Understanding Mental Health Apps for Youth: Focus Group Study With Latinx Youth.

BACKGROUND: An increasing number of mental health apps (MHapps) are being developed for youth. In addition, youth are high users of both technologies and MHapps. However, little is known about their perspectives on MHapps. MHapps might be particularly well suited to reach the youth underserved by traditional mental health resources, and incorporating their perspectives is especially critical to ensure such tools are useful to them. OBJECTIVE: The goal of this study was to develop and pilot a process for eliciting youth perspectives on MHapps in a structured and collaborative way. We also sought to generate learnings on the perspectives of Latinx youth on MHapps and their use in ways that might facilitate discovery, activation, or engagement in MHapps, especially in Latinx populations. METHODS: We created a series of focus groups consisting of 5 sessions. The groups introduced different categories of MHapps (cognitive behavioral therapy apps, mindfulness apps, and miscellaneous apps). Within each category, we selected 4 MHapps that participants chose to use for a week and provided feedback through both between-session and in-session activities. We recruited 5 youths ranging in age from 15 to 21 (mean 18, SD 2.2) years. All the participants identified as Hispanic or Latinx. After completing all 5 focus groups, the participants completed a brief questionnaire to gather their impressions of the apps they had used. RESULTS: Our focus group methodology collected detailed and diverse information about youth perspectives on MHapps. However, we did identify some aspects of our methods that were less successful at engaging the youth, such as our between-session activities. The Latinx youth in our study wanted apps that were accessible, relatable, youth centric, and simple and could be integrated with their offline lives. We also found that the mindfulness apps were viewed most favorably but that the miscellaneous and cognitive behavioral therapy apps were viewed as more impactful. CONCLUSIONS: Eliciting youth feedback on MHapps is critical if these apps are going to serve a role in supporting their mental health and well-being. We refined a process for collecting feedback from the youth and identified factors that were important to a set of Latinx youth. Future work could be broader, that is, recruit larger samples of more diverse youth, or deeper, that is, collect more information from each youth around interests, needs, barriers, or facilitators or better understand the various impacts of MHapps by using qualitative and quantitative measures. Nevertheless, this study advances the formative understanding of how the youth, particularly Latinx youth, might be viewing these tools.

Comparing Professional and Consumer Ratings of Mental Health Apps: Mixed Methods Study.

BACKGROUND: As the number of mental health apps has grown, increasing efforts have been focused on establishing quality tailored reviews. These reviews prioritize clinician and academic views rather than the views of those who use them, particularly those with lived experiences of mental health problems. Given that the COVID-19 pandemic has increased reliance on web-based and mobile mental health support, understanding the views of those with mental health conditions is of increasing importance. OBJECTIVE: This study aimed to understand the opinions of people with mental health problems on mental health apps and how they differ from established ratings by professionals. METHODS: A mixed methods study was conducted using a web-based survey administered between December 2020 and April 2021, assessing 11 mental health apps. We recruited individuals who had experienced mental health problems to download and use 3 apps for 3 days and complete a survey. The survey consisted of the One Mind PsyberGuide Consumer Review Questionnaire and 2 items from the Mobile App Rating Scale (star and recommendation ratings from 1 to 5). The consumer review questionnaire contained a series of open-ended questions, which were thematically analyzed and using a predefined protocol, converted into binary (positive or negative) ratings, and compared with app ratings by professionals and star ratings from app stores. RESULTS: We found low agreement between the participants' and professionals' ratings. More than half of the app ratings showed disagreement between participants and professionals (198/372, 53.2%). Compared with participants, professionals gave the apps higher star ratings (3.58 vs 4.56) and were more likely to recommend the apps to others (3.44 vs 4.39). Participants' star ratings were weakly positively correlated with app store ratings (r=0.32, P=.01). Thematic analysis found 11 themes, including issues of user experience, ease of use and interactivity, privacy concerns, customization, and integration with daily life. Participants particularly valued certain aspects of mental health apps, which appear to be overlooked by professional reviewers. These included functions such as the ability to track and measure mental health and providing general mental health education. The cost of apps was among the most important factors for participants. Although this is already considered by professionals, this information is not always easily accessible. CONCLUSIONS: As reviews on app stores and by professionals differ from those by people with lived experiences of mental health problems, these alone are not sufficient to provide people with mental health problems with the information they desire when choosing a mental health app. App rating measures must include the perspectives of mental health service users to ensure ratings represent their priorities. Additional work should be done to incorporate the features most important to mental health service users into mental health apps.

Understanding the Potential of Mental Health Apps to Address Mental Health Needs of the Deaf and Hard of Hearing Community: Mixed Methods Study.

BACKGROUND: Mental health concerns are a significant issue among the deaf and hard of hearing (D/HH) community, but community members can face several unique challenges to accessing appropriate resources. OBJECTIVE: The aim of this study was to investigate the mental health needs of the D/HH community and how mental health apps may be able to support these needs. METHODS: A total of 10 members of the D/HH community participated in a focus group and survey to provide their perspectives and experiences. Participants were members of the Center on Deafness Inland Empire team, which comprises people with lived experience as members of and advocates for the D/HH community. RESULTS: Findings identified a spectrum of needs for mental health apps, including offering American Sign Language and English support, increased education of mental health to reduce stigma around mental health, direct communication with a Deaf worker, and apps that are accessible to a range of community members in terms of culture, resources required, and location. CONCLUSIONS: These findings can inform the development of digital mental health resources and outreach strategies that are appropriate for the D/HH community.

A process for reviewing mental health apps: Using the One Mind PsyberGuide Credibility Rating System.

OBJECTIVE: Given the increasing number of publicly available mental health apps, we need independent advice to guide adoption. This paper discusses the challenges and opportunities of current mental health app rating systems and describes the refinement process of one prominent system, the One Mind PsyberGuide Credibility Rating Scale (PGCRS). METHODS: PGCRS Version 1 was developed in 2013 and deployed for 7 years, during which time a number of limitations were identified. Version 2 was created through multiple stages, including a review of evaluation guidelines and consumer research, input from scientific experts, testing, and evaluation of face validity. We then re-reviewed 161 mental health apps using the updated rating scale, investigated the reliability and discrepancy of initial scores, and updated ratings on the One Mind PsyberGuide public app guide. RESULTS: Reliabilities across the scale's 9 items ranged from -0.10 to 1.00, demonstrating that some characteristics of apps are more difficult to rate consistently. The average overall score of the 161 reviewed mental health apps was 2.51/5.00 (range 0.33-5.00). Ratings were not strongly correlated with app store star ratings, suggesting that credibility scores provide different information to what is contained in star ratings. CONCLUSION: PGCRS summarizes and weights available information in 4 domains: intervention specificity, consumer ratings, research, and development. Final scores are created through an iterative process of initial rating and consensus review. The process of updating this rating scale and integrating it into a procedure for evaluating apps demonstrates one method for determining app quality.

Understanding People's Use of and Perspectives on Mood-Tracking Apps: Interview Study.

BACKGROUND: Supporting mental health and wellness is of increasing interest due to a growing recognition of the prevalence and burden of mental health issues. Mood is a central aspect of mental health, and several technologies, especially mobile apps, have helped people track and understand it. However, despite formative work on and dissemination of mood-tracking apps, it is not well understood how mood-tracking apps used in real-world contexts might benefit people and what people hope to gain from them. OBJECTIVE: To address this gap, the purpose of this study was to understand motivations for and experiences in using mood-tracking apps from people who used them in real-world contexts. METHODS: We interviewed 22 participants who had used mood-tracking apps using a semistructured interview and card sorting task. The interview focused on their experiences using a mood-tracking app. We then conducted a card sorting task using screenshots of various data entry and data review features from mood-tracking apps. We used thematic analysis to identify themes around why people use mood-tracking apps, what they found useful about them, and where people felt these apps fell short. RESULTS: Users of mood-tracking apps were primarily motivated by negative life events or shifts in their own mental health that prompted them to engage in tracking and improve their situation. In general, participants felt that using a mood-tracking app facilitated self-awareness and helped them to look back on a previous emotion or mood experience to understand what was happening. Interestingly, some users reported less inclination to document their negative mood states and preferred to document their positive moods. There was a range of preferences for personalization and simplicity of tracking. Overall, users also liked features in which their previous tracked emotions and moods were visualized in figures or calendar form to understand trends. One gap in available mood-tracking apps was the lack of app-facilitated recommendations or suggestions for how to interpret their own data or improve their mood. CONCLUSIONS: Although people find various features of mood-tracking apps helpful, the way people use mood-tracking apps, such as avoiding entering negative moods, tracking infrequently, or wanting support to understand or change their moods, demonstrate opportunities for improvement. Understanding why and how people are using current technologies can provide insights to guide future designs and implementations.

Curating the Digital Mental Health Landscape With a Guide to Behavioral Health Apps: A County-Driven Resource.

With more than 10,000 mental health apps available, consumers and clinicians who want to adopt such tools can be overwhelmed by the multitude of options and lack of clear evaluative standards. Despite the increasing prevalence of curated lists, or app guides, challenges remain. Organizations providing mental health services to consumers have an opportunity to address these challenges by producing guides that meet relevant standards of quality and are tailored to local needs. This column summarizes an example of the collaborative process of app guide development in a publicly funded mental health service context and highlights opportunities and barriers identified through the process.

Rise in Use of Digital Mental Health Tools and Technologies in the United States During the COVID-19 Pandemic: Survey Study.

BACKGROUND: Accompanying the rising rates of reported mental distress during the COVID-19 pandemic has been a reported increase in the use of digital technologies to manage health generally, and mental health more specifically. OBJECTIVE: The objective of this study was to systematically examine whether there was a COVID-19 pandemic-related increase in the self-reported use of digital mental health tools and other technologies to manage mental health. METHODS: We analyzed results from a survey of 5907 individuals in the United States using Amazon Mechanical Turk (MTurk); the survey was administered during 4 week-long periods in 2020 and survey respondents were from all 50 states and Washington DC. The first set of analyses employed two different logistic regression models to estimate the likelihood of having symptoms indicative of clinical depression and anxiety, respectively, as a function of the rate of COVID-19 cases per 10 people and survey time point. The second set employed seven different logistic regression models to estimate the likelihood of using seven different types of digital mental health tools and other technologies to manage one's mental health, as a function of symptoms indicative of clinical depression and anxiety, rate of COVID-19 cases per 10 people, and survey time point. These models also examined potential interactions between symptoms of clinical depression and anxiety, respectively, and rate of COVID-19 cases. All models controlled for respondent sociodemographic characteristics and state fixed effects. RESULTS: Higher COVID-19 case rates were associated with a significantly greater likelihood of reporting symptoms of depression (odds ratio [OR] 2.06, 95% CI 1.27-3.35), but not anxiety (OR 1.21, 95% CI 0.77-1.88). Survey time point, a proxy for time, was associated with a greater likelihood of reporting clinically meaningful symptoms of depression and anxiety (OR 1.19, 95% CI 1.12-1.27 and OR 1.12, 95% CI 1.05-1.19, respectively). Reported symptoms of depression and anxiety were associated with a greater likelihood of using each type of technology. Higher COVID-19 case rates were associated with a significantly greater likelihood of using mental health forums, websites, or apps (OR 2.70, 95% CI 1.49-4.88), and other health forums, websites, or apps (OR 2.60, 95% CI 1.55-4.34). Time was associated with increased odds of reported use of mental health forums, websites, or apps (OR 1.20, 95% CI 1.11-1.30), phone-based or text-based crisis lines (OR 1.20, 95% CI 1.10-1.31), and online, computer, or console gaming/video gaming (OR 1.12, 95% CI 1.05-1.19). Interactions between COVID-19 case rate and mental health symptoms were not significantly associated with any of the technology types. CONCLUSIONS: Findings suggested increased use of digital mental health tools and other technologies over time during the early stages of the COVID-19 pandemic. As such, additional effort is urgently needed to consider the quality of these products, either by ensuring users have access to evidence-based and evidence-informed technologies and/or by providing them with the skills to make informed decisions around their potential efficacy.

The Needle in the Haystack: Identifying Credible Mobile Health Apps for Pediatric Populations during a Pandemic and beyond.

BACKGROUND: The COVID-19 pandemic has ignited wider clinical adoption of digital health tools, including mobile health apps (mHealth apps), to address mental and behavioral health concerns at a distance. While mHealth apps offer many compelling benefits, identifying effective apps in the crowded and largely unregulated marketplace is laborious. Consumer demand and industry productivity are increasing, although research is slower, making it challenging for providers to determine the most credible and safe apps for patients in need. OBJECTIVES/METHODS: This commentary offers a practical, empirically guided framework and associated resources for selecting appropriate mHealth apps for pediatric populations during the pandemic and beyond. RESULTS: In the first stage, Narrow the target problem, end user, and contender apps. Beginning the search with continuously updated websites that contain expert app ratings can help expedite this process (e.g., Psyberguide). Second, Explore each contender app's: (a) scientific and theoretical support (e.g., are app components consistent with health behavior change theories?), (b) privacy policies, and (c) user experience (e.g., through crowdsourcing feedback about app usability and appeal via social media). Third, use clinical expertise and stakeholder feedback to Contextualize whether the selected app is a good fit for a particular patient and/or caregiver (e.g., by considering age, race/ethnicity, ability, gender, sexual orientation, technology access), including conducting a brief self-pilot of the app. CONCLUSION: Youth are increasingly turning to technology for support, especially during the pandemic, and pediatric psychologists must be primed to recommend the most credible tools. We offer additional recommendations for rapidly disseminating evidence-based apps to the public.

Piloting a surveillance system for HIV drug resistance in the European Union.

BackgroundA steady increase in HIV drug resistance (HIVDR) has been demonstrated globally in individuals initiating first-line antiretroviral therapy (ART). To support effective use of ART and prevent spread of HIVDR, monitoring is essential.AimWe piloted a surveillance system for transmitted HIVDR to assess the feasibility of implementation at the European level.MethodAll 31 countries in the European Union and European Economic Area were invited to retrospectively submit data on individuals newly diagnosed with HIV in 2015 who were tested for antiviral susceptibility before ART, either as case-based or as aggregate data. We used the Stanford HIV database algorithm to translate genetic sequences into levels of drug resistance.ResultsNine countries participated, with six reporting case-based data on 1,680 individuals and four reporting aggregated data on 1,402 cases. Sequence data were available for 1,417 cases: 14.5% of individuals (n = 244) showed resistance to at least one antiretroviral drug. In case-based surveillance, the highest levels of transmitted HIVDR were observed for non-nucleoside reverse-transcriptase inhibitors (NNRTIs) with resistance detected in 8.6% (n = 145), followed by resistance to nucleoside reverse-transcriptase inhibitors (NRTI) (5.1%; n = 85) and protease inhibitors (2.0%; n = 34).ConclusionWe conclude that standard reporting of HIVDR data was feasible in the participating countries. Legal barriers for data sharing, consensus on definitions and standardisation of interpretation algorithms should be clarified in the process of enhancing European-wide HIV surveillance with drug resistance information.

Reviewing the data security and privacy policies of mobile apps for depression.

BACKGROUND: Mobile apps have become popular resources for mental health support. Availability of information about developers' data security procedures for health apps, specifically those targeting mental health, has not been thoroughly investigated. If people are to use and trust these tools for their mental health, it is crucial we evaluate the transparency and quality around the data practices of these apps. The present study reviewed data security and privacy policies of mobile apps for depression. METHODS: We reviewed mobile apps retrieved from iTunes and Google Play stores in October 2017, using the term "depression", and evaluated the transparency of data handling procedures of those apps. RESULTS: We identified 116 eligible mobile phone apps. Of those, 4% (5/116) received a transparency score of acceptable, 28% (32/116) questionable, and 68% (79/116) unacceptable. Only a minority of the apps (49%) had a privacy policy. The availability of policies differed significantly by platform, with apps from iTunes more likely to have a policy than from the Google Play store. Mobile apps collecting identifiable information were significantly more likely to have a privacy policy (79%) compared to those collecting only non-identifiable information (34%). CONCLUSION: The majority of apps reviewed were not sufficiently transparent with information regarding data security. Apps have great potential to scale mental health resources, providing resources to people unable or reluctant to access traditional face-to-face care, or as an adjunct to treatment. However, if they are to be a reasonable resource, they must be safe, secure, and responsible.

Discovery of and Interest in Health Apps Among Those With Mental Health Needs: Survey and Focus Group Study.

BACKGROUND: A large number of health apps are available directly to consumers through app marketplaces. Little information is known, however, about how consumers search for these apps and which factors influence their uptake, adoption, and long-term use. OBJECTIVE: The aim of this study was to understand what people look for when they search for health apps and the aspects and features of those apps that consumers find appealing. METHODS: Participants were recruited from Northwestern University's Center for Behavioral Intervention Technologies' research registry of individuals with mental health needs. Most participants (n=811) completed a survey asking about their use and interest in health and mental health apps. Local participants were also invited to participate in focus groups. A total of 7 focus groups were conducted with 30 participants that collected more detailed information about their use and interest in health and mental health apps. RESULTS: Survey participants commonly found health apps through social media (45.1%, 366/811), personal searches (42.7%, 346/811), or word of mouth (36.9%, 299/811), as opposed to professional sources such as medical providers (24.6%, 200/811). From the focus groups, common themes related to uptake and use of health apps included the importance of personal use before adoption, specific features that users found desirable, and trusted sources either developing or promoting the apps. CONCLUSIONS: As the number of mental health and health apps continue to increase, it is imperative to better understand the factors that impact people's adoption and use of such technologies. Our findings indicated that a number of factors-ease of use, aesthetics, and individual experience-drove adoption and use and highlighted areas of focus for app developers and disseminators.

State of the Field of Mental Health Apps.

Mental health apps offer unique opportunities for self-management of mental health and well-being in mobile, cost-effective ways. There is an abundance of apps available to consumers, but selecting a useful one presents a challenge. Most available apps are not supported by empirical evidence and thus consumers have access to a range of unreviewed apps, the benefits of which are not known or supported. While user ratings exist, and are likely to be considered by consumers when selecting an app, they do not actually yield information on app suitability. A possible alternative way for consumers to choose an app would be to use an app review platform. A number of attempts have been made to construct such a platform, and this paper introduces PsyberGuide, which offers a step towards providing objective and actionable information for publicly available mental health apps.

The association between paternal and adolescent depressive symptoms: evidence from two population-based cohorts.

BACKGROUND: Incidence of depression increases markedly around age 13 years, and nearly three-quarters of adults report that their mental health problems started in adolescence. Although maternal depression is a risk factor for adolescent depression, evidence about the association between paternal and adolescent depression is inconclusive, and many studies have methodological limitations. We aimed to assess the association between paternal and adolescent depressive symptoms in two large population-based cohort studies. METHODS: We used data for two-parent families from two representative prospective cohorts in Ireland (Growing up in Ireland [GUI]) and the UK (Millennium Cohort Study [MCS]). Parental depressive symptoms were measured with the Centre for Epidemiological Studies Depression Scale in the GUI cohort when children were 9 years old, and the Kessler six-item psychological distress scale in the MCS cohort when children were 7 years old. Adolescent depressive symptoms were measured with the Short Mood and Feelings Questionnaire (SMFQ) at age 13 years in the GUI cohort and age 14 years in the MCS cohort. We analysed data using linear regression models, before and after adjustment for confounders, in both multiply imputed and complete case samples. FINDINGS: There were 6070 families in GUI and 7768 in MCS. After all adjustments, a 1 SD (three-point) increase in paternal depressive symptoms was associated with an increase of 0·24 SMFQ points (95% CI 0·03-0·45; p=0·023) in the GUI cohort and 0·18 SMFQ points (0·01-0·36; p=0·041) in the MCS cohort. This association was independent of, and not different in magnitude to, the association between maternal and adolescent depressive symptoms (Wald test p=0·435 in the GUI cohort and 0·470 in the MCS cohort). INTERPRETATION: Our results show an association between depressive symptoms in fathers and depressive symptoms in their adolescent offspring. These findings support the involvement of fathers as well as mothers in early interventions to reduce the prevalence of adolescent depression, and highlight the importance of treating depression in both parents. FUNDING: Department of Children and Youth Affairs and Economic and Social Research Council.