Self-tracking for Mental Wellness: Understanding Expert Perspectives and Student Experiences

Mental Health Self-Tracking Preferences of Young Adults With Depression and Anxiety Not Engaged in Treatment: Qualitative Analysis

BACKGROUND

Despite the high prevalence of anxiety and depression among young adults, many do not seek formal treatment. Some may turn to digital mental health tools for support instead, including to self-track moods, behaviors, and other variables related to mental health. Researchers have sought to understand processes and motivations involved in self-tracking, but few have considered the specific needs and preferences of young adults who are not engaged in treatment and who seek to use self-tracking to support mental health.

OBJECTIVE

This study seeks to assess the types of experiences young adults not engaged in treatment have had with digital self-tracking for mood and other mental health data and to assess how young adults not seeking treatment want to engage in self-tracking to support their mental health.

METHODS

We conducted 2 online asynchronous discussion groups with 50 young adults aged 18 years to 25 years who were not engaged in treatment. Participants were recruited after indicating moderate to severe symptoms of depression or anxiety on screening surveys hosted on the website of Mental Health America. Participants who enrolled in the study responded anonymously to discussion prompts on a message board, as well as to each other's responses, and 3 coders performed a thematic analysis of their responses.

RESULTS

Participants had mixed experiences with self-tracking in the past, including disliking when tracking highlighted unwanted behaviors and discontinuing tracking for a variety of reasons. They had more positive past experiences tracking behaviors and tasks they wanted to increase, using open-ended journaling, and with gamified elements to increase motivation. Participants highlighted several design considerations they wanted self-tracking tools to address, including building self-understanding; organization, reminders, and structure; and simplifying the self-tracking experience. Participants wanted self-tracking to help them identify their feelings and how their feelings related to other variables like sleep, exercise, and events in their lives. Participants also highlighted self-tracking as useful for motivating and supporting basic activities and tasks of daily living during periods of feeling overwhelmed or low mood and providing a sense of accomplishment and stability. Although self-tracking can be burdensome, participants were interested and provided suggestions for simplifying the process.

CONCLUSIONS

These young adults not engaged in treatment reported interest in using self-tracking to build self-understanding as a goal in and of itself or as a first step in contemplating and preparing for behavior change or treatment-seeking. Alexithymia, amotivation, and feeling overwhelmed may serve both as barriers to self-tracking and opportunities for self-tracking to help.

The Perceived Utility of Smartphone and Wearable Sensor Data in Digital Self-tracking Technologies for Mental Health

Mental health symptoms are commonly discovered in primary care. Yet, these settings are not set up to provide psychological treatment. Digital interventions can play a crucial role in stepped care management of patients' symptoms where patients are offered a low intensity intervention, and treatment evolves to incorporate providers if needed. Though digital interventions often use smartphone and wearable sensor data, little is known about patients' desires to use these data to manage mental health symptoms. In 10 interviews with patients with symptoms of depression and anxiety, we explored their: symptom self-management, current and desired use of sensor data, and comfort sharing such data with providers. Findings support the use digital interventions to manage mental health, yet they also highlight a misalignment in patient needs and current efforts to use sensors. We outline considerations for future research, including extending design thinking to wraparound services that may be necessary to truly reduce healthcare burden.

Developing a Mobile App for Young Adults with Nonsuicidal Self-Injury: A Prototype Feedback Study

Nonsuicidal self-injury (NSSI) affects approximately 13% of young adults. Though evidence-based treatments for NSSI exist, most young adults do not receive treatment. Digital interventions can provide access to evidence-based treatments for NSSI at scale. Further, preliminary research suggests the acceptability, feasibility, and potential efficacy of digital interventions for NSSI. To date, however, there are few publicly available digital interventions developed specifically for young adults who engage in NSSI. The aim of this study was to solicit young adults' impressions of early app prototypes to identify ways of improving interactive features and content needs. Building on a prior interview study which explored young adults' self-management of NSSI and their use of technology in self-management, this study involved three waves of iterative app prototype feedback sessions with 10 young adults with past month NSSI. In general, participants responded favorably and provided feedback to augment the app to better meet their needs, including adding new features and functionality as well as increasing opportunities for personalization. We discuss two key design challenges related to the roles of tracking and temporality in digital interventions for NSSI, and then frame design considerations related to these challenges within the lived informatics model.

"I Wanted to See How Bad it Was": Online Self-screening as a Critical Transition Point Among Young Adults with Common Mental Health Conditions

Young adults have high rates of mental health conditions, yet they are the age group least likely to seek traditional treatment. They do, however, seek information about their mental health online, including by filling out online mental health screeners. To better understand online self-screening, and its role in help-seeking, we conducted focus groups with 50 young adults who voluntarily completed a mental health screener hosted on an advocacy website. We explored (1) catalysts for taking the screener, (2) anticipated outcomes, (3) reactions to the results, and (4) desired next steps. For many participants, the screener results validated their lived experiences of symptoms, but they were nevertheless unsure how to use the information to improve their mental health moving forward. Our findings suggest that online screeners can serve as a transition point in young people's mental health journeys. We discuss design implications for online screeners, post-screener feedback, and digital interventions broadly.

Barriers to and Facilitators of Using a One Button Tracker and Web-Based Data Analytics Tool for Personal Science: Exploratory Study

Background

Individuals’ self-tracking of subjectively experienced phenomena related to health can be challenging, as current options for instrumentation often involve too much effort in the moment or rely on retrospective self-reporting, which is likely to impair accuracy and compliance.

Objective

This study aims to assess the usability and perceived usefulness of low-effort, in-the-moment self-tracking using simple instrumentation and to establish the amount of support needed when using this approach.

Methods

In this exploratory study, the One Button Tracker—a press-button device that records time stamps and durations of button presses—was used for self-tracking. A total of 13 employees of an academic medical center chose a personal research question and used the One Button Tracker to actively track specific subjectively experienced phenomena for 2 to 4 weeks. To assess usability and usefulness, we combined qualitative data from semistructured interviews with quantitative results from the System Usability Scale.

Results

In total, 29 barriers and 15 facilitators for using the One Button Tracker were found. Ease of use was the most frequently mentioned facilitator. The One Button Tracker’s usability received a median System Usability Scale score of 75.0 (IQR 42.50), which is considered as good usability. Participants experienced effects such as an increased awareness of the tracked phenomenon, a confirmation of personal knowledge, a gain of insight, and behavior change. Support and guidance during all stages of the self-tracking process were judged as valuable.

Conclusions

The low-effort, in-the-moment self-tracking of subjectively experienced phenomena has been shown to support personal knowledge gain and health behavior change for people with an interest in health promotion. After addressing barriers and formally validating the collected data, self-tracking devices may well be helpful for additional user types or health questions.

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

Understanding what we know so far about young people's engagement with wellbeing apps. A scoping review and narrative synthesis

Background

Increased levels of wellbeing contribute to people being more productive, resilient, physically healthy and showing lower levels of mental illness. Using mobile apps to increase wellbeing in young people is becoming the method of choice. This study sought to critically appraise the current evidence base with regards to young people's (16–24 years of age) engagement with wellbeing apps.

Methods

A systematic review of the literature and narrative synthesis was conducted to investigate users’ characteristics and other potential engagement elements. A total of 11,245 titles, 160 abstracts and 68 full-text articles published between 2002 and 2021 were screened, of which 22 studies were included.

Results

Main themes/findings indicated that a user's engagement with wellbeing apps was dependant on the presence of strong identity elements, including motivation, mood and values; design elements such as meaningful rewards, short duration of studies and seamless automatic delivery with low contact with researchers; and being innovative and contextualised. The majority of the studies did not report outcomes by social determinants such as ethnicity, education and others.

Conclusion

This research reflects on the need to consider participants’ individuality when designing app mediated wellbeing interventions.

Durrant A, Lloyd K. Understanding the attitudes and experiences of people living with potentially stigmatised long-term health conditions with respect to collecting and sharing health and lifestyle data

Background

The emerging landscape of patient-generated data (PGData) provides an opportunity to collect large quantities of information that can be used to develop our understanding of different health conditions and potentially improve the quality of life for those living with long-term health condition (LTHCs). If the potential benefits of PGData are to be realised, we need a better understanding of the psychological barriers and facilitators to the collection and beneficial sharing of health and lifestyle data. Due to the understudied role that stigma plays in sharing PGData, we explore the attitudes and experiences of those living with potentially stigmatised LTHCs with respect to collecting and sharing health and lifestyle data.

Methods

This study used semi-structured interviews and a card sorting task to explore the attitudes and experiences of people living with potentially stigmatised LTHCs. Fourteen adult participants who reported having a range of conditions were recruited in England. Template analysis was used to analyse interview transcripts and descriptive statistics were used for the card sorting task.

Results

The findings present four overarching themes: Preferences for collecting health and lifestyle data, Importance of anonymity, Expected use of data, and Sources of emotional support. Participants illustrated a general willingness to share health and lifestyle data; however, there were some notable differences in sharing experiences, varying both by information type and recipient group. Overall, participants did not identify health-related stigma as a barrier to collecting or sharing their personal health and lifestyle data.

Conclusions

We outline a number of preferences that participants feel would encourage them to collect and share data more readily, which may be considered when developing data sharing tools for the future.

Investigating the needs and concerns of older adults with multimorbidity and their healthcare professionals for conceivable digital psychotherapeutic interventions

Multimorbidity, defined as the concurrent experience of more than one chronic health condition in an individual, affects ∼65% of people over 65 and 85% of those over 85 years old with 30% of those also experiencing mental health concerns. This can lead to reduced quality of life and functioning as well as poorer outcomes in terms of condition management, adherence to treatment, and ultimately disease prognosis and progression. Digital health interventions offer a viable means of condition self-management, as well as psychological support, particularly for those who may have difficulty accessing in-person services. To best meet the needs of older adults with multimorbidity, deeper insights are needed into their specific concerns and issues around condition management, particularly with regard to distress in relation to managing one's condition. The present study aimed to explore this using one-to-one qualitative interviews and focus groups with people with chronic health conditions and healthcare professionals. Participants were 11 older adults with multimorbidity (4 males; mean age: M = 72.7 years) and 14 healthcare professionals including five clinical nurse specialists, four pharmacists, two general practitioners, one occupational therapist, one speech and language therapist and one dietician. Thematic analysis was used to identify key themes, which included: patient feelings of anxiety or worry leading to an unwillingness to access essential information; the various mental health challenges faced by those with multimorbidity; the importance of personal values in providing motivation; and the importance of social support. Findings are discussed in relation to the potential development of transdiagnostically applicable digital interventions for the management of distress in those with multimorbidity.

Understanding the Barriers and Facilitators to Sharing Patient-Generated Health Data Using Digital Technology for People Living With Long-Term Health Conditions: A Narrative Review

Using digital technology to share patient-generated health data has the potential to improve the self-management of multiple long-term health conditions. Sharing these data can allow patients to receive additional support from healthcare professionals and peer communities, as well as enhance their understanding of their own health. A deeper understanding of the concerns raised by those living with long-term health conditions when considering whether to share health data via digital technology may help to facilitate effective data sharing practices in the future. The aim of this review is to identify whether trust, identity, privacy and security concerns present barriers to the successful sharing of patient-generated data using digital technology by those living with long-term health conditions. We also address the impact of stigma on concerns surrounding sharing health data with others. Searches of CINAHL, PsychInfo and Web of Knowledge were conducted in December 2019 and again in October 2020 producing 2,581 results. An iterative review process resulted in a final dataset of 23 peer-reviewed articles. A thorough analysis of the selected articles found that issues surrounding trust, identity, privacy and security clearly present barriers to the sharing of patient-generated data across multiple sharing contexts. The presence of enacted stigma also acts as a barrier to sharing across multiple settings. We found that the majority of literature focuses on clinical settings with relatively little attention being given to sharing with third parties. Finally, we suggest the need for more solution-based research to overcome the discussed barriers to sharing.

How Self-tracking and the Quantified Self Promote Health and Well-being: Systematic Review

BACKGROUND

Self-tracking technologies are widely used in people's daily lives and health care. Academic research on self-tracking and the quantified self has also accumulated rapidly in recent years. Surprisingly, there is a paucity of research that reviews, classifies, and synthesizes the state of the art with respect to self-tracking and the quantified self.

OBJECTIVE

Our objective was to identify the state of the art of self-tracking and the quantified self in terms of health and well-being.

METHODS

We have undertaken a systematic literature review on self-tracking and the quantified self in promoting health and well-being. After a rigorous literature search, followed by inclusions, exclusions, and the application of article quality assessment protocols, 67 empirical studies qualified for the review.

RESULTS

Our results demonstrate that prior research has focused on 3 stakeholders with respect to self-tracking and the quantified self, namely end users, patients and people with illnesses, and health care professionals and caregivers. We used these stakeholder groups to cluster the research themes of the reviewed studies. We identified 11 research themes. There are 6 themes under the end-user cluster: user motivation and goal setting, usage and effects of self-tracking, continuance intention and long-term usage, management of personal data, rejection and discontinuance, and user characteristics. The patient and people with illnesses cluster contains three themes: usage experience of patients and people with illnesses, management of patient-generated data, and advantages and disadvantages in the clinical context. The health care professional and caregiver cluster contains two themes: collaboration among patients, health care professionals, and caregivers, and changes in the roles of patients and professionals. Moreover, we classified the future research suggestions given in the literature into 5 directions in terms of research designs and research topics. Finally, based on our reflections on the observations from the review, we suggest four future research directions: (1) users' cognitions and emotions related to processing and interpreting the information produced by tracking devices and apps; (2) the dark side of self-tracking (eg, its adverse psychosocial consequences); (3) self-tracking as a societal phenomenon; and (4) systemic impacts of self-tracking on health care and the actors involved.

CONCLUSIONS

This systematic literature review contributes to research and practice by assisting future research activities and providing practitioners with a concise overview of the state of the art of self-tracking and the quantified self.

Understanding Mental Health App Use Among Community College Students: Web-Based Survey Study

Background

Mental 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.

Objective

This study aimed to understand facilitators of and barriers to mental health app use among community college students.

Methods

A 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.

Results

Of 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.

Conclusions

These findings can inform development of new digital interventions and appropriate outreach strategies to engage community college students in using mental health apps.

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.

A scoping review of qualitative research in JAMIA: past contributions and opportunities for future work

OBJECTIVE

Qualitative methods are particularly well-suited to studying the complexities and contingencies that emerge in the development, preparation, and implementation of technological interventions in real-world clinical practice, and much remains to be done to use these methods to their full advantage. We aimed to analyze how qualitative methods have been used in health informatics research, focusing on objectives, populations studied, data collection, analysis methods, and fields of analytical origin.

METHODS

We conducted a scoping review of original, qualitative empirical research in JAMIA from its inception in 1994 to 2019. We queried PubMed to identify relevant articles, ultimately including and extracting data from 158 articles.

RESULTS

The proportion of qualitative studies increased over time, constituting 4.2% of articles published in JAMIA overall. Studies overwhelmingly used interviews, observations, grounded theory, and thematic analysis. These articles used qualitative methods to analyze health informatics systems before, after, and separate from deployment. Providers have typically been the main focus of studies, but there has been an upward trend of articles focusing on healthcare consumers.

DISCUSSION

While there has been a rich tradition of qualitative inquiry in JAMIA, its scope has been limited when compared with the range of qualitative methods used in other technology-oriented fields, such as human-computer interaction, computer-supported cooperative work, and science and technology studies.

CONCLUSION

We recommend increased public funding for and adoption of a broader variety of qualitative methods by scholars, practitioners, and policy makers and an expansion of the variety of participants studied. This should lead to systems that are more responsive to practical needs, improving usability, safety, and outcomes.

Perceptions of Mobile Health Apps and Features to Support Psychosocial Well-being Among Frontline Health Care Workers Involved in the COVID-19 Pandemic Response: Qualitative Study

BACKGROUND

Frontline health care workers are experiencing a myriad of physical and psychosocial challenges amid the COVID-19 pandemic. There is growing recognition that digital technologies have the potential to improve the well-being of frontline workers. However, there has been limited development of wellness interventions using mobile health (mHealth) technology. More importantly, little research has been conducted on how frontline workers perceive mHealth-based support to promote their well-being.

OBJECTIVE

This study aimed to explore frontline workers' experience of conventional psychological wellness programs and their perceptions of the usefulness of mHealth apps and features for promoting well-being. It also sought to identify factors that could potentially influence uptake and retention of an mHealth-based wellness program.

METHODS

We conducted semistructured interviews using purposive sampling with frontline workers involved in the COVID-19 response. Various visual materials, collated from existing mHealth app features, were presented to facilitate discussion. Interviews were audio-recorded and transcribed verbatim. Thematic analysis based on grounded theory was undertaken. Themes were subsequently mapped to key nudge strategies-those commonly used for mHealth development-to assess participants' preferences for particular features and their reasoning.

RESULTS

A total of 42 frontline workers participated in 12 one-on-one interviews or focus group discussions. Frontline workers generally had a limited ability to identify their own psychological problems and liked the reminders functionality of the app to track their mood over time. A personalized goal-setting feature (ie, tailoring) and in-app resources were generally valued, while frequent coaching and messages (ie, framing) were seen as a distraction. The majority of participants desired a built-in chat function with a counselor (ie, guidance) for reasons of accessibility and protection of privacy. Very few participants appreciated a gamification function. Frontline workers commonly reported the need for ongoing social support and desired access to an in-app peer support community (ie, social influence). There were, however, concerns regarding potential risks from virtual peer interactions. Intrinsic motivational factors, mHealth app technicality, and tangible rewards were identified as critical for uptake and retention.

CONCLUSIONS

Our study highlights the potential of mHealth apps with relevant features to be used as wellness tools by frontline health care workers. Future work should focus on developing a nonintrusive and personalized mHealth app with in-app counseling, peer support to improve well-being, and tangible and extrinsic rewards to foster continued use.

“They don’t always think about that”: Translational Needs in the Design of Personal Health Informatics Applications

Personal health informatics continues to grow in both research and practice, revealing many challenges of designing applications that address people's needs in their health, everyday lives, and collaborations with clinicians. Research suggests strategies to address such challenges, but has struggled to translate these strategies into design practice. This study examines translation of insights from personal health informatics research into resources to support designers. Informed by a review of relevant literature, we present our development of a prototype set of design cards intended to support designers in re-thinking potential assumptions about personal health informatics. We examined our design cards in semi-structured interviews, first with 12 student designers and then with 12 health-focused professional designers and researchers. Our results and discussion reveal tensions and barriers designers encounter, the potential for translational resources to inform the design of health-related technologies, and a need to support designers in addressing challenges of knowledge, advocacy, and evidence in designing for health.

A Review on Strategies for Data Collection, Reflection, and Communication in Eating Disorder Apps

Eating disorders (EDs) constitute a mental illness with the highest mortality. Today, mobile health apps provide promising means to ED patients for managing their condition. Apps enable users to monitor their eating habits, thoughts, and feelings, and offer analytic insights for behavior change. However, not only have scholars critiqued the clinical validity of these apps, their underlying design principles are not well understood. Through a review of 34 ED apps, we uncovered 11 different data types ED apps collect, and 9 strategies they employ to support collection and reflection. Drawing upon personal health informatics and visualization frameworks, we found that most apps did not adhere to best practices on what and how data should be collected from and reflected to users, or how data-driven insights should be communicated. Our review offers suggestions for improving the design of ED apps such that they can be useful and meaningful in ED recovery.

Things that help out: designing smart wearables as partners in stress management

We propose an approach to designing smart wearables that act as partners to help people cope with stress in daily life. Our approach contributes to the developing field of smart wearables by addressing how technological capabilities can be designed to establish partnerships that consider the person, the situation, and the appropriate type of support. As such, this study also contributes to healthcare by opening up novel technology-supported routes to stress treatment and care. We present the results of a phenomenological study conducted with three war veterans who suffer from chronic posttraumatic stress disorder. We describe how their experiences of dealing with their stress informed our design approach, and discuss the implications of these results on smart wearables and stress management in general. We conclude by reflecting on the limitations of this study and directions for future work.

The Importance of Starting With Goals in N-of-1 Studies

N-of-1 tools offer the potential to support people in monitoring health and identifying individualized health management strategies. We argue that elicitation of individualized goals and customization of tracking to support those goals are a critical yet under-studied and under-supported aspect of self-tracking. We review examples of self-tracking from across a range of chronic conditions and self-tracking designs (e.g., self-monitoring, correlation analyses, self-experimentation). Together, these examples show how failure to elicit goals can lead to ineffective tracking routines, breakdowns in collaboration (e.g., between patients and providers, among families), increased burdens, and even designs that encourage behaviors counter to a person's goals. We discuss potential techniques for eliciting and refining goals, scaffolding an appropriate tracking routine based on those goals, and presenting results in ways that advance individual goals while preserving individual agency. We then describe open challenges, including how to reconcile competing goals and support evolution of goals over time.

Clinician Perspectives and Design Implications in Using Patient-Generated Health Data to Improve Mental Health Practices: Mixed Methods Study

Background

Patient-generated health data (PGHD) have been largely collected through mobile health (mHealth) apps and wearable devices. PGHD can be especially helpful in mental health, as patients’ illness history and symptom narratives are vital to developing diagnoses and treatment plans. However, the extent to which clinicians use mental health–related PGHD is unknown.

Objective

A mixed methods study was conducted to understand clinicians’ perspectives on PGHD and current mental health apps. This approach uses information gathered from semistructured interviews, workflow analysis, and user-written mental health app reviews to answer the following research questions: (1) What is the current workflow of mental health practice and how are PGHD integrated into this workflow, (2) what are clinicians’ perspectives on PGHD and how do they choose mobile apps for their patients, (3) and what are the features of current mobile apps in terms of interpreting and sharing PGHD?

Methods

The study consists of semistructured interviews with 12 psychiatrists and clinical psychologists from a large academic hospital. These interviews were thematically and qualitatively analyzed for common themes and workflow elements. User-posted reviews of 56 sleep and mood tracking apps were analyzed to understand app features in comparison with the information gathered from interviews.

Results

The results showed that PGHD have been part of the workflow, but its integration and use are not optimized. Mental health clinicians supported the use of PGHD but had concerns regarding data reliability and accuracy. They also identified challenges in selecting suitable apps for their patients. From the app review, it was discovered that mHealth apps had limited features to support personalization and collaborative care as well as data interpretation and sharing.

Conclusions

This study investigates clinicians’ perspectives on PGHD use and explored existing app features using the app review data in the mental health setting. A total of 3 design guidelines were generated: (1) improve data interpretation and sharing mechanisms, (2) consider clinical workflow and electronic health record integration, and (3) support personalized and collaborative care. More research is needed to demonstrate the best practices of PGHD use and to evaluate their effectiveness in improving patient outcomes.

Personality and Subjective Well-Being: Towards Personalized Persuasive Interventions for Health and Well-Being

Subjective well-being (SWB) is an individual's judgment about their overall well-being. Research has shown that activities that elevate people's sense of SWB have a significant effect on their overall health. There are two dimensions of SWB: Affective and Cognitive dimensions. However, studies on SWB usually focus more on one dimension, ignoring the other dimension. Also, most existing studies on SWB focused on individuals from Western cultures. Research has shown that the influence of personality on subjective well-being is moderated by culture. Thus, to advance research in personalizing persuasive health interventions, this study focuses on Africans (n=732). Specifically, we investigate the relationship between the Big-Five personality traits and both dimensions of SWB using the constructs: Happiness, Satisfaction with Life, Social, Psychological and Emotional well-being. Our results reveal that health informatics designers who design persuasive technologies to promote SWB would need to tailor designs along personality traits and SWB constructs. Accordingly, for users high in Agreeableness, the design should be focus on promoting their feelings of Happiness and Social Well-being. For users who exhibit Neuroticism, designers should focus on designing to promote Psychological well-being and Emotional well-being. Based on our findings, we offer guidelines for tailoring persuasive health interventions to promote individuals' SWB based on their personality. We thus highlight areas personal health informatics design can benefit.

CCS CONCEPTS

• Human-centered computing → Personalization → HCI design and evaluation methods → User models.

Designing Mental Health Technologies that Support the Social Ecosystem of College Students

The last decade has seen increased reports of mental health problems among college students, with college counseling centers struggling to keep up with the demand for services. Digital mental health tools offer a potential solution to expand the reach of mental health services for college students. In this paper, we present findings from a series of design activities conducted with college students and counseling center staff aimed at identifying needs and preferences for digital mental health tools. Results emphasize the social ecosystems and social support networks in a college student's life. Our findings highlight the predominant role of known peers, and the ancillary roles of unknown peers and non-peers (e.g., faculty, family) in influencing the types of digital mental health tools students desire, and the ways in which they want to learn about mental health tools. We identify considerations for designing digital mental health tools for college students that take into account the identified social factors and roles.

"Energy is a Finite Resource": Designing Technology to Support Individuals across Fluctuating Symptoms of Depression

While the HCI field increasingly examines how digital tools can support individuals in managing mental health conditions, it remains unclear how these tools can accommodate these conditions' temporal aspects. Based on weekly interviews with five individuals with depression, conducted over six weeks, this study identifies design opportunities and challenges related to extending technology-based support across fluctuating symptoms. Our findings suggest that participants perceive events and contexts in daily life to have marked impact on their symptoms. Results also illustrate that ebbs and flows in symptoms profoundly affect how individuals practice depression self-management. While digital tools often aim to reach individuals while they feel depressed, we suggest they should also engage individuals when they are less symptomatic, leveraging their energy and motivation to build habits, establish plans and goals, and generate and organize content to prepare for symptom onset.

Understanding Students' Mental Well-Being Challenges on a University Campus: Interview Study

BACKGROUND

Research shows that emerging adults face numerous stressors as they transition from adolescence to adulthood. This paper investigates university students' lived experiences of maintaining mental well-being during major life events and challenges associated with this transitional period. As we continue to design health technology to support students' mental health needs, it is imperative to understand the fundamental needs and issues particular to this phase of their life to effectively engage and lower the barriers to seeking help.

OBJECTIVE

This study first aimed to understand how university students currently seek and receive support to maintain their mental well-being while going through frequent life events during this period of emerging adulthood. The study then aimed to provide design requirements for how social and technical systems should support the students' mental well-being maintenance practice.

METHODS

Semistructured interviews with 19 students, including graduate and undergraduate students, were conducted at a large university in the Midwest in the United States.

RESULTS

This study's findings identified three key needs: students (1) need to receive help that aligns with the perceived severity of the problem caused by a life event, (2) have to continuously rebuild relationships with support givers because of frequent life events, and (3) negotiate tensions between the need to disclose and the stigma associated with disclosure. The study also identified three key factors related to maintaining mental well-being: time, audience, and disclosure.

CONCLUSIONS

On the basis of this study's empirical findings, we discuss how and when help should be delivered through technology to better address university students' needs for maintaining their mental well-being, and we argue for reconceptualizing seeking and receiving help as a colearning process.

Informational Practices of Postacute Brain Injury Patients During Personal Recovery: Qualitative Study

BACKGROUND

The effects of brain injury, structural damage, or the physiological disruption of brain function last far beyond initial clinical treatment. Self-tracking and management technologies have the potential to help individuals experiencing brain injury in their personal recovery-helping them to function at their best despite ongoing symptoms of illness. However, current self-tracking technologies may be unsuited for measuring the interconnected, nonlinear ways in which brain injury manifests.

OBJECTIVE

This study aimed to investigate (1) the current informational practices and sensemaking processes used by postacute brain injury patients during personal recovery and (2) the potential role of quality-of-life instruments in improving patient awareness of brain injury recovery, advocacy, and involvement in care used outside the clinical context. Our objective was to explore the means of improving awareness through reflection that leads to compensatory strategies by anticipating or recognizing the occurrence of a problem caused by impairment.

METHODS

We conducted a qualitative study and used essentialist or realist thematic analysis to analyze the data collected through semistructured interviews and questionnaires, 2 weeks of structured data collection using brain injury-specific health-related quality of life instrument, quality of life after brain injury (QoLIBRI), and final interviews.

RESULTS

Informational practices of people with brain injury involve data collection, data synthesis, and obtaining and applying the insights to their lifestyles. Participants collected data through structured tools such as spreadsheets and wearable devices but switched to unstructured tools such as journals and blogs as changes in overall progress became more qualitative in nature. Although data collection helped participants summarize their progress better, the lack of conceptual understanding made it challenging to know what to monitor or communicate with clinicians. QoLIBRI served as an education tool in this scenario but was inadequate in facilitating reflection and sensemaking.

CONCLUSIONS

Individuals with postacute brain injury found the lack of conceptual understanding of recovery and tools for making sense of their health data as major impediments for tracking and being aware of their personal recovery. There is an urgent need for a better framework for recovery and a process model for choosing patient-generated health data tools that focus on the holistic nature of recovery and improve the understanding of brain injury for all stakeholders involved throughout recovery.

Provider Perspectives on Integrating Sensor-Captured Patient-Generated Data in Mental Health Care

The increasing ubiquity of health sensing technology holds promise to enable patients and health care providers to make more informed decisions based on continuously-captured data. The use of sensor-captured patient-generated data (sPGD) has been gaining greater prominence in the assessment of physical health, but we have little understanding of the role that sPGD can play in mental health. To better understand the use of sPGD in mental health, we interviewed care providers in an intensive treatment program (ITP) for veterans with post-traumatic stress disorder. In this program, patients were given Fitbits for their own voluntary use. Providers identified a number of potential benefits from patients' Fitbit use, such as patient empowerment and opportunities to reinforce therapeutic progress through collaborative data review and interpretation. However, despite the promise of sensor data as offering an "objective" view into patients' health behavior and symptoms, the relationships between sPGD and therapeutic progress are often ambiguous. Given substantial subjectivity involved in interpreting data from commercial wearables in the context of mental health treatment, providers emphasized potential risks to their patients and were uncertain how to adjust their practice to effectively guide collaborative use of the FitBit and its sPGD. We discuss the implications of these findings for designing systems to leverage sPGD in mental health care.

The Determinants of M-Health Adoption in Developing Countries: An Empirical Investigation

BACKGROUND

The potential benefit of mobile health (M-Health) in developing countries for improving the efficiency of health care service delivery, health care quality, and patient safety, as well as reducing cost, has been increasingly recognized and emphasized in the last few years.

OBJECTIVE

Limited research has investigated the facilitators and barriers for the adoption of M-Health in developing countries to secure successful implementation of the technology. To fill this knowledge gap, we propose an integrative model that explains the patient's adoption behavior of M-Health in developing countries grounded on the unified theory of acceptance and use of technology, dual-factor model, and health belief model.

METHOD

We empirically tested and evaluated the model based on data collected using a survey method from 280 patients living in a developing country. Partial least squares (PLS-SEM) technique was used for data analysis.

RESULTS

The results showed that performance expectancy, effort expectancy, social influence, perceived health threat, M-Health app quality, and life quality expectancy have a direct positive effect on patients' intention to use M-Health. The results also showed that security and privacy risks have a direct negative effect on the patient's intention to use M-Health. However, resistance to change was found to have an indirect negative effect on patients' intention to use M-Health through the performance expectancy.

CONCLUSION

The research contributes to the existing literature of health information systems and M-Health by better understanding how technological, social, and functional factors are associated with digital health applications and services use and success in the context of developing countries. With the widespread availability of mobile technologies and services and the growing demand for M-Health apps, this research can help guide the development of the next generation of M-Health apps with a focus on the needs of patients in developing countries. The research has several theoretical and practical implications for the health care industry, government, policy makers, and technology developers and designers.

Data-Driven Learning in High-Resolution Activity Sampling From Patients With Bipolar Depression: Mixed-Methods Study

BACKGROUND

Behavioral activation is a pen and paper-based therapy form for treating depression. The patient registers their activity hourly, and together with the therapist, they agree on a plan to change behavior. However, with the limited clinical personnel, and a growing patient population, new methods are needed to advance behavioral activation.

OBJECTIVE

The objectives of this paper were to (1) automatically identify behavioral patterns through statistical analysis of the paper-based activity diaries, and (2) determine whether it is feasible to move the behavioral activation therapy format to a digital solution.

METHODS

We collected activity diaries from seven patients with bipolar depression, covering in total 2,480 hours of self-reported activities. A pleasure score, on a 1-10 rating scale, was reported for each activity. The activities were digitalized into 6 activity categories, and statistical analyses were conducted.

RESULTS

Across all patients, movement-related activities were associated with the highest pleasure score followed by social activities. On an individual level, through a nonparametric Wilcoxon Signed-Rank test, one patient had a statistically significant larger amount of spare time activities when feeling bad (z=-2.045, P=.041). Through a within-subject analysis of covariance, the patients were found to have a better day than the previous, if that previous day followed their diurnal rhythm (ρ=.265, P=.029). Furthermore, a second-order trend indicated that two hours of daily social activity was optimal for the patients (β₂=-0.08, t (63)=-1.22, P=.23).

CONCLUSIONS

The data-driven statistical approach was able to find patterns within the behavioral traits that could assist the therapist in as well as help design future technologies for behavioral activation.

User Experience of Cognitive Behavioral Therapy Apps for Depression: An Analysis of App Functionality and User Reviews

Background

Hundreds of mental health apps are available to the general public. With increasing pressures on health care systems, they offer a potential way for people to support their mental health and well-being. However, although many are highly rated by users, few are evidence-based. Equally, our understanding of what makes apps engaging and valuable to users is limited.

Objective

The aim of this paper was to analyze functionality and user opinions of mobile apps purporting to support cognitive behavioral therapy for depression and to explore key factors that have an impact on user experience and support engagement.

Methods

We systematically identified apps described as being based on cognitive behavioral therapy for depression. We then conducted 2 studies. In the first, we analyzed the therapeutic functionality of apps. This corroborated existing work on apps’ fidelity to cognitive behavioral therapy theory, but we also extended prior work by examining features designed to support user engagement. Engagement features found in cognitive behavioral therapy apps for depression were compared with those found in a larger group of apps that support mental well-being in a more general sense. Our second study involved a more detailed examination of user experience, through a thematic analysis of publicly available user reviews of cognitive behavioral therapy apps for depression.

Results

We identified 31 apps that purport to be based on cognitive behavioral therapy for depression. Functionality analysis (study 1) showed that they offered an eclectic mix of features, including many not based on cognitive behavioral therapy practice. Cognitive behavioral therapy apps used less varied engagement features compared with 253 other mental well-being apps. The analysis of 1287 user reviews of cognitive behavioral therapy apps for depression (study 2) showed that apps are used in a wide range of contexts, both replacing and augmenting therapy, and allowing users to play an active role in supporting their mental health and well-being. Users, including health professionals, valued and used apps that incorporated both core cognitive behavioral therapy and non-cognitive behavioral therapy elements, but concerns were also expressed regarding the unsupervised use of apps. Positivity was seen as important to engagement, for example, in the context of automatic thoughts, users expressed a preference to capture not just negative but also positive ones. Privacy, security, and trust were crucial to the user experience.

Conclusions

Cognitive behavioral therapy apps for depression need to improve with respect to incorporating evidence-based cognitive behavioral therapy elements. Equally, a positive user experience is dependent on other design factors, including consideration of varying contexts of use. App designers should be able to clearly identify the therapeutic basis of their apps, but they should also draw on evidence-based strategies to support a positive and engaging user experience. The most effective apps are likely to strike a balance between evidence-based cognitive behavioral therapy strategies and evidence-based design strategies, including the possibility of eclectic therapeutic techniques.