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BackgroundIt is difficult for families to navigate and access services for their children with autism. Barriers to service access are compounded among families from low-resourced backgrounds. ObjectiveThe purpose of our study was to explore the development of an app to facilitate access to services among families of children with autism from low-resourced backgrounds. Our specific aims were to explore feedback from an advisory board about the app and to explore feedback from navigators about the app. MethodsVia a multistage codevelopment process, we elicited feedback from 5 key parties: the research team, a community organization, the app development team, the advisory board, and family navigators. Collectively, 36 individuals provided feedback about the development of the app via individual interviews, focus groups, observations, and surveys. The key features of the app included a dashboard showing the service needs of the family and related resources, a messaging feature between the family, the navigator, and the supervisor, and a fidelity checklist and evaluation feature. ResultsThe advisory board provided feedback about the app to increase its user-friendliness, include the ability to develop an action plan, improve the identification of needed services, and add information about service providers. Navigators suggested that the app should connect navigators to one another, have a clearer purpose for the notes section, and reflect an easier log-in process. Navigators also wanted training to role-play using the app. After participating in a role play using the app, navigators reported significantly more satisfaction with the app and greater usefulness (P

Technology-enabled services (TESs) are clinical interventions that combine technological and human components to provide health services. TESs for mental health are efficacious in the treatment of anxiety and depression and are currently being offered as frontline treatments around the world. It is hoped that these interventions will be able to reach diverse populations across a range of identities and ultimately decrease disparities in mental health treatment. However, this hope is largely unrealized. TESs include both technology and human service components, and we argue that cultural responsivity must be considered in each of these components to help address existing treatment disparities. To date, there is limited guidance on how to consider cultural responsivity within these interventions, including specific targets for the development, tailoring, or design of the technologies and services within TESs. In response, we propose a framework that provides specific recommendations for targets based on existing models, both at the technological component level (informed by the Behavioral Intervention Technology Model) and the human support level (informed by the Efficiency Model of Support). We hope that integrating culturally responsive considerations into these existing models will facilitate increased attention to cultural responsivity within TESs to ensure they are ethical and responsive for everyone.

BackgroundTeletherapy apps have emerged as a promising alternative to traditional in-person therapy, especially after the COVID-19 pandemic, as they help overcome a range of geographical and emotional barriers to accessing care. However, the rapid proliferation of teletherapy apps has occurred in an environment in which development has outpaced the various regulatory and ethical considerations of this space. Thus, researchers have raised concerns about the ethical implications and potential risks of teletherapy apps given the lack of regulation and oversight. Teletherapy apps have distinct aims to more directly replicate practices of traditional care, as opposed to mental health apps, which primarily provide supplemental support, suggesting a need to examine the ethical considerations of teletherapy apps from the lens of existing ethical guidelines for providing therapy. ObjectiveIn this study, we examined user reviews of commercial teletherapy apps to understand user perceptions of whether and how ethical principles are followed and incorporated. MethodsWe identified 8 mobile apps that (1) provided teletherapy on 2 dominant mobile app stores (Google Play and Apple App Store) and (2) had received >5000 app reviews on both app stores. We wrote Python scripts (Python Software Foundation) to scrape user reviews from the 8 apps, collecting 3268 user reviews combined across 2 app stores. We used thematic analysis to qualitatively analyze user reviews, developing a codebook drawing from the ethical codes of conduct for psychologists, psychiatrists, and social workers. ResultsThe qualitative analysis of user reviews revealed the ethical concerns and opportunities of teletherapy app users. Users frequently perceived unprofessionalism in their teletherapists, mentioning that their therapists did not listen to them, were distracted during therapy sessions, and did not keep their appointments. Users also noted technical glitches and therapist unavailability on teletherapy apps that might affect their ability to provide continuity of care. Users held varied opinions on the affordability of those apps, with some perceiving them as affordable and others not. Users further brought up that the subscription model resulted in unfair pricing and expressed concerns about the lack of cost transparency. Users perceived that these apps could help promote access to care by overcoming geographical and social constraints. ConclusionsOur study suggests that users perceive commercial teletherapy apps as adhering to many ethical principles pertaining to therapy but falling short in key areas regarding professionalism, continuity of care, cost fairness, and cost transparency. Our findings suggest that, to provide high-quality care, teletherapy apps should prioritize fair compensation for therapists, develop more flexible and transparent payment models, and invest in measures to ensure app stability and therapist availability. Future work is needed to develop standards for teletherapy and improve the quality and accessibility of those services.

BackgroundDigital mental health interventions (DMHIs) can help bridge the gap between the demand for mental health care and availability of treatment resources. The affordances of DMHIs have been proposed to overcome barriers to care such as accessibility, cost, and stigma. Despite these proposals, most evaluations of the DMHI focus on clinical effectiveness, with less consideration of users’ perspectives and experiences. ObjectiveWe conducted a pilot randomized controlled trial of “Overcoming Thoughts,” a web-based platform that uses cognitive and behavioral principles to address depression and anxiety. The “Overcoming Thoughts” platform included 2 brief interventions—cognitive restructuring and behavioral experimentation. Users accessed either a version that included asynchronous interactions with other users (“crowdsourced” platform) or a completely self-guided version (control condition). We aimed to understand the users’ perspectives and experiences by conducting a subset of interviews during the follow-up period of the trial. MethodsWe used purposive sampling to select a subset of trial participants based on group assignment (treatment and control) and symptom improvement (those who improved and those who did not on primary outcomes). We conducted semistructured interviews with 23 participants during the follow-up period that addressed acceptability, usability, and impact. We conducted a thematic analysis of the interviews until saturation was reached. ResultsA total of 8 major themes were identified: possible opportunities to expand the platform; improvements in mental health because of using the platform; increased self-reflection skills; platform being more helpful for certain situations or domains; implementation of skills into users’ lives, even without direct platform use; increased coping skills because of using the platform; repetitiveness of platform exercises; and use pattern. Although no differences in themes were found among groups based on improvement status (all P values >.05, ranging from .12 to .86), there were 4 themes that differed based on conditions (P values from .01 to .046): helpfulness of self-reflection supported by an exercise summary (greater in control); aiding in slowing thoughts and feeling calmer (greater in control); overcoming patterns of avoidance (greater in control); and repetitiveness of content (greater in the intervention). ConclusionsWe identified the different benefits that users perceived from a novel DMHI and opportunities to improve the platform. Interestingly, we did not note any differences in themes between those who improved and those who did not, but we did find some differences between those who received the control and intervention versions of the platform. Future research should continue to investigate users’ experiences with DMHIs to better understand the complex dynamics of their use and outcomes.

BackgroundDigital mental health interventions (DMHIs) represent a promising solution to address the growing unmet mental health needs and increase access to care. Integrating DMHIs into clinical and community settings is challenging and complex. Frameworks that explore a wide range of factors, such as the Exploration, Preparation, Implementation, Sustainment (EPIS) framework, can be useful for examining multilevel factors related to DMHI implementation efforts. ObjectiveThis paper aimed to identify the barriers to, facilitators of, and best practice recommendations for implementing DMHIs across similar organizational settings, according to the EPIS domains of inner context, outer context, innovation factors, and bridging factors. MethodsThis study stems from a large state-funded project in which 6 county behavioral health departments in California explored the use of DMHIs as part of county mental health services. Our team conducted interviews with clinical staff, peer support specialists, county leaders, project leaders, and clinic leaders using a semistructured interview guide. The development of the semistructured interview guide was informed by expert input regarding relevant inner context, outer context, innovation factors, and bridging factors in the exploration, preparation, and implementation phases of the EPIS framework. We followed a recursive 6-step process to conduct qualitative analyses using inductive and deductive components guided by the EPIS framework. ResultsOn the basis of 69 interviews, we identified 3 main themes that aligned with the EPIS framework: readiness of individuals, readiness of innovations, and readiness of organizations and systems. Individual-level readiness referred to the extent to which clients had the necessary technological tools (eg, smartphones) and knowledge (digital literacy) to support the DMHI. Innovation-level readiness pertained to the accessibility, usefulness, safety, and fit of the DMHI. Organization- and system-level readiness concerned the extent to which providers and leadership collectively held positive views about DMHIs as well as the extent to which infrastructure (eg, staffing and payment model) was appropriate. ConclusionsThe successful implementation of DMHIs requires readiness at the individual, innovation, and organization and system levels. To improve individual-level readiness, we recommend equitable device distribution and digital literacy training. To improve innovation readiness, we recommend making DMHIs easier to use and introduce, clinically useful, and safe and adapting them to fit into the existing client needs and clinical workflow. To improve organization- and system-level readiness, we recommend supporting providers and local behavioral health departments with adequate technology and training and exploring potential system transformations (eg, integrated care model). Conceptualizing DMHIs as services allows the consideration of both the innovation characteristics of DMHIs (eg, efficacy, safety, and clinical usefulness) and the ecosystem around DMHIs, such as individual and organizational characteristics (inner context), purveyors and intermediaries (bridging factor), client characteristics (outer context), as well as the fit between the innovation and implementation settings (innovation factor).

BackgroundDespite significant research done on youth experiencing homelessness, few studies have examined movement patterns and digital habits in this population. Examining these digital behaviors may provide useful data to design new digital health intervention models for youth experiencing homelessness. Specifically, passive data collection (data collected without extra steps for a user) may provide insights into lived experience and user needs without putting an additional burden on youth experiencing homelessness to inform digital health intervention design. ObjectiveThe objective of this study was to explore patterns of mobile phone Wi-Fi usage and GPS location movement among youth experiencing homelessness. Additionally, we further examined the relationship between usage and location as correlated with depression and posttraumatic stress disorder (PTSD) symptoms. MethodsA total of 35 adolescent and young adult participants were recruited from the general community of youth experiencing homelessness for a mobile intervention study that included installing a sensor data acquisition app (Purple Robot) for up to 6 months. Of these participants, 19 had sufficient passive data to conduct analyses. At baseline, participants completed self-reported measures for depression (Patient Health Questionnaire-9 [PHQ-9]) and PTSD (PTSD Checklist for DSM-5 [PCL-5]). Behavioral features were developed and extracted from phone location and usage data. ResultsAlmost all participants (18/19, 95%) used private networks for most of their noncellular connectivity. Greater Wi-Fi usage was associated with a higher PCL-5 score (P=.006). Greater location entropy, representing the amount of variability in time spent across identified clusters, was also associated with higher severity in both PCL-5 (P=.007) and PHQ-9 (P=.045) scores. ConclusionsLocation and Wi-Fi usage both demonstrated associations with PTSD symptoms, while only location was associated with depression symptom severity. While further research needs to be conducted to establish the consistency of these findings, they suggest that the digital patterns of youth experiencing homelessness offer insights that could be used to tailor digital interventions.

BackgroundIncreasing rates of mental health diagnoses in college students signal the need for new opportunities to support the mental health of this population. With many mental health apps being efficacious, they may be a promising resource for college campuses to provide support to their students. However, it is important to understand why (or why not) students might want to use apps and their desired features. ObjectiveInformation on students’ interest in mental health apps may inform which apps are to be provided and how campuses can support their use. This study aimed to understand the interest and hesitation in app use and the relationship between mental health needs, as defined by depression, anxiety, and positive mental health, and app use. MethodsThe web-based Healthy Minds Study collected information on mental health needs, perceptions, and service use across colleges and universities. We used a sample of 989 participants who completed the survey between 2018 and 2020 and an elective module on digital mental health. We analyzed the elective module responses using a mixed methods approach, including both descriptive and inferential statistics, along with thematic coding for open text responses. ResultsThe Results from this study revealed that anxiety (b=−0.07; P

The growing number of mental health smartphone applications has led to increased interest in how these tools might support users in different models of care. However, research on the use of these interventions in real-world settings has been scarce. It is important to understand how apps are used in a deployment setting, especially among populations where such tools might add value to current models of care. The objective of this study is to explore the daily use of commercially-available mobile apps for anxiety that integrate CBT, with a focus on understanding reasons for and barriers for app use and engagement. This study recruited 17 young adults (age M = 24.17 years) while on a waiting list to receive therapy in a Student Counselling Service. Participants were asked to select up to two of a list of three selected apps (Wysa, Woebot, and Sanvello) and instructed to use the apps for two weeks. Apps were selected because they used techniques from cognitive behavioral therapy, and offer diverse functionality for anxiety management. Qualitative and quantitative data were gathered through daily questionnaires to capture participants' experiences with the mobile apps. In addition, eleven semi-structured interviews were conducted at the end of the study. We used descriptive statistics to analyze participants' interaction with different app features and used a general inductive approach to analyze the collected qualitative data. The results highlight that users form opinions about the apps during the first days of app use. A number of barriers to sustained use are identified including cost-related issues, inadequate content to support long-term use, and a lack of customization options for different app functions. The app features used differ among participants with self-monitoring and treatment elements being the most used features.

BackgroundDigital mental health interventions have the potential to increase mental health support among isolated older adults. However, the older adult population can experience several barriers to accessing and using digital health resources and may need extra support to experience its benefits. ObjectiveThis paper aimed to understand what older adults experience as an important aspect of support during engagement in a digital mental health program. The program entailed 3 months of staff support to participate in digital literacy training and engage with the digital mental health platform myStrength, which offers support for a range of mental health challenges, including depression and anxiety. MethodsA total of 30 older adults participated in surveys and interviews to assess their experience of participating in a digital mental health program provided by county mental health services. As part of the program, participants attended 4 classes of digital literacy training, had access to the digital mental health platform myStrength for 2 months with staff support (and 10 months after the program without support), and received support from program staff during the entire 3-month program. Survey data were analyzed using descriptive statistics, and interview data were analyzed using thematic analysis. ResultsA thematic analysis of the interview data revealed that participants valued ongoing support in 3 main areas: technical support to assist them in using technology, guided support to remind them to use myStrength and practice skills they had learned, and social support to enable them to connect with others through the program. Furthermore, participants reported that social connections was the most important aspect of the program and that they were mainly motivated to participate in the program because it was recommended to them by trusted others such as a community partner or because they believed it could potentially help others. ConclusionsOur findings can be used to inform the design of future digital mental health programs for older adults who may have unique support needs in terms of dedicated technical support and ongoing guided support to use technology and social support to increase social connectedness.

The current manuscript is a commentary on "Mobile phone-based interventions for mental health: A systematic meta-review of 14 meta-analyses of randomized controlled trials". Although embedded within a nuanced discussion, one of the primary conclusions readers have taken from the meta-analysis was "we failed to find convincing evidence in support of any mobile phone-based intervention on any outcome", which seems to contradict the entirety of the evidence presented when taken out of context of the methods applied. In evaluating whether the area produced "convincing evidence of efficacy," the authors used a standard that appeared destined to fail. Specifically, the authors required "no evidence of publication bias", which is a standard that would be unlikely to be found in any area of psychology or medicine. Second, the authors required low to moderate heterogeneity in effect sizes when comparing interventions with fundamentally different and entirely dissimilar target mechanisms. However absent these 2 untenable criteria, the authors actually found highly suggestive evidence of efficacy (N > 1,000, p < .000001) in (1) anxiety; (2) depression; (3) smoking cessation; (4) stress; and (5) quality of life. Perhaps the appropriate conclusions would be that existing syntheses of data testing smartphone intervention suggests that these interventions are promising, but additional work is needed to separate what types of interventions and mechanisms are more promising. Evidence syntheses will be useful as the field matures, but such syntheses should focus on smartphone treatments that are created equal (i.e., similar intent, features, goals, and linkages in a continuum of care model) or use standards for evidence that promote rigorous evaluation while allowing identification of resources that can help those in need.

BackgroundAn 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. ObjectiveThe 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. MethodsWe 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. ResultsOur 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. ConclusionsEliciting 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.

BackgroundAs 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. ObjectiveThis 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. MethodsA 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. ResultsWe 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. ConclusionsAs 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.

Digital health behavior change interventions (DHBCIs) offer users accessible support, yet their promise to improve health behaviors at scale has not been met. One reason for this unmet potential may be a failure to offer users support that is tailored to their personal characteristics and goals. We apply the concept of antifragility to propose how DHBCIs could be better designed to support diverse users’ behavior change journeys. We first define antifragility as a feature of an individual’s relationship to a particular challenge such that if one is antifragile to a challenge, one is well positioned to benefit from facing that challenge. Second, we introduce antifragile behavior change to describe behavior change processes that leverage person-specific antifragilities to maximize benefits and minimize risk in the behavior change process. While most existing behavior change models focus on improving one’s motivation and ability to face challenges, antifragile behavior change complements these models by helping to select challenges that are most likely to produce desired outcomes. Next, we propose three principles by which DHBCIs can help users to develop antifragile behavior change strategies: providing personalized guidance, embracing variance and exploration in choosing behaviors, and prioritizing user agency. Finally, we offer an example of how a DHBCI could be designed to support antifragile behavior change.

BackgroundMental 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. ObjectiveThe 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. MethodsA 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. ResultsFindings 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. ConclusionsThese findings can inform the development of digital mental health resources and outreach strategies that are appropriate for the D/HH community.

BackgroundUser experience and engagement are critical elements of mental health apps’ abilities to support users. However, work examining the relationships among user experience, engagement, and popularity has been limited. Understanding how user experience relates to engagement with and popularity of mental health apps can demonstrate the relationship between subjective and objective measures of app use. In turn, this may inform efforts to develop more effective and appealing mental health apps and ensure that they reach wide audiences. ObjectiveWe aimed to examine the relationship among subjective measures of user experience, objective measures of popularity, and engagement in mental health apps. MethodsWe conducted a preregistered secondary data analysis in a sample of 56 mental health apps. To measure user experience, we used expert ratings on the Mobile App Rating Scale (MARS) and consumer ratings from the Apple App Store and Google Play. To measure engagement, we acquired estimates of monthly active users (MAU) and user retention. To measure app popularity, we used download count, total app revenue, and MAU again. ResultsMARS total score was moderately positively correlated with app-level revenue (Kendall rank [T]=0.30, P=.002), MAU (T=0.39, P

BackgroundA range of mobile apps for anxiety have been developed in response to the high prevalence of anxiety disorders. Although the number of publicly available apps for anxiety is increasing, attrition rates among mobile apps are high. These apps must be engaging and relevant to end users to be effective; thus, engagement features and the ability to tailor delivery to the needs of individual users are key. However, our understanding of the functionality of these apps concerning engagement and tailoring features is limited. ObjectiveThe aim of this study is to review how cognitive behavioral elements are delivered by anxiety apps and their functionalities to support user engagement and tailoring based on user needs. MethodsA systematic search for anxiety apps described as being based on cognitive behavioral therapy (CBT) was conducted on Android and iPhone marketplaces. Apps were included if they mentioned the use of CBT for anxiety-related disorders. We identified 597 apps, of which 36 met the inclusion criteria and were reviewed through direct use. ResultsCognitive behavioral apps for anxiety incorporate a variety of functionalities, offer several engagement features, and integrate low-intensity CBT exercises. However, the provision of features to support engagement is highly uneven, and support is provided only for low-intensity CBT treatment. Cognitive behavioral elements combine various modalities to deliver intervention content and support the interactive delivery of these elements. Options for personalization are limited and restricted to goal selection upon beginning use or based on self-monitoring entries. Apps do not appear to provide individualized content to users based on their input. ConclusionsEngagement and tailoring features can be significantly expanded in existing apps, which make limited use of social features and clinical support and do not use sophisticated features such as personalization based on sensor data. To guide the evolution of these interventions, further research is needed to explore the effectiveness of different types of engagement features and approaches to tailoring therapeutic content.

BackgroundMental health concerns are a significant issue among community college students, who often have less access to resources than traditional university college students. Mobile apps have the potential to increase access to mental health care, but there has been little research investigating factors associated with mental health app use within the community college population. ObjectiveThis study aimed to understand facilitators of and barriers to mental health app use among community college students. MethodsA web-based survey was administered to a randomly selected sample of 500 community college students from April 16 to June 30, 2020. Structural equation modeling was used to test the relationships between the use of mental health apps, perceived stress, perceived need to seek help for mental health concerns, perceived stigma, past use of professional mental health services, privacy concerns, and social influence of other people in using mental health apps. ResultsOf the 500 participants, 106 (21.2%) reported use of mental health apps. Perceived stress, perceived need to seek help, past use of professional services, and social influence were positively associated with mental health app use. Furthermore, the effect of stress was mediated by a perceived need to seek help. Privacy concerns were negatively associated with mental health app use. Stigma, age, and gender did not have a statistically significant effect. ConclusionsThese findings can inform development of new digital interventions and appropriate outreach strategies to engage community college students in using mental health apps.

BackgroundSupporting 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. ObjectiveTo 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. MethodsWe 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. ResultsUsers 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. ConclusionsAlthough 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.

BackgroundThe development of mobile computing technology has enabled the delivery of psychological interventions while people go about their everyday lives. The original visions of the potential of these "ecological momentary interventions" were presented over a decade ago, and the widespread adoption of smartphones in the intervening years has led to a variety of research studies exploring the feasibility of these aspirations. However, there is a dearth of research describing the different dimensions, characteristics, and features of these interventions, as constructed.ObjectiveTo provide an overview of the definitions given for "ecological momentary interventions" in the treatment of common mental health disorders, and describe the set of technological and interaction possibilities which have been used in the design of these interventions.MethodsA systematic search identified relevant literature published between 2009 and 2020 in the PubMed, PsycInfo, and ACM Guide to the Computing Literature databases. Following screening, data were extracted from eligible articles using a standardized extraction worksheet. Selected articles were then thematically categorized.ResultsThe search identified 583 articles of which 64 met the inclusion criteria. The interventions target a range of mental health problems, with diverse aims, intervention designs and evaluation approaches. The studies employed a variety of features for intervention delivery, but recent research is overwhelmingly comprised of studies based on smartphone apps (30 of 42 papers that described an intervention). Twenty two studies employed sensors for the collection of data in order to provide just-in-time support or predict psychological states.ConclusionsWith the shift towards smartphone apps, the vision for EMIs has begun to be realised. Recent years have seen increased exploration of the use of sensors and machine learning, but the role of humans in the delivery of EMI is also varied. The variety of capabilities exhibited by EMIs motivates development of a more precise vocabulary for capturing both automatic and human tailoring of these interventions.