JMIR Publications

Recent Articles:

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  Depression and Mood Disorders

  Jun 22, 2018

  Using Neural Networks with Routine Health Records to Identify Suicide Risk: Feasibility Study

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  Authors List:

  • Marcos DelPozo-Banos  
  • Ann John  
  • Nicolai Petkov  
  • Damon Mark Berridge  
  • Kate Southern  
  • Keith LLoyd  
  • Caroline Jones  
  • Sarah Spencer  
  • Carlos Manuel Travieso  

  Abstract:

  Background: Each year, approximately 800,000 people die by suicide worldwide, accounting for 1–2 in every 100 deaths. It is always a tragic event with a huge impact on family, friends, the community and health professionals. Unfortunately, suicide prevention and the development of risk assessment tools have been hindered by the complexity of the underlying mechanisms and the dynamic nature of a person’s motivation and intent. Many of those who die by suicide had contact with health services in the preceding year but identifying those most at risk remains a challenge. Objective: To explore the feasibility of using artificial neural networks with routinely collected electronic health records to support the identification of those at high risk of suicide when in contact with health services. Methods: Using the Secure Anonymised Information Linkage Databank UK, we extracted the data of those who died by suicide between 2001 and 2015 and paired controls. Looking at primary (general practice) and secondary (hospital admissions) electronic health records, we built a binary feature vector coding the presence of risk factors at different times prior to death. Risk factors included: general practice contact and hospital admission; diagnosis of mental health issues; injury and poisoning; substance misuse; maltreatment; sleep disorders; and the prescription of opiates and psychotropics. Basic artificial neural networks were trained to differentiate between the suicide cases and paired controls. We interpreted the output score as the estimated suicide risk. System performance was assessed with 10x10-fold repeated cross-validation, and its behavior was studied by representing the distribution of estimated risk across the cases and controls, and the distribution of factors across estimated risks. Results: We extracted a total of 2604 suicide cases and 20 paired controls per case. Our best system attained a mean error rate of 26.78% (SD 1.46; 64.57% of sensitivity and 81.86% of specificity). While the distribution of controls was concentrated around estimated risks < 0.5, cases were almost uniformly distributed between 0 and 1. Prescription of psychotropics, depression and anxiety, and self-harm increased the estimated risk by ~0.4. At least 95% of those presenting these factors were identified as suicide cases. Conclusions: Despite the simplicity of the implemented system, the proposed methodology obtained an accuracy like other published methods based on specialized questionnaire generated data. Most of the errors came from the heterogeneity of patterns shown by suicide cases, some of which were identical to those of the paired controls. Prescription of psychotropics, depression and anxiety, and self-harm were strongly linked with higher estimated risk scores, followed by hospital admission and long-term drug and alcohol misuse. Other risk factors like sleep disorders and maltreatment had more complex effects.

  • JMIR Ment Health 2018;5(2):e10144

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  Innovations in Mental Health Systems

  Jun 21, 2018

  Open Notes in Swedish Psychiatric Care (Part 2): Survey Among Psychiatric Care Professionals

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  Authors List:

  • Lena Petersson  
  • Gudbjörg Erlingsdóttir  

  Abstract:

  Background: This is the second of two papers presenting the results from a study of the implementation of patient online access to their electronic health records (here referred to as Open Notes) in adult psychiatric care in Sweden. The study contributes an important understanding of both the expectations and concerns that existed among health care professionals before the introduction of the Open Notes Service in psychiatry and the perceived impact of the technology on their own work and patient behavior after the implementation. The results from the previously published baseline survey showed that psychiatric health care professionals generally thought that Open Notes would influence both the patients and their own practice negatively. Objective: The objective of this study was to describe and discuss how health care professionals in adult psychiatric care in Region Skåne in southern Sweden experienced the influence of Open Notes on their patients and their own practice, and to compare the results with those of the baseline study. Methods: We distributed a full population Web-based questionnaire to psychiatric care professionals in Region Skåne in the spring of 2017, which was one and a half years after the implementation of the service. The response rate was 27.73% (699/2521). Analyses showed that the respondents were representative of the staff as a whole. A statistical analysis examined the relationships between health professional groups and attitudes to the Open Notes Service. Results: A total of 41.5% (285/687) of the health care professionals reported that none of their patients stated that they had read their Open Notes. Few health care professionals agreed with the statements about the potential benefits for patients from Open Notes. Slightly more of the health care professionals agreed with the statements about the potential risks. In addition, the results indicate that there was little impact on practice in terms of longer appointments or health care professionals having to address patients’ questions outside of appointments. However, the results also indicate that changes had taken place in clinical documentation. Psychologists (39/63, 62%) and doctors (36/94, 38%) in particular stated that they were less candid in their documentation after the implementation of Open Notes. Nearly 40% of the health care professionals (239/650, 36.8%) reported that the Open Notes Service in psychiatry was a good idea. Conclusions: Most health care professionals who responded to the postimplementation survey did not experience that patients in adult psychiatric care had become more involved in their care after the implementation of Open Notes. The results also indicate that the clinical documentation had changed after the implementation of Open Notes. Finally, the results indicate that it is important to prepare health care professionals before an implementation of Open Notes, especially in medical areas where the service is considered sensitive.

  • JMIR Ment Health 2018;5(2):e10521

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  Posttraumatic Stress Disorder (PTSD)

  Jun 15, 2018

  Veterans’ Perspectives on Fitbit Use in Treatment for Post-Traumatic Stress Disorder: An Interview Study

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  Authors List:

  • Ada Ng  
  • Madhu Reddy  
  • Alyson K Zalta  
  • Stephen M Schueller  

  Abstract:

  Background: The increase in availability of patient data through consumer health wearable devices and mobile phone sensors provides opportunities for mental health treatment beyond traditional self-report measurements. Previous studies have suggested that wearables can be effectively used to benefit the physical health of people with mental health issues, but little research has explored the integration of wearable devices into mental health care. As such, early research is still necessary to address factors that might impact integration including patients' motivations to use wearables and their subsequent data. Objective: The aim of this study was to gain an understanding of patients’ motivations to use or not to use wearables devices during an intensive treatment program for post-traumatic stress disorder (PTSD). During this treatment, they received a complementary Fitbit. We investigated the following research questions: How did the veterans in the intensive treatment program use their Fitbit? What are contributing motivators for the use and nonuse of the Fitbit? Methods: We conducted semistructured interviews with 13 veterans who completed an intensive treatment program for PTSD. We transcribed and analyzed interviews using thematic analysis. Results: We identified three major motivations for veterans to use the Fitbit during their time in the program: increase self-awareness, support social interactions, and give back to other veterans. We also identified three major reasons certain features of the Fitbit were not used: lack of clarity around the purpose of the Fitbit, lack of meaning in the Fitbit data, and challenges in the veteran-provider relationship. Conclusions: To integrate wearable data into mental health treatment programs, it is important to understand the patient’s perspectives and motivations in using wearables. We also discuss how the military culture and PTSD may have contributed to our participants' behaviors and attitudes toward Fitbit usage. We conclude with possible approaches for integrating patient-generated data into mental health treatment settings that may address the challenges we identified.

  • JMIR Ment Health 2018;5(2):e10415

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  Innovations in Mental Health Systems

  Jun 12, 2018

  Expert Consensus Survey on Digital Health Tools for Patients With Serious Mental Illness: Optimizing for User Characteristics and User Support

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  Authors List:

  • Ainslie Hatch  
  • Julia E Hoffman  
  • Ruth Ross  
  • John P Docherty  

  Abstract:

  Background: Digital technology is increasingly being used to enhance health care in various areas of medicine. In the area of serious mental illness, it is important to understand the special characteristics of target users that may influence motivation and competence to use digital health tools, as well as the resources and training necessary for these patients to facilitate the use of this technology. Objective: The aim of this study was to conduct a quantitative expert consensus survey to identify key characteristics of target users (patients and health care professionals), barriers and facilitators for appropriate use, and resources needed to optimize the use of digital health tools in patients with serious mental illness. Methods: A panel of 40 experts in digital behavioral health who met the participation criteria completed a 19-question survey, rating predefined responses on a 9-point Likert scale. Consensus was determined using a chi-square test of score distributions across three ranges (1-3, 4-6, 7-9). Categorical ratings of first, second, or third line were designated based on the lowest category into which the CI of the mean ratings fell, with a boundary >6.5 for first line. Here, we report experts’ responses to nine questions (265 options) that focused on (1) user characteristics that would promote or hinder the use of digital health tools, (2) potential benefits or motivators and barriers or unintended consequences of digital health tool use, and (3) support and training for patients and health care professionals. Results: Among patient characteristics most likely to promote use of digital health tools, experts endorsed interest in using state-of-the-art technology, availability of necessary resources, good occupational functioning, and perception of the tool as beneficial. Certain disease-associated signs and symptoms (eg, more severe symptoms, substance abuse problems, and a chaotic living situation) were considered likely to make it difficult for patients to use digital health tools. Enthusiasm among health care professionals for digital health tools and availability of staff and equipment to support their use were identified as variables to enable health care professionals to successfully incorporate digital health tools into their practices. The experts identified a number of potential benefits of and barriers to use of digital health tools by patients and health care professionals. Experts agreed that both health care professionals and patients would need to be trained in the use of these new technologies. Conclusions: These results provide guidance to the mental health field on how to optimize the development and deployment of digital health tools for patients with serious mental illness.

  • JMIR Ment Health 2018;5(2):e46

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  Methods and New Tools in Mental...

  Jun 11, 2018

  Predicting Caller Type From a Mental Health and Well-Being Helpline: Analysis of Call Log Data

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  Authors List:

  • Alexander Grigorash  
  • Siobhan O'Neill  
  • Raymond Bond  
  • Colette Ramsey  
  • Cherie Armour  
  • Maurice D Mulvenna  

  Abstract:

  Background: This paper presents an analysis of call data records pertaining to a telephone helpline in Ireland among individuals seeking mental health and well-being support and among those who are in a suicidal crisis. Objective: The objective of our study was to examine whether rule sets generated from decision tree classification, trained using features derived from callers’ several initial calls, could be used to predict what caller type they would become. Methods: Machine learning techniques were applied to the call log data, and five distinct patterns of caller behaviors were revealed, each impacting the helpline capacity in different ways. Results: The primary findings of this study indicate that a significant model (P<.001) for predicting caller type from call log data obtained from the first 8 calls is possible. This indicates an association between callers’ behavior exhibited during initial calls and their behavior over the lifetime of using the service. Conclusions: These data-driven findings contribute to advanced workload forecasting for operational management of the telephone-based helpline and inform the literature on helpline caller behavior in general.

  • JMIR Ment Health 2018;5(2):e47

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  Depression and Mood Disorders

  May 31, 2018

  Mobile Phone Intervention to Reduce Youth Suicide in Rural Communities: Field Test

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  Authors List:

  • Anthony R Pisani  
  • Peter A Wyman  
  • Kunali Gurditta  
  • Karen Schmeelk-Cone  
  • Carolyn L Anderson  
  • Emily Judd  

  Abstract:

  Background: Suicide is a leading cause of death among 10- to 19-year-olds in the United States, with 5% to 8% attempting suicide each year. Suicide risk rises significantly during early adolescence and is higher in rural and underserved communities. School-based universal prevention programs offer a promising way of reducing suicide by providing strategies for emotion regulation and encouraging help-seeking behaviors and youth-adult connectedness. However, such programs frequently run into difficulties in trying to engage a broad range of students. Text messaging is a dominant medium of communication among youths, and studies show both efficacy and uptake in text messaging interventions aimed at adolescents. Text-based interventions may, thus, offer a means for school-based universal prevention programs to engage adolescents who would otherwise be difficult to reach. Objective: We field tested Text4Strength, an automated, interactive text messaging intervention that seeks to reach a broad range of early adolescents in rural communities. Text4Strength extends Sources of Strength, a peer-led school suicide prevention program, by encouraging emotion regulation, help-seeking behaviors, and youth-adult connectedness in adolescents. The study tested the appeal and feasibility of Text4Strength and its potential to extend universal school-based suicide prevention. Methods: We field tested Text4Strength with 42 ninth-grade students. Over 9 weeks, students received 28 interactive message sequences across 9 categories (Sources of Strength introduction, positive friend, mentors, family support, healthy activities, generosity, spirituality, medical access, and emotion regulation strategies). The message sequences included games, requests for advice, questions about students’ own experiences, and peer testimonial videos. We measured baseline mental health characteristics, frequency of replies, completion of sequences and video viewing, appeal to students, and their perception of having benefited from the program. Results: Of the 42 participating students, 38 (91%) responded to at least one sequence and 22 (52%) responded to more than a third of the sequences. The proportion of students who completed multistep sequences they had started ranged from 35% (6/17) to 100% (3/3 to 28/28), with responses dropping off when more than 4 replies were needed. With the exception of spirituality and generosity, each of the content areas generated at least a moderate number of student replies from both boys and girls. Students with higher and lower levels of risk and distress interacted with the sequences at similar rates. Contrary to expectations, few students watched videos. Students viewed the intervention as useful—even those who rarely responded to messages. More than 70% found the texts useful (3 items, n range 29-34) and 90% (36) agreed the program should be repeated. Conclusions: Text4Strength offers a potentially engaging way to extend school-based interventions that promote protective factors for suicide. Text4Strength is ready to be revised, based on findings and student feedback from this field test, and rigorously tested for efficacy.

  • JMIR Ment Health 2018;5(2):e10425

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  Diagnostic Tools in Mental Health

  May 31, 2018

  Preliminary Evaluation of a Web-Based Psychological Screening Tool in Adolescents Undergoing Minimally Invasive Pectus Surgery: Single-Center Observational...

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  Authors List:

  • Davina Wildemeersch  
  • Lisa Bernaerts  
  • Michiel D’Hondt  
  • Guy Hans  

  Abstract:

  Background: Preoperative anxiety and depression are predominant risk factors for increased postoperative pain. Thoracic wall deformities in adolescents often cause low self-esteem, which contributes to psychological concerns. Several studies have suggested a relationship between preoperative mental health support and enhanced recovery after surgery. Objective: This study investigated the validity of screening questionnaires concerning psychological trait and state characteristics via a patient-specific online platform. Methods: Patients scheduled for elective pectus surgery between June 2017 and August 2017 were invited to participate in clinical interviews and online self-report questionnaires. All patients were recruited in the Anesthesiology Department, Antwerp University Hospital, Belgium. This single-center observational cohort study was performed in accordance with the ethical standards of the International Council for Harmonisation–Good Clinical Practice guidelines and the Declaration of Helsinki after obtaining study approval by the Institutional Review Board and Ethics Committee of the Antwerp University Hospital, Belgium (study identifier: 17/08/082). An online preoperative psychological inventory was performed using the Rosenberg Self-Esteem Scale, Hospital Anxiety and Depression Scale, and State-Trait Anxiety Inventory. Postoperatively, pain intensity and interference were assessed using the Multidisciplinary Pain Inventory, Coping With Pain Questionnaire, and numeric pain rating scale assessment. Patient satisfaction of the Web-based platform was evaluated. Results: A total of 21 adolescent patients used our Web-based psychological perioperative screening platform. Patients rated the mobile phone app, usability, and accessibility of the digital platform as good or excellent in 85% (17/20), 89% (17/19), and 95% (20/21) of the cases, respectively. A total of 89% (17/19) of the patients rated the effort of generating answers to the online questionnaires as low. The results from the completed questionnaires indicated a strong negative correlation between self-esteem and the anxiety trait (R=–0.72, P<.001) and overall anxiety characteristics (R=–0.49, P=.04). There was a positive correlation between depressive and anxiety characteristics and the anxiety trait (R=0.52, P=.03 and R=0.6, P=.02, respectively) measured by the online self-report questionnaires. Moreover, preoperative anxiety was positively correlated with postoperative pain interference (R=0.58, P=.02). Finally, there was a negative correlation between self-esteem and pain interference (R=–0.62, P=.01). Conclusions: Perioperative screening of psychological symptoms and trait characteristics with specific treatment, if necessary, could further improve postoperative pain and overall health status. Research on eHealth technology, even for psychological patient care, is rapidly increasing. Trial Registration: ClinicalTrials.gov NCT03100669; https://clinicaltrials.gov/ct2/show/NCT03100669 (Archived by WebCite at http://www.webcitation.org/6zPvHDhU5)

  • JMIR Ment Health 2018;5(2):e45

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  Diagnostic Tools in Mental Health

  May 28, 2018

  A Smart Screening Device for Patients with Mental Health Problems in Primary Health Care: Development and Pilot Study

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  Authors List:

  • Jan van Bebber  
  • Rob R Meijer  
  • Johana TW Wigman  
  • Sjoerd Sytema  
  • Lex Wunderink  

  Abstract:

  Background: Adequate recognition of mental health problems is a prerequisite for successful treatment. Although most people tend to consult their general practitioner (GP) when they first experience mental health problems, GPs are not very well equipped to screen for various forms of psychopathology to help them determine clients’ need for treatment. Objective: In this paper, the development and characteristics of CATja, a computerized adaptive test battery built to facilitate triage in primary care settings, are described, and first results of its implementation are reported. Methods: CATja was developed in close collaboration with GPs and mental health assistants (MHAs). During implementation, MHAs were requested to appraise clients’ rankings (N=91) on the domains to be tested and to indicate the treatment level they deemed most appropriate for clients before test administration. We compared the agreement between domain score appraisals and domain score computed by CATja and the agreement between initial (before test administration) treatment level advice and final treatment level advice. Results: Agreements (Cohen kappas) between MHAs’ appraisals of clients’ scores and clients’ scores computed by CATja were mostly between .40 and .50 (Cohen kappas=.10-.20), and the agreement between “initial” treatment levels and the final treatment level advised was .65 (Cohen kappa=.55). Conclusions: Using CATja, caregivers can efficiently generate summaries of their clients’ mental well-being on which decisions about treatment type and care level may be based. Further validation research is needed.

  • JMIR Ment Health 2018;5(2):e41

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  Autism Spectrum Disorder (ASD)

  May 25, 2018

  Computerized Cognitive Training in Children With Autism and Intellectual Disabilities: Feasibility and Satisfaction Study

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  Authors List:

  • Songpoom Benyakorn  
  • Catrina A Calub  
  • Steven J Riley  
  • Andrea Schneider  
  • Ana-Maria Iosif  
  • Marjorie Solomon  
  • David Hessl  
  • Julie B Schweitzer  

  Abstract:

  Background: Researchers are increasingly interested in testing and developing computerized cognitive training interventions for individuals with autism spectrum disorder due to the limited accessibility of treatments for this disorder. Understanding the feasibility of testing cognitive interventions for this population is critical, especially for individuals with ASD who have low to moderate intellectual ability. Objective: The aim of the study was to evaluate the feasibility of computerized cognitive training as measured by attrition rate and a parent satisfaction survey. Methods: A total of 26 participants aged 8-17 years with an autism spectrum disorder diagnosis and significant intellectual impairment were enrolled (mean age 11.1 years). They were instructed to complete 25 sessions of Cogmed Working Memory Training in 5 to 6 weeks with coach assistance. Attrition rate and parent satisfaction surveys were measured after the completion of training. Results: Most participants (96%, 25/26) completed the training and indicated high satisfaction (>88%). However, among the participants who completed the training, 5 participants (19%) were unable to finish in 6 weeks, the recommended training period by Cogmed. Parents noted various positive (eg, voice-overs) and negative (eg, particular graphic and sounds associated with a stimulus) features of the game that they thought affected their child’s response. Conclusions: Children with autism spectrum disorder and intellectual impairments can successfully participate in computerized cognitive training interventions but may require additional weeks to complete the training beyond the time needed for children without intellectual impairments. The overall completion rate, with extended time to complete the training, was high. Developers of cognitive training programs for this population should take into account potential issues regarding the noise level of stimuli and characteristics of the visual graphics.

  • JMIR Ment Health 2018;5(2):e40

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  Transdiagnostic Mental Health...

  May 24, 2018

  A Web-Based Transdiagnostic Intervention for Affective and Mood Disorders: Randomized Controlled Trial

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  Authors List:

  • Bogdan Tudor Tulbure  
  • Andrei Rusu  
  • Florin Alin Sava  
  • Nastasia Sălăgean  
  • Todd J Farchione  

  Abstract:

  Background: Research increasingly supports a transdiagnostic conceptualization of emotional disorders (ie applying the same underlying treatment principles across mental disorders, without tailoring the protocol to specific diagnoses), and many international researchers are currently investigating this issue. Objective: The aim of this study was to evaluate the efficacy and acceptability of a Web-based transdiagnostic program using a sample of Romanian adults diagnosed with anxiety and/or depression. Methods: Volunteer participants registered for the study and completed a series of online self-report measures. Participants who fulfilled basic inclusion criteria on these measures were contacted for a telephone diagnostic interview using the Structural Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th Edition Axis I Disorders (SCID-I). Enrolled participants were randomized to either the active treatment group (N=69) or the wait-list control group (N=36) using a 2:1 ratio. The transdiagnostic treatment was based on the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP; Barlow et al, 2011) that addresses common underlying mechanisms of anxiety and depression. Participants randomized to the active treatment condition received 10 weeks of Web-based treatment based on the UP. Throughout treatment, graduate students in clinical psychology provided guidance that consisted of asynchronous written communication on a secure Web platform. After the intervention, participants in both study conditions were invited to complete a set of self-report measures and a postintervention SCID-I interview conducted by a different team of graduate students blinded to participants’ group and diagnostic status. Six months later, participants in the active treatment group were invited to complete an online follow-up assessment. Results: During the intervention, active treatment participants completed on average 19 homework assignments (SD 12.10), and we collected data from 79.0% (83/105) at postintervention and 51% (35/69) at follow-up for self-report measures. Postintervention SCID-I interviews were collected from 77.1% (81/105) participants. Relative to the wait-list control group, the transdiagnostic intervention yielded overall medium to large effect sizes for the primary outcome measures (within-group Hedges g=0.52-1.34 and between-group g=0.39-0.86), and also for anxiety sensitivity (g=0.80), symptom interference (g=0.48), and quality of life (g=0.38). Significant within-groups effects only were reported for the active treatment group on Panic Disorder Severity Scale-Self Report (PDSS-SR, g=0.58-0.65) and Yale-Brown Obsessive Compulsive Scale (Y-BOCS, g=0.52-0.58). Conclusions: Insignificant between-group differences for the Y-BOCS and PDSS-SR could be explained by the small number of participants with the associated primary diagnostic (eg, only 3 participants with obsessive compulsive disorder) by the choice of outcome measure (PDSS-SR was not rated among the evidence-based measures) and by the fact that these disorders may be more difficult to treat. However, the overall results suggest that the transdiagnostic intervention tested in this study represents an effective treatment option that may prove easier to disseminate through the use of Web-based delivery systems. Trial Registration: ClinicalTrials.gov CT02739607; https://clinicaltrials.gov/ct2/show/study/NCT02739607 (Archived by WebCite at http://www.webcitation.org/6yY1VeYIZ)

  • JMIR Ment Health 2018;5(2):e36

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  Depression and Mood Disorders

  May 23, 2018

  Diurnal Variations of Depression-Related Health Information Seeking: Case Study in Finland Using Google Trends Data

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  Authors List:

  • Jonas Christoffer Tana  
  • Jyrki Kettunen  
  • Emil Eirola  
  • Heikki Paakkonen  

  Abstract:

  Background: Some of the temporal variations and clock-like rhythms that govern several different health-related behaviors can be traced in near real-time with the help of search engine data. This is especially useful when studying phenomena where little or no traditional data exist. One specific area where traditional data are incomplete is the study of diurnal mood variations, or daily changes in individuals’ overall mood state in relation to depression-like symptoms. Objective: The objective of this exploratory study was to analyze diurnal variations for interest in depression on the Web to discover hourly patterns of depression interest and help seeking. Methods: Hourly query volume data for 6 depression-related queries in Finland were downloaded from Google Trends in March 2017. A continuous wavelet transform (CWT) was applied to the hourly data to focus on the diurnal variation. Longer term trends and noise were also eliminated from the data to extract the diurnal variation for each query term. An analysis of variance was conducted to determine the statistical differences between the distributions of each hour. Data were also trichotomized and analyzed in 3 time blocks to make comparisons between different time periods during the day. Results: Search volumes for all depression-related query terms showed a unimodal regular pattern during the 24 hours of the day. All queries feature clear peaks during the nighttime hours around 11 PM to 4 AM and troughs between 5 AM and 10 PM. In the means of the CWT-reconstructed data, the differences in nighttime and daytime interest are evident, with a difference of 37.3 percentage points (pp) for the term “Depression,” 33.5 pp for “Masennustesti,” 30.6 pp for “Masennus,” 12.8 pp for “Depression test,” 12.0 pp for “Masennus testi,” and 11.8 pp for “Masennus oireet.” The trichotomization showed peaks in the first time block (00.00 AM-7.59 AM) for all 6 terms. The search volumes then decreased significantly during the second time block (8.00 AM-3.59 PM) for the terms “Masennus oireet” (P<.001), “Masennus” (P=.001), “Depression” (P=.005), and “Depression test” (P=.004). Higher search volumes for the terms “Masennus” (P=.14), “Masennustesti” (P=.07), and “Depression test” (P=.10) were present between the second and third time blocks. Conclusions: Help seeking for depression has clear diurnal patterns, with significant rise in depression-related query volumes toward the evening and night. Thus, search engine query data support the notion of the evening-worse pattern in diurnal mood variation. Information on the timely nature of depression-related interest on an hourly level could improve the chances for early intervention, which is beneficial for positive health outcomes.

  • JMIR Ment Health 2018;5(2):e43

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  Anxiety and Stress Disorders

  May 22, 2018

  Internet Use, Depression, and Anxiety in a Healthy Adolescent Population: Prospective Cohort Study

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  Authors List:

  • Robyn Pauline Thom  
  • David S Bickham  
  • Michael Rich  

  Abstract:

  Background: Psychiatric disorders, including conduct disturbances, substance abuse, and affective disorders, emerge in approximately 20% of adolescents. In parallel with the rise in internet use, the prevalence of depression among adolescents has increased. It remains unclear whether and how internet use impacts mental health in adolescents. Objective: We assess the association between patterns of internet use and two mental health outcomes (depression and anxiety) in a healthy adolescent population. Methods: A total of 126 adolescents between the ages of 12 and 15 years were recruited. Participants reported their typical computer and internet usage patterns. At baseline and one-year follow-up, they completed the Beck Depression Index for primary care (BDI-PC) and the Beck Anxiety Inventory for Primary Care (BAI-PC). Individual linear regressions were completed to determine the association between markers of internet use at baseline and mental health outcomes at one-year follow-up. All models controlled for age, gender, and ethnicity. Results: There was an inverse correlation between minutes spent on a favorite website per visit and BAI-PC score. No association was found between internet use and BDI-PC score. Conclusions: There is no relationship between internet use patterns and depression in adolescents, whereas internet use may mitigate anxiety in adolescents with higher levels of baseline anxiety.

  • JMIR Ment Health 2018;5(2):e44

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