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(Toronto, Aug 29, 2019) Clarivate Analytics has now confirmed that JMIR Mental Health has (finally) been admitted to SCIE/JCR, meaning that it will receive its first official 2019 Impact Factor, to be released by Clarivate in June 2020, reflecting the number of citations in 2019 to articles published in 2018 or 2017. We expect the IF to place the journal firmly in the Q1 (top 25% of journals).
JMIR Mental Health (JMH, ISSN 2368-7959, Editor-in-Chief: John Torous MD MBI) is a PubMed-indexed, peer-reviewed journal which has a unique focus on digital health and Internet/mobile interventions, technologies and electronic innovations (software and hardware) for mental health, addictions, online counselling and behaviour change. This includes formative evaluation and system descriptions, theoretical papers, review papers, viewpoint/vision papers, and rigorous evaluations related to digital psychiatry, e-mental health, and clinical informatics in psychiatry/psychology. The main themes/topics covered by this journal can be found here.
JMIR Mental Health has an international author- and readership and welcomes submissions from around the world.
JMIR Mental Health features a rapid and thorough peer-review process, professional copyediting, professional production of PDF, XHTML, and XML proofs.
The journal is indexed in PubMed, PubMed Central, and SCIE (Science Citation Index Expanded)/WoS/JCR (Journal Citation Reports).
Background: Innovative interventions are needed to address the increasing mental health needs of university students. Given the demonstrated anxiolytic and antidepressant benefits of mindfulness training, we developed an 8-week, Web-based Mindfulness Virtual Community (MVC) intervention informed by cognitive behavioral therapy (CBT) constructs.
Objective: This study investigated the efficacy of the MVC intervention in reducing symptoms of depression, anxiety, and stress among undergraduate students in Toronto, Canada. The secondary outcomes included quality of life, life satisfaction, and mindfulness.
Methods: The first 4 weeks of the full MVC intervention (F-MVC) comprised: (1) 12 video-based modules with psycho-education on students’ preidentified stressful topics and topically applied mindfulness practice; (2) anonymous peer-to-peer discussion forums; and (3) anonymous, group-based, professionally guided, 20-min live videoconferences. The second 4 weeks of F-MVC involved access only to video-based modules. The 8-week partial MVC (P-MVC) comprised 12 video-based modules. A randomized controlled trial was conducted with 4 parallel arms: F-MVC, P-MVC, waitlist control (WLC), and group-based face-to-face CBT; results for the latter group are presented elsewhere. Students recruited through multiple strategies consented and were randomized: WLC=40; F-MVC=40, P-MVC=39; all learned about allocation after consenting. The online surveys at baseline (T1), 4 weeks (T2), and 8 weeks (T3) included the Patient Health Questionnaire-9 item, Beck Anxiety Inventory, Perceived Stress Scale, Quality of Life Scale, Brief Multi-Dimensional Students Life Satisfaction Scale, and Five-Facet Mindfulness Questionnaire. Analyses employed generalized estimation equation methods with AR(1) covariance structures and were adjusted for possible confounders (gender, age, birth country, paid work, unpaid work, physical activities, self-rated health, and mental health counseling access).
Results: Of the 113 students who provided T1 data, 28 were males and 85 were females with a mean age of 24.8 years. Participants in F-MVC (n=39), P-MVC (n=35), and WLC (n=39) groups were similar in sociodemographic characteristics at T1. At T3 follow-up, per adjusted comparisons, there were statistically significant reductions in depression scores for F-MVC (score change −4.03; P<.001) and P-MVC (score change −4.82; P<.001) when compared with WLC. At T3, there was a statistically significant reduction in anxiety scores only for P-MVC (score change −7.35; P=.01) when compared with WLC. There was a statistically significant reduction in scores for perceived stress for both F-MVC (score change −5.32; P<.001) and P-MVC (score change −5.61; P=.005) compared with WLC. There were statistically significant changes at T3 for quality of life and mindfulness for F-MVC and P-MVC vs WLC but not for life satisfaction.
Conclusions: Internet-based mindfulness CBT–based interventions, such as F-MVC and P-MVC, can result in significant reductions in symptoms of depression, anxiety, and stress in a student population. Future research with a larger sample from multiple universities would more precisely test generalizability.
Trial Registration: International Standard Randomized Controlled Trial Number ISRCTN92827275; https://www.isrctn.com/ISRCTN92827275
Background: In-person motivational interventions increase engagement with evidence-based cessation treatments among smokers with schizophrenia, but access to such interventions can be limited because of workforce shortages and competing demands in mental health clinics. The use of digital technology to deliver interventions can increase access, but cognitive impairments in schizophrenia may impede the use of standard digital interventions. We developed an interactive, multimedia, digital motivational decision support system for smokers with schizophrenia (Let’s Talk About Smoking). We also digitalized a standard educational pamphlet from the National Cancer Institute (NCI Education). Both were tailored to reduce cognitive load during use.
Objective: We conducted a randomized trial of Let’s Talk About Smoking versus NCI Education to test whether the interactive motivational intervention was more effective and more appealing than the static educational intervention for increasing use of smoking cessation treatment, quit attempts, and abstinence among smokers with schizophrenia, accounting for the level of cognitive functioning.
Methods: Adult smokers with schizophrenia (n=162) were enrolled in the study from 2014 to 2015, randomly assigned to an intervention condition, and assessed in person at 3- and 6-month follow-ups. Interventions were delivered on a laptop computer in a single session. All participants had access to standard, community-delivered cessation treatments during follow-up. Multivariate models were used to evaluate outcomes.
Results: Treatment initiation outcomes were not different between intervention conditions (27/84 [32%] for Let’s Talk About Smoking vs 36/78 [46%] for NCI Education; odds ratio [OR] 0.71 [95% CI 0.37-1.33]); 38.9% (63/162) of participants initiated treatment. Older age (OR 1.03 [95% CI 1.00-1.07]; P=.05), higher education (OR 1.21 [95% CI 1.04-1.41]; P=.03), and fewer positive symptoms (OR 0.87 [95% CI 0.80-0.96]; P=.01) predicted cessation treatment initiation, whereas level of cognition did not. The mean satisfaction and usability index score was higher for Let’s Talk About Smoking versus NCI Education (8.9 [SD 1.3] vs 8.3 [SD 2.1]; t120.7=2.0; P=.045). Quit attempts (25/84, 30% vs 36/78, 46%; estimate [Est]=−0.093, SE 0.48; P=.85) and abstinence (1/84, 1% vs 6/78, 7%; χ21=3.4; P=.07) were not significantly different between intervention conditions. Cognitive functioning at baseline (Est=1.47, SE 0.47; P=.002) and use of any behavioral or medication cessation treatment (Est=1.43, SE 0.47; P=.003) predicted quit attempts with self-reported abstinence over the 6-month follow-up.
Conclusions: The interactive, multimedia intervention was not more effective than the static, text-based intervention among smokers with schizophrenia. Both tailored digital interventions resulted in levels of treatment engagement and quit attempts that were similar to findings from previous studies of in-person interventions, confirming the potential role of digital interventions to educate and motivate smokers with schizophrenia to use cessation treatment and to quit smoking. These findings indicate that additional cessation treatment is needed after brief education or motivational interventions, and that cessation treatment should be adjusted for people with cognitive impairment.
Trial Registration: ClinicalTrials.gov NCT02086162; https://clinicaltrials.gov/show/NCT02086162
Background: Health information technologies (HITs) hold enormous promise for improving access to and providing better quality of mental health care. However, despite the spread of such technologies in high-income countries, these technologies have not yet been commonly adopted in low- and middle-income countries. People living in these parts of the world are at risk of experiencing physical, technological, and social health inequalities. A possible solution is to utilize the currently available HITs developed in other counties.
Objective: Using participatory design methodologies with Colombian end users (young people, their supportive others, and health professionals), this study aimed to conduct co-design workshops to culturally adapt a Web-based Mental Health eClinic (MHeC) for young people, perform one-on-one user-testing sessions to evaluate an alpha prototype of a Spanish version of the MHeC and adapt it to the Colombian context, and inform the development of a skeletal framework and alpha prototype for a Colombian version of the MHeC (MHeC-C).
Methods: This study involved the utilization of a research and development (R&D) cycle including 4 iterative phases: co-design workshops; knowledge translation; tailoring to language, culture, and place (or context); and one-on-one user-testing sessions.
Results: A total of 2 co-design workshops were held with 18 users—young people (n=7) and health professionals (n=11). Moreover, 10 users participated in one-on-one user-testing sessions—young people (n=5), supportive others (n=2), and health professionals (n=3). A total of 204 source documents were collected and 605 annotations were coded. A thematic analysis resulted in 6 themes (ie, opinions about the MHeC-C, Colombian context, functionality, content, user interface, and technology platforms). Participants liked the idea of having an MHeC designed and adapted for Colombian young people, and its 5 key elements were acceptable in this context (home page and triage system, self-report assessment, dashboard of results, booking and video-visit system, and personalized well-being plan). However, to be relevant in Colombia, participants stressed the need to develop additional functionality (eg, phone network backup; chat; geolocation; and integration with electronic medical records, apps, or electronic tools) as well as an adaptation of the self-report assessment. Importantly, the latter not only included language but also culture and context.
Conclusions: The application of an R&D cycle that also included processes for adaptation to Colombia (language, culture, and context) resulted in the development of an evidence-based, language-appropriate, culturally sensitive, and context-adapted HIT that is relevant, applicable, engaging, and usable in both the short and long term. The resultant R&D cycle allowed for the adaptation of an already available HIT (ie, MHeC) to the MHeC-C—a low-cost and scalable technology solution for low- and middle-income countries like Colombia, which has the potential to provide young people with accessible, available, affordable, and integrated mental health care at the right time.
Background: Internet-based cognitive behavioral therapy (iCBT) increases treatment access for adolescents with anxiety; however, completion rates of iCBT programs are typically low. Understanding adolescents’ experiences with iCBT, what program features and changes in anxiety (minimal clinically important difference [MCID]) are important to them, may help explain and improve iCBT program use and impact.
Objective: Within a randomized controlled trial comparing a six-session iCBT program for adolescent anxiety, Being Real, Easing Anxiety: Tools Helping Electronically (Breathe), with anxiety-based resource webpages, we aimed to (1) describe intervention use among adolescents allocated to Breathe or webpages and those who completed postintervention assessments (Breathe or webpage respondents); (2) describe and compare user experiences between groups; and (3) calculate an MCID for anxiety and explore relationships between iCBT use, experiences, and treatment response among Breathe respondents.
Methods: Enrolled adolescents with self-reported anxiety, aged 13 to 19 years, were randomly allocated to Breathe or webpages. Self-reported demographics and anxiety symptoms (Multidimensional Anxiety Scale for Children—2nd edition [MASC-2]) were collected preintervention. Automatically-captured Breathe or webpage use and self-reported symptoms and experiences (User Experience Questionnaire for Internet-based Interventions) were collected postintervention. Breathe respondents also reported their perceived change in anxiety (Global Rating of Change Scale [GRCS]) following program use. Descriptive statistics summarized usage and experience outcomes, and independent samples t tests and correlations examined relationships between them. The MCID was calculated using the mean MASC-2 change score among Breathe respondents reporting somewhat better anxiety on the GRCS.
Results: Adolescents were mostly female (382/536, 71.3%), aged 16.6 years (SD 1.7), with very elevated anxiety (mean 92.2, SD 18.1). Intervention use was low for adolescents allocated to Breathe (mean 2.2 sessions, SD 2.3; n=258) or webpages (mean 2.1 visits, SD 2.7; n=278), but was higher for Breathe (median 6.0, range 1-6; 81/258) and webpage respondents (median 2.0, range 1-9; 148/278). Total user experience was significantly more positive for Breathe than webpage respondents (P<.001). Breathe respondents reported program design and delivery factors that may have challenged (eg, time constraints and program support) or facilitated (eg, demonstration videos, self-management activities) program use. The MCID was a mean MASC-2 change score of 13.8 (SD 18.1). Using the MCID, a positive treatment response was generated for 43% (35/81) of Breathe respondents. Treatment response was not correlated with respondents’ experiences or use of Breathe (P=.32 to P=.88).
Conclusions: Respondents reported positive experiences and changes in their anxiety with Breathe; however, their reports were not correlated with program use. Breathe respondents identified program design and delivery factors that help explain their experiences and use of iCBT and inform program improvements. Future studies can apply our measures to compare user experiences between internet-based interventions, interpret treatment outcomes and improve treatment decision making for adolescents with anxiety.
Trial Registration: ClinicalTrials.gov NCT02970734; https://clinicaltrials.gov/ct2/show/NCT02970734
Background: Anxiety and depression are leading causes of disability but are often undertreated. Internet-delivered cognitive behavioral therapy (ICBT) improves access to treatment by overcoming barriers to obtaining care. ICBT has been found to be efficacious in research trials and routine care, but there is limited research of ICBT when it is recommended and funded by insurance companies for clients on or recently in receipt of disability benefits or accommodations.
Objective: The aim of this study was to examine ICBT engagement, treatment satisfaction, and effectiveness among individuals involved with 2 insurance companies. The 2 samples were benchmarked against published outcomes from a publicly funded (PF) ICBT clinic.
Methods: Individuals who were on or recently in receipt of disability benefits and were either insurance company (IC) employees (n=21) or IC plan members (n=19) were referred to ICBT funded by the respective insurance companies. Outcomes were benchmarked against outcomes of ICBT obtained in a PF ICBT clinic, with clients in the clinic divided into those who reported no involvement with insurance companies (n=414) and those who were on short-term disability (n=44). All clients received the same 8-week, therapist-assisted, transdiagnostic ICBT course targeting anxiety and depression. Engagement was assessed using completion rates, log-ins, and emails exchanged. Treatment satisfaction was assessed posttreatment. Depression, anxiety, and disability measures were administered pretreatment, posttreatment, and at 3 months.
Results: All samples showed high levels of ICBT engagement and treatment satisfaction. IC employees experienced significant improvement at posttreatment (depression d=0.77; anxiety d=1.13; and disability d=0.91) with outcomes maintained at 3 months. IC plan members, who notably had greater pretreatment disability than the other samples, experienced significant moderate effects at posttreatment (depression d=0.58; anxiety d=0.54; and disability d=0.60), but gains were not maintained at 3 months. Effect sizes at posttreatment in both IC samples were significantly smaller than in the PF sample who reported no insurance benefits (depression d=1.14 and anxiety d=1.30) and the PF sample who reported having short-term disability benefits (depression d=0.95 and anxiety d=1.07). No difference was seen in effect sizes among IC employees and the PF samples on disability. However, IC plan members experienced significantly smaller effects on disability d=0.60) compared with the PF sample with no disability benefits d=0.90) and those on short-term disability benefits d=0.94).
Conclusions: Many clients referred and funded by insurance companies were engaged with ICBT and found it acceptable and effective. Results, however, were not maintained among those with very high levels of pretreatment disability. Small sample sizes in the IC groups are a limitation. Directions for research related to ICBT funded by insurance companies have been described.
Background: The rates of mental illness among African American women are comparable with the general population; however, they significantly underutilize mental health services compared with their white counterparts. Previous studies revealed that interventions delivered via text messaging are effective and can be used to increase access to services and resources. More insight into whether or not this modality is acceptable for use to deliver mental health care to help African American women manage anxiety and depression is needed.
Objective: This exploratory study aimed to gain insight into the acceptability of using text messaging to help African American women manage anxiety and depression.
Methods: A self-administered Web-based survey was launched in June 2018 and closed in August 2018. Eligible participants were African American women (18 years or older) who reside in the United States. Participants were recruited through convenience sampling (eg, email sent via listservs and social media posts). Respondents were provided an anonymous link to the questionnaire. The survey consisted of 53 questions on the following subjects: sociodemographic characteristics, attitudes toward seeking professional psychological help, mobile phone use, and acceptability of using a mobile phone to receive mental health care.
Results: The results of this exploratory study (N=101) showed that fewer than half of respondents endorsed the use of text messaging to communicate with a professional to receive help to manage anxiety (49/101, 48.5%) and depression (43/101, 42.6%). Approximately 51.4% (52/101) agreed that having the option to use text messaging to communicate with a professional if they are dealing with anxiety would be helpful. Similarly, 48.5% (49/101) agreed that having the option to use text messaging to communicate with a professional if they are dealing with depression would be helpful. Among participants who agreed that text messaging would be helpful, more than 80% noted being comfortable with its use to receive help for managing anxiety (approximately 86%, 45/52) and depression (approximately 82%, 40/49; highly significant positive association, all P<.001). More than 50% of respondents (56/101, 55.4%) indicated having concerns about using text messaging. No statistically significant associations were found between age and agreement with the use of text messaging to communicate with a professional to receive help for managing anxiety (P=.26) or depression (P=.27).
Conclusions: The use of text messaging was not highly endorsed by African American women as an acceptable mode of communication with a professional to help them manage anxiety or depression. Concerns around privacy, confidentiality, and the impersonal feel of communicating about sensitive issues via text messages must be addressed for this modality to be a viable option. The findings of this study demonstrated the need for further research into the use of mobile technology to provide this population with more accessible and convenient options for mental health care.
Background: Internet-delivered treatments for depressive symptoms have proved to be successful in high-income Western countries. There may be potential for implementing such treatments in low- and middle-income countries such as Colombia, where access to mental health services is limited.
Objective: The objective of this study was to assess the efficacy of a culturally adapted cognitive behavioral internet-delivered treatment for college students with depressive symptoms in Colombia.
Methods: This was a randomized controlled trial with a 3-month follow-up. The program comprised seven modules. A total of 214 Colombian college students were recruited. They were assessed and randomly assigned to either the treatment group (n=107) or a waiting list (WL) control group (n=107). Participants received weekly support from a trained supporter. The primary outcome was symptoms of depression, as measured by the Patient Health Questionnaire - 9, and the secondary outcomes were anxiety symptoms assessed by the Generalized Anxiety Disorder questionnaire - 7. Other measures, including satisfaction with treatment, were evaluated after 7 weeks.
Results: Research attrition and treatment dropouts were high in this study. On average, 7.6 sessions were completed per user. The mean time spent on the program was 3 hours and 18 min. The linear mixed model (LMM) showed significant effects after treatment (t197.54=−5.189; P<.001) for the treatment group, and these effects were maintained at the 3-month follow-up (t39.62=4.668; P<.001). Within-group results for the treatment group yielded a large effect size post treatment (d=1.44; P<.001), and this was maintained at the 3-month follow-up (d=1.81; P<.001). In addition, the LMM showed significant differences between the groups (t197.54=−5.189; P<.001). The results showed a large effect size between the groups (d=0.91; P<.001). In the treatment group, 76.0% (16/107) achieved a reliable change, compared with 32.0% (17/107) in the WL control group. The difference between groups was statistically significant (X22=10.5; P=.001).
Conclusions: This study was the first contribution to investigating the potential impact of a culturally adapted internet-delivered treatment on depressive symptoms for college students as compared with a WL control group in South America. Future research should focus on identifying variables associated both with premature dropout and treatment withdrawal at follow-up.
Trial Registration: ClinicalTrials.gov NCT03062215; https://clinicaltrials.gov/ct2/show/NCT03062215
Background: Population-based studies show that the risk of mental ill health is highest among young people aged 10 to 24 years, who are also the least likely to seek professional treatment because of a number of barriers. Electronic mental (e-mental) health services have been advocated as a method for decreasing these barriers for young people, among which text-based online counseling (TBOC) is a primary intervention used at many youth-oriented services. Although TBOC has shown promising results, its outcome variance is greater in comparison with other electronic interventions and adult user groups.
Objective: This pilot study aimed to explore and confirm e-mental health professional’s perspectives about various domains and themes related to young service users’ (YSUs) motivations for accessing TBOC services and factors related to higher and lower effectiveness on these modalities.
Methods: Participants were 9 e-mental health professionals who were interviewed individually and in focus groups using a semistructured interview. Thematic analysis of qualitative themes from interview transcripts was examined across the areas of YSU motivations for access and factors that increase and decrease TBOC effectiveness.
Results: A total of 4 domains and various subthemes were confirmed and identified to be related to YSUs’ characteristics, motivations for accessing TBOC, and moderators of service effectiveness: user characteristics (ie, prior negative help-seeking experience, mental health syndrome, limited social support, and perceived social difficulties), selection factors (ie, safety, avoidance motivation, accessibility, and expectation), and factors perceived to increase effectiveness (ie, general therapeutic benefits, positive service-modality factors, and persisting with counseling despite substantial benefit) and decrease effectiveness (ie, negative service-modality factors).
Conclusions: Participants perceived YSUs to have polarized expectations of TBOC effectiveness and be motivated by service accessibility and safety, in response to several help-seeking concerns. Factors increasing TBOC effectiveness were using text-based communication, the online counselor’s interpersonal skills and use of self-management and crisis-support strategies, and working with less complex presenting problems or facilitating access to more intensive support. Factors decreasing TBOC effectiveness were working with more complex problems owing to challenges with assessment, the slow pace of text communication, lack of nonverbal conversational cues, and environmental and connectivity issues. Other factors were using ineffective techniques (eg, poor goal setting, focusing, and postcounseling direction) that produced only short-term outcomes, poor timeliness in responding to service requests, rupture in rapport from managing service boundaries, and low YSU readiness and motivation.
Background: Although patient history is essential for informing mental health assessment, diagnosis, and prognosis, there is a dearth of standardized instruments measuring time-dependent factors relevant to psychiatric disorders. Previous research has demonstrated the potential utility of graphical representations, termed life charts, for depicting the complexity of the course of mental illness. However, the implementation of these assessments is limited by the exclusive focus on specific mental illnesses (ie, bipolar disorder) and the lack of intuitive graphical interfaces for data collection and visualization.
Objective: This study aimed to develop and test the utility of the Tulsa Life Chart (TLC) as a Web-based, structured approach for obtaining and graphically representing historical information on psychosocial and mental health events relevant across a spectrum of psychiatric disorders.
Methods: The TLC interview was completed at baseline by 499 participants of the Tulsa 1000, a longitudinal study of individuals with depressive, anxiety, substance use, or eating disorders and healthy comparisons (HCs). All data were entered electronically, and a 1-page electronic and interactive graphical representation was developed using the Google Visualization Application Programming Interface. For 8 distinct life epochs (periods of approximately 5-10 years), the TLC assessed the following factors: school attendance, hobbies, jobs, social support, substance use, mental health treatment, family structure changes, negative and positive events, and epoch and event-related mood ratings. We used generalized linear mixed models (GLMMs) to evaluate trajectories of each domain over time and by sex, age, and diagnosis, using case examples and Web-based interactive graphs to visualize data.
Results: GLMM analyses revealed main or interaction effects of epoch and diagnosis for all domains. Epoch by diagnosis interactions were identified for mood ratings and the number of negative-versus-positive events (all P values <.001), with all psychiatric groups reporting worse mood and greater negative-versus-positive events than HCs. These differences were most robust at different epochs, depending on diagnosis. There were also diagnosis and epoch main effects for substance use, mental health treatment received, social support, and hobbies (P<.001). User experience ratings (each on a 1-5 scale) revealed that participants found the TLC pleasant to complete (mean 3.07, SD 1.26) and useful for understanding their mental health (mean 3.07, SD 1.26), and that they were likely to recommend it to others (mean 3.42, SD 0.85).
Conclusions: The TLC provides a structured, Web-based transdiagnostic assessment of psychosocial history relevant for the diagnosis and treatment of psychiatric disorders. Interactive, 1-page graphical representations of the TLC allow for the efficient communication of historical life information that would be useful for clinicians, patients, and family members.
Background: Web-based information and interventions for mental illness are increasingly being provided. There is an expectation that citizens have access to the internet and are competent in using technology. People with schizophrenia are often excluded from social engagement, have cognitive impairment, and have very limited income, all of which may reduce their use of technology.
Objective: This study aimed to investigate technology access, use of digital technology, and confidence in using technology among people with schizophrenia living in the community.
Methods: Face-to-face structured interviews with 50 people with schizophrenia (aged 18-65 years) living in the northern suburbs of Adelaide, South Australia, were conducted using an instrument designed to assess technology access and utilization.
Results: Most participants (42/50, 84%) owned a mobile phone, but only 58% (29/50) owned a smartphone. Two-thirds of participants (33/50, 66%) had access to the internet at home, using a smartphone or computer. Moreover, 40% (20/50) of participants used the internet at least daily, but 30% (15/50) of participants had never accessed the internet from any device. Approximately half of the participants (24/50, 48%) had never used Facebook. Participants rarely used community facilities (eg, libraries and cafes) to access the internet. There were no significant differences (P values ranged from .14 to .70) between younger participants (aged 18-34 years) and older participants (aged 35-64 years) in internet or smartphone access or confidence in using technology.
Conclusions: Although the sample size of this study is small, it shows limited technology access, use of digital technology, and confidence in using technology among the participants. This could be a barrier to the online delivery of information and interventions for people with schizophrenia. To better understand the impacts of such technological disadvantage and potential disparities in access and use of online resources, prospective studies should recruit a larger sample size and include control subjects matched for socioeconomic disadvantage.
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.
Background: In the last decade, there has been a proliferation of mobile apps claiming to support the needs of people living with depression. However, it is unclear what functionality is actually provided by apps for depression, or for whom they are intended.
Objective: This paper aimed to explore the key features of top-rated apps for depression, including descriptive characteristics, functionality, and ethical concerns, to better inform the design of apps for depression.
Methods: We reviewed top-rated iPhone OS (iOS) and Android mobile apps for depression retrieved from app marketplaces in spring 2019. We applied a systematic analysis to review the selected apps, for which data were gathered from the 2 marketplaces and through direct use of the apps. We report an in-depth analysis of app functionality, namely, screening, tracking, and provision of interventions. Of the initially identified 482 apps, 29 apps met the criteria for inclusion in this review. Apps were included if they remained accessible at the moment of evaluation, were offered in mental health–relevant categories, received a review score greater than 4.0 out of 5.0 by more than 100 reviewers, and had depression as a primary target.
Results: The analysis revealed that a majority of apps specify the evidence base for their intervention (18/29, 62%), whereas a smaller proportion describes receiving clinical input into their design (12/29, 41%). All the selected apps are rated as suitable for children and adolescents on the marketplace, but 83% (24/29) do not provide a privacy policy consistent with their rating. The findings also show that most apps provide multiple functions. The most commonly implemented functions include provision of interventions (24/29, 83%) either as a digitalized therapeutic intervention or as support for mood expression; tracking (19/29, 66%) of moods, thoughts, or behaviors for supporting the intervention; and screening (9/29, 31%) to inform the decision to use the app and its intervention. Some apps include overtly negative content.
Conclusions: Currently available top-ranked apps for depression on the major marketplaces provide diverse functionality to benefit users across a range of age groups; however, guidelines and frameworks are still needed to ensure users’ privacy and safety while using them. Suggestions include clearly defining the age of the target population and explicit disclosure of the sharing of users’ sensitive data with third parties. In addition, we found an opportunity for apps to better leverage digital affordances for mitigating harm, for personalizing interventions, and for tracking multimodal content. The study further demonstrated the need to consider potential risks while using depression apps, including the use of nonvalidated screening tools, tracking negative moods or thinking patterns, and exposing users to negative emotional expression content.
