank. Multiple neuropsychiatric PRSs were added to a previously validated suicide prediction model in a prospective cohort enrolled between February 4, 2015, and March 13, 2017. Data analysis was performed from July 11, 2022, to August 31, 2023. Suicide attempt was defined using diagnostic codes from longitudinal EHRs combined with 6-month follow-up surveys. The clinical risk score for suicide attempt was calculated from an ensemble model trained using an EHR-based suicide risk score and a brief survey, and it was subsequently used to define the baseline model. We generated PRSs for depression, bipolar disorder, schizophrenia, suicide attempt, and externalizing traits using a Bayesian polygenic scoring method for European ancestry participants. Model performance was evaluated using area under the receiver operator curve (AUC), area under the precision-recall curve, and positive predictive values. Results: Of the 333 patients (n=178, 53.5% male; mean age 36.8, SD 13.6 years; n=333, 100% non-Hispanic and n=324, 97.3% self-reported White), 28 (8.4%) had a suicide attempt within 6 months. Adding either the schizophrenia PRS or all PRSs to the baseline model resulted in the numerically highest discrimination (AUC 0.86, 95% CI 0.73-0.99) compared to the baseline model (AUC 0.84, 95% Cl 0.70-0.98). However, the improvement in model performance was not statistically significant. Conclusions: In this study, incorporating genomic information into clinical prediction models for suicide attempt did not improve patient risk stratification. Larger studies that include more diverse participants are required to validate whether the inclusion of psychiatric PRSs in clinical prediction models can enhance the stratification of patients at risk of suicide attempts. %M 39442166 %R 10.2196/58357 %U https://bioinform.jmir.org/2024/1/e58357 %U https://doi.org/10.2196/58357 %U http://www.ncbi.nlm.nih.gov/pubmed/39442166 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e63067 %T The Impact of Social Support on the Relationship Between Physical Exercise and Cognitive Function in Older Adults: Sociological Perspective %A Li,Yuan %A Zhai,Qun %A Peng,Weihang %K social support %K physical exercise %K cognitive function %K elderly %K sociological perspective %D 2024 %7 4.10.2024 %9 %J JMIR Public Health Surveill %G English %X %R 10.2196/63067 %U https://publichealth.jmir.org/2024/1/e63067 %U https://doi.org/10.2196/63067 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e51653 %T Loneliness and Social Isolation Factors Under the Prolonged COVID-19 Pandemic in Japan: 2-Year Longitudinal Study %A Sugaya,Nagisa %A Yamamoto,Tetsuya %A Suzuki,Naho %A Uchiumi,Chigusa %+ National Institute of Occupational Safety and Health, Japan, 6-21-1 Nagao,Tama-ku, Kawasaki, 214-8585, Japan, 81 44 865 6111 ext 8568, sugaya-nagisa@h.jniosh.johas.go.jp %K COVID-19 %K pandemic %K loneliness %K social isolation %K longitudinal survey %K epidemiology %K mental health %D 2024 %7 9.9.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Worsening loneliness and social isolation during the COVID-19 pandemic have become serious public health concerns worldwide. Despite previous research reporting persistent loneliness and social isolation under repeated emergency declarations and prolonged pandemics, long-term studies are needed to identify the actual conditions of loneliness and social isolation, and the factors that explain them. Objective: In this study, 3 web-based surveys were conducted at 1-year intervals during the 2 years after the first state of emergency to examine changes in loneliness and social isolation and the psychosocial factors associated with them in the Japanese population. Methods: The first survey (phase 1, May 11-12, 2020) was conducted at the end of the first emergency declaration period, the second survey (phase 2, June 14-20, 2021) was conducted at the end of the third emergency declaration period, and the third survey (phase 3, May 13-30, 2022) was conducted when the state of emergency had not been declared but many COVID-19–positive cases occurred during this period. We collected data on 3892 inhabitants (n=1813, 46.58% women; age: mean 50.3, SD 13.4 y) living in the 4 prefectures where emergency declaration measures were applied in phases 1 and 2. A linear mixed model analysis was performed to examine the association between psychosocial variables as explanatory variables and loneliness scores as the dependent variable in each phase. Results: While many psychosocial and physical variables showed improvement for the 2 years, loneliness, social isolation, and the relationship with familiar people deteriorated, and the opportunities for exercise, favorite activities, and web-based interaction with familiar people decreased. Approximately half of those experiencing social isolation in phase 1 remained isolated throughout the 2-year period, and a greater number of people developed social isolation than those who were able to resolve it. The results of the linear mixed model analysis showed that most psychosocial and physical variables were related to loneliness regardless of the phase. Regarding the variables that showed a significant interaction with the phase, increased altruistic preventive behavior and a negative outlook for the future were more strongly associated with severe loneliness in phase 3 (P=.01 to <.001), while the association between fewer social networks and stronger loneliness tended to be more pronounced in phase 2. Although the interaction was not significant, the association between reduced face-to-face interaction, poorer relationships with familiar people, and increased loneliness tended to be stronger in phase 3. Conclusions: This study found that loneliness and social isolation remained unresolved throughout the long-term COVID-19 pandemic. Additionally, in the final survey phase, these issues were influenced by a broader and more complex set of factors compared to earlier phases. %M 39250195 %R 10.2196/51653 %U https://publichealth.jmir.org/2024/1/e51653 %U https://doi.org/10.2196/51653 %U http://www.ncbi.nlm.nih.gov/pubmed/39250195 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e58259 %T Natural Language Processing for Depression Prediction on Sina Weibo: Method Study and Analysis %A Zhang,Zhenwen %A Zhu,Jianghong %A Guo,Zhihua %A Zhang,Yu %A Li,Zepeng %A Hu,Bin %K depression %K social media %K natural language processing %K deep learning %K mental health %K statistical analysis %K linguistic analysis %K Sina Weibo %K risk prediction %K mood analysis %D 2024 %7 4.9.2024 %9 %J JMIR Ment Health %G English %X Background: Depression represents a pressing global public health concern, impacting the physical and mental well-being of hundreds of millions worldwide. Notwithstanding advances in clinical practice, an alarming number of individuals at risk for depression continue to face significant barriers to timely diagnosis and effective treatment, thereby exacerbating a burgeoning social health crisis. Objective: This study seeks to develop a novel online depression risk detection method using natural language processing technology to identify individuals at risk of depression on the Chinese social media platform Sina Weibo. Methods: First, we collected approximately 527,333 posts publicly shared over 1 year from 1600 individuals with depression and 1600 individuals without depression on the Sina Weibo platform. We then developed a hierarchical transformer network for learning user-level semantic representations, which consists of 3 primary components: a word-level encoder, a post-level encoder, and a semantic aggregation encoder. The word-level encoder learns semantic embeddings from individual posts, while the post-level encoder explores features in user post sequences. The semantic aggregation encoder aggregates post sequence semantics to generate a user-level semantic representation that can be classified as depressed or nondepressed. Next, a classifier is employed to predict the risk of depression. Finally, we conducted statistical and linguistic analyses of the post content from individuals with and without depression using the Chinese Linguistic Inquiry and Word Count. Results: We divided the original data set into training, validation, and test sets. The training set consisted of 1000 individuals with depression and 1000 individuals without depression. Similarly, each validation and test set comprised 600 users, with 300 individuals from both cohorts (depression and nondepression). Our method achieved an accuracy of 84.62%, precision of 84.43%, recall of 84.50%, and F1-score of 84.32% on the test set without employing sampling techniques. However, by applying our proposed retrieval-based sampling strategy, we observed significant improvements in performance: an accuracy of 95.46%, precision of 95.30%, recall of 95.70%, and F1-score of 95.43%. These outstanding results clearly demonstrate the effectiveness and superiority of our proposed depression risk detection model and retrieval-based sampling technique. This breakthrough provides new insights for large-scale depression detection through social media. Through language behavior analysis, we discovered that individuals with depression are more likely to use negation words (the value of “swear” is 0.001253). This may indicate the presence of negative emotions, rejection, doubt, disagreement, or aversion in individuals with depression. Additionally, our analysis revealed that individuals with depression tend to use negative emotional vocabulary in their expressions (“NegEmo”: 0.022306; “Anx”: 0.003829; “Anger”: 0.004327; “Sad”: 0.005740), which may reflect their internal negative emotions and psychological state. This frequent use of negative vocabulary could be a way for individuals with depression to express negative feelings toward life, themselves, or their surrounding environment. Conclusions: The research results indicate the feasibility and effectiveness of using deep learning methods to detect the risk of depression. These findings provide insights into the potential for large-scale, automated, and noninvasive prediction of depression among online social media users. %R 10.2196/58259 %U https://mental.jmir.org/2024/1/e58259 %U https://doi.org/10.2196/58259 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e52759 %T Association Between COVID-19 and Self-Harm: Nationwide Retrospective Ecological Spatiotemporal Study in Metropolitan France %A Baillet,Maëlle %A Wathelet,Marielle %A Lamer,Antoine %A Frévent,Camille %A Fovet,Thomas %A D'Hondt,Fabien %A Notredame,Charles-Edouard %A Vaiva,Guillaume %A Génin,Michael %K self-harm %K COVID-19 %K spatiotemporal analysis %K ecological regression %K data reuse %D 2024 %7 27.8.2024 %9 %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic has not been associated with increases in suicidal behavior at the national, regional, or county level. However, previous studies were not conducted on a finer scale or adjusted for ecological factors. Objective: Our objective was to assess the fine-scale spatiotemporal association between self-harm and COVID-19 hospitalizations, while considering ecological factors. Methods: Using the French national hospital discharge database, we extracted data on hospitalizations for self-harm of patients older than 10 years (from 2019 to 2021) or for COVID-19 (from 2020 to 2021) in metropolitan France. We first calculated monthly standardized incidence ratios (SIRs) for COVID-19 between March 2020 and December 2021, using a Besag, York, and Mollié spatiotemporal model. Next, we entered the SIRs into an ecological regression in order to test the association between hospital admissions for self-harm and those for COVID-19. Lastly, we adjusted for ecological variables with time lags of 0 to 6 months. Results: Compared with a smoothed SIR of ≤1, smoothed SIRs from 1 to 3, from 3 to 4, and greater than 4 for COVID-19 hospital admissions were associated with a subsequent increase in hospital admissions for self-harm, with a time lag of 2 to 4 months, 4 months, and 6 months, respectively. Conclusions: A high SIR for hospital admissions for COVID-19 was a risk factor for hospital admission for self-harm some months after the epidemic peaks. This finding emphasizes the importance of monitoring and seeking to prevent suicide attempts outside the epidemic peak periods. %R 10.2196/52759 %U https://publichealth.jmir.org/2024/1/e52759 %U https://doi.org/10.2196/52759 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e57584 %T Implementation of a Novel Epidemiological Surveillance System for Children’s Mental Health and Well-Being in France: Protocol for the National “Enabee” Cross-Sectional Study %A Motreff,Yvon %A Marillier,Maude %A Saoudi,Abdessattar %A Verdot,Charlotte %A Seconda,Louise %A Pognon,Damien %A Khireddine-Medouni,Imane %A Richard,Jean-Baptiste %A Kovess-Masfety,Viviane %A Delorme,Richard %A Decio,Valentina %A Perrine,Anne-Laure %A El Haddad,Maria %A Gallay,Anne %A Monnier-Besnard,Stéphanie %A Regnault,Nolwenn %A , %+ Direction des maladies non transmissibles et traumatismes, Santé publique France, 12 rue du Val d'Osne, Saint-Maurice, 94415, France, 33 141796960, yvon.motreff@santepubliquefrance.fr %K child %K mental health %K epidemiological surveillance %K well-being %D 2024 %7 13.8.2024 %9 Protocol %J JMIR Public Health Surveill %G English %X Background: Children’s mental health, including their well-being, is a major public health concern, as the burden of related disorders may last throughout one’s life. Although epidemiological mental health surveillance systems for children and adolescents have been implemented in several countries, they are sorely lacking in France. Objective: This study aims to describe the first step of the implementation of a novel surveillance system in France called Enabee (Etude nationale sur le bien-être des enfants), which focuses on the issue of mental health in children. The system aims to (1) describe the temporal trends in the population-based prevalence of the main mental health disorders and well-being in children aged 3 to 11 years, (2) explore their major determinants, and (3) assess mental health care use by this population. To do this, Enabee will rely on results from a recurrent national cross-sectional homonymous study. This paper presents the protocol for the first edition of this study (called Enabee 2022), as well as initial results regarding participation. Methods: Enabee 2022 is a national cross-sectional study that was implemented in French schools in 2022. It used a probabilistic, multistage, stratified, and balanced sampling plan as follows: first, schools were randomly drawn and stratified according to the type of school. Up to 4 classes per school were then randomly drawn, and finally, all the pupils within each class were selected. The study covered children from preschool and kindergarten (aged 3 to 6 years, US grading system) to fifth grade (aged 6 to 11 years). Children from first to fifth grades provided a self-assessment of their mental health using 2 validated self-administered questionnaires: the Dominic Interactive (DI) and the KINDL. Parents and teachers completed a web-based questionnaire, including the Strengths and Difficulties Questionnaire. Parents also answered additional questions about their parenting attitudes; their own mental health; known social, economic, and environmental determinants of mental health in children; and their child’s life habits. Health, education, and family stakeholders were involved in designing and implementing the study as part of a large consultation group. Results: Data were collected from May 2, 2022, to July 31, 2022, in 399 schools across metropolitan France. Teachers completed questionnaires for 5721 pupils in preschool and kindergarten and for 15,263 pupils from first to fifth grades. Parents completed questionnaires for 3785 children in preschool and kindergarten and for 9227 children from first to fifth grades. Finally, 15,206 children from first to fifth grades completed the self-administered questionnaire. Conclusions: Enabee 2022 constitutes the first milestone in the development of a novel national epidemiological surveillance system, paving the way for improved children’s mental health policies in France. %M 39137010 %R 10.2196/57584 %U https://publichealth.jmir.org/2024/1/e57584 %U https://doi.org/10.2196/57584 %U http://www.ncbi.nlm.nih.gov/pubmed/39137010 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e48907 %T Identifying Reddit Users at a High Risk of Suicide and Their Linguistic Features During the COVID-19 Pandemic: Growth-Based Trajectory Model %A Yan,Yifei %A Li,Jun %A Liu,Xingyun %A Li,Qing %A Yu,Nancy Xiaonan %+ Department of Social and Behavioural Sciences, City University of Hong Kong, Tat Chee Avenue, Kowloon, HKSAR, P. R. China, Hong Kong, 000, China (Hong Kong), 852 34429436, nancy.yu@cityu.edu.hk %K COVID-19 pandemic %K Reddit %K suicide risk %K trajectory %D 2024 %7 8.8.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Suicide has emerged as a critical public health concern during the COVID-19 pandemic. With social distancing measures in place, social media has become a significant platform for individuals expressing suicidal thoughts and behaviors. However, existing studies on suicide using social media data often overlook the diversity among users and the temporal dynamics of suicide risk. Objective: By examining the variations in post volume trajectories among users on the r/SuicideWatch subreddit during the COVID-19 pandemic, this study aims to investigate the heterogeneous patterns of change in suicide risk to help identify social media users at high risk of suicide. We also characterized their linguistic features before and during the pandemic. Methods: We collected and analyzed post data every 6 months from March 2019 to August 2022 for users on the r/SuicideWatch subreddit (N=6163). A growth-based trajectory model was then used to investigate the trajectories of post volume to identify patterns of change in suicide risk during the pandemic. Trends in linguistic features within posts were also charted and compared, and linguistic markers were identified across the trajectory groups using regression analysis. Results: We identified 2 distinct trajectories of post volume among r/SuicideWatch subreddit users. A small proportion of users (744/6163, 12.07%) was labeled as having a high risk of suicide, showing a sharp and lasting increase in post volume during the pandemic. By contrast, most users (5419/6163, 87.93%) were categorized as being at low risk of suicide, with a consistently low and mild increase in post volume during the pandemic. In terms of the frequency of most linguistic features, both groups showed increases at the initial stage of the pandemic. Subsequently, the rising trend continued in the high-risk group before declining, while the low-risk group showed an immediate decrease. One year after the pandemic outbreak, the 2 groups exhibited differences in their use of words related to the categories of personal pronouns; affective, social, cognitive, and biological processes; drives; relativity; time orientations; and personal concerns. In particular, the high-risk group was discriminant in using words related to anger (odds ratio [OR] 3.23, P<.001), sadness (OR 3.23, P<.001), health (OR 2.56, P=.005), achievement (OR 1.67, P=.049), motion (OR 4.17, P<.001), future focus (OR 2.86, P<.001), and death (OR 4.35, P<.001) during this stage. Conclusions: Based on the 2 identified trajectories of post volume during the pandemic, this study divided users on the r/SuicideWatch subreddit into suicide high- and low-risk groups. Our findings indicated heterogeneous patterns of change in suicide risk in response to the pandemic. The high-risk group also demonstrated distinct linguistic features. We recommend conducting real-time surveillance of suicide risk using social media data during future public health crises to provide timely support to individuals at potentially high risk of suicide. %M 39115925 %R 10.2196/48907 %U https://www.jmir.org/2024/1/e48907 %U https://doi.org/10.2196/48907 %U http://www.ncbi.nlm.nih.gov/pubmed/39115925 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53404 %T Association Between Prosuicide Website Searches Through Google and Suicide Death in the United States From 2010 to 2021: Lagged Time-Series Analysis %A Kelsall,Nora Clancy %A Gimbrone,Catherine %A Olfson,Mark %A Gould,Madelyn S %A Shaman,Jeffrey %A Keyes,Katherine %+ Department of Epidemiology, Columbia University, 722 West 168th Street, Room 733, New York, NY, 10032, United States, 1 2023600113, nk3067@cumc.columbia.edu %K pro-suicide forum %K suicide %K google search %K social media %K online forum %K internet search %K death %K United States %K suicide death %K forum %K analysis %K association %K poisoning %K suffocation %D 2024 %7 26.7.2024 %9 Original Paper %J J Med Internet Res %G English %X Background:  The rate of suicide death has been increasing, making understanding risk factors of growing importance. While exposure to explicit suicide-related media, such as description of means in news reports or sensationalized fictional portrayal, is known to increase population suicide rates, it is not known whether prosuicide website forums, which often promote or facilitate information about fatal suicide means, are related to change in suicide deaths overall or by specific means. Objective:  This study aimed to estimate the association of the frequency of Google searches of known prosuicide web forums and content with death by suicide over time in the United States, by age, sex, and means of death. Methods:  National monthly Google search data for names of common prosuicide websites between January 2010 and December 2021 were extracted from Google Health Trends API (application programming interface). Suicide deaths were identified using the CDC (Centers for Disease Control and Prevention) National Vital Statistics System (NVSS), and 3 primary means of death were identified (poisoning, suffocation, and firearm). Distributed lag nonlinear models (DLNMs) were then used to estimate the lagged association between the number of Google searches on suicide mortality, stratified by age, sex, and means, and adjusted for month. Sensitivity analyses, including using autoregressive integrated moving average (ARIMA) modeling approaches, were also conducted. Results:  Months in the United States in which search rates for prosuicide websites increased had more documented deaths by intentional poisoning and suffocation among both adolescents and adults. For example, the risk of poisoning suicide among youth and young adults (age 10-24 years) was 1.79 (95% CI 1.06-3.03) times higher in months with 22 searches per 10 million as compared to 0 searches. The risk of poisoning suicide among adults aged 25-64 was 1.10 (95% CI 1.03-1.16) times higher 1 month after searches reached 9 per 10 million compared with 0 searches. We also observed that increased search rates were associated with fewer youth suicide deaths by firearms with a 3-month time lag for adolescents. These models were robust to sensitivity tests. Conclusions:  Although more analysis is needed, the findings are suggestive of an association between increased prosuicide website access and increased suicide deaths, specifically deaths by poisoning and suffocation. These findings emphasize the need to further investigate sites containing potentially dangerous information and their associations with deaths by suicide, as they may affect vulnerable individuals. %M 39059004 %R 10.2196/53404 %U https://www.jmir.org/2024/1/e53404 %U https://doi.org/10.2196/53404 %U http://www.ncbi.nlm.nih.gov/pubmed/39059004 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e53980 %T In-Person and Teleconsultation Services at a National Hospital in Peru: Time Series Analysis of General and Psychiatric Care Amid the COVID-19 Pandemic %A Villarreal-Zegarra,David %A García-Serna,Jackeline %A Segovia-Bacilio,Piero %A Mayo-Puchoc,Nikol %A Navarro-Flores,Alba %A Huarcaya-Victoria,Jeff %+ Escuela Profesional de Medicina Humana, Universidad Privada San Juan Bautista, Carretera Panamericana Sur N° 103, 113 y 123, Ica, Peru, 51 950322888, jeff.huarcaya@upsjb.edu.pe %K health care utilization %K mental health use %K COVID-19 %K mental health %K health care %K psychiatric care %K teleconsultation %K hospital %K Peru %K chronic %K patient %K patients %K telemonitoring %D 2024 %7 8.7.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: The COVID-19 pandemic led to a global reduction in health care accessibility for both infected and noninfected patients, posing a particular burden on those with chronic conditions, including mental health issues. Peru experienced significant devastation from the pandemic, resulting in a collapsed health care system and leading to the world’s highest per capita mortality rate as a result of COVID-19. Understanding the trends in health care utilization, particularly in mental health care, is crucial for informing pandemic response efforts and guiding future recovery strategies. Objective: This study aims to analyze the trends of outpatient medical and psychiatric consultations during the COVID-19 pandemic in a national hospital in Peru. Methods: This observational study was conducted at a national hospital in Lima, Peru. We analyzed data on user care across all services, including psychiatric services, from May 2019 to December 2022. The data were calculated for users served per month, including the number of users seen monthly in mental health services. Sociodemographic variables such as sex (female or male), age (≥0 years), type of medical appointment (regular or additional), and modality of care (in-person or teleconsultations) were taken into account. An interrupted time series regression model was conducted to assess the number of outpatient medical and psychiatric consultations. Subgroup analyses were performed based on service modality, including overall consultations, telemonitoring/teleconsultations only, or face-to-face only, for all service users and for mental health service users. Results: A total of 1,515,439 participants were included, with females comprising 275,444/484,994 (56.80%) of the samples. Only 345,605/1,515,439 (22.81%) visits involved telemedicine. The total monthly outpatient visits were significantly reduced compared with the expected projection (P<.001) at the beginning of the pandemic, followed by a later monthly increment of 298.7 users. Face-to-face interventions experienced a significant reduction at the beginning of the pandemic (P<.001), gradually recovering in the following months. By contrast, telemedicine use initially increased but subsequently declined toward the end of the pandemic. A similar trend was observed in mental health units. Conclusions: During the pandemic years, health care utilization in both general and psychiatric services experienced a significant decrease, particularly at the beginning of the pandemic (March 2020). However, no significant trends were observed in either case throughout the pandemic period. Telemedicine consultations witnessed a significant increase overall during this period, particularly among mental health users. %M 38976320 %R 10.2196/53980 %U https://mental.jmir.org/2024/1/e53980 %U https://doi.org/10.2196/53980 %U http://www.ncbi.nlm.nih.gov/pubmed/38976320 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e52773 %T Predicting the Population Risk of Suicide Using Routinely Collected Health Administrative Data in Quebec, Canada: Model-Based Synthetic Estimation Study %A Wang,JianLi %A Kharrat,Fatemeh Gholi Zadeh %A Gariépy,Geneviève %A Gagné,Christian %A Pelletier,Jean-François %A Massamba,Victoria Kubuta %A Lévesque,Pascale %A Mohammed,Mada %A Lesage,Alain %+ Department of Community Health and Epidemiology, Faculty of Medicine, Dalhousie University, 5790 University Ave, Halifax, NS, B3H 1V7, Canada, 1 9024736684, JianLi.Wang@dal.ca %K population risk prediction %K case-control %K development %K validation %K health administrative data %K suicide %K depression %K anxiety %K Quebec %K Canada %K mental health %K suicide prevention %K prevention %K adolescent %K adolescents %K teen %K teens %K teenager %K teenagers %K male %K female %D 2024 %7 28.6.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual’s risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed. Objective: This study aims to develop and validate prediction models for the population risk of suicide using health administrative data, considering individual-, health system–, and community-level predictors. Methods: We used a case-control study design to develop sex-specific risk prediction models for suicide, using the health administrative data in Quebec, Canada. The training data included all suicide cases (n=8899) that occurred from January 1, 2002, to December 31, 2010. The control group was a 1% random sample of living individuals in each year between January 1, 2002, and December 31, 2010 (n=645,590). Logistic regression was used to develop the prediction models based on individual-, health care system–, and community-level predictors. The developed model was converted into synthetic estimation models, which concerted the individual-level predictors into community-level predictors. The synthetic estimation models were directly applied to the validation data from January 1, 2011, to December 31, 2019. We assessed the performance of the synthetic estimation models with four indicators: the agreement between predicted and observed proportions of suicide, mean average error, root mean square error, and the proportion of correctly identified high-risk regions. Results: The sex-specific models based on individual data had good discrimination (male model: C=0.79; female model: C=0.85) and calibration (Brier score for male model 0.01; Brier score for female model 0.005). With the regression-based synthetic models applied in the validation data, the absolute differences between the synthetic risk estimates and observed suicide risk ranged from 0% to 0.001%. The root mean square errors were under 0.2. The synthetic estimation model for males correctly predicted 4 of 5 high-risk regions in 8 years, and the model for females correctly predicted 4 of 5 high-risk regions in 5 years. Conclusions: Using linked health administrative databases, this study demonstrated the feasibility and the validity of developing prediction models for the population risk of suicide, incorporating individual-, health system–, and community-level variables. Synthetic estimation models built on routinely collected health administrative data can accurately predict the population risk of suicide. This effort can be enhanced by timely access to other critical information at the population level. %M 38941610 %R 10.2196/52773 %U https://publichealth.jmir.org/2024/1/e52773 %U https://doi.org/10.2196/52773 %U http://www.ncbi.nlm.nih.gov/pubmed/38941610 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e48776 %T Investigating the Interrelationships Among Mental Health, Substance Use Disorders, and Suicidal Ideation Among Lesbian, Gay, and Bisexual Adults in the United States: Population-Based Statewide Survey Study %A Chan,Alex Siu Wing %A Tam,Hon Lon %A Wong,Florence Kwai Ching %A Wong,Gordon %A Leung,Lok Man %A Ho,Jacqueline Mei Chi %A Tang,Patrick Ming Kuen %A Yan,Elsie %+ Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, ELB704B, Hong Kong, 999077, China, 852 39439306, hltam@cuhk.edu.hk %K mental health %K adults %K lesbian, gay, and bisexual %K depression %K drug abuse %K drug dependence %K suicidality risk %K mental illness %D 2024 %7 25.6.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Mental health disparities have been documented among lesbian, gay, and bisexual (LGB) adults in the United States. Substance use disorders and suicidal ideation have been identified as important health concerns for this population. However, the interrelationships among these factors are not well understood. Objective: This study aims to investigate the interrelationships among mental health, substance use disorders, and suicidal ideation among LGB adults in the United States using a population-based statewide survey. Methods: Our study was an observational cross-sectional analysis, and the data for this study were collected from a sample of LGB adults who participated in the statewide survey. The survey collected information on mental health, substance use disorders, and suicidal ideation using validated measures. Descriptive statistics and inferential data analysis were conducted to explore the interrelationships among these factors. Results: The results showed that LGB adults who reported higher levels of depression and drug abuse and dependence also reported higher levels of suicidal tendency and mental illness. Inferential data analysis using χ2 tests revealed significant differences in depression score (χ22=458.241; P<.001), drug abuse and dependence score (χ22=226.946; P<.001), suicidal tendency score (χ22=67.795; P<.001), and mental illness score (χ22=363.722; P<.001) among the 3 sexual identity groups. Inferential data analysis showed significant associations between sexual identity and mental health outcomes, with bisexual individuals reporting the highest levels of depression, drug abuse and dependence, suicidal tendency, and mental illness. Conclusions: This study provides important insights into the interrelationships among mental health, substance use disorders, and suicidal ideation among LGB adults in the United States. The findings underscore the need for targeted interventions and research aimed at addressing the mental health needs of sexual minority populations. Future research should aim to better understand the underlying mechanisms driving these disparities and develop culturally sensitive and tailored interventions that meet the unique needs of LGB individuals. Reducing stigma and discrimination against sexual minority populations is also crucial to improving their mental health outcomes. %M 38916938 %R 10.2196/48776 %U https://publichealth.jmir.org/2024/1/e48776 %U https://doi.org/10.2196/48776 %U http://www.ncbi.nlm.nih.gov/pubmed/38916938 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e46072 %T Adherence to 24-Hour Movement Guidelines Among Chinese Older Adults: Prevalence, Correlates, and Associations With Physical and Mental Health Outcomes %A Liang,Wei %A Wang,Yanping %A Huang,Qian %A Shang,Borui %A Su,Ning %A Zhou,Lin %A Rhodes,Ryan E %A Baker,Julien Steven %A Duan,Yanping %+ Department of Sport, Physical Education and Health, Hong Kong Baptist University, 15 Baptist Road, Kowloon Tong, Hong Kong, 999077, China (Hong Kong), 852 34113038, duanyp@hkbu.edu.hk %K physical activity %K sedentary behavior %K sleep %K cardiometabolic indicators %K physical fitness %K mental health %K post–COVID-19 era %K older adults %K COVID-19 %K systolic blood pressure %K diastolic blood pressure %K depression %K loneliness %D 2024 %7 13.6.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: It is known that 24-hour movement behaviors, including physical activity (PA), sedentary behavior (SB), and sleep, are crucial components affecting older adults’ health. Canadian 24-hour movement guidelines for older adults were launched in 2020, emphasizing the combined role of these 3 movement behaviors in promoting older adults’ health. However, research on the prevalence and correlates of guideline adherence and its associations with health-related outcomes is limited, especially among Chinese older adults. Objective: This study aimed to investigate the prevalence and correlates of meeting 24-hour movement guidelines among Chinese older adults. Furthermore, this study aimed to examine the associations of guideline adherence with older adults’ physical and mental health outcomes. Methods: Using a stratified cluster random sampling approach, a total of 4562 older adults (mean age 67.68 years, SD 5.03 years; female proportion: 2544/4562, 55.8%) were recruited from the latest provincial health surveillance of Hubei China from July 25 to November 19, 2020. Measures included demographics, movement behaviors (PA, SB, and sleep), BMI, waist circumference, waist-hip ratio (WHR), percentage body fat (PBF), systolic and diastolic blood pressure, physical fitness, depressive symptoms, and loneliness. Generalized linear mixed models were employed to examine the associations between variables using SPSS 28.0 (IBM Corp). Results: Only 1.8% (83/4562) of participants met all 3 movement guidelines, while 32.1% (1466/4562), 3.4% (155/4562), and 66.4% (3031/4562) met the individual behavioral guidelines for PA, SB, and sleep, respectively. Participants who were older, were female, and lived in municipalities with lower economic levels were less likely to meet all 3 movement guidelines. Adhering to individual or combined movement guidelines was associated with greater physical fitness and lower values of BMI, waist circumference, WHR, PBF, depressive symptoms, and loneliness, with the exception of the relationship of SB+sleep guidelines with loneliness. Furthermore, only meeting SB guidelines or meeting both PA and SB guidelines was associated with lower systolic blood pressure. Conclusions: This is the first study to investigate adherence to 24-hour movement guidelines among Chinese older adults with regard to prevalence, correlates, and associations with physical and mental health outcomes. The findings emphasize the urgent need for promoting healthy movement behaviors among Chinese older adults. Future interventions to improve older adults’ physical and mental health should involve enhancing their overall movement behaviors and should consider demographic differences. %M 38869941 %R 10.2196/46072 %U https://publichealth.jmir.org/2024/1/e46072 %U https://doi.org/10.2196/46072 %U http://www.ncbi.nlm.nih.gov/pubmed/38869941 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 8 %N %P e50024 %T A Web-Based Training Program for School Staff to Respond to Self-Harm: Design and Development of the Supportive Response to Self-Harm Program %A Burn,Anne-Marie %A Hall,Poppy %A Anderson,Joanna %+ Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Forvie Site, Robinson Way, Cambridge, CB2 0SZ, United Kingdom, 44 1223336961, amb278@cam.ac.uk %K self-harm %K schools %K young people %K youth %K school staff %K training %K coproduction %K qualitative %D 2024 %7 4.6.2024 %9 Original Paper %J JMIR Form Res %G English %X Background: Self-harm is common among adolescents and is a major public health concern. School staff may be the first adults to notice a young person’s self-harm and are well placed to provide support or signpost students to help. However, school staff often report that they do not feel equipped or confident to support students. Despite the need, there is a lack of evidence-based training about self-harm for school staff. A web-based training program would provide schools with a flexible and cost-effective method of increasing staff knowledge, skills, and confidence in how to respond to students who self-harm. Objective: The main objective of this study was to coproduce an evidence-based training program for school staff to improve their skills and confidence in responding to students who self-harm (Supportive Response to Self-Harm [SORTS]). This paper describes the design and development process of an initial prototype coproduced with stakeholders to ensure that the intervention meets their requirements. Methods: Using a user-centered design and person-based approach, the SORTS prototype was informed by (1) a review of research literature, existing guidelines, and policies; (2) coproduction discussions with the technical provider and subject matter experts (mental health, education, and self-harm); (3) findings from focus groups with young people; and (4) coproduction workshops with school staff. Thematic analysis using the framework method was applied. Results: Coproduction sessions with experts and the technical provider enabled us to produce a draft of the training content, a wireframe, and example high-fidelity user interface designs. Analysis of focus groups and workshops generated four key themes: (1) need for a training program; (2) acceptability, practicality, and implementation; (3) design, content, and navigation; and (4) adaptations and improvements. The findings showed that there is a clear need for a web-based training program about self-harm in schools, and the proposed program content and design were useful, practical, and acceptable. Consultations with stakeholders informed the iterative development of the prototype. Conclusions: SORTS is a web-based training program for school staff to appropriately respond to students who self-harm that is based on research evidence and developed in collaboration with stakeholders. The SORTS program will equip school staff with the skills and strategies to respond in a supportive way to students who self-harm and encourage schools to adopt a whole-school approach to self-harm. Further research is needed to complete the intervention development based on the feedback from this study and evaluate the program’s effectiveness. If found to be effective, the SORTS program could be implemented in schools and other youth organizations. %M 38833286 %R 10.2196/50024 %U https://formative.jmir.org/2024/1/e50024 %U https://doi.org/10.2196/50024 %U http://www.ncbi.nlm.nih.gov/pubmed/38833286 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e49790 %T Relationship Between Physical Exercise and Cognitive Function Among Older Adults in China: Cross-Sectional Population-Based Study %A Wang,Fubaihui %A Gao,Changqing %A Wang,Yantao %A Li,Zhuo %A Zheng,Feiran %A Luo,Yanan %+ Department of Global Health, School of Public Health, Peking University, No 38 Xuyuan Road, Haidian District, Beijing, 100191, China, 86 18519621115, luoyanan@bjmu.edu.cn %K cognitive function %K exercise %K physical activity %K mindfulness %K cognitive exercise %K mind stimulation %K dementia treatment %K cognitive intervention %K cognitive treatment %D 2024 %7 30.5.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The existing literature reveals several significant knowledge gaps that hinder health care providers in formulating exercise prescriptions for cognitive health. Objective: This study endeavors to elucidate the relationship between the level of physical activity and cognitive function in older adults in China. Moreover, it seeks to explore the associations between distinct exercise behaviors—such as exercise types, the purpose motivating engagement in exercise, the accessibility of exercise fields, and the inclination toward exercise—and cognitive function. Methods: Using data from the China Longitudinal Aging Social Survey (CLASS conducted in 2016, cognitive function was meticulously assessed through the modified Chinese version of the Mini-Mental State Examination, encompassing measures of orientation, memory, and calculation. Using self-report structured questionnaires, a myriad of information about physical activity during leisure time, exercise engagement, exercise intensity, primary exercise types, reasons for exercise participation, availability of sports facilities, and exercise willingness was diligently gathered. Robust ordinary least squares regression models were then used to compute coefficients along with 95% CIs. Results: A discernible inverted U-shaped trend in cognitive scores emerged as the level of physical activity surpassed the threshold of 500 metabolic equivalents of task (MET) minutes per week. Notably, individuals with a physical activity level between 500 and 999 MET minutes per week exhibited a coefficient of 0.31 (95% CI 0.09 to 0.54), those with a physical activity level between 1000 and 1499 MET minutes per week displayed a coefficient of 0.75 (95% CI 0.52 to 0.97), and those with a physical activity level above 1500 MET minutes per week demonstrated a coefficient of 0.45 (95% CI 0.23 to 0.68). Older individuals engaging in exercise at specific MET levels showcased superior cognitive function compared to their inactive counterparts. Furthermore, individuals driven by exercise motivations aimed at enhancing physical fitness and health, as well as those using sports facilities or public spaces for exercise, exhibited notably higher cognitive function scores. Conclusions: The findings underscore the potential of exercise as a targeted intervention for the prevention and treatment of dementia or cognitive decline associated with aging in older individuals. Leveraging these insights to formulate informed exercise recommendations holds promise in addressing a significant public health challenge linked to aging populations. %M 38815262 %R 10.2196/49790 %U https://publichealth.jmir.org/2024/1/e49790 %U https://doi.org/10.2196/49790 %U http://www.ncbi.nlm.nih.gov/pubmed/38815262 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e44827 %T An Accessible Web-Based Survey to Monitor the Mental Health of People With Mild Intellectual Disability or Low Literacy Skills During the COVID-19 Pandemic: Comparative Data Analysis %A Koks-Leensen,Monique CJ %A Menko,Anouk %A Raaijmakers,Fieke %A Fransen-Kuppens,Gerdine AJ %A Bevelander,Kirsten E %+ Department of Primary and Community Care, Radboud university medical center, Geert Grooteplein 21, Nijmegen, 6525 EZ, Netherlands, 31 243618181, monique.koks-leensen@radboudumc.nl %K monitoring %K mental health %K intellectual disabilities %K low literacy %K COVID-19 %K web-based survey %D 2024 %7 30.5.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The COVID-19 pandemic and related control measures affected the mental health of all populations. Particular subgroups are underrepresented in mainstream surveys because they are hard to reach, and study measurements are not adapted to their skills. These subgroups include people with lower cognitive and literacy skills, such as people with mild intellectual disability (MID), who were considered vulnerable during the COVID-19 pandemic given their low socioeconomic status, small social networks, increased risks of health problems, and difficulties understanding health-related information. Objective: This study examines the impact of the COVID-19 pandemic on mental health among people with MID or low literacy skills compared with those predominantly represented in national surveys. Methods: A repeated cross-sectional study of people with MID or low literacy skills and a general population sample was conducted in the Netherlands. An easy-read web-based survey was co-designed with, and tested among, people with MID or low literacy skills and conducted in 3 rounds within 1 year of the COVID-19 pandemic (T1: November to December 2020, T2: March to April 2021, and T3: September to October 2021). The survey contained questions about demographics and 6 aspects of mental health: feeling happy, feeling energized, feeling stressed, worry, feeling lonely, and sleeping problems. Results: Our adapted survey and recruitment procedure enabled 1059 persons with MID or low literacy skills to participate (T1: n=412, 38.9%; T2: n=351, 33.1%; and T3: n=296, 28%). They were significantly younger, had a lower level of education, and more often than not were born outside the Netherlands compared to the general population sample (P<.001). Approximately half of them (604/1059, 57.03%) received professional care. They displayed poorer mental health scores than the general population sample. The percentages of people with MID or low literacy skills who reported more negative feelings in T1 ranged from 20.6% (85/412) reporting feeling lonely often or almost always to 57.8% (238/412) reporting feeling happy almost never or sometimes. The general population sample’s percentages were 5.4% (160/2930) and 32.2% (941/2918), respectively. Although scores improved over time in both populations, the disproportional effects remained. Conclusions: General COVID-19–related restrictions for the entire Dutch population affected people with MID or low literacy skills more negatively than the general population. Our study underscores the relevance of including these subpopulations in public health research because they are often overlooked in regular health data. An accessible web-based survey particularly targeted at this population enabled us to do so, and we reached a group of respondents significantly different from regular survey participants. This survey’s results provided insights into the health of people with MID or low literacy skills and gained knowledge to be used by care organizations and policy makers to reduce health disparities during a pandemic and in general. %M 38607229 %R 10.2196/44827 %U https://publichealth.jmir.org/2024/1/e44827 %U https://doi.org/10.2196/44827 %U http://www.ncbi.nlm.nih.gov/pubmed/38607229 %0 Journal Article %@ 2561-6722 %I %V 7 %N %P e57041 %T Social Media Use and Serious Psychological Distress Among Adolescents %A Shimkhada,Riti %A Ponce,Ninez A %K social media %K socials %K youth %K adolescents %K teens %K teenager %K mental health %K mental illness %K mental disease %K mental illnesses %K psychological distress %K psychological %K psychology %D 2024 %7 23.5.2024 %9 %J JMIR Pediatr Parent %G English %X This Research Letter describes the increasing trend of almost-constant social media use among California adolescents and the association with serious psychological distress, focusing on the influence of familial and experiential factors. %R 10.2196/57041 %U https://pediatrics.jmir.org/2024/1/e57041 %U https://doi.org/10.2196/57041 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e53968 %T User Dynamics and Thematic Exploration in r/Depression During the COVID-19 Pandemic: Insights From Overlapping r/SuicideWatch Users %A Zhu,Jianfeng %A Jin,Ruoming %A Kenne,Deric R %A Phan,NhatHai %A Ku,Wei-Shinn %+ Department of Computer Science, Kent State University, 800 E. Summit St., Kent, OH, 44242, United States, 1 3306729980, jzhu10@kent.edu %K reddit %K natural language processing %K NLP %K suicidal ideation %K SI %K online communities %K depression symptoms %K COVID-19 pandemic %K bidirectional encoder representations from transformers %K BERT %K r/SuicideWatch %K r/Depression %D 2024 %7 20.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: In 2023, the United States experienced its highest- recorded number of suicides, exceeding 50,000 deaths. In the realm of psychiatric disorders, major depressive disorder stands out as the most common issue, affecting 15% to 17% of the population and carrying a notable suicide risk of approximately 15%. However, not everyone with depression has suicidal thoughts. While “suicidal depression” is not a clinical diagnosis, it may be observed in daily life, emphasizing the need for awareness. Objective: This study aims to examine the dynamics, emotional tones, and topics discussed in posts within the r/Depression subreddit, with a specific focus on users who had also engaged in the r/SuicideWatch community. The objective was to use natural language processing techniques and models to better understand the complexities of depression among users with potential suicide ideation, with the goal of improving intervention and prevention strategies for suicide. Methods: Archived posts were extracted from the r/Depression and r/SuicideWatch Reddit communities in English spanning from 2019 to 2022, resulting in a final data set of over 150,000 posts contributed by approximately 25,000 unique overlapping users. A broad and comprehensive mix of methods was conducted on these posts, including trend and survival analysis, to explore the dynamic of users in the 2 subreddits. The BERT family of models extracted features from data for sentiment and thematic analysis. Results: On August 16, 2020, the post count in r/SuicideWatch surpassed that of r/Depression. The transition from r/Depression to r/SuicideWatch in 2020 was the shortest, lasting only 26 days. Sadness emerged as the most prevalent emotion among overlapping users in the r/Depression community. In addition, physical activity changes, negative self-view, and suicidal thoughts were identified as the most common depression symptoms, all showing strong positive correlations with the emotion tone of disappointment. Furthermore, the topic “struggles with depression and motivation in school and work” (12%) emerged as the most discussed topic aside from suicidal thoughts, categorizing users based on their inclination toward suicide ideation. Conclusions: Our study underscores the effectiveness of using natural language processing techniques to explore language markers and patterns associated with mental health challenges in online communities like r/Depression and r/SuicideWatch. These insights offer novel perspectives distinct from previous research. In the future, there will be potential for further refinement and optimization of machine classifications using these techniques, which could lead to more effective intervention and prevention strategies. %M 38767953 %R 10.2196/53968 %U https://www.jmir.org/2024/1/e53968 %U https://doi.org/10.2196/53968 %U http://www.ncbi.nlm.nih.gov/pubmed/38767953 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 26 %N %P e55913 %T Machine Learning–Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study %A Kim,Hyejun %A Son,Yejun %A Lee,Hojae %A Kang,Jiseung %A Hammoodi,Ahmed %A Choi,Yujin %A Kim,Hyeon Jin %A Lee,Hayeon %A Fond,Guillaume %A Boyer,Laurent %A Kwon,Rosie %A Woo,Selin %A Yon,Dong Keon %+ Center for Digital Health, Medical Science Research Institute, Kyung Hee University College of Medicine, 23 Kyungheedae–ro, Dongdaemun–gu, Seoul, 02447, Republic of Korea, 82 2 6935 2476, yonkkang@gmail.com %K adolescent %K machine learning %K Shapley additive explanations %K SHAP value %K suicidal thinking %K XGBoost %K mental health %K predictive model %K risk behavior %D 2024 %7 17.5.2024 %9 Original Paper %J J Med Internet Res %G English %X Background: Suicide is the second-leading cause of death among adolescents and is associated with clusters of suicides. Despite numerous studies on this preventable cause of death, the focus has primarily been on single nations and traditional statistical methods. Objective: This study aims to develop a predictive model for adolescent suicidal thinking using multinational data sets and machine learning (ML). Methods: We used data from the Korea Youth Risk Behavior Web-based Survey with 566,875 adolescents aged between 13 and 18 years and conducted external validation using the Youth Risk Behavior Survey with 103,874 adolescents and Norway’s University National General Survey with 19,574 adolescents. Several tree-based ML models were developed, and feature importance and Shapley additive explanations values were analyzed to identify risk factors for adolescent suicidal thinking. Results: When trained on the Korea Youth Risk Behavior Web-based Survey data from South Korea with a 95% CI, the XGBoost model reported an area under the receiver operating characteristic (AUROC) curve of 90.06% (95% CI 89.97-90.16), displaying superior performance compared to other models. For external validation using the Youth Risk Behavior Survey data from the United States and the University National General Survey from Norway, the XGBoost model achieved AUROCs of 83.09% and 81.27%, respectively. Across all data sets, XGBoost consistently outperformed the other models with the highest AUROC score, and was selected as the optimal model. In terms of predictors of suicidal thinking, feelings of sadness and despair were the most influential, accounting for 57.4% of the impact, followed by stress status at 19.8%. This was followed by age (5.7%), household income (4%), academic achievement (3.4%), sex (2.1%), and others, which contributed less than 2% each. Conclusions: This study used ML by integrating diverse data sets from 3 countries to address adolescent suicide. The findings highlight the important role of emotional health indicators in predicting suicidal thinking among adolescents. Specifically, sadness and despair were identified as the most significant predictors, followed by stressful conditions and age. These findings emphasize the critical need for early diagnosis and prevention of mental health issues during adolescence. %M 38758578 %R 10.2196/55913 %U https://www.jmir.org/2024/1/e55913 %U https://doi.org/10.2196/55913 %U http://www.ncbi.nlm.nih.gov/pubmed/38758578 %0 Journal Article %@ 2291-5222 %I %V 12 %N %P e53596 %T User Experience of Persons Using Ingestible Sensor–Enabled Pre-Exposure Prophylaxis to Prevent HIV Infection: Cross-Sectional Survey Study %A Browne,Sara %A Umlauf,Anya %A Moore,David J %A Benson,Constance A %A Vaida,Florin %K ingestible sensor %K sensor %K sensors %K oral %K UX %K user experience %K HIV prevention %K medication adherence %K HIV %K prevention %K prophylaxis %K STI %K STD %K sexually transmitted %K sexual transmission %K drug %K drugs %K pharmacy %K pharmacies %K pharmacology %K pharmacotherapy %K pharmaceutic %K pharmaceutics %K pharmaceuticals %K pharmaceutical %K medication %K medications %K adherence %K compliance %K sexually transmitted infection %K sexually transmitted disease %D 2024 %7 3.5.2024 %9 %J JMIR Mhealth Uhealth %G English %X Background: A digital health technology’s success or failure depends on how it is received by users. Objectives: We conducted a user experience (UX) evaluation among persons who used the Food and Drug Administration–approved Digital Health Feedback System incorporating ingestible sensors (ISs) to capture medication adherence, after they were prescribed oral pre-exposure prophylaxis (PrEP) to prevent HIV infection. We performed an association analysis with baseline participant characteristics, to see if “personas” associated with positive or negative UX emerged. Methods: UX data were collected upon exit from a prospective intervention study of adults who were HIV negative, prescribed oral PrEP, and used the Digital Health Feedback System with IS-enabled tenofovir disoproxil fumarate plus emtricitabine (IS-Truvada). Baseline demographics; urine toxicology; and self-report questionnaires evaluating sleep (Pittsburgh Sleep Quality Index), self-efficacy, habitual self-control, HIV risk perception (Perceived Risk of HIV Scale 8-item), and depressive symptoms (Patient Health Questionnaire–8) were collected. Participants with ≥28 days in the study completed a Likert-scale UX questionnaire of 27 questions grouped into 4 domain categories: overall experience, ease of use, intention of future use, and perceived utility. Means and IQRs were computed for participant total and domain subscores, and linear regressions modeled baseline participant characteristics associated with UX responses. Demographic characteristics of responders versus nonresponders were compared using the Fisher exact and Wilcoxon rank-sum tests. Results: Overall, 71 participants were enrolled (age: mean 37.6, range 18-69 years; n=64, 90% male; n=55, 77% White; n=24, 34% Hispanic; n=68, 96% housed; and n=53, 75% employed). No demographic differences were observed in the 63 participants who used the intervention for ≥28 days. Participants who completed the questionnaire were more likely to be housed (52/53, 98% vs 8/10, 80%; P=.06) and less likely to have a positive urine toxicology (18/51, 35% vs 7/10, 70%; P=.08), particularly methamphetamine (4/51, 8% vs 4/10, 40%; P=.02), than noncompleters. Based on IQR values, ≥75% of participants had a favorable UX based on the total score (median 3.78, IQR 3.17-4.20), overall experience (median 4.00, IQR 3.50-4.50), ease of use (median 3.72, IQR 3.33-4.22), and perceived utility (median 3.72, IQR 3.22-4.25), and ≥50% had favorable intention of future use (median 3.80, IQR 2.80-4.40). Following multipredictor modeling, self-efficacy was significantly associated with the total score (0.822, 95% CI 0.405-1.240; P<.001) and all subscores (all P<.05). Persons with more depressive symptoms reported better perceived utility (P=.01). Poor sleep was associated with a worse overall experience (−0.07, 95% CI −0.133 to −0.006; P=.03). Conclusions: The UX among persons using IS-enabled PrEP (IS-Truvada) to prevent HIV infection was positive. Association analysis of baseline participant characteristics linked higher self-efficacy with positive UX, more depressive symptoms with higher perceived utility, and poor sleep with negative UX. Trial Registration: ClinicalTrials.gov NCT03693040; https://clinicaltrials.gov/study/NCT03693040 %R 10.2196/53596 %U https://mhealth.jmir.org/2024/1/e53596 %U https://doi.org/10.2196/53596 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e47428 %T Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation %A Zhu,Yue %A Zhang,Ran %A Yin,Shuluo %A Sun,Yihui %A Womer,Fay %A Liu,Rongxun %A Zeng,Sheng %A Zhang,Xizhe %A Wang,Fei %+ Early Intervention Unit, Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 264 Guangzhou Road, Gulou District, Nanjing City, China, Nanjing, 210000, China, 1 86 02583295953, zhangxizhe@njmu.edu.cn %K dietary behaviors %K digital marker %K depression %K mental health %K appetite disturbance %K behavioral monitoring %K eating pattern %K electronic record %K digital health %K behavioral %K surveillance %D 2024 %7 22.4.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device–based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings. Objective: The study aims to characterize digital dietary behaviors in depression, and to determine whether these behaviors could be used to detect depression. Methods: A total of 3310 students (2222 healthy controls [HCs], 916 with mild depression, and 172 with moderate-severe depression) were recruited for the study of their dietary behaviors via electronic records over a 1-month period, and depression severity was assessed in the middle of the month. The differences in dietary behaviors across the HCs, mild depression, and moderate-severe depression were determined by ANCOVA (analyses of covariance) with age, gender, BMI, and educational level as covariates. Multivariate logistic regression analyses were used to examine the association between dietary behaviors and depression severity. Support vector machine analysis was used to determine whether changes in dietary behaviors could detect mild and moderate-severe depression. Results: The study found that individuals with moderate-severe depression had more irregular eating patterns, more fluctuated feeding times, spent more money on dinner, less diverse food choices, as well as eating breakfast less frequently, and preferred to eat only lunch and dinner, compared with HCs. Moderate-severe depression was found to be negatively associated with the daily 3 regular meals pattern (breakfast-lunch-dinner pattern; OR 0.467, 95% CI 0.239-0.912), and mild depression was positively associated with daily lunch and dinner pattern (OR 1.460, 95% CI 1.016-2.100). These changes in digital dietary behaviors were able to detect mild and moderate-severe depression (accuracy=0.53, precision=0.60), with better accuracy for detecting moderate-severe depression (accuracy=0.67, precision=0.64). Conclusions: This is the first study to develop a profile of changes in digital dietary behaviors in individuals with depression using real-world behavioral monitoring. The results suggest that digital markers may be a promising approach for detecting depression. %M 38648087 %R 10.2196/47428 %U https://publichealth.jmir.org/2024/1/e47428 %U https://doi.org/10.2196/47428 %U http://www.ncbi.nlm.nih.gov/pubmed/38648087 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 11 %N %P e50136 %T Time-Varying Network Models for the Temporal Dynamics of Depressive Symptomatology in Patients With Depressive Disorders: Secondary Analysis of Longitudinal Observational Data %A Siepe,Björn Sebastian %A Sander,Christian %A Schultze,Martin %A Kliem,Andreas %A Ludwig,Sascha %A Hegerl,Ulrich %A Reich,Hanna %+ Psychological Methods Lab, Department of Psychology, University of Marburg, Gutenbergstraße 18, Marburg, 35032, Germany, 49 6421 28 23616, bjoern.siepe@uni-marburg.de %K depression %K time series analysis %K network analysis %K experience sampling %K idiography %K time varying %K mobile phone %D 2024 %7 18.4.2024 %9 Original Paper %J JMIR Ment Health %G English %X Background: As depression is highly heterogenous, an increasing number of studies investigate person-specific associations of depressive symptoms in longitudinal data. However, most studies in this area of research conceptualize symptom interrelations to be static and time invariant, which may lead to important temporal features of the disorder being missed. Objective: To reveal the dynamic nature of depression, we aimed to use a recently developed technique to investigate whether and how associations among depressive symptoms change over time. Methods: Using daily data (mean length 274, SD 82 d) of 20 participants with depression, we modeled idiographic associations among depressive symptoms, rumination, sleep, and quantity and quality of social contacts as dynamic networks using time-varying vector autoregressive models. Results: The resulting models showed marked interindividual and intraindividual differences. For some participants, associations among variables changed in the span of some weeks, whereas they stayed stable over months for others. Our results further indicated nonstationarity in all participants. Conclusions: Idiographic symptom networks can provide insights into the temporal course of mental disorders and open new avenues of research for the study of the development and stability of psychopathological processes. %M 38635978 %R 10.2196/50136 %U https://mental.jmir.org/2024/1/e50136 %U https://doi.org/10.2196/50136 %U http://www.ncbi.nlm.nih.gov/pubmed/38635978 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e50996 %T Association Between Frequency of Muscle-Strengthening Exercise and Depression Symptoms Among Middle and High School Students: Cross-Sectional Survey Study %A Wang,Hao %A Du,Huaidong %A Guan,Yunqi %A Zhong,Jieming %A Li,Na %A Pan,Jin %A Yu,Min %+ Department of Noncommunicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, 3399 Binsheng Road, Binjiang Distric, Hangzhou, 310051, China, 86 571 87115005, zjcdcmyu@163.com %K depression symptoms %K muscle-strengthening exercise %K adolescents %K cross-sectional study %D 2024 %7 17.4.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Existing literature on the association between the frequency of muscle-strengthening exercise (MSE) and depression among adolescents is limited and contradictory. Objective: This study aimed to elucidate the association of MSE frequency with depression symptoms among middle and high school students in China. Methods: A total of 27,070 students in grades 7-12 from 376 middle and high schools were surveyed using an anonymous self-administered questionnaire between April and June 2022. Information on engaging in MSE was self-reported, and depression symptoms were assessed using the Patient Health Questionnaire-9 (PHQ-9). Poisson regression was used to examine the association between MSE frequency and depression symptoms. Results: Among the 27,006 eligible students, 51.6% (n=13,933) were boys, and the mean age was 15.6 (SD 1.7) years. The overall prevalence of meeting MSE recommendations (ie, engaging in MSE ≥3 days/week) was 34.6% (95% CI 32.6%-36.6%; n=9145); the prevalence was higher in boys (43.8%, 95% CI 41.8%-45.8%; 6067/13,933) than in girls (24.3%, 95% CI 22%-26.6%; 3078/13,073; P<.001). A total of 5882 (21.8%) students reported having depression symptoms. After adjustment for sociodemographic status, lifestyle factors, academic performance, and experience of physical fighting, compared to students who did not engage in MSE, the prevalence ratios (PRs) for depression symptoms were 0.98 (95% CI 0.97-0.99) for those engaging in MSE once a week, 0.95 (95% CI 0.93-0.97) for 2 days/week, 0.93 (95% CI 0.90-0.96) for 3 days/week, 0.90 (95% CI 0.87-0.94) for 4 days/week, 0.88 (95% CI 0.84-0.93) for 5 days/week, 0.86 (95% CI 0.81-0.92) for 6 days/week, and 0.84 (95% CI 0.78-0.90) for 7 days/week, respectively. Conclusions: The overall prevalence of meeting MSE recommendations among Chinese adolescents is low. The frequency of MSE was inversely associated with depression symptoms. %M 38630529 %R 10.2196/50996 %U https://publichealth.jmir.org/2024/1/e50996 %U https://doi.org/10.2196/50996 %U http://www.ncbi.nlm.nih.gov/pubmed/38630529 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 10 %N %P e48685 %T Digital Health Literacy of the Population in Germany and Its Association With Physical Health, Mental Health, Life Satisfaction, and Health Behaviors: Nationally Representative Survey Study %A König,Lars %A Kuhlmey,Adelheid %A Suhr,Ralf %+ Institut für Medizinische Soziologie und Rehabilitationswissenschaft, Charité – Universitätsmedizin Berlin, Charitéplatz 1, Berlin, 10117, Germany, 49 30419549262, lars.koenig@charite.de %K digital health %K digital health literacy %K eHealth %K eHealth literacy %K health behaviors %K health literacy %K life satisfaction %K mental health %K physical health %K representative survey %D 2024 %7 21.2.2024 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Digital health literacy, also known as eHealth literacy, describes the ability to seek, find, understand, and apply health information from the internet to address health problems. The World Health Organization calls for actions to improve digital health literacy. To develop target group–specific digital health literacy interventions, it is necessary to know the digital health literacy of the general population and relevant subgroups. Objective: This study aims to representatively assess the digital health literacy of the population in Germany and relevant subgroups. The results are meant to facilitate the development of target group–specific digital health literacy interventions. Additionally, this study further explores the associations between digital health literacy and physical health, mental health, life satisfaction, and diverse health behaviors. Methods: Study participants were drawn from a representative panel of the German-speaking population with internet access. To further increase the representativeness of the sample, survey weights were calculated using an iterative proportional fitting procedure. Participants answered a series of questionnaires regarding their digital health literacy, physical health, mental health, life satisfaction, and diverse health behaviors. Two-sided independent sample t tests were conducted to determine the significant differences between societal subgroups. Pearson correlation coefficients were calculated to explore the correlates of digital health literacy. Results: Digital health literacy is unevenly distributed within German society. The results of this study suggest that people with a low level of formal education and people with a low social status would benefit from digital health literacy interventions that address their competencies in the domains of information seeking and information appraisal. Furthermore, the results suggest that older people would likely benefit from digital health literacy interventions that address their competencies in the domains of information seeking and also information appraisal. Regarding sex, this study suggests that men might benefit from digital health literacy interventions that specifically address their competencies in the domain of information seeking. Furthermore, digital health literacy is weakly positively correlated with physical health, mental health, life satisfaction, exercise routines, fruit consumption, and vegetable consumption. Conclusions: Overall, the results of this study demonstrate that digital health literacy is associated with diverse health outcomes and behaviors. Furthermore, the results provide a starting point for the development of target group–specific digital health literacy interventions. %M 38381497 %R 10.2196/48685 %U https://publichealth.jmir.org/2024/1/e48685 %U https://doi.org/10.2196/48685 %U http://www.ncbi.nlm.nih.gov/pubmed/38381497 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 13 %N %P e51820 %T Fatigue and Mental Illness Symptoms in Long COVID: Protocol for a Prospective Cohort Multicenter Observational Study %A Pires,Ligia %A Reis,Cláudia %A Mesquita Facão,Ana Rita %A Moniri,Armin %A Marreiros,Ana %A Drummond,Marta %A Berger-Estilita,Joana %+ Institute of Anaesthesiology and Intensive Care, Salem Spital, Hirslanden Medical Group, Schänzlistrasse 39, Bern, 3013, Switzerland, 41 788438161, joanamberger@gmail.com %K SARS-CoV-2 %K coronavirus %K COVID %K long COVID %K fatigue %K tired %K tiredness %K anxiety %K depression %K PTSD %K stress %K quality of life %K mental health %K post-COVID-condition %K neuropsychological %K neuropsychology %K psychological %K long COVID-19 %K COVID-19 %K myalgia %K correlation %K impairment %D 2024 %7 19.1.2024 %9 Protocol %J JMIR Res Protoc %G English %X Background: The aftermath of the COVID-19 pandemic continues to affect millions worldwide, resulting in persisting postvirus complaints and impacting peoples’ quality of life. Long COVID, characterized by lingering symptoms like fatigue and mental illness, can extend beyond a few months, necessitating further research to understand its implications. Objective: This study aims to quantify the degree of physical and psychological fatigue in patients following COVID-19 infection and examine its correlation with mental health disorders. Methods: Using a consecutive nonrandom sampling technique, we will conduct a prospective cohort multicenter observational study in 5 Portuguese hospitals. Symptomatic adult patients with previous COVID-19 attending follow-up consultations will be enrolled. We will include patients who had mild, moderate, and severe acute disease. We will assess clinical outcomes related to COVID-19, including the type of respiratory support such as high-flow nasal cannula, noninvasive ventilation, and invasive mechanical ventilation. The exclusion criteria will include previous severe psychiatric disorders confirmed by a psychiatrist; refusal or inability to respond to the questionnaire; concomitant neurological disorder; persistent fatigue symptoms during the 6 months before infection; and the need for invasive mechanical ventilation during COVID-19 infection due to a high prevalence of postintensive care syndrome. Our primary outcome is the prevalence of fatigue in patients with post–COVID-19 depression and/or anxiety, as measured by the Chalder Fatigue Scale (CFQ-11) and the Hospital Anxiety and Depression Scale (HADS). The secondary outcomes will include an assessment of health-related quality of life via the EQ-5D questionnaire and an exploration of the prevalence of symptoms of posttraumatic stress disorder (PTSD) using the 14-item Posttraumatic Stress Scale (PTSS-14). We will also examine the association between mental health symptoms and the severity of acute COVID-19. The post–COVID-19 data will be collected at least 6 months after the positive test and no longer than 9 months during the clinical appointment. Results: We expect our multicenter study on patients post COVID-19 to reveal a significant link between mental illness symptoms and both physical and psychological fatigue. Patients with heightened depression and anxiety may report increased levels of fatigue. Additionally, we expect to find persistent PTSD symptoms in a subset of participants, indicating the enduring psychological impact of the virus. Conclusions: This study may underscore the need for integrated care addressing physical and mental health in patients post COVID-19. The observed connections emphasize the importance of considering mental well-being for long-term health outcomes. Despite study limitations, our findings contribute valuable insights for future treatment strategies and highlight the necessity for comprehensive mental health support in post–COVID-19 care. This research provides valuable insights into the mental health implications of COVID-19 and its impact on post–COVID-19 fatigue and the overall well-being of affected individuals. Trial Registration: ClinicalTrials.gov NCT05323318; https://clinicaltrials.gov/study/NCT05323318 International Registered Report Identifier (IRRID): DERR1-10.2196/51820 %M 38241071 %R 10.2196/51820 %U https://www.researchprotocols.org/2024/1/e51820 %U https://doi.org/10.2196/51820 %U http://www.ncbi.nlm.nih.gov/pubmed/38241071 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 9 %N %P e42469 %T Association of Catastrophic Health Expenditure With the Risk of Depression in Chinese Adults: Population-Based Cohort Study %A Wang,Yaping %A Liang,Wannian %A Liu,Min %A Liu,Jue %+ Department of Epidemiology and Biostatistics, School of Public Health, Peking University, No. 38 Xueyuan Road, Haidian District, Beijing, 100191, China, 86 10 8 2805146, liumin@bjmu.edu.cn %K catastrophic health expenditure %K depression %K universal health coverage %K economic burden %K socioeconomic status %D 2023 %7 15.8.2023 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Depression is one of the most common mental illnesses, and it may have a lasting effect on one’s whole life. As a form of financial hardship, catastrophic health expenditure (CHE) may be associated with depression. However, current evidence about the relationship between CHE and the risk of depression is insufficient. Objective: This study aimed to explore the relationship between CHE and the risk of depression among Chinese adults. Methods: In this study, we used 3 waves of the China Family Panel Studies (CFPS) from 2012, 2016, and 2018. The CFPS are a nationally representative study covering 25 of 31 provinces in Chinese mainland and representing nearly 94.5% of the total population. We selected eligible household heads as participants, divided them into 2 groups by CHE events at baseline (exposed group: with CHE; unexposed group: without CHE), and followed them up. Households with CHE were defined as having out-of-pocket medical expenditures exceeding 40% of the total household nonfood expenditure, and people with depression were identified by the 8-item Centre for Epidemiological Studies Depression Scale (CES-D). We first described the baseline characteristics and used logistical regression to estimate their effects on CHE events. Then, we used Cox proportional hazard models to estimate adjusted hazard ratios and 95% CIs of depression among participants with CHE compared with those without CHE. Finally, we analyzed the subgroup difference in the association between CHE and depression. Results: Of a total of 13,315 households, 9629 were eligible for analysis. Among them, 6824 (70.9%) were men. The mean age was 50.15 (SD 12.84) years. Only 987 (10.3%) participants had no medical insurance. The prevalence of CHE at baseline was 12.9% (1393/9629). Participants with a higher family economic level (adjusted odds ratio [aOR] 1.15, 95% CI 1.02-1.31) and with the highest socioeconomic development level (aOR 1.18, 95% CI 1.04-1.34) had a higher prevalence of CHE than reference groups. During a median of 71 (IQR 69-72) person-months of follow-up, the depression incidence of participants with CHE (1.41 per 1000 person-months) was higher than those without CHE (0.73 per 1000 person-months). Multivariable models revealed that the adjusted hazard ratio for the incidence of depression in participants with CHE was 1.33 (95% CI 1.08-1.64), and this association appeared to be greater in participants without outpatient services (for interaction, P=.048). Conclusions: CHE was significantly associated with increased risk of depression among Chinese adults. Concentrated work should be done to monitor CHE, and more efforts to ensure financial protection need to be made to prevent depression, especially for people with high health care needs. %M 37581926 %R 10.2196/42469 %U https://publichealth.jmir.org/2023/1/e42469 %U https://doi.org/10.2196/42469 %U http://www.ncbi.nlm.nih.gov/pubmed/37581926 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 9 %N %P e46289 %T Association Between Comorbid Anxiety and Depression and Health Risk Behaviors Among Chinese Adolescents: Cross-Sectional Questionnaire Study %A Wang,Meng %A Mou,Xingyue %A Li,Tingting %A Zhang,Yi %A Xie,Yang %A Tao,Shuman %A Wan,Yuhui %A Tao,Fangbiao %A Wu,Xiaoyan %+ Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81, Meishan Road, Shushan District, Hefei, 230032, China, 86 551 65161168, xywu@ahmu.edu.cn %K health risk behaviors %K anxiety %K depression %K comorbidity %K adolescent %K mental health %K children %K intervention %K lifestyle behavior %K mental disorder %K public health %K cross-sectional study %D 2023 %7 5.7.2023 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Comorbidity of psychiatric disorders such as depression and anxiety is very common among children and adolescents. Few studies have examined how comorbid anxiety and depression are associated with health risk behaviors (HRBs) in adolescents, which could inform preventative approaches for mental health. Objective: We evaluated the association between HRBs and comorbid anxiety and depression in a large adolescent cohort. Methods: We used data from 22,868 adolescents in the National Youth Cohort (China). Anxiety and depression symptoms were assessed using the 9-item Patient Health Questionnaire scale and the 7-item Generalized Anxiety Disorder scale, respectively. Comorbidity was determined by the coexistence of anxiety and depression. HRBs including poor diet, smoking, physical inactivity, and poor sleep, as well as the above HRB scores, were added to obtain the total HRB score (HRB risk index). Based on single and total HRB scores, we divided participants into low-, medium-, and high-risk groups. Potential confounders included gender, presence of siblings, regional economic level, educational status, self-rated health, parental education level, self-reported family income, number of friends, learning burden, and family history of psychosis. Correlation analysis was used to explore associations between single risk behaviors. Binary logistic regression estimated the association between HRBs and anxiety-depression comorbidity before and after adjusting for potential confounders. Results: The comorbidity rate of anxiety and depression among Chinese adolescents was 31.6% (7236/22,868). There was a statistically significant association between each HRB (P<.05), and HRBs were positively associated with comorbid anxiety and depression in the above population. For single HRBs, adolescents with poor diet, smoking, and poor sleep (medium-risk) were more prone to anxiety-depression comorbidity after adjusting for confounders compared to low-risk adolescents. However, adolescents with all high-risk HRBs were more likely to have comorbid anxiety and depression after adjusting for confounders (poor diet odds ratio [OR] 1.50, 95% CI 1.39-1.62; smoking OR 2.17, 95% CI 1.67-2.81; physical inactivity OR 1.16, 95% CI 1.06-1.28; poor sleep OR 1.84, 95% CI 1.70-2.01). Moreover, in both unadjusted (medium risk OR 1.79, 95% CI 1.56-2.05; high risk OR 3.09, 95% CI 2.72-3.52) and adjusted (medium risk OR 1.57, 95% CI 1.37-1.80; high risk OR 2.33, 95% CI 2.03-2.68) models, HRB risk index, like clustered HRBs, was positively associated with anxiety-depression comorbidity, and the strength of the association was stronger than for any single HRB. In addition, we found that compared to girls, the association between clustered HRBs and anxiety-depression comorbidity was stronger in boys after adjustment. Conclusions: We provide evidence that HRBs are related to comorbid anxiety and depression. Interventions that decrease HRBs may support mental health development in adolescence, with the potential to improve health and well-being through to adulthood. %M 37405826 %R 10.2196/46289 %U https://publichealth.jmir.org/2023/1/e46289 %U https://doi.org/10.2196/46289 %U http://www.ncbi.nlm.nih.gov/pubmed/37405826 %0 Journal Article %@ 2561-6722 %I JMIR Publications %V 6 %N %P e42349 %T Implementing a Digital Depression Prevention Program in Australian Secondary Schools: Cross-Sectional Qualitative Study %A Beames,Joanne R %A Werner-Seidler,Aliza %A Hodgins,Michael %A Brown,Lyndsay %A Fujimoto,Hiroko %A Bartholomew,Alexandra %A Maston,Kate %A Huckvale,Kit %A Zbukvic,Isabel %A Torok,Michelle %A Christensen,Helen %A Batterham,Philip J %A Calear,Alison L %A Lingam,Raghu %A Boydell,Katherine M %+ Black Dog Institute, University of New South Wales, Hospital Road, Sydney, NSW, 2031, Australia, 61 02 9382 ext 4530, z3330693@zmail.unsw.edu.au %K implementation %K youth %K digital %K depression %K secondary school %K qualitative %K consolidated framework for implementation research %K teacher %K educator %K perspective %K mental health %K student %K child %K adolescent %K adolescence %K school %K social work %D 2023 %7 12.6.2023 %9 Original Paper %J JMIR Pediatr Parent %G English %X Background: Depression is common during adolescence and is associated with adverse educational, employment, and health outcomes in later life. Digital programs are increasingly being implemented in schools to improve and protect adolescent mental health. Although digital depression prevention programs can be effective, there is limited knowledge about how contextual factors influence real-world delivery at scale in schools. Objective: The purpose of this study was to examine the contextual factors that influence the implementation of the Future Proofing Program (FPP) from the perspectives of school staff. The FPP is a 2-arm hybrid type 1 effectiveness-implementation trial evaluating whether depression can be prevented at scale in schools, using an evidence-based smartphone app delivered universally to year 8 students (13-14 years of age). Methods: Qualitative interviews were conducted with 23 staff from 20 schools in New South Wales, Australia, who assisted with the implementation of the FPP. The interviews were guided by our theory-driven logic model. Reflexive thematic analysis, using both deductive and inductive coding, was used to analyze responses. Results: Staff perceived the FPP as a novel (“innovative approach”) and appropriate way to address an unmet need within schools (“right place at the right time”). Active leadership and counselor involvement were critical for planning and engaging; teamwork, communication, and staff capacity were critical for execution (“ways of working within schools”). Low student engagement and staffing availability were identified as barriers for future adoption and implementation by schools (“reflecting on past experiences”). Conclusions: Four superordinate themes pertaining to the program, implementation processes, and implementation barriers were identified from qualitative responses by school staff. On the basis of our findings, we proposed a select set of recommendations for future implementation of digital prevention programs delivered at scale in schools. These recommendations were designed to facilitate an organizational change and help staff to implement digital mental health programs within their schools. International Registered Report Identifier (IRRID): RR2-10.1136/bmjopen-2020-042133 %M 37307051 %R 10.2196/42349 %U https://pediatrics.jmir.org/2023/1/e42349 %U https://doi.org/10.2196/42349 %U http://www.ncbi.nlm.nih.gov/pubmed/37307051 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 25 %N %P e47225 %T Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022 %A Wang,Siqin %A Ning,Huan %A Huang,Xiao %A Xiao,Yunyu %A Zhang,Mengxi %A Yang,Ellie Fan %A Sadahiro,Yukio %A Liu,Yan %A Li,Zhenlong %A Hu,Tao %A Fu,Xiaokang %A Li,Zi %A Zeng,Ye %+ Graduate School of Interdisciplinary Information Studies, University of Tokyo, 7 Chome-3 Hongo, Bunkyo City, Tokyo, 113-0033, Japan, 81 358415938, sisiplanner@gmail.com %K suicide %K suicidal ideation %K suicide-risk identification %K natural language processing %K social media %K Japan %D 2023 %7 2.6.2023 %9 Original Paper %J J Med Internet Res %G English %X Background: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A large body of literature has explored the suicide risks identified by people’s expressions on social media. However, there is not enough evidence to conclude that social media provides public surveillance for suicide without aligning suicide risks detected on social media with actual suicidal behaviors. Corroborating this alignment is a crucial foundation for suicide prevention and intervention through social media and for estimating and predicting suicide in countries with no reliable suicide statistics. Objective: This study aimed to corroborate whether the suicide risks identified on social media align with actual suicidal behaviors. This aim was achieved by tracking suicide risks detected by 62 million tweets posted in Japan over a 10-year period and assessing the locational and temporal alignment of such suicide risks with actual suicide behaviors recorded in national suicide statistics. Methods: This study used a human-in-the-loop approach to identify suicide-risk tweets posted in Japan from January 2013 to December 2022. This approach involved keyword-filtered data mining, data scanning by human efforts, and data refinement via an advanced natural language processing model termed Bidirectional Encoder Representations from Transformers. The tweet-identified suicide risks were then compared with actual suicide records in both temporal and spatial dimensions to validate if they were statistically correlated. Results: Twitter-identified suicide risks and actual suicide records were temporally correlated by month in the 10 years from 2013 to 2022 (correlation coefficient=0.533; P<.001); this correlation coefficient is higher at 0.652 when we advanced the Twitter-identified suicide risks 1 month earlier to compare with the actual suicide records. These 2 indicators were also spatially correlated by city with a correlation coefficient of 0.699 (P<.001) for the 10-year period. Among the 267 cities with the top quintile of suicide risks identified from both tweets and actual suicide records, 73.5% (n=196) of cities overlapped. In addition, Twitter-identified suicide risks were at a relatively lower level after midnight compared to a higher level in the afternoon, as well as a higher level on Sundays and Saturdays compared to weekdays. Conclusions: Social media platforms provide an anonymous space where people express their suicidal thoughts, ideation, and acts. Such expressions can serve as an alternative source to estimating and predicting suicide in countries without reliable suicide statistics. It can also provide real-time tracking of suicide risks, serving as an early warning for suicide. The identification of areas where suicide risks are highly concentrated is crucial for location-based mental health planning, enabling suicide prevention and intervention through social media in a spatially and temporally explicit manner. %M 37267022 %R 10.2196/47225 %U https://www.jmir.org/2023/1/e47225 %U https://doi.org/10.2196/47225 %U http://www.ncbi.nlm.nih.gov/pubmed/37267022 %0 Journal Article %@ 1929-073X %I JMIR Publications %V 11 %N 2 %P e41456 %T Scientific Publication Patterns of Systematic Reviews on Psychosocial Interventions Improving Well-being: Bibliometric Analysis %A Shubina,Ivanna %+ Liberal Arts Department, American University of the Middle East, Block 6, Building 1, Egaila, 25612, Kuwait, 965 97420150, ivanna.shubina@aum.edu.kw %K psychosocial intervention %K well-being %K systematic review %K bibliometric analysis %K bibliometrics %K scientific research %K medical research %K publication %K publish %K citation %K scientometrics %K mental health %D 2022 %7 11.11.2022 %9 Review %J Interact J Med Res %G English %X Background: Despite numerous empirical studies and systematic reviews conducted on the effectiveness of interventions improving psychological well-being, there is no holistic overview of published systematic reviews in this field. Objective: This bibliometric study explored the scientific patterns of the effectiveness of different psychosocial interventions improving well-being among various categories of individuals with mental and physical diseases, to synthesize well-being intervention studies, and to suggest gaps and further studies in this emerging field. Methods: The bibliometric analysis included identifying the most productive authors, institutions, and countries; most explored fields and subjects of study; most active journals and publishers; and performing citation analysis and analyzing publication trends between 2014 and 2022. We focused on data retrieved from known databases, and the study was conducted with a proven bibliometric approach. Results: In total, 156 studies were found concerning the research domains and retrieved using LENS software from high-ranking databases (Crossref, Microsoft Academic, PubMed, and Core). These papers were written in English by 100 authors from 24 countries, among which, the leading country was the United Kingdom. Descriptive characteristics of the publications involved an increased number of publications in 2017 (n=35) and 2019 (n=34) and a decreased number in 2021 (n=4). The top 2 leading authors by citation score are James Thomas (3 papers and 260 citations) and Chris Dickens (3 papers and 182 citations). However, the most cited study had 592 citations. BMJ Open (n=6 articles) is the leading journal in the field of medicine; Clinical Psychology Review (n=5), in psychology; and Frontiers in Psychology, in psychological intervention (n=5) and psychology (n=5). The top 2 publishers were Wiley (n=28) and Elsevier (n=25). Conclusions: This study indicates an overall interest in the declared domains within the last decade. Our findings primarily indicate that psychosocial interventions (PIs) were evaluated as being effective in managing mental and physical problems and enhancing well-being. Cognitive behavioral therapy was assessed as being effective in treating anxiety, psychoeducation in relapse prevention, and gratitude interventions in improving overall health, and the mindfulness approach had a positive impact on decreasing distress and depression. Moreover, all these intervention types resulted in an overall increase in an individuals’ well-being and resilience. Integrating social and cultural factors while considering individual differences increases the efficiency of PIs. Furthermore, PIs were evaluated as being effective in managing symptoms of eating disorders, dementia, and cancer. Our findings could help provide researchers an overview of the publication trends on research domains of focus for further studies, since it shows current findings and potential research needs in these fields, and would also benefit practitioners working on increasing their own and their patients' well-being. %M 36367767 %R 10.2196/41456 %U https://www.i-jmr.org/2022/2/e41456 %U https://doi.org/10.2196/41456 %U http://www.ncbi.nlm.nih.gov/pubmed/36367767 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 10 %P e39710 %T Social Media Use and Health-Related Quality of Life Among Adolescents: Cross-sectional Study %A You,Yueyue %A Yang-Huang,Junwen %A Raat,Hein %A Van Grieken,Amy %+ Department of Public Health, Erasmus Medical Center, Doctor Molewaterplein 40, Rotterdam, 3015 GD, Netherlands, 31 10 7043498, a.vangrieken@erasmusmc.nl %K adolescents %K social media platforms %K social media %K health-related quality of life %K EuroQol 5-dimension questionnaire, youth version %D 2022 %7 4.10.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: Using social media is a time-consuming activity of children and adolescents. Health authorities have warned that excessive use of social media can negatively affect adolescent social, physical, and psychological health. However, scientific findings regarding associations between time spent on social media and adolescent health-related quality of life (HRQoL) are not consistent. Adolescents typically use multiple social media platforms. Whether the use of multiple social media platforms impacts adolescent health is unclear. Objective: The aim of this study was to examine the relationship between social media use, including the number of social media platforms used and time spent on social media, and adolescent HRQoL. Methods: We analyzed the data of 3397 children (mean age 13.5, SD 0.4 years) from the Generation R Study, a population-based cohort study in the Netherlands. Children reported the number of social media platforms used and time spent on social media during weekdays and weekends separately. Children’s HRQoL was self-reported with the EuroQol 5-dimension questionnaire–youth version. Data on social media use and HRQoL were collected from 2015 to 2019. Multiple logistic and linear regressions were applied. Results: In this study, 72.6% (2466/3397) of the children used 3 or more social media platforms, and 37.7% (1234/3276) and 58.3% (1911/3277) of the children used social media at least 2 hours per day during weekdays and weekends, respectively. Children using more social media platforms (7 or more platforms) had a higher odds of reporting having some or a lot of problems on “having pain or discomfort” (OR 1.55, 95% CI 1.20 to 1.99) and “feeling worried, sad or unhappy” (OR 1.99, 95% CI 1.52 to 2.60) dimensions and reported lower self-rated health (β –3.81, 95% CI –5.54 to –2.09) compared with children who used 0 to 2 social media platforms. Both on weekdays and weekends, children spent more time on social media were more likely to report having some or a lot of problems on “doing usual activities,” “having pain or discomfort,” “feeling worried, sad or unhappy,” and report lower self-rated health (all P<.001). Conclusions: Our findings indicate that using more social media platforms and spending more time on social media were significantly related to lower HRQoL. We recommend future research to study the pathway between social media use and HRQoL among adolescents. %M 36194460 %R 10.2196/39710 %U https://mental.jmir.org/2022/10/e39710 %U https://doi.org/10.2196/39710 %U http://www.ncbi.nlm.nih.gov/pubmed/36194460 %0 Journal Article %@ 2291-9279 %I JMIR Publications %V 10 %N 2 %P e29077 %T Associations Between Addictive Behaviors, Individual Characteristics, and the Use of Gambling Services Within the World of Gaming: Cross-sectional Survey Study %A Kisch,Mark %A Håkansson,Anders %+ Division of Psychiatry, Department of Clinical Sciences, Lund University, Baravägen 1, Lund, 22100, Sweden, 46 070 3135677, anders_c.hakansson@med.lu.se %K gambling disorder %K gaming disorder %K behavioral addiction %K mental health %K gambling %K gaming %K addiction %K behavior %K cross-sectional %K online survey %K age %K gender %D 2022 %7 22.4.2022 %9 Original Paper %J JMIR Serious Games %G English %X Background: Gambling within the world of gaming is an emerging phenomenon that may share common conceptual characteristics with traditional forms of gambling. The current literature suggests a higher degree of problematic behaviors in this gambling pattern, but studies are few, prompting for further research regarding individual characteristics and comorbid conditions associated with this activity. Objective: The aim of the study is to investigate correlations between the use of gambling services within the world of gaming and individual characteristics and addictive behaviors including problem gambling. Methods: A cross-sectional web survey was distributed to an existing panel of online respondents in Sweden. A total of 2001 respondents were included. Chi-square and Mann-Whitney U tests, followed by a logistic regression, were used in order to determine independent variables associated with gambling in the context of gaming. Results: A total of 2.9% (58/1984) of respondents reported past-year gambling within gaming. Significant associations were found with male sex, younger age, history of treatment-seeking for alcohol problems, and higher Gaming Addiction Scale scores. Conclusions: The demonstrated findings strengthen previously found associations between gambling in gaming and younger age, male sex, and problematic gaming behaviors. Additionally, the association with a history of treatment needs for alcohol problems adds to the previous impression of increased problem severity and comorbidity in within-gaming gamblers. %M 35451974 %R 10.2196/29077 %U https://games.jmir.org/2022/2/e29077 %U https://doi.org/10.2196/29077 %U http://www.ncbi.nlm.nih.gov/pubmed/35451974 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 3 %P e35253 %T Utilizing Big Data From Google Trends to Map Population Depression in the United States: Exploratory Infodemiology Study %A Wang,Alex %A McCarron,Robert %A Azzam,Daniel %A Stehli,Annamarie %A Xiong,Glen %A DeMartini,Jeremy %+ Department of Psychiatry and Human Behavior, University of California, Irvine, 101 The City Dr S, Orange, CA, 92868, United States, 1 8584059768, wangaj3@uci.edu %K depression %K epidemiology %K internet %K google trends %K big data %K mental health %D 2022 %7 31.3.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: The epidemiology of mental health disorders has important theoretical and practical implications for health care service and planning. The recent increase in big data storage and subsequent development of analytical tools suggest that mining search databases may yield important trends on mental health, which can be used to support existing population health studies. Objective: This study aimed to map depression search intent in the United States based on internet-based mental health queries. Methods: Weekly data on mental health searches were extracted from Google Trends for an 11-year period (2010-2021) and separated by US state for the following terms: “feeling sad,” “depressed,” “depression,” “empty,” “insomnia,” “fatigue,” “guilty,” “feeling guilty,” and “suicide.” Multivariable regression models were created based on geographic and environmental factors and normalized to the following control terms: “sports,” “news,” “google,” “youtube,” “facebook,” and “netflix.” Heat maps of population depression were generated based on search intent. Results: Depression search intent grew 67% from January 2010 to March 2021. Depression search intent showed significant seasonal patterns with peak intensity during winter (adjusted P<.001) and early spring months (adjusted P<.001), relative to summer months. Geographic location correlated with depression search intent with states in the Northeast (adjusted P=.01) having higher search intent than states in the South. Conclusions: The trends extrapolated from Google Trends successfully correlate with known risk factors for depression, such as seasonality and increasing latitude. These findings suggest that Google Trends may be a valid novel epidemiological tool to map depression prevalence in the United States. %M 35357320 %R 10.2196/35253 %U https://mental.jmir.org/2022/3/e35253 %U https://doi.org/10.2196/35253 %U http://www.ncbi.nlm.nih.gov/pubmed/35357320 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 3 %P e32598 %T The Impact of COVID-19 Lockdown on Daily Activities, Cognitions, and Stress in a Lonely and Distressed Population: Temporal Dynamic Network Analysis %A Haucke,Matthias %A Heinz,Andreas %A Liu,Shuyan %A Heinzel,Stephan %+ Department of Psychiatry and Neurosciences, Charité–Universitätsmedizin Berlin, Campus Charité Mitte, Charitéplatz 1, Berlin, 10117, Germany, 49 015155710318, matthias.haucke@fu-berlin.de %K COVID-19 %K mental health %K outbreak %K epidemic %K pandemic %K psychological response %K emotional well-being %K ecological momentary assessment %K risk %K protective factors %K lockdown measures %K loneliness %K mood inertia %K stressors %K mobile apps %K mHealth %K digital health %K EMA %K smartphone apps %K network model %K cognition %K stress %K temporal dynamic network %K permutation testing %K network comparison %K network characteristics %K multilevel vector autoregressive model %K mlVAR %D 2022 %7 17.3.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: The COVID-19 pandemic and its associated lockdown measures impacted mental health worldwide. However, the temporal dynamics of causal factors that modulate mental health during lockdown are not well understood. Objective: We aimed to understand how a COVID-19 lockdown changes the temporal dynamics of loneliness and other factors affecting mental health. This is the first study that compares network characteristics between lockdown stages to prioritize mental health intervention targets. Methods: We combined ecological momentary assessments with wrist-worn motion tracking to investigate the mechanism and changes in network centrality of symptoms and behaviors before and during lockdown. A total of 258 participants who reported at least mild loneliness and distress were assessed 8 times a day for 7 consecutive days over a 213-day period from August 8, 2020, through March 9, 2021, in Germany, covering a “no-lockdown” and a “lockdown” stage. COVID-19–related worry, information-seeking, perceived restriction, and loneliness were assessed by digital visual analog scales ranging from 0 to 100. Social activity was assessed on a 7-point Likert scale, while physical activity was recorded from wrist-worn actigraphy devices. Results: We built a multilevel vector autoregressive model to estimate dynamic networks. To compare network characteristics between a no-lockdown stage and a lockdown stage, we performed permutation tests. During lockdown, loneliness had the highest impact within the network, as indicated by its centrality index (ie, an index to identify variables that have a strong influence on the other variables). Moreover, during lockdown, the centrality of loneliness significantly increased. Physical activity contributed to a decrease in loneliness amid the lockdown stage. Conclusions: The COVID-19 lockdown increased the central role of loneliness in triggering stress-related behaviors and cognition. Our study indicates that loneliness should be prioritized in mental health interventions during lockdown. Moreover, physical activity can serve as a buffer for loneliness amid social restrictions. %M 35191843 %R 10.2196/32598 %U https://www.jmir.org/2022/3/e32598 %U https://doi.org/10.2196/32598 %U http://www.ncbi.nlm.nih.gov/pubmed/35191843 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 9 %N 2 %P e33585 %T Depressive Symptoms and Anxiety During the COVID-19 Pandemic: Large, Longitudinal, Cross-sectional Survey %A MacDonald,James J %A Baxter-King,Ryan %A Vavreck,Lynn %A Naeim,Arash %A Wenger,Neil %A Sepucha,Karen %A Stanton,Annette L %+ Department of Psychology, University of California, Los Angeles, 1285 Franz Hall, Los Angeles, CA, 90025-1563, United States, 1 7742701642, jamesjmacdonald7@gmail.com %K COVID-19 %K depression %K anxiety %K pandemic %K mental health %K public health %K psychological variables %K younger adults %K symptom monitoring %K health intervention %D 2022 %7 10.2.2022 %9 Original Paper %J JMIR Ment Health %G English %X Background: The COVID-19 pandemic has influenced the mental health of millions across the globe. Understanding factors associated with depressive symptoms and anxiety across 12 months of the pandemic can help identify groups at higher risk and psychological processes that can be targeted to mitigate the long-term mental health impact of the pandemic. Objective: This study aims to determine sociodemographic features, COVID-19-specific factors, and general psychological variables associated with depressive symptoms and anxiety over 12 months of the pandemic. Methods: Nationwide, cross-sectional electronic surveys were implemented in May (n=14,636), July (n=14,936), October (n=14,946), and December (n=15,265) 2020 and March/April 2021 (n=14,557) in the United States. Survey results were weighted to be representative of the US population. The samples were drawn from a market research platform, with a 69% cooperation rate. Surveys assessed depressive symptoms in the past 2 weeks and anxiety in the past week, as well as sociodemographic features; COVID-19 restriction stress, worry, perceived risk, coping strategies, and exposure; intolerance of uncertainty; and loneliness. Results: Across 12 months, an average of 24% of respondents reported moderate-to-severe depressive symptoms and 32% reported moderate-to-severe anxiety. Of the sociodemographic variables, age was most consistently associated with depressive symptoms and anxiety, with younger adults more likely to report higher levels of those outcomes. Intolerance of uncertainty and loneliness were consistently and strongly associated with the outcomes. Of the COVID-19-specific variables, stress from COVID-19 restrictions, worry about COVID-19, coping behaviors, and having COVID-19 were associated with a higher likelihood of depressive symptoms and anxiety. Conclusions: Depressive symptoms and anxiety were high in younger adults, adults who reported restriction stress or worry about COVID-19 or who had had COVID-19, and those with intolerance of uncertainty and loneliness. Symptom monitoring as well as early and accessible intervention are recommended. %M 35142619 %R 10.2196/33585 %U https://mental.jmir.org/2022/2/e33585 %U https://doi.org/10.2196/33585 %U http://www.ncbi.nlm.nih.gov/pubmed/35142619 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 10 %N 1 %P e28183 %T Effects of Social Media Use for Health Information on COVID-19–Related Risk Perceptions and Mental Health During Pregnancy: Web-Based Survey %A Wang,Qian %A Xie,Luyao %A Song,Bo %A Di,Jiangli %A Wang,Linhong %A Mo,Phoenix Kit-Han %+ Center for Health Behaviours Research, Faculty of Medicine, School of Public Health and Primary Care, The Chinese University of Hong Kong, Prince of Wales Hospital, 202D, Hong Kong, Hong Kong, 852 2252 8765, phoenix.mo@cuhk.edu.hk %K COVID-19 %K pregnant %K social media use %K risk perception %K worry %K depression %D 2022 %7 13.1.2022 %9 Original Paper %J JMIR Med Inform %G English %X Background: Social media has become an important source of health information during the COVID-19 pandemic. Very little is known about the potential mental impact of social media use on pregnant women. Objective: This study aims to examine the association between using social media for health information and risk perception for COVID-19, worry due to COVID-19, and depression among pregnant women in China. Methods: A total of 4580 pregnant women were recruited from various provinces of China. The participants completed a cross-sectional, web-based survey in March 2020. Results: More than one-third (1794/4580, 39.2%) of the participants reported always using social media for obtaining health information. Results of structural equation modeling showed that the frequency of social media use for health information was positively associated with perceived susceptibility (β=.05; P<.001) and perceived severity (β=.12; P<.001) of COVID-19, which, in turn, were positively associated with worry due to COVID-19 (β=.19 and β=.72, respectively; P<.001). Perceived susceptibility (β=.09; P<.001), perceived severity (β=.08; P<.001), and worry due to COVID-19 (β=.15; P<.001) all had a positive association with depression. Bootstrapping analysis showed that the indirect effects of frequency of social media use for health information on both worry due to COVID-19 (β=.09, 95% CI 0.07-0.12) and depression (β=.05, 95% CI 0.02-0.07) were statistically significant. Conclusions: This study provides empirical evidence on how social media use for health information might have a negative impact on the mental health of pregnant women. Interventions are needed to equip this population with the skills to use social media properly and with caution. %M 34762065 %R 10.2196/28183 %U https://medinform.jmir.org/2022/1/e28183 %U https://doi.org/10.2196/28183 %U http://www.ncbi.nlm.nih.gov/pubmed/34762065 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 11 %N 1 %P e34984 %T Well-being of Canadian Armed Forces Veterans and Spouses of Veterans During the COVID-19 Pandemic: Protocol for a Prospective Longitudinal Survey %A Forchuk,Callista A %A Nazarov,Anthony %A Plouffe,Rachel A %A Liu,Jenny J W %A Deda,Erisa %A Le,Tri %A Gargala,Dominic %A Soares,Vanessa %A Bourret-Gheysen,Jesse %A St Cyr,Kate %A Nouri,Maede S %A Hosseiny,Fardous %A Smith,Patrick %A Dupuis,Gabrielle %A Roth,Maya %A Marlborough,Michelle %A Jetly,Rakesh %A Heber,Alexandra %A Lanius,Ruth %A Richardson,J Don %+ The MacDonald Franklin Operational Stress Injury Research Centre, Parkwood Institute, St. Joseph's Health Care, 550 Wellington Rd, London, ON, N6C 5J1, Canada, 1 519 685 4292 ext 42399, don.richardson@sjhc.london.on.ca %K well-being %K mental health %K veterans %K military %K survey %K COVID-19 %K protocol %K veteran %K physical health %K pandemic %K longitudinal survey %K healthcare %K treatment %K family support %K peer support %D 2022 %7 11.1.2022 %9 Protocol %J JMIR Res Protoc %G English %X Background: The COVID-19 pandemic has resulted in significant changes to everyday life, including social distancing mandates, changes to health care, and a heightened risk of infection. Previous research has shown that Canadian Armed Forces (CAF) veterans are at higher risk of developing mental and physical health conditions. Veterans and their families may face unique social challenges that can compound with pandemic-related disruptions to negatively impact well-being. Objective: This study aims to longitudinally characterize the mental health of CAF veterans and spouses of CAF veterans throughout the pandemic and to understand the dynamic influences of pandemic-related stressors on psychological health over time. Methods: We employed a prospective longitudinal panel design using an online data collection platform. Study participation was open to all CAF veterans and spouses of CAF veterans residing in Canada. Participants were asked to complete a comprehensive battery of assessments representing psychological well-being, chronic pain, health care access patterns, physical environment, employment, social integration, and adjustment to pandemic-related lifestyle changes. Follow-up assessments were conducted every 3 months over an 18-month period. This study was approved by the Western University Health Sciences and Lawson Health Research Institute Research Ethics Boards. Results: Baseline data were collected between July 2020 and February 2021. There were 3 population segments that participated in the study: 1047 veterans, 366 spouses of veterans, and 125 veterans who are also spouses of veterans completed baseline data collection. As of November 2021, data collection is ongoing, with participants completing the 9- or 12-month follow-up surveys depending on their date of self-enrollment. Data collection across all time points will be complete in September 2022. Conclusions: This longitudinal survey is unique in its comprehensive assessment of domains relevant to veterans and spouses of veterans during the COVID-19 pandemic, ranging from occupational, demographic, social, mental, and physical domains, to perceptions and experiences with health care treatments and access. The results of this study will be used to inform policy for veteran and veteran family support, and to best prepare for similar emergencies should they occur in the future. International Registered Report Identifier (IRRID): DERR1-10.2196/34984 %M 34935624 %R 10.2196/34984 %U https://www.researchprotocols.org/2022/1/e34984 %U https://doi.org/10.2196/34984 %U http://www.ncbi.nlm.nih.gov/pubmed/34935624 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 24 %N 1 %P e27000 %T Heterogeneity of Prevalence of Social Media Addiction Across Multiple Classification Schemes: Latent Profile Analysis %A Cheng,Cecilia %A Ebrahimi,Omid V %A Luk,Jeremy W %+ Social and Health Psychology Lab, Department of Psychology, The University of Hong Kong, Pokfulam, China (Hong Kong), 852 39174224, ceci-cheng@hku.hk %K behavioral addiction %K compulsive social media use %K information technology addiction %K mental health %K psychological assessment %K sensitivity %K social network site %K social networking %K well-being %D 2022 %7 10.1.2022 %9 Original Paper %J J Med Internet Res %G English %X Background: As social media is a major channel of interpersonal communication in the digital age, social media addiction has emerged as a novel mental health issue that has raised considerable concerns among researchers, health professionals, policy makers, mass media, and the general public. Objective: The aim of this study is to examine the prevalence of social media addiction derived from 4 major classification schemes (strict monothetic, strict polythetic, monothetic, and polythetic), with latent profiles embedded in the empirical data adopted as the benchmark for comparison. The extent of matching between the classification of each scheme and the actual data pattern was evaluated using sensitivity and specificity analyses. The associations between social media addiction and 2 comorbid mental health conditions—depression and anxiety—were investigated. Methods: A cross-sectional web-based survey was conducted, and the replicability of findings was assessed in 2 independent samples comprising 573 adults from the United Kingdom (261/573, 45.6% men; mean age 43.62 years, SD 12.24 years) and 474 adults from the United States (224/474, 47.4% men; mean age 44.67 years, SD 12.99 years). The demographic characteristics of both samples were similar to those of their respective populations. Results: The prevalence estimates of social media addiction varied across the classification schemes, ranging from 1% to 15% for the UK sample and 0% to 11% for the US sample. The latent profile analysis identified 3 latent groups for both samples: low-risk, at-risk, and high-risk. The sensitivity, specificity, and negative predictive values were high (83%-100%) for all classification schemes, except for the relatively lower sensitivity (73%-74%) for the polythetic scheme. However, the polythetic scheme had high positive predictive values (88%-94%), whereas such values were low (2%-43%) for the other 3 classification schemes. The group membership yielded by the polythetic scheme was largely consistent (95%-96%) with that of the benchmark. Conclusions: Among the classification schemes, the polythetic scheme is more well-balanced across all 4 indices. %M 35006084 %R 10.2196/27000 %U https://www.jmir.org/2022/1/e27000 %U https://doi.org/10.2196/27000 %U http://www.ncbi.nlm.nih.gov/pubmed/35006084 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 11 %P e32876 %T Machine Learning–Based Predictive Modeling of Anxiety and Depressive Symptoms During 8 Months of the COVID-19 Global Pandemic: Repeated Cross-sectional Survey Study %A Hueniken,Katrina %A Somé,Nibene Habib %A Abdelhack,Mohamed %A Taylor,Graham %A Elton Marshall,Tara %A Wickens,Christine M %A Hamilton,Hayley A %A Wells,Samantha %A Felsky,Daniel %+ Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, 250 College St, 12th Floor, Toronto, ON, M5T 1R8, Canada, 1 (416) 535 8501 ext 33587, Daniel.Felsky@camh.ca %K mental health %K machine learning %K COVID-19 %K emotional distress %K emotion %K distress %K prediction %K model %K anxiety %K depression %K symptom %K cross-sectional %K survey %D 2021 %7 17.11.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: The COVID-19 global pandemic has increased the burden of mental illness on Canadian adults. However, the complex combination of demographic, economic, and lifestyle factors and perceived health risks contributing to patterns of anxiety and depression has not been explored. Objective: The aim of this study is to harness flexible machine learning methods to identify constellations of factors related to symptoms of mental illness and to understand their changes over time during the COVID-19 pandemic. Methods: Cross-sectional samples of Canadian adults (aged ≥18 years) completed web-based surveys in 6 waves from May to December 2020 (N=6021), and quota sampling strategies were used to match the English-speaking Canadian population in age, gender, and region. The surveys measured anxiety and depression symptoms, sociodemographic characteristics, substance use, and perceived COVID-19 risks and worries. First, principal component analysis was used to condense highly comorbid anxiety and depression symptoms into a single data-driven measure of emotional distress. Second, eXtreme Gradient Boosting (XGBoost), a machine learning algorithm that can model nonlinear and interactive relationships, was used to regress this measure on all included explanatory variables. Variable importance and effects across time were explored using SHapley Additive exPlanations (SHAP). Results: Principal component analysis of responses to 9 anxiety and depression questions on an ordinal scale revealed a primary latent factor, termed “emotional distress,” that explained 76% of the variation in all 9 measures. Our XGBoost model explained a substantial proportion of variance in emotional distress (r2=0.39). The 3 most important items predicting elevated emotional distress were increased worries about finances (SHAP=0.17), worries about getting COVID-19 (SHAP=0.17), and younger age (SHAP=0.13). Hopefulness was associated with emotional distress and moderated the impacts of several other factors. Predicted emotional distress exhibited a nonlinear pattern over time, with the highest predicted symptoms in May and November and the lowest in June. Conclusions: Our results highlight factors that may exacerbate emotional distress during the current pandemic and possible future pandemics, including a role of hopefulness in moderating distressing effects of other factors. The pandemic disproportionately affected emotional distress among younger adults and those economically impacted. %M 34705663 %R 10.2196/32876 %U https://mental.jmir.org/2021/11/e32876 %U https://doi.org/10.2196/32876 %U http://www.ncbi.nlm.nih.gov/pubmed/34705663 %0 Journal Article %@ 2291-9694 %I JMIR Publications %V 9 %N 11 %P e28962 %T Machine Learning Applications in Mental Health and Substance Use Research Among the LGBTQ2S+ Population: Scoping Review %A Kundu,Anasua %A Chaiton,Michael %A Billington,Rebecca %A Grace,Daniel %A Fu,Rui %A Logie,Carmen %A Baskerville,Bruce %A Yager,Christina %A Mitsakakis,Nicholas %A Schwartz,Robert %+ Centre for Addiction and Mental Health, 1000 Queen Street West, Toronto, ON, M6J 1H4, Canada, 1 6476326493, anasua.kundu@mail.utoronto.ca %K sexual and gender minorities %K mental health %K mental disorders %K substance-related disorders %K machine learning %D 2021 %7 11.11.2021 %9 Review %J JMIR Med Inform %G English %X Background: A high risk of mental health or substance addiction issues among sexual and gender minority populations may have more nuanced characteristics that may not be easily discovered by traditional statistical methods. Objective: This review aims to identify literature studies that used machine learning (ML) to investigate mental health or substance use concerns among the lesbian, gay, bisexual, transgender, queer or questioning, and two-spirit (LGBTQ2S+) population and direct future research in this field. Methods: The MEDLINE, Embase, PubMed, CINAHL Plus, PsycINFO, IEEE Xplore, and Summon databases were searched from November to December 2020. We included original studies that used ML to explore mental health or substance use among the LGBTQ2S+ population and excluded studies of genomics and pharmacokinetics. Two independent reviewers reviewed all papers and extracted data on general study findings, model development, and discussion of the study findings. Results: We included 11 studies in this review, of which 81% (9/11) were on mental health and 18% (2/11) were on substance use concerns. All studies were published within the last 2 years, and most were conducted in the United States. Among mutually nonexclusive population categories, sexual minority men were the most commonly studied subgroup (5/11, 45%), whereas sexual minority women were studied the least (2/11, 18%). Studies were categorized into 3 major domains: web content analysis (6/11, 54%), prediction modeling (4/11, 36%), and imaging studies (1/11, 9%). Conclusions: ML is a promising tool for capturing and analyzing hidden data on mental health and substance use concerns among the LGBTQ2S+ population. In addition to conducting more research on sexual minority women, different mental health and substance use problems, as well as outcomes and future research should explore newer environments, data sources, and intersections with various social determinants of health. %M 34762059 %R 10.2196/28962 %U https://medinform.jmir.org/2021/11/e28962 %U https://doi.org/10.2196/28962 %U http://www.ncbi.nlm.nih.gov/pubmed/34762059 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 11 %P e24471 %T Suicide Risk and Protective Factors in Online Support Forum Posts: Annotation Scheme Development and Validation Study %A Chancellor,Stevie %A Sumner,Steven A %A David-Ferdon,Corinne %A Ahmad,Tahirah %A De Choudhury,Munmun %+ Department of Computer Science & Engineering, University of Minnesota - Twin Cities, 200 Union Street SE, 4-189 Keller Hall, Minneapolis, MN, 55455, United States, 1 612 625 4002, steviec@umn.edu %K online communities %K suicide crisis %K construct validity %K annotation scheme %K Reddit %K annotation %D 2021 %7 8.11.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Online communities provide support for individuals looking for help with suicidal ideation and crisis. As community data are increasingly used to devise machine learning models to infer who might be at risk, there have been limited efforts to identify both risk and protective factors in web-based posts. These annotations can enrich and augment computational assessment approaches to identify appropriate intervention points, which are useful to public health professionals and suicide prevention researchers. Objective: This qualitative study aims to develop a valid and reliable annotation scheme for evaluating risk and protective factors for suicidal ideation in posts in suicide crisis forums. Methods: We designed a valid, reliable, and clinically grounded process for identifying risk and protective markers in social media data. This scheme draws on prior work on construct validity and the social sciences of measurement. We then applied the scheme to annotate 200 posts from r/SuicideWatch—a Reddit community focused on suicide crisis. Results: We documented our results on producing an annotation scheme that is consistent with leading public health information coding schemes for suicide and advances attention to protective factors. Our study showed high internal validity, and we have presented results that indicate that our approach is consistent with findings from prior work. Conclusions: Our work formalizes a framework that incorporates construct validity into the development of annotation schemes for suicide risk on social media. This study furthers the understanding of risk and protective factors expressed in social media data. This may help public health programming to prevent suicide and computational social science research and investigations that rely on the quality of labels for downstream machine learning tasks. %M 34747705 %R 10.2196/24471 %U https://mental.jmir.org/2021/11/e24471 %U https://doi.org/10.2196/24471 %U http://www.ncbi.nlm.nih.gov/pubmed/34747705 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 11 %P e29896 %T Psychosocial and Behavioral Effects of the COVID-19 Pandemic in the Indian Population: Protocol for a Cross-sectional Study %A Joshi,Megha %A Shah,Aangi %A Trivedi,Bhavi %A Trivedi,Jaahnavee %A Patel,Viral %A Parghi,Devam %A Thakkar,Manini %A Barot,Kanan %A Jadawala,Vivek %+ Department of Psychiatry, Shrimati Nathiba Hargovandas Lakhamichand Municipal Medical College, Gujarat University, Pritamrai cross road,, Ellisbridge, Paldi, Ahmedabad, 380006, India, 91 9909896196, joshimegha1@gmail.com %K COVID-19 %K mental health %K India %K lockdown %K isolation %K social isolation %K behavior %K psychology %K psychosocial effects %D 2021 %7 5.11.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: During the year 2020, the COVID-19 pandemic spread from China to the rest of the world, which prompted the world to implement a widespread mandated quarantine or social isolation. The impending uncertainty of the pandemic must have resulted in a variety of widespread mental health maladies. There has been documentation in the literature about a lot of these in small populations of the world but limited studies have been conducted in India, leading to limited evidence in the literature. Objective: The main objective of our study is to investigate the mental health effects that the COVID-19 pandemic has had on the general population in India both quantitatively and qualitatively. These results will help contribute to reducing the knowledge gap that is recognized in the literature, which is the result of the unprecedented and novel nature of the pandemic. Methods: We designed and validated our own questionnaire and used the method of circulating the questionnaire via WhatsApp (Facebook Inc). WhatsApp is a social media app that is very popularly used in India; hence, it turned out to be an effective medium for gathering pilot data. We analyzed the pilot data and used them to validate the questionnaire. This was done with the expertise of our mentor, Nilima Shah, MD (psychiatry). We gathered pilot data on 545 subjects and used the results to determine the changes that were needed for the questionnaire while simultaneously validating the questionnaire. Results: The study protocol was approved in September 2020 by the institutional review board at Vadilal Sarabhai General Hospital, Ahmedabad, Gujarat, India. Conclusions: The following preliminary assumptions can be made about the study based on the pilot data: the majority of the survey respondents were male (289/545, 53%), most of them were educated and employed as health care workers (199/545, 36.5%). The majority of the responders were self-employed (185/545, 33.9%), single (297/545, 54.5%), and stayed with their families (427/541, 79%) for the lockdown, which helped them psychologically. Findings that are specific to mental health have been elaborated upon in the manuscript. It is evident from the data collected in previous literature that the pandemic has had significant detrimental effects on the mental health of a vast proportion of the Indian population. International Registered Report Identifier (IRRID): DERR1-10.2196/29896 %M 34519652 %R 10.2196/29896 %U https://www.researchprotocols.org/2021/11/e29896 %U https://doi.org/10.2196/29896 %U http://www.ncbi.nlm.nih.gov/pubmed/34519652 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e25329 %T Body Image Distress and Its Associations From an International Sample of Men and Women Across the Adult Life Span: Web-Based Survey Study %A Milton,Alyssa %A Hambleton,Ashlea %A Roberts,Anna %A Davenport,Tracey %A Flego,Anna %A Burns,Jane %A Hickie,Ian %+ Sydney School of Medicine, Faculty of Medicine and Health, University of Sydney, Professor Marie Bashir Centre, 67-73 Missenden Rd, Camperdown, 2050, Australia, 61 02 93510774, alyssa.milton@sydney.edu.au %K body image %K mental health %K well-being %K web-based survey %K sex differences %K age %D 2021 %7 4.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Previous research on body image distress mainly relied on samples that were small, generally homogeneous in age or sex, often limited to one geographical region, and were characterized by a lack of comprehensive analysis of multiple psychosocial domains. The research presented in this paper extends the international literature using the results of the web-based Global Health and Wellbeing Survey 2015. The survey included a large sample of both men and women aged ≥16 years from Australia, Canada, New Zealand, the United Kingdom, or the United States. Objective: The main objectives of this study are to examine body image distress across the adult life span (≥16 years) and sex and assess the association between body image distress and various psychosocial risk and protective factors. Methods: Data were extracted from the Global Health and Wellbeing Survey 2015, a web-based international self-report survey with 10,765 respondents, and compared with previous web-based surveys conducted in 2009 and 2012. Results: The body image distress of young Australians (aged 16-25 years) significantly rose by 33% from 2009 to 2015. In 2015, 75.19% (961/1278) of 16- to 25-year-old adults reported body image distress worldwide, and a decline in body image distress was noted with increasing age. More women reported higher levels of body image distress than men (1953/3338, 58.51% vs 853/2175, 39.22%). Sex, age, current dieting status, perception of weight, psychological distress, alcohol and other substance misuse, and well-being significantly explained 24% of the variance in body image distress in a linear regression (F15,4966=105.8; P<.001). Conclusions: This study demonstrates the significant interplay between body image distress and psychosocial factors across age and sex. %M 34734831 %R 10.2196/25329 %U https://formative.jmir.org/2021/11/e25329 %U https://doi.org/10.2196/25329 %U http://www.ncbi.nlm.nih.gov/pubmed/34734831 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 11 %P e27114 %T Understanding the Social Determinants of Mental Health of Undergraduate Students in Bangladesh: Interview Study %A Bhattacharjee,Ananya %A Haque,S M Taiabul %A Hady,Md Abdul %A Alam,S M Raihanul %A Rabbi,Mashfiqui %A Kabir,Muhammad Ashad %A Ahmed,Syed Ishtiaque %+ Department of Computer Science, University of Toronto, 40 St George Street, Toronto, ON, M5S 2E4, Canada, 1 6476196982, ananya@cs.toronto.edu %K Bangladesh %K global south %K social determinant %K students %K undergraduate %K religion %K women %K mobile phone %D 2021 %7 2.11.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The undergraduate student population has been actively studied in digital mental health research. However, the existing literature primarily focuses on students from high-income nations, and undergraduates from limited-income nations remain understudied. Objective: This study aims to identify the broader social determinants of mental health among undergraduate students in Bangladesh, a limited-income nation in South Asia; study the manifestation of these determinants in their day-to-day lives; and explore the feasibility of self-monitoring tools in helping them identify the specific factors or relationships that affect their mental health. Methods: We conducted a 21-day study with 38 undergraduate students from 7 universities in Bangladesh. We conducted 2 semistructured interviews: one prestudy and one poststudy. During the 21-day study, participants used an Android app to self-report and self-monitor their mood after each phone conversation. The app prompted participants to report their mood after each phone conversation and provided graphs and charts so that the participants could independently review their mood and conversation patterns. Results: Our results show that academics, family, job and economic condition, romantic relationship, and religion are the major social determinants of mental health among undergraduate students in Bangladesh. Our app helped the participants pinpoint the specific issues related to these factors, as the participants could review the pattern of their moods and emotions from past conversation history. Although our app does not provide any explicit recommendation, the participants took certain steps on their own to improve their mental health (eg, reduced the frequency of communication with certain persons). Conclusions: Although some of the factors (eg, academics) were reported in previous studies conducted in the Global North, this paper sheds light on some new issues (eg, extended family problems and religion) that are specific to the context of the Global South. Overall, the findings from this study would provide better insights for researchers to design better solutions to help the younger population from this part of the world. %M 34726609 %R 10.2196/27114 %U https://formative.jmir.org/2021/11/e27114 %U https://doi.org/10.2196/27114 %U http://www.ncbi.nlm.nih.gov/pubmed/34726609 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 10 %P e28088 %T Perceptions and Feelings of Brazilian Health Care Professionals Regarding the Effects of COVID-19: Cross-sectional Web-Based Survey %A Corrêa,Roberta Pires %A Castro,Helena Carla %A Quaresma,Bruna Maria Castro Salomão %A Stephens,Paulo Roberto Soares %A Araujo-Jorge,Tania Cremonini %A Ferreira,Roberto Rodrigues %+ Laboratory of Innovations in Therapies, Education and Bioproducts, Oswaldo Cruz Institute, Oswaldo Cruz Foundation (Fiocruz), Av Brasil, 4365, Rio de Janeiro, Brazil, 55 21 2562 1295, robertoferreira@ioc.fiocruz.br %K COVID-19 %K SARS-CoV-2 %K health professionals %K Brazil %K pandemic %K mental health %K health planning %D 2021 %7 22.10.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The importance of health professionals has been recognized in COVID-19 pandemic–affected countries, especially in those such as Brazil, which is one of the top 3 countries that have been affected in the world. However, the workers’ perception of the stress and the changes that the pandemic has caused in their lives vary according to the conditions offered by these affected countries, including salaries, individual protection equipment, and psychological support. Objective: The purpose of this study was to identify the perceptions of Brazilian health workers regarding the COVID-19 pandemic impact on their lives, including possible self-contamination and mental health. Methods: This cross-sectional web-based survey was conducted in Brazil by applying a 32-item questionnaire, including multiple-choice questions by using the Google Forms electronic assessment. This study was designed to capture spontaneous perceptions from health professionals. All questions were mandatory and divided into 2 blocks with different proposals: personal profile and COVID-19 pandemic impact. Results: We interviewed Brazilian health professionals from all 5 Brazilian regions (N=1376). Our study revealed that 1 in 5 (23%) complained about inadequate personal protective equipment, including face shields (234/1376, 17.0%), masks (206/1376, 14.9%), and laboratory coats (138/1376, 10.0%), whereas 1 in 4 health professionals did not have enough information to protect themselves from the coronavirus disease. These professionals had anxiety due to COVID-19 (604/1376, 43.9%), difficulties in sleep (593/1376, 43.1%), and concentrating on work (453/1376, 32.9%). Almost one-third experienced traumatic situations at work (385/1376, 28.0%), which may have led to negative feelings of fear of COVID-19 and sadness. Despite this situation, there was hope and empathy among their positive feelings. The survey also showed that 1 in 5 acquired COVID-19 with the most classic and minor symptoms, including headache (274/315, 87.0%), body pain (231/315, 73.3%), tiredness (228/315, 72.4%), and loss of taste and smell (208/315, 66.0%). Some of their negative feelings were higher than those of noninfected professionals (fear of COVID-19, 243/315, 77.1% vs 509/1061, 48.0%; impotence, 142/315, 45.1% vs 297/1061, 28.0%; and fault, 38/315, 12.1% vs 567/1061, 53.4%, respectively). Another worrying outcome was that 61.3% (193/315) reported acquiring an infection while working at a health facility and as expected, most of the respondents felt affected (344/1376, 25.0%) or very affected (619/1376, 45.0%) by the COVID-19. Conclusions: In Brazil, the health professionals were exposed to a stressful situation and to the risk of self-contamination—conditions that can spell future psychological problems for these workers. Our survey findings showed that the psychological support for this group should be included in the future health planning of Brazil and of other hugely affected countries to assure a good mental health condition for the medical teams in the near future. %M 34519656 %R 10.2196/28088 %U https://formative.jmir.org/2021/10/e28088 %U https://doi.org/10.2196/28088 %U http://www.ncbi.nlm.nih.gov/pubmed/34519656 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 10 %P e29199 %T Understanding the Associations of Prenatal Androgen Exposure on Sleep Physiology, Circadian Proteins, Anthropometric Parameters, Hormonal Factors, Quality of Life, and Sex Among Healthy Young Adults: Protocol for an International, Multicenter Study %A Kuczyński,Wojciech %A Wibowo,Erik %A Hoshino,Tetsuro %A Kudrycka,Aleksandra %A Małolepsza,Aleksandra %A Karwowska,Urszula %A Pruszkowska,Milena %A Wasiak,Jakub %A Kuczyńska,Aleksandra %A Spałka,Jakub %A Pruszkowska-Przybylska,Paulina %A Mokros,Łukasz %A Białas,Adam %A Białasiewicz,Piotr %A Sasanabe,Ryujiro %A Blagrove,Mark %A Manning,John %+ Department of Anatomy, School of Biomedical Sciences, University of Otago, 270 Great King St, Dunedin, 9016, New Zealand, 64 34704692, erik.wibowo@otago.ac.nz %K digit ratio %K sleep %K sex hormones %K testosterone %K estrogen %K circadian proteins %K circadian rhythm %K chronotype %K miRNA %D 2021 %7 6.10.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The ratio of the second finger length to the fourth finger length (2D:4D ratio) is considered to be negatively correlated with prenatal androgen exposure (PAE) and positively correlated with prenatal estrogen. Coincidentally, various brain regions are sensitive to PAE, and their functions in adults may be influenced by the prenatal actions of sex hormones. Objective: This study aims to assess the relationship between PAE (indicated by the 2D:4D ratio) and various physiological (sex hormone levels and sleep-wake parameters), psychological (mental health), and sexual parameters in healthy young adults. Methods: This study consists of two phases. In phase 1, we will conduct a survey-based study and anthropometric assessments (including 2D:4D ratio and BMI) in healthy young adults. Using validated questionnaires, we will collect self-reported data on sleep quality, sexual function, sleep chronotype, anxiety, and depressive symptoms. In phase 2, a subsample of phase 1 will undergo polysomnography and physiological and genetic assessments. Sleep architecture data will be obtained using portable polysomnography. The levels of testosterone, estradiol, progesterone, luteinizing hormone, follicle-stimulating hormone, prolactin, melatonin, and circadian regulatory proteins (circadian locomotor output cycles kaput [CLOCK], timeless [TIM], and period [PER]) and the expression levels of some miRNAs will be measured using blood samples. The rest and activity cycle will be monitored using actigraphy for a 7-day period. Results: In Poland, 720 participants were recruited for phase 1. Among these, 140 completed anthropometric measurements. In addition, 25 participants joined and completed phase 2 data collection. Recruitment from other sites will follow. Conclusions: Findings from our study may help to better understand the plausible role of PAE in sleep physiology, mental health, and sexual quality of life in young adults. International Registered Report Identifier (IRRID): DERR1-10.2196/29199 %M 34612837 %R 10.2196/29199 %U https://www.researchprotocols.org/2021/10/e29199 %U https://doi.org/10.2196/29199 %U http://www.ncbi.nlm.nih.gov/pubmed/34612837 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 9 %P e27741 %T Emotional Analysis of Twitter Posts During the First Phase of the COVID-19 Pandemic in Greece: Infoveillance Study %A Geronikolou,Styliani %A Drosatos,George %A Chrousos,George %+ Biomedical Research Foundation of the Academy of Athens, Soranou Ephessiou 4, Athens, 11527, Greece, 30 2106597403, sgeronik@gmail.com %K emotional analysis %K COVID-19 %K Twitter %K Greece %K infodemics %K emotional contagion %K epidemiology %K pandemic %K mental health %D 2021 %7 29.9.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: The effectiveness of public health measures depends upon a community’s compliance as well as on its positive or negative emotions. Objective: The purpose of this study was to perform an analysis of the expressed emotions in English tweets by Greek Twitter users during the first phase of the COVID-19 pandemic in Greece. Methods: The period of this study was from January 25, 2020 to June 30, 2020. Data collection was performed by using appropriate search words with the filter-streaming application programming interface of Twitter. The emotional analysis of the tweets that satisfied the inclusion criteria was achieved using a deep learning approach that performs better by utilizing recurrent neural networks on sequences of characters. Emotional epidemiology tools such as the 6 basic emotions, that is, joy, sadness, disgust, fear, surprise, and anger based on the Paul Ekman classification were adopted. Results: The most frequent emotion that was detected in the tweets was “surprise” at the emerging contagion, while the imposed isolation resulted mostly in “anger” (odds ratio 2.108, 95% CI 0.986-4.506). Although the Greeks felt rather safe during the first phase of the COVID-19 pandemic, their positive and negative emotions reflected a masked “flight or fight” or “fear versus anger” response to the contagion. Conclusions: The findings of our study show that emotional analysis emerges as a valid tool for epidemiology evaluations, design, and public health strategy and surveillance. %M 34469328 %R 10.2196/27741 %U https://formative.jmir.org/2021/9/e27741 %U https://doi.org/10.2196/27741 %U http://www.ncbi.nlm.nih.gov/pubmed/34469328 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 9 %P e32663 %T Exploring the Well-being of Health Care Workers During the COVID-19 Pandemic: Protocol for a Prospective Longitudinal Study %A Liu,Jenny J W %A Nazarov,Anthony %A Plouffe,Rachel A %A Forchuk,Callista A %A Deda,Erisa %A Gargala,Dominic %A Le,Tri %A Bourret-Gheysen,Jesse %A Soares,Vanessa %A Nouri,Maede S %A Hosseiny,Fardous %A Smith,Patrick %A Roth,Maya %A MacDougall,Arlene G %A Marlborough,Michelle %A Jetly,Rakesh %A Heber,Alexandra %A Albuquerque,Joy %A Lanius,Ruth %A Balderson,Ken %A Dupuis,Gabrielle %A Mehta,Viraj %A Richardson,J Don %+ MacDonald Franklin Operational Stress Injury Research Centre, Lawson Health Research Institute, St. Joseph's Health Care London, Parkwood Institute Research, Mental Health Building RM F4-367, 550 Wellington Road, London, ON, N6C 0A7, Canada, 1 519 685 4292 ext 48211, jenny.liu@sjhc.london.on.ca %K COVID-19 %K health care worker %K pandemic %K mental health %K wellbeing %K survey %K design %K longitudinal %K prospective %K protocol %K challenge %K impact %K distress %K perception %D 2021 %7 27.9.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Health care workers (HCWs) have experienced several stressors associated with the COVID-19 pandemic. Structural stressors, including extended work hours, redeployment, and changes in organizational mandates, often intersect with interpersonal and personal stressors, such as caring for those with COVID-19 infections; worrying about infection of self, family, and loved ones; working despite shortages of personal protective equipment; and encountering various difficult moral-ethical dilemmas. Objective: The paper describes the protocol for a longitudinal study seeking to capture the unique experiences, challenges, and changes faced by HCWs during the COVID-19 pandemic. The study seeks to explore the impact of COVID-19 on the mental well-being of HCWs with a particular focus on moral distress, perceptions of and satisfaction with delivery of care, and how changes in work structure are tolerated among HCWs providing clinical services. Methods: A prospective longitudinal design is employed to assess HCWs’ experiences across domains of mental health (depression, anxiety, posttraumatic stress, and well-being), moral distress and moral reasoning, work-related changes and telehealth, organizational responses to COVID-19 concerns, and experiences with COVID-19 infections to self and to others. We recruited HCWs from across Canada through convenience snowball sampling to participate in either a short-form or long-form web-based survey at baseline. Respondents to the baseline survey are invited to complete a follow-up survey every 3 months, for a total of 18 months. Results: A total of 1926 participants completed baseline surveys between June 26 and December 31, 2020, and 1859 participants provided their emails to contact them to participate in follow-up surveys. As of July 2021, data collection is ongoing, with participants nearing the 6- or 9-month follow-up periods depending on their initial time of self-enrollment. Conclusions: This protocol describes a study that will provide unique insights into the immediate and longitudinal impact of the COVID-19 pandemic on the dimensions of mental health, moral distress, health care delivery, and workplace environment of HCWs. The feasibility and acceptability of implementing a short-form and long-form survey on participant engagement and data retention will also be discussed. International Registered Report Identifier (IRRID): DERR1-10.2196/32663 %M 34477557 %R 10.2196/32663 %U https://www.researchprotocols.org/2021/9/e32663 %U https://doi.org/10.2196/32663 %U http://www.ncbi.nlm.nih.gov/pubmed/34477557 %0 Journal Article %@ 1438-8871 %I JMIR Publications %V 23 %N 9 %P e21316 %T Roles of Psychosocial Factors on the Association Between Online Social Networking Use Intensity and Depressive Symptoms Among Adolescents: Prospective Cohort Study %A Li,Ji-Bin %A Feng,Li-Fen %A Wu,Anise M S %A Mai,Jin-Chen %A Chen,Yu-Xia %A Mo,Phoenix K H %A Lau,Joseph T F %+ Center for Health Behaviours Research, The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, 5/F, School of Public Health, Prince of Wales Hospital, Hong Kong, China, 86 26376606, jlau@cuhk.edu.hk %K online social networking use intensity %K depressive symptoms %K psychosocial factors %K mediation and suppression %K longitudinal study %D 2021 %7 21.9.2021 %9 Original Paper %J J Med Internet Res %G English %X Background: The potential mechanisms underlying the association between online social networking use intensity and depressive symptoms are unclear and underresearched. Objective: We aimed to investigate the potential roles of interpersonal psychosocial factors on the association between online social networking use intensity and depressive symptoms among early adolescents. Methods: A total of 4237 adolescents from a 9-month longitudinal study were included. Score changes (indicated as △) for the social function use intensity (SFUI) and entertainment function use intensity (EFUI) subscales of the Online Social Networking Activity Intensity Scale and for friendship quality, perceived family support, perceived friend support, parent–adolescent conflict, social nonconfidence, and depressive symptoms were analyzed. The potential mediation effects of unfavorable psychosocial factors and suppression effects of favorable psychosocial factors on the association of △SFUI with △CES-D and the association of △EFUI with △CES-D were tested using hierarchical regression models. Results: The association between △SFUI and △CES-D was partially mediated by △mother–adolescent conflict (mediation effect size 5.11%, P=.02) and △social nonconfidence (mediation effect size 20.97%, P<.001) but partially suppressed by △friendship quality, △perceived family support, and △perceived friend support, with suppression effects of –0.011 (P=.003), –0.009 (P=.003), and –0.022 (P<.001), respectively. The association between △EFUI and △CES-D was partially mediated by △social nonconfidence (mediation effect size 30.65%, P<.001) but partially suppressed by △perceived family support and △perceived friend support, with suppression effects of –0.036 (P<.001) and –0.039 (P<.001), respectively. Conclusions: The association between online social networking use intensity and depressive symptoms was partially mediated through the indirect increase in social nonconfidence and mother–adolescent conflict; however, better perceived social support and friendship quality would partially compensate for the harmful impact of online social networking use intensity on depressive symptoms among early adolescents. %M 34546173 %R 10.2196/21316 %U https://www.jmir.org/2021/9/e21316 %U https://doi.org/10.2196/21316 %U http://www.ncbi.nlm.nih.gov/pubmed/34546173 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 9 %P e30504 %T An App-Based Surveillance System for Undergraduate Students’ Mental Health During the COVID-19 Pandemic: Protocol for a Prospective Cohort Study %A Brogly,Chris %A Bauer,Michael A %A Lizotte,Daniel J %A Press,MacLean L %A MacDougall,Arlene %A Speechley,Mark %A Huner,Erin %A Mitchell,Marc %A Anderson,Kelly K %A Pila,Eva %+ School of Kinesiology, Faculty of Health Sciences, Western University, 1151 Richmond Street, London, ON, N6A 3K7, Canada, 1 519 661 2111, epila@uwo.ca %K undergraduate %K mental health %K smartphone %K app %K COVID-19 %K postsecondary institutions %K mobile apps %K mHealth %K mobile health %D 2021 %7 17.9.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The COVID-19 pandemic is a public health emergency that poses challenges to the mental health of approximately 1.4 million university students in Canada. Preliminary evidence has shown that the COVID-19 pandemic had a detrimental impact on undergraduate student mental health and well-being; however, existing data are predominantly limited to cross-sectional survey-based studies. Owing to the evolving nature of the pandemic, longer-term prospective surveillance efforts are needed to better anticipate risk and protective factors during a pandemic. Objective: The overarching aim of this study is to use a mobile (primarily smartphone-based) surveillance system to identify risk and protective factors for undergraduate students’ mental health. Factors will be identified from weekly self-report data (eg, affect and living accommodation) and device sensor data (eg, physical activity and device usage) to prospectively predict self-reported mental health and service utilization. Methods: Undergraduate students at Western University (London, Ontario, Canada), will be recruited via email to complete an internet-based baseline questionnaire with the option to participate in the study on a weekly basis, using the Student Pandemic Experience (SPE) mobile app for Android/iOS. The app collects sensor samples (eg, GPS coordinates and steps) and self-reported weekly mental health and wellness surveys. Student participants can opt in to link their mobile data with campus-based administrative data capturing health service utilization. Risk and protective factors that predict mental health outcomes are expected to be estimated from (1) cross-sectional associations among students’ characteristics (eg, demographics) and key psychosocial factors (eg, affect, stress, and social connection), and behaviors (eg, physical activity and device usage) and (2) longitudinal associations between psychosocial and behavioral factors and campus-based health service utilization. Results: Data collection began November 9, 2020, and will be ongoing through to at least October 31, 2021. Retention from the baseline survey (N=427) to app sign-up was 74% (315/427), with 175-215 (55%-68%) app participants actively responding to weekly surveys. From November 9, 2020, to August 8, 2021, a total of 4851 responses to the app surveys and 25,985 sensor samples (consisting of up to 68 individual data items each; eg, GPS coordinates and steps) were collected from the 315 participants who signed up for the app. Conclusions: The results of this real-world longitudinal cohort study of undergraduate students’ mental health based on questionnaires and mobile sensor metrics is expected to show psychosocial and behavioral patterns associated with both positive and negative mental health–related states during pandemic conditions at a relatively large, public, and residential Canadian university campus. The results can be used to support decision-makers and students during the ongoing COVID-19 pandemic and similar future events. For comparable settings, new interventions (digital or otherwise) might be designed using these findings as an evidence base. International Registered Report Identifier (IRRID): DERR1-10.2196/30504 %M 34516391 %R 10.2196/30504 %U https://www.researchprotocols.org/2021/9/e30504 %U https://doi.org/10.2196/30504 %U http://www.ncbi.nlm.nih.gov/pubmed/34516391 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 9 %P e28337 %T The Impact of COVID-19–Related Restrictions on Social and Daily Activities of Parents, People With Disabilities, and Older Adults: Protocol for a Longitudinal, Mixed Methods Study %A Reid,Holly %A Miller,William Cameron %A Esfandiari,Elham %A Mohammadi,Somayyeh %A Rash,Isabelle %A Tao,Gordon %A Simpson,Ethan %A Leong,Kai %A Matharu,Parmeet %A Sakakibara,Brodie %A Schmidt,Julia %A Jarus,Tal %A Forwell,Susan %A Borisoff,Jaimie %A Backman,Catherine %A Alic,Adam %A Brooks,Emily %A Chan,Janice %A Flockhart,Elliott %A Irish,Jessica %A Tsukura,Chihori %A Di Spirito,Nicole %A Mortenson,William Ben %+ Rehabilitation Research Program, GF Strong Rehabilitation Centre, 4255 Laurel Street, Vancouver, BC, Canada, 1 604 714 4108, bill.miller@ubc.ca %K COVID-19 %K longitudinal study %K spinal cord injury %K disability %K adult %K occupational disruption %K stroke %K older adults %D 2021 %7 1.9.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The COVID-19 pandemic has led to wide-scale changes in societal organization. This has dramatically altered people’s daily activities, especially among families with young children, those living with disabilities such as spinal cord injury (SCI), those who have experienced a stroke, and older adults. Objective: We aim to (1) investigate how COVID-19 restrictions influence daily activities, (2) track the psychosocial effects of these restrictions over time, and (3) identify strategies to mitigate the potential negative effects of these restrictions. Methods: This is a longitudinal, concurrent, mixed methods study being conducted in British Columbia (BC), Canada. Data collection occurred at four time points, between April 2020 and February 2021. The first three data collection time points occurred within phases 1 to 3 of the Province of BC’s Restart Plan. The final data collection coincided with the initial distribution of the COVID-19 vaccines. At each time point, data regarding participants’ sociodemographics, depressive and anxiety symptoms, resilience, boredom, social support, instrumental activities of daily living, and social media and technology use were collected in an online survey. These data supplemented qualitative videoconference interviews exploring participants’ COVID-19–related experiences. Participants were also asked to upload photos representing their experience during the restriction period, which facilitated discussion during the final interview. Five groups of participants were recruited: (1) families with children under the age of 18 years, (2) adults with an SCI, (3) adults who experienced a stroke, (4) adults with other types of disabilities, and (5) older adults (>64 years of age) with no self-reported disability. The number of participants we could recruit from each group was limited, which may impact the validity of some subgroup analyses. Results: This study was approved by the University of British Columbia Behavioural Research Ethics Board (Approval No. H20-01109) on April 17, 2020. A total of 81 participants were enrolled in this study and data are being analyzed. Data analyses are expected to be completed in fall 2021; submission of multiple papers for publication is expected by winter 2021. Conclusions: Findings from our study will inform the development and recommendations of a new resource guide for the post–COVID-19 period and for future public health emergencies. International Registered Report Identifier (IRRID): DERR1-10.2196/28337 %M 34292163 %R 10.2196/28337 %U https://www.researchprotocols.org/2021/9/e28337 %U https://doi.org/10.2196/28337 %U http://www.ncbi.nlm.nih.gov/pubmed/34292163 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 8 %P e27713 %T Cross-Canada Release of the Post-Secondary Student Stressors Index (PSSI): Protocol for a Cross-sectional, Repeated Measures Study %A Linden,Brooke %+ Health Services and Policy Research Institute, Queen's University, 99 University Avenue, Kingston, ON, K7L 3P5, Canada, 1 613 533 2000, brooke.linden@queensu.ca %K stress %K mental health %K health promotion %K postsecondary %K higher education %K measurement tool %K study protocol %D 2021 %7 31.8.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: The prevalence of mental health–related problems, including stress, psychological distress, and symptoms of mental illnesses, continues to increase among Canadian postsecondary student populations. Excessive stress in this population has been linked to a number of negative academic and health outcomes. Despite attempts to improve mental health at postsecondary institutions, a persistent gap exists in the evaluation of the specific sources of stress for students within the postsecondary setting. Objective: The purpose of this paper is to report the study protocol for a cross-Canada, multisite launch of the Post-Secondary Student Stressors Index (PSSI), which will engage postsecondary institutions across the country as partners and facilitate improved measurement of the sources of student stress, in addition to contributing toward improved tailoring of upstream mental health services and support. Methods: Created in collaboration with students, the PSSI is a validated 46-item tool assessing stressors across five domains: academics, learning environment, campus culture, interpersonal, and personal stressors. The tool is designed to be applicable to students at all years, levels, and areas of study. Data will be collected longitudinally at multiple time points over the course of each academic year. Results: We recruited 15 postsecondary institutions across Canada for the first year, inviting students to participate in an online survey including questions concerning sociodemographic characteristics, stress, mental health, and resiliency. Analyses, including appropriate data visualization, will be conducted to determine the impact of specific stressors on mental health, linking responses over time to allow for the observation of changes in trends. Conclusions: The PSSI is an intuitive and evidence-informed tool that can aid postsecondary institutions in evaluating the sources of student stress on their campuses. This multisite project will make a substantial contribution to the current literature regarding postsecondary student stress and allow institutions across the country to improve the tailoring of upstream mental health services in order to directly support the unique needs of their student body. Opportunities for knowledge translation and exchange are discussed. International Registered Report Identifier (IRRID): DERR1-10.2196/27713 %M 34463632 %R 10.2196/27713 %U https://www.researchprotocols.org/2021/8/e27713 %U https://doi.org/10.2196/27713 %U http://www.ncbi.nlm.nih.gov/pubmed/34463632 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 6 %P e20128 %T Tracking Stress, Mental Health, and Resilience Factors in Medical Students Before, During, and After a Stress-Inducing Exam Period: Protocol and Proof-of-Principle Analyses for the RESIST Cohort Study %A Fritz,Jessica %A Stochl,Jan %A Kievit,Rogier A %A van Harmelen,Anne-Laura %A Wilkinson,Paul O %+ Department of Psychiatry, University of Cambridge, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom, 0044 1223 465253, jf585@cam.ac.uk %K exam stress %K perceived stress %K mental distress %K student mental health %K mental health resilience %K protective factors %K resilience factors %D 2021 %7 8.6.2021 %9 Original Paper %J JMIR Form Res %G English %X Background: Knowledge of mental distress and resilience factors over the time span from before to after a stressor is important to be able to leverage the most promising resilience factors and promote mental health at the right time. To shed light on this topic, we designed the RESIST (Resilience Study) study, in which we assessed medical students before, during, and after their yearly exam period. Exam time is generally a period of notable stress among medical students, and it has been suggested that exam time triggers mental distress. Objective: In this paper, we aim to describe the study protocol and to examine whether the exam period indeed induces higher perceived stress and mental distress. We also aim to explore whether perceived stress and mental distress coevolve in response to exams. Methods: RESIST is a cohort study in which exam stress functions as a within-subject natural stress manipulation. In this paper, we outline the sample (N=451), procedure, assessed measures (including demographics, perceived stress, mental distress, 13 resilience factors, and adversity), and ethical considerations. Moreover, we conducted a series of latent growth models and bivariate latent change score models to analyze perceived stress and mental distress changes over the 3 time points. Results: We found that perceived stress and mental distress increased from the time before the exams to the exam period and decreased after the exams to a lower level than before the exams. Our findings further suggest that higher mental distress before exams increased the risk of developing more perceived stress during exams. Higher perceived stress during exams, in turn, increased the risk of experiencing a less successful (or quick) recovery of mental distress after exams. Conclusions: As expected, the exam period caused a temporary increase in perceived stress and mental distress. Therefore, the RESIST study lends itself well to exploring resilience factors in response to naturally occurring exam stress. Such knowledge will eventually help researchers to find out which resilience factors lend themselves best as prevention targets and which lend themselves best as treatment targets for the mitigation of mental health problems that are triggered or accelerated by natural exam stress. The findings from the RESIST study may therefore inform student support services, mental health services, and resilience theory. %M 34100761 %R 10.2196/20128 %U https://formative.jmir.org/2021/6/e20128 %U https://doi.org/10.2196/20128 %U http://www.ncbi.nlm.nih.gov/pubmed/34100761 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 5 %P e24623 %T The Differential Effects of Social Media on Depressive Symptoms and Suicidal Ideation Among the Younger and Older Adult Population in Hong Kong During the COVID-19 Pandemic: Population-Based Cross-sectional Survey Study %A Yang,Xue %A Yip,Benjamin H K %A Mak,Arthur D P %A Zhang,Dexing %A Lee,Eric K P %A Wong,Samuel Y S %+ Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, School of Public Health Building, Prince of Wales Hospital, 30-32 Ngan Shing Street, Shatin, New Territories, Hong Kong, Hong Kong, 852 2252 8488, yeungshanwong@cuhk.edu.hk %K social media %K depression %K suicidal ideation %K social loneliness %K posttraumatic stress %K suicide %K mental health %K COVID-19 %K loneliness %K age %K mediation %D 2021 %7 25.5.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: Social media has become a ubiquitous part of daily life during the COVID-19 pandemic isolation. However, the role of social media use in depression and suicidal ideation of the general public remains unclear. Related empirical studies were limited and reported inconsistent findings. Little is known about the potential underlying mechanisms that may illustrate the relationship between social media use and depression and suicidal ideation during the COVID-19 pandemic. Objective: This study tested the mediation effects of social loneliness and posttraumatic stress disorder (PTSD) symptoms on the relationship between social media use and depressive symptoms and suicidal ideation, as well as the moderation effect of age on the mediation models. Methods: We administered a population-based random telephone survey in May and June 2020, when infection control measures were being vigorously implemented in Hong Kong. A total of 1070 adults (658 social media users and 412 nonusers) completed the survey. Structural equation modeling (SEM) and multigroup SEM were conducted to test the mediation and moderation effects. Results: The weighted prevalence of probable depression was 11.6%; 1.6% had suicidal ideation in the past 2 weeks. Both moderated mediation models of depressive symptoms (χ262=335.3; P<.05; comparative fit index [CFI]=0.94; nonnormed fit index [NNFI]=0.92; root mean square error of approximation [RMSEA]=0.06) and suicidal ideation (χ234=50.8; P<.05; CFI=0.99; NNFI=0.99; RMSEA=0.02) showed acceptable model fit. There was a significantly negative direct effect of social media use on depressive symptoms among older people (β=–.07; P=.04) but not among younger people (β=.04; P=.55). The indirect effect via PTSD symptoms was significantly positive among both younger people (β=.09; P=.02) and older people (β=.10; P=.01). The indirect effect via social loneliness was significant among older people (β=–.01; P=.04) but not among younger people (β=.01; P=.31). The direct effect of social media use on suicidal ideation was not statistically significant in either age group (P>.05). The indirect effects via PTSD symptoms were statistically significant among younger people (β=.02; P=.04) and older people (β=.03; P=.01). Social loneliness was not a significant mediator between social media use and suicidal ideation among either age group (P>.05). Conclusions: Social media may be a “double-edged sword” for psychosocial well-being during the COVID-19 pandemic, and its roles vary across age groups. The mediators identified in this study can be addressed by psychological interventions to prevent severe mental health problems during and after the COVID-19 pandemic. %M 33835937 %R 10.2196/24623 %U https://publichealth.jmir.org/2021/5/e24623 %U https://doi.org/10.2196/24623 %U http://www.ncbi.nlm.nih.gov/pubmed/33835937 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 5 %P e25009 %T Promoting the Mental Health of University Students in China: Protocol for Contextual Assessment to Inform Intervention Design and Adaptation %A Wong,Josephine Pui-Hing %A Jia,Cun-Xian %A Vahabi,Mandana %A Liu,Jenny Jing Wen %A Li,Alan Tai-Wai %A Cong,Xiaofeng %A Poon,Maurice Kwong-Lai %A Yamada,Janet %A Ning,Xuan %A Gao,Jianguo %A Cheng,Shengli %A Sun,Guoxiao %A Wang,Xinting %A Fung,Kenneth Po-Lun %+ Daphne Cockwell School of Nursing, Ryerson University, 350 Victoria Street, Toronto, ON, M5B2K3, Canada, 1 416 979 5000 ext 556303, jph.wong@ryerson.ca %K mental health %K mental illness %K stigma %K protocol %K acceptance and commitment therapy %K implementation science %K student mental health %D 2021 %7 11.5.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: Chinese students are extremely vulnerable to developing mental illness. The stigma associated with mental illness presents a barrier to seeking help for their mental health. Objective: The Linking Hearts—Linking Youth and ‘Xin’ (hearts) project is an implementation science project that seeks to reduce mental illness stigma and promote the mental health of university students in Jinan, China. The Linking Hearts project consists of 3 components. In this paper, we outline the protocol for the first component, that is, the contextual assessment and analysis of the mental health needs of university students as the first step to inform the adaptation of an evidence-based intervention to be implemented in Jinan, China. Methods: Six local universities will participate in the Linking Hearts project. A total of 100 students from each university (n=600) will engage in the contextual assessment through self-report surveys on depression, anxiety, stress, mental health knowledge, and mental health stigma. Quantitative data will be analyzed using several descriptive and inferential analyses via SPSS. A small number of participants (144 students and 144 service providers) will also be engaged in focus groups to assess the socio-environmental contexts of university students’ health and availability of mental health resources. Qualitative data will be transcribed verbatim and NVivo will be used for data management. Social network analysis will also be performed using EgoNet. Results: Linking Hearts was funded in January 2018 for 5 years. The protocol of Linking Hearts and its 3 components was approved by the research ethics boards of all participating institutions in China in November 2018. Canadian institutions that gave approval were Ryerson University (REB2018-455) in January 2019, University of Alberta (Pro00089364), York University (e2019-162) in May 2019, and University of Toronto (RIS37724) in August 2019. Data collection took place upon ethics approval and was completed in January 2020. A total of 600 students were surveyed. An additional 147 students and 138 service providers took part in focus groups. Data analysis is ongoing. Results will be published in 2021. Conclusions: Findings from this contextual assessment and analysis will generate new knowledge on university students’ mental health status, mental health knowledge, and resources available for them. These findings will be used to adapt and refine the Acceptance and Commitment to Empowerment-Linking Youth N’ Xin intervention model. The results of this contextual assessment will be used to inform the adaptation and refinement of the mental health intervention to promote the mental health of Chinese university students in Jinan. International Registered Report Identifier (IRRID): RR1-10.2196/25009 %M 33973869 %R 10.2196/25009 %U https://www.researchprotocols.org/2021/5/e25009 %U https://doi.org/10.2196/25009 %U http://www.ncbi.nlm.nih.gov/pubmed/33973869 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 8 %N 5 %P e27663 %T The Use of Closed-Circuit Television and Video in Suicide Prevention: Narrative Review and Future Directions %A Onie,Sandersan %A Li,Xun %A Liang,Morgan %A Sowmya,Arcot %A Larsen,Mark Erik %+ Black Dog Institute, University of New South Wales, Sydney, Hospital Road, Sydney, 2031, Australia, 61 432359134, sandy.onie@gmail.com %K suicide %K suicide prevention %K CCTV %K video %K computer vision %K machine learning %D 2021 %7 7.5.2021 %9 Original Paper %J JMIR Ment Health %G English %X Background: Suicide is a recognized public health issue, with approximately 800,000 people dying by suicide each year. Among the different technologies used in suicide research, closed-circuit television (CCTV) and video have been used for a wide array of applications, including assessing crisis behaviors at metro stations, and using computer vision to identify a suicide attempt in progress. However, there has been no review of suicide research and interventions using CCTV and video. Objective: The objective of this study was to review the literature to understand how CCTV and video data have been used in understanding and preventing suicide. Furthermore, to more fully capture progress in the field, we report on an ongoing study to respond to an identified gap in the narrative review, by using a computer vision–based system to identify behaviors prior to a suicide attempt. Methods: We conducted a search using the keywords “suicide,” “cctv,” and “video” on PubMed, Inspec, and Web of Science. We included any studies which used CCTV or video footage to understand or prevent suicide. If a study fell into our area of interest, we included it regardless of the quality as our goal was to understand the scope of how CCTV and video had been used rather than quantify any specific effect size, but we noted the shortcomings in their design and analyses when discussing the studies. Results: The review found that CCTV and video have primarily been used in 3 ways: (1) to identify risk factors for suicide (eg, inferring depression from facial expressions), (2) understanding suicide after an attempt (eg, forensic applications), and (3) as part of an intervention (eg, using computer vision and automated systems to identify if a suicide attempt is in progress). Furthermore, work in progress demonstrates how we can identify behaviors prior to an attempt at a hotspot, an important gap identified by papers in the literature. Conclusions: Thus far, CCTV and video have been used in a wide array of applications, most notably in designing automated detection systems, with the field heading toward an automated detection system for early intervention. Despite many challenges, we show promising progress in developing an automated detection system for preattempt behaviors, which may allow for early intervention. %M 33960952 %R 10.2196/27663 %U https://mental.jmir.org/2021/5/e27663 %U https://doi.org/10.2196/27663 %U http://www.ncbi.nlm.nih.gov/pubmed/33960952 %0 Journal Article %@ 2369-2960 %I JMIR Publications %V 7 %N 4 %P e25438 %T Exploring the Association Between Physical Activity and Risk of Mental Health Disorders in Saudi Arabian Adults: Cross-sectional Study %A Althumiri,Nora A %A Basyouni,Mada H %A BinDhim,Nasser F %+ Sharik Association For Health Research, Anas Ibn Malik RD, Riyadh, Saudi Arabia, 966 505435544, nora@althumiri.net %K Saudi Arabia %K physical activity %K mental health %K depression %K anxiety %K risk %K symptoms %K cross-sectional %K survey %D 2021 %7 14.4.2021 %9 Original Paper %J JMIR Public Health Surveill %G English %X Background: The relationship between physical activity and mental health, especially the symptoms of major depressive disorder (MDD) and generalized anxiety disorder (GAD), has received increasing attention in recent years. Objective: The aim of this study was to explore the association between fulfilling the World Health Organization (WHO) global recommendations on physical activity and the risk and symptoms of MDD and GAD in the Saudi population. Methods: This study was a secondary analysis of data from a large nationwide cross-sectional survey conducted via phone interviews in June and July 2020. In this study, a proportional quota sampling technique was used to obtain an equal distribution of participants, stratified by age and gender, across the 13 regions of Saudi Arabia. The main mental health screening tool used for the risk of MDD was the Patient Health Questionnaire-9 (PHQ-9). Risk of GAD was measured using the Generalized Anxiety Disorder-7 (GAD-7) scale. Participants self-reported whether they fulfill the WHO global recommendations on (1) moderate-intensity aerobic physical activity (MIPA) and (2) vigorous-intensity aerobic physical activity (VIPA). The results were then analyzed based on the following two categories: fulfilling the WHO global recommendations or not. Results: The data analysis included 8333 participants recruited in the main study between June and July 2020. The response rate was 81.45% (8333/10,231). Of them, 50.3% (4192/8333) were female, and the mean age was 36.5 years, with a median age of 36 years and a range from 18 to 90 years. The average total PHQ-9 score was 5.61, and the average total GAD-7 score was 4.18. For men, the average total PHQ-9 and GAD-7 scores were associated with fulfilling recommendations for MIPA; however, there were no associations for VIPA in both sexes. Fulfilling the WHO’s recommendations for MIPA was associated with considerably fewer depressive symptoms in six of the nine items in the PHQ-9. Moreover, fulfilling recommendations for MIPA was associated with considerably fewer anxiety symptoms in six of the seven items in the GAD-7. However, fulfilling recommendations for VIPA was significantly associated with more depressive symptoms in one of the PHQ-9 items (“Thoughts that you would be better off dead or thoughts of hurting yourself in some way;” P<.001). Conclusions: This study has shown that fulfilling guidelines on MIPA is associated with less overall risk of MDD and GAD in males and fewer depressive and anxiety symptoms generally in a nonclinical population. In the general population, an increase in MIPA may improve well-being and general mental health. %M 33851932 %R 10.2196/25438 %U https://publichealth.jmir.org/2021/4/e25438 %U https://doi.org/10.2196/25438 %U http://www.ncbi.nlm.nih.gov/pubmed/33851932 %0 Journal Article %@ 2561-326X %I JMIR Publications %V 5 %N 3 %P e18591 %T Recruitment and Retention Strategies for Community-Based Longitudinal Studies in Diverse Urban Neighborhoods %A Ferris,Emily B %A Wyka,Katarzyna %A Evenson,Kelly R %A Dorn,Joan M %A Thorpe,Lorna %A Catellier,Diane %A Huang,Terry T-K %+ Center for Systems and Community Design, Graduate School of Public Health and Health Policy, City University of New York, 55 W 125th St Room 80, New York, NY, 10027, United States, 1 646 364 0247, terry.huang@sph.cuny.edu %K community-based %K participant engagement %K natural experiment %K built environment intervention %K health disparities %K study adaptations %D 2021 %7 24.3.2021 %9 Viewpoint %J JMIR Form Res %G English %X Longitudinal, natural experiments provide an ideal evaluation approach to better understand the impact of built environment interventions on community health outcomes, particularly health disparities. As there are many participant engagement challenges inherent in the design of large-scale community-based studies, adaptive and iterative participant engagement strategies are critical. This paper shares practical lessons learned from the Physical Activity and Redesigned Community Spaces (PARCS) study, which is an evaluation of the impact of a citywide park renovation initiative on physical activity, psychosocial health, and community well-being. The PARCS study, although ongoing, has developed several approaches to improve participant engagement: building trust with communities, adapting the study protocol to meet participants’ needs and to reflect their capacity for participation, operational flexibility, and developing tracking systems. These strategies may help researchers anticipate and respond to participant engagement challenges in community-based studies, particularly in low-income communities of color. %M 33759799 %R 10.2196/18591 %U https://formative.jmir.org/2021/3/e18591 %U https://doi.org/10.2196/18591 %U http://www.ncbi.nlm.nih.gov/pubmed/33759799 %0 Journal Article %@ 1929-0748 %I JMIR Publications %V 10 %N 2 %P e24392 %T Prospective Associations Between Fixed-Term Contract Positions and Mental Illness Rates in Denmark’s General Workforce: Protocol for a Cohort Study %A Hannerz,Harald %A Burr,Hermann %A Soll-Johanning,Helle %A Nielsen,Martin Lindhardt %A Garde,Anne Helene %A Flyvholm,Mari-Ann %+ The National Research Center for the Working Environment, Lersø Parkallé 105, Copenhagen, 2100, Denmark, 45 39165460 ext 39165460, hha@nrcwe.dk %K cohort study %K fixed-term employment %K fixed term contract %K unemployment %K psychotropic drugs %K psychiatric hospital treatment %D 2021 %7 5.2.2021 %9 Protocol %J JMIR Res Protoc %G English %X Background: In 2018, 14% of employees in the European Union had fixed-term contracts. Fixed-term contract positions are often less secure than permanent contract positions. Perceived job insecurity has been associated with increased rates of mental ill health. However, the association between fixed-term contract positions and mental ill health is uncertain. A recent review concluded that the quality of most existing studies is low and that the results of the few studies with high quality are contradictory. Objective: This study aims to estimate the incidence rate ratios (RRs) of psychotropic drug use and psychiatric hospital treatment. These ratios will be considered, first, in relation to the contrast fixed-term versus permanent contract and, second, to fixed-term contract versus unemployment. Methods: Interview data with baseline information on employment status from the Danish Labor Force Surveys in the years 2001-2013 will be linked to data from national registers. Participants will be followed up for up to 5 years after the interview. Poisson regression will be used to estimate incidence RRs for psychiatric hospital treatment for mood, anxiety, or stress-related disorders and redeemed prescriptions for psychotropic drugs, as a function of employment status at baseline. The following contrasts will be considered: full-time temporary employment versus full-time permanent employment and temporary employment (regardless of weekly working hours) versus unemployment. The analyses will be controlled for a series of possible confounders. People who have received sickness benefits, have received social security cash benefits, have redeemed a prescription for psychotropic drugs, or have received psychiatric hospital treatment for a mental disorder sometime during a 1-year period preceding baseline will be excluded from the study. The study will include approximately 134,000 participants (13,000 unemployed, 106,000 with permanent contracts, and 15,000 with fixed-term contracts). We expect to find approximately 16,400 incident cases of redeemed prescriptions of psychotropic drugs and 2150 incident cases of psychiatric hospital treatment for mood, anxiety, or stress-related disorders. Results: We expect the analyses to be completed by the end of 2021 and the results to be published in mid-2022. Conclusions: The statistical power of the study will be large enough to test the hypothesis of a prospective association between fixed-term contract positions and mental illness in the general workforce of Denmark. International Registered Report Identifier (IRRID): DERR1-10.2196/24392 %M 33325837 %R 10.2196/24392 %U https://www.researchprotocols.org/2021/2/e24392 %U https://doi.org/10.2196/24392 %U http://www.ncbi.nlm.nih.gov/pubmed/33325837 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 7 %N 1 %P e12503 %T The Role of Campus Data in Representing Depression Among College Students: Exploratory Research %A Mei,Guang %A Xu,Weisheng %A Li,Li %A Zhao,Zhen %A Li,Hao %A Liu,Wenqing %A Jiao,Yueming %+ Department of Control Science and Engineering, College of Electronic and Information Engineering, Tongji University, Zhixin Bldg, 6th Fl, 4800 Caoan Rd, Shanghai, China, 86 18916087269, lili@tongji.edu.cn %K depression %K mental health %K behavior analysis %D 2020 %7 27.1.2020 %9 Original Paper %J JMIR Ment Health %G English %X Background: Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. Objective: The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. Methods: To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. Results: The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (r=–.179, P<.001), and, compared with other factors, had the greatest impact on students’ daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (r=.185, P=.02). Conclusions: The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data. %M 32012070 %R 10.2196/12503 %U http://mental.jmir.org/2020/1/e12503/ %U https://doi.org/10.2196/12503 %U http://www.ncbi.nlm.nih.gov/pubmed/32012070 %0 Journal Article %@ 2368-7959 %I JMIR Publications %V 6 %N 5 %P e13498 %T Adverse Childhood Experiences Ontology for Mental Health Surveillance, Research, and Evaluation: Advanced Knowledge Representation and Semantic Web Techniques %A Brenas,Jon Hael %A Shin,Eun Kyong %A Shaban-Nejad,Arash %+ Department of Pediatrics, Oak Ridge National Laboratory Center for Biomedical Informatics, University of Tennessee Health Science Center, 50 N Dunlap Street, R492, Memphis, TN, 38103, United States, 1 901 287 5836, ashabann@uthsc.edu %K ontologies %K mental health surveillance %K adverse childhood experiences %K semantics %K computational psychiatry %D 2019 %7 21.05.2019 %9 Original Paper %J JMIR Ment Health %G English %X Background: Adverse Childhood Experiences (ACEs), a set of negative events and processes that a person might encounter during childhood and adolescence, have been proven to be linked to increased risks of a multitude of negative health outcomes and conditions when children reach adulthood and beyond. Objective: To better understand the relationship between ACEs and their relevant risk factors with associated health outcomes and to eventually design and implement preventive interventions, access to an integrated coherent dataset is needed. Therefore, we implemented a formal ontology as a resource to allow the mental health community to facilitate data integration and knowledge modeling and to improve ACEs’ surveillance and research. Methods: We use advanced knowledge representation and semantic Web tools and techniques to implement the ontology. The current implementation of the ontology is expressed in the description logic ALCRIQ(D), a sublogic of Web Ontology Language (OWL 2). Results: The ACEs Ontology has been implemented and made available to the mental health community and the public via the BioPortal repository. Moreover, multiple use-case scenarios have been introduced to showcase and evaluate the usability of the ontology in action. The ontology was created to be used by major actors in the ACEs community with different applications, from the diagnosis of individuals and predicting potential negative outcomes that they might encounter to the prevention of ACEs in a population and designing interventions and policies. Conclusions: The ACEs Ontology provides a uniform and reusable semantic network and an integrated knowledge structure for mental health practitioners and researchers to improve ACEs’ surveillance and evaluation. %M 31115344 %R 10.2196/13498 %U http://mental.jmir.org/2019/5/e13498/ %U https://doi.org/10.2196/13498 %U http://www.ncbi.nlm.nih.gov/pubmed/31115344