scholarly journals Popular Evidence-Based Commercial Mental Health Apps: Analysis of Engagement, Functionality, Aesthetics, and Information Quality (Preprint)

2021 ◽  
Author(s):  
Nancy Lau ◽  
Alison O'Daffer ◽  
Joyce P Yi-Frazier ◽  
Abby R Rosenberg
Keyword(s):  
Mental Health ◽  
Information Quality ◽  
Evidence Based ◽  
User Centered Design ◽  
Design Elements ◽  
Evidence Based Treatment ◽  
Health Apps ◽  
Consumer Ratings ◽  
App Design ◽  
User Ratings

BACKGROUND There is a robust market for mobile health (mHealth) apps focused on self-guided interventions to address a high prevalence of mental health disorders and behavioral health needs in the general population. Disseminating mental health interventions via mHealth technologies may help overcome barriers in access to care and has broad consumer appeal. However, development and testing of mental health apps in formal research settings are limited and far outpaced by everyday consumer use. In addition to prioritizing efficacy and effectiveness testing, researchers should examine and test app design elements that impact the user experience, increase engagement, and lead to sustained use over time. OBJECTIVE The aim of this study was to evaluate the objective and subjective quality of apps that are successful across both research and consumer sectors, and the relationships between objective app quality, subjective user ratings, and evidence-based behavior change techniques. This will help inform user-centered design considerations for mHealth researchers to maximize design elements and features associated with consumer appeal, engagement, and sustainability. METHODS We conducted a user-centered design analysis of popular consumer apps with scientific backing utilizing the well-validated Mobile Application Rating Scale (MARS). Popular consumer apps with research support were identified via a systematic search of the App Store iOS (Apple Inc) and Google Play (Google LLC) and literature review. We evaluated the quality metrics of 19 mental health apps along 4 MARS subscales, namely, Engagement, Functionality, Aesthetics, and Information Quality. MARS total and subscale scores range from 1 to 5, with higher scores representing better quality. We then extracted user ratings from app download platforms and coded apps for evidence-based treatment components. We calculated Pearson correlation coefficients to identify associations between MARS scores, App Store iOS/Google Play consumer ratings, and number of evidence-based treatment components. RESULTS The mean MARS score was 3.52 (SD 0.71), consumer rating was 4.22 (SD 0.54), and number of evidence-based treatment components was 2.32 (SD 1.42). Consumer ratings were significantly correlated with the MARS Functionality subscale (r=0.74, <i>P</i>&lt;.001), Aesthetics subscale (r=0.70, <i>P</i>&lt;.01), and total score (r=0.58, <i>P</i>=.01). Number of evidence-based intervention components was not associated with MARS scores (r=0.085, <i>P</i>=.73) or consumer ratings (r=–0.329, <i>P</i>=.16). CONCLUSIONS In our analysis of popular research-supported consumer apps, objective app quality and subjective consumer ratings were generally high. App functionality and aesthetics were highly consistent with consumer appeal, whereas evidence-based components were not. In addition to designing treatments that work, we recommend that researchers prioritize aspects of app design that impact the user experience for engagement and sustainability (eg, ease of use, navigation, visual appeal). This will help translate evidence-based interventions to the competitive consumer app market, thus bridging the gap between research development and real-world implementation.

scholarly journals Popular Evidence-Based Commercial Mental Health Apps: Analysis of Engagement, Functionality, Aesthetics, and Information Quality

10.2196/29689 ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. e29689
Author(s):  
Nancy Lau ◽  
Alison O'Daffer ◽  
Joyce P Yi-Frazier ◽  
Abby R Rosenberg
Keyword(s):  
Mental Health ◽  
Information Quality ◽  
Evidence Based ◽  
User Centered Design ◽  
Design Elements ◽  
Evidence Based Treatment ◽  
Health Apps ◽  
Consumer Ratings ◽  
App Design ◽  
User Ratings

Background There is a robust market for mobile health (mHealth) apps focused on self-guided interventions to address a high prevalence of mental health disorders and behavioral health needs in the general population. Disseminating mental health interventions via mHealth technologies may help overcome barriers in access to care and has broad consumer appeal. However, development and testing of mental health apps in formal research settings are limited and far outpaced by everyday consumer use. In addition to prioritizing efficacy and effectiveness testing, researchers should examine and test app design elements that impact the user experience, increase engagement, and lead to sustained use over time. Objective The aim of this study was to evaluate the objective and subjective quality of apps that are successful across both research and consumer sectors, and the relationships between objective app quality, subjective user ratings, and evidence-based behavior change techniques. This will help inform user-centered design considerations for mHealth researchers to maximize design elements and features associated with consumer appeal, engagement, and sustainability. Methods We conducted a user-centered design analysis of popular consumer apps with scientific backing utilizing the well-validated Mobile Application Rating Scale (MARS). Popular consumer apps with research support were identified via a systematic search of the App Store iOS (Apple Inc) and Google Play (Google LLC) and literature review. We evaluated the quality metrics of 19 mental health apps along 4 MARS subscales, namely, Engagement, Functionality, Aesthetics, and Information Quality. MARS total and subscale scores range from 1 to 5, with higher scores representing better quality. We then extracted user ratings from app download platforms and coded apps for evidence-based treatment components. We calculated Pearson correlation coefficients to identify associations between MARS scores, App Store iOS/Google Play consumer ratings, and number of evidence-based treatment components. Results The mean MARS score was 3.52 (SD 0.71), consumer rating was 4.22 (SD 0.54), and number of evidence-based treatment components was 2.32 (SD 1.42). Consumer ratings were significantly correlated with the MARS Functionality subscale (r=0.74, P<.001), Aesthetics subscale (r=0.70, P<.01), and total score (r=0.58, P=.01). Number of evidence-based intervention components was not associated with MARS scores (r=0.085, P=.73) or consumer ratings (r=–0.329, P=.16). Conclusions In our analysis of popular research-supported consumer apps, objective app quality and subjective consumer ratings were generally high. App functionality and aesthetics were highly consistent with consumer appeal, whereas evidence-based components were not. In addition to designing treatments that work, we recommend that researchers prioritize aspects of app design that impact the user experience for engagement and sustainability (eg, ease of use, navigation, visual appeal). This will help translate evidence-based interventions to the competitive consumer app market, thus bridging the gap between research development and real-world implementation.

scholarly journals Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments

2016 ◽  
Vol 3 (1) ◽  
pp. e7 ◽  
Author(s):  
David Bakker ◽  
Nikolaos Kazantzis ◽  
Debra Rickwood ◽  
Nikki Rickard
Keyword(s):  
Mental Health ◽  
Mental Health Problems ◽  
Mobile App ◽  
Evidence Based ◽  
Previous Systematic Review ◽  
Overall Design ◽  
Health Apps ◽  
Preventative Health ◽  
Mental Health Interventions ◽  
App Design

Background The number of mental health apps (MHapps) developed and now available to smartphone users has increased in recent years. MHapps and other technology-based solutions have the potential to play an important part in the future of mental health care; however, there is no single guide for the development of evidence-based MHapps. Many currently available MHapps lack features that would greatly improve their functionality, or include features that are not optimized. Furthermore, MHapp developers rarely conduct or publish trial-based experimental validation of their apps. Indeed, a previous systematic review revealed a complete lack of trial-based evidence for many of the hundreds of MHapps available. Objective To guide future MHapp development, a set of clear, practical, evidence-based recommendations is presented for MHapp developers to create better, more rigorous apps. Methods A literature review was conducted, scrutinizing research across diverse fields, including mental health interventions, preventative health, mobile health, and mobile app design. Results Sixteen recommendations were formulated. Evidence for each recommendation is discussed, and guidance on how these recommendations might be integrated into the overall design of an MHapp is offered. Each recommendation is rated on the basis of the strength of associated evidence. It is important to design an MHapp using a behavioral plan and interactive framework that encourages the user to engage with the app; thus, it may not be possible to incorporate all 16 recommendations into a single MHapp. Conclusions Randomized controlled trials are required to validate future MHapps and the principles upon which they are designed, and to further investigate the recommendations presented in this review. Effective MHapps are required to help prevent mental health problems and to ease the burden on health systems.

scholarly journals Education on depression in mental health apps: Systematic assessment of characteristics and adherence with evidence-based guidelines (Preprint)

10.2196/28942 ◽  
2021 ◽  
Author(s):  
Laura Martinengo ◽  
Anne-Claire Stona ◽  
Lorainne Tudor Car ◽  
Jimmy Lee ◽  
Konstadina Griva ◽  
...  
Keyword(s):  
Mental Health ◽  
Evidence Based ◽  
Systematic Assessment ◽  
Health Apps ◽  
Evidence Based Guidelines

scholarly journals Self-guided cognitive behavioral therapy apps: Can they help? Systematic assessment of features, functionality, and congruence with evidence (Preprint)

2021 ◽  
Author(s):  
Laura Martinengo ◽  
Anne-Claire Stona ◽  
Konstadina Griva ◽  
Paola Dazzan ◽  
Carmine Maria Pariante ◽  
...  
Keyword(s):  
Mental Health ◽  
Risk Management ◽  
Data Security ◽  
Suicide Risk ◽  
Behavioral Therapy ◽  
Cognitive Restructuring ◽  
Evidence Based ◽  
Inclusion Criteria ◽  
Systematic Assessment ◽  
Health Apps

BACKGROUND Mental health disorders affect one in ten people globally, of which around 300 million are affected by depression. At least half of affected people remain untreated. Cognitive behavioral therapy (CBT) is an effective treatment but access to specialized providers, habitually challenging, has worsened with COVID-19. Internet-based CBT (iCBT) is effective and a feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression but accessing the right app might be cumbersome given the large number and wide variety of apps offered by public app marketplaces. OBJECTIVE To systematically assess features, functionality, data security and congruence with evidence of self-guided CBT-based apps available in major app stores, suitable for users suffering from depression. METHODS A systematic assessment of self-guided CBT-based apps available in Google Play and Apple’s App Store was conducted. Apps launched or updated since August 2018 were identified through a systematic search in 42matters using CBT-related terms. Apps meeting inclusion criteria were downloaded and assessed using a Samsung Galaxy J7 Pro (Android 9) and iPhone 7 (iOS 13.3.1). Apps were appraised using a 182-question checklist developed by the research team, comprising apps’ general characteristics, CBT-related features, including six evidence-based CBT techniques as informed by a CBT manual, CBT competences framework and a literature review of iCBT clinical trial protocols (psychoeducation, behavioral activation, cognitive restructuring, problem solving, relaxation, and exposure for comorbid anxiety), and technical aspects and quality assurance. Results were reported as a narrative review, using descriptive statistics. RESULTS The initial search yielded 3006 apps, of which 98 apps met inclusion criteria and were systematically assessed. There were 20 wellbeing apps, 65 mental health apps and 13 depression apps. Twenty-eight apps offered at least four evidence-based CBT techniques, particularly depression apps. Cognitive restructuring was the most common technique, offered by 77/98 apps. Only a third of apps offered suicide- risk management resources while less than 20% of apps offered COVID-19-related information. Most apps included a privacy policy, but only a third of apps presented it before account creation. Eighty percent of privacy policies stated sharing data with third party service providers. Half of app development teams included academic institutions or healthcare providers. CONCLUSIONS Only few self-guided CBT-based apps offer comprehensive CBT programs or suicide risk management resources. Sharing of users’ data is widespread, highlighting shortcomings in the health app market governance. To fulfill their potential, self-guided CBT-based apps should follow evidence-based clinical guidelines, be patient-centered and enhance users’ data security. CLINICALTRIAL NA

scholarly journals Dialectical Behavioural Therapy Skills for Employment

2018 ◽  
pp. 734-768
Author(s):  
Janet D. Feigenbaum
Keyword(s):  
Mental Health ◽  
Personality Disorder ◽  
Social Functioning ◽  
Feasibility Studies ◽  
Behavioural Therapy ◽  
Evidence Based ◽  
Complex Relationship ◽  
Evidence Based Treatment ◽  
Direct Association ◽  
Dialectical Tension

The complex relationship between mental health and employment is transactional and unique to each individual. Thus the decision to commence (or return) to employment for this population requires an individualized formulation emphasizing the dialectical tension between the benefits of employment and stressors in the workplace. In addition, unemployment is associated with a number of social exclusion risks which may impact upon an individual’s mental health. Vocational functioning in those with personality disorder (PD) is more compromised than social functioning and does not improve in direct association with change in mental health symptoms. Obtaining and retaining employment requires the ability to manage workplace emotions, behaviour, and relationships. Dialectical behavioural therapy (DBT) is an evidence-based treatment that addresses these key areas of dysfunction—adaptations for employment include DBT-W, DBT-ACES, and DBT-SE, each with their own focus. Feasibility studies have shown these adaptations are acceptable to and may be effective for participants.

Mental health apps education on depression: Systematic assessment (Preprint)

2021 ◽  
Author(s):  
Laura Martinengo ◽  
Anne-Claire Stona ◽  
Lorainne Tudor Car ◽  
Jimmy Lee ◽  
Konstadina Griva ◽  
...  
Keyword(s):  
Mental Health ◽  
Clinical Guidelines ◽  
Help Seeking ◽  
Support Network ◽  
Evidence Based ◽  
Educational Content ◽  
Systematic Assessment ◽  
Android Apps ◽  
Symptoms Of Depression ◽  
Health Apps

BACKGROUND Suboptimal understanding of depression and mental health disorders by the general population is an important contributor to the wide treatment gap in depression. Mental health literacy encompasses knowledge and beliefs about mental disorders and supports their recognition, management, and prevention. Besides knowledge improvement, psychoeducational interventions reduce symptoms of depression, enhance help-seeking behavior, and decrease stigma. Mental health apps often offer educational content, but the trustworthiness of included information is unclear OBJECTIVE To systematically evaluate adherence to depression clinical guidelines of the information offered by mental health apps available in major commercial app stores. METHODS A systematic assessment of the educational content about depression in apps available in Google Play and Apple’s App Store was conducted in July 2020. A systematic search for apps published or updated since January 2019 was performed using 42matters. Apps meeting inclusion criteria were downloaded and assessed using an iPhone 7 (iOS 14.0.1) and a Sony XPERIA XZs (Android 8.0.0) smartphones. The 156 questions assessment checklist comprised general characteristics of apps, appraisal of educational content and its adherence to evidence-based clinical guidelines, and technical aspects and quality assurance. Results were tabulated and reported as a narrative review, using descriptive statistics. RESULTS The app search retrieved 2,218 apps of which 58 were included in the analysis (29 Android apps and 29 iOS apps). Thirty-seven apps (64%) offered educational content within a more comprehensive depression or mental health management app. Twelve apps (21%) provided non-evidence-based information. Most apps (51/58, 88%) included up to 20/38 educational topics assessed. Common educational topics were listing symptoms of depression (52/58, 90%) and available treatments (48/58, 83%), particularly psychotherapy. Depression-associated stigma was mentioned by 38% of apps, while suicide risk was mentioned by 71% of apps, generally as one item in a list of symptoms. Forty-four (76%) apps highlighted the importance of help-seeking, and 50% of apps emphasized the importance of involving the user’s support network. Thirty apps (52%) referenced their content and ten apps (17%) included advertisements. CONCLUSIONS Information in mental health and depression apps is often brief and incomplete. One in five apps provided non-evidence-based information. Given the unmet needs and stigma associated with the disease, it is imperative that apps seize the opportunity to offer quality, evidence-based education and/or point the users to relevant resources. A multi-stakeholder consensus on a more stringent development and publication process for mental health apps is imperative.

Utilization of evidence-based treatment models at community-based mental health settings for young children exposed to violence

2020 ◽  
Vol 116 ◽  
pp. 105233
Author(s):  
Tamaki H. Urban ◽  
Thuy Trang T. Nguyen ◽  
Alexandra E. Morford ◽  
Tawny Spinelli ◽  
Zoran Martinovich ◽  
...  
Keyword(s):  
Mental Health ◽  
Young Children ◽  
Evidence Based ◽  
Community Based ◽  
Evidence Based Treatment ◽  
Treatment Models ◽  
Mental Health Settings ◽  
Children Exposed To Violence

scholarly journals The Juggling Act of Supervision in Community Mental Health: Implications for Supporting Evidence-Based Treatment

2017 ◽  
Vol 44 (6) ◽  
pp. 838-852 ◽  
Author(s):  
Shannon Dorsey ◽  
Michael D. Pullmann ◽  
Suzanne E. U. Kerns ◽  
Nathaniel Jungbluth ◽  
Rosemary Meza ◽  
...  
Keyword(s):  
Mental Health ◽  
Community Mental Health ◽  
Evidence Based ◽  
Supporting Evidence ◽  
Evidence Based Treatment ◽  
Health Implications
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