Clinical review of user engagement with mental health smartphone apps: evidence, theory and improvements

The efficacy of automated feedback after internet-based depression screening: Study protocol of the German, three-armed, randomised controlled trial DISCOVER

BACKGROUND

Depression is one of the most disabling disorders worldwide, yet it often remains undetected. One promising approach to address both early detection and disease burden is depression screening followed by direct feedback to patients. Evidence suggests that individuals often seek information regarding mental health on the internet. Thus, internet-based screening with automated feedback has great potential to address individuals with undetected depression.

OBJECTIVES

To determine whether automated feedback after internet-based depression screening reduces depression severity as compared to no feedback.

METHODS

The internet-based, observer-blinded DISCOVER RCT aims to recruit a total of 1074 individuals. Participants will be screened for depression using the Patient Health Questionnaire (PHQ-9). In case of a positive screening result (PHQ-9 ≥ 10), participants with undetected depression will be randomised into one of three balanced study arms to receive either (a) no feedback (control arm), (b) standard feedback, or (c) tailored feedback on their screening result. The tailored feedback version will be adapted to participants' characteristics, i.e. symptom profile, preferences, and demographic characteristics. The primary hypothesis is that feedback reduces depression severity six months after screening compared to no feedback. The secondary hypothesis is that tailored feedback is more efficacious compared to standard feedback. Further outcomes are depression care, help-seeking behaviour, health-related quality of life, anxiety, somatic symptom severity, intervention acceptance, illness beliefs, adverse events, and a health economic evaluation. Follow-ups will be conducted one month and six months after screening by self-report questionnaires and clinical interviews. According to a statistical analysis plan, the primary outcome will be analysed on an intention-to-treat basis applying multilevel modelling.

DISCUSSION

The results of the DISCOVER RCT will inform about how automated feedback after internet-based screening could improve early detection and resolution of depression. Ways of dissemination and how the trial can contribute to an understanding of help-seeking behaviour processes will be discussed. If the results show that automated feedback after internet-based depression screening can reduce depression severity, the intervention could be easily implemented and might substantially reduce the disease burden of individuals with undetected depression.

ETHICAL APPROVAL

The study is approved by the Ethics Committee of the Hamburg Medical Association.

TRIAL REGISTRATION

The trial was registered at ClinicalTrials.gov in November 2020 (identifier: NCT04633096).

A School-Based Mobile App Intervention for Enhancing Emotion Regulation in Children: Exploratory Trial

BACKGROUND

Most mental health disorders are first experienced in childhood. The rising rates of mental health difficulties in children highlight the need for innovative approaches to supporting children and preventing these difficulties. School-based digital interventions that address shared risk factors and symptoms, such as emotion dysregulation, present exciting opportunities to enhance mental health support for children on a larger scale.

OBJECTIVE

This study investigates the use of a new app-based intervention designed to support children's emotion regulation in schools. The aim is to optimize the usability, acceptability, and utility of the app and explore its scope for implementation with the target user in the school context.

METHODS

As part of an interdisciplinary development framework, the app is being evaluated in a 3-month trial across 4 primary schools. In total, 144 children (aged 10-12 years) took part and accessed the intervention app in the classroom or at home. Outcomes regarding usability, acceptability, and implementation opportunities were assessed through digital user data, self-report questionnaires (132/144, 91.6%), and semistructured interviews with children (19/144, 13.2%) and teachers (6/8, 75%).

RESULTS

The app usage data showed that 30% (128/426) of the users were returning users. Self-report data indicated that 40.1% (53/132) of the children had not used the app, whereas 57.5% (76/132) had used it once or more. Of the children who had used the app, 67% (51/76) reported that the app was helpful. Interviews with children and teachers suggested positive experiences with the app and that it helped them to calm down and relax. Children reported that they perceived the app as acceptable, usable, and helpful. In terms of the intervention's usability, most features functioned well; however, certain technical issues were reported, which may have led to reduced engagement levels. Teachers not only reported overall positive experiences but also discussed access difficulties and reported a lack of content as one of the main barriers to implementing the app. Having a web-based app significantly enhanced accessibility across devices and settings and provided teachers with more opportunities to use it. We identified the need for new, activating app features in addition to the existing, primarily relaxing ones. The findings indicated that it is possible to use and evaluate an app intervention in the school context and that the app could help enhance children's emotion regulation. We discuss areas for improvement regarding the app, study design, and future implementation strategies.

CONCLUSIONS

We share important insights with regard to the development, implementation, and evaluation of a new app for supporting children's emotion regulation in schools. Our results demonstrate that mental health apps represent a promising means to facilitate effective mental health service provision in and outside of the school context. Important lessons learned are shared to support other researchers and clinicians on similar journeys.

User Perspectives on a Resilience-Building App (JoyPop): Qualitative Study

BACKGROUND

Resilience is the capability, resources, and processes that are available to a person or system to adapt successfully in the face of stress or adversity. Given that resilience can be enhanced, using advances in technology to deliver and evaluate the impact of resilience interventions is warranted. Evidence supports the effectiveness of the resilience-building JoyPop app in improving resilience-related outcomes after use; however, experiential data from users is also needed to provide a more comprehensive account of its utility.

OBJECTIVE

The aim of this study was to explore users' experiences with the JoyPop app and their perspectives on its utility.

METHODS

This qualitative description study involved a combination of group and one-on-one semistructured interviews with a subset of first-year undergraduate students who participated in a larger evaluation of the JoyPop app. Participants used the app for a 4-week period and were subsequently asked about their frequency of app use, most and least used features (and associated reasons), most and least helpful features (and associated reasons), barriers to use, facilitators of use and continuation, and recommendations for improvement. Data were coded and categorized through inductive content analysis.

RESULTS

The sample of 30 participants included 24 females and 6 males, with a mean age of 18.77 years (SD 2.30). App use ranged from 1 to 5 times daily (mean 2.11, SD 0.74), with the majority indicating that they used the app at least twice daily. The Rate My Mood, Journal, and SquareMoves features were reported to be used most often, while the Rate My Mood, Journal, and Breathing Exercises features were identified as the most helpful. A number of themes and subthemes pertaining to facilitators of app use (prompts, creating routine, self-monitoring opportunities, expressive opportunities), barriers to app use (editing, lack of variety, student lifestyle), outcomes of app use (increased awareness, checking in with oneself, helpful distraction, emotional control), and recommendations for app improvement (adding more features, enhancing existing features, enhancing tracking abilities, providing personalization) were identified.

CONCLUSIONS

This study provides insight into the aspects of the JoyPop app that motivated and benefitted users, as well as measures that can be taken to improve user experiences and promote longer-term uptake. Users were willing to engage with the app and incorporate it into their routine, and they valued the ability to self-monitor, express emotion, and engage in distraction.

Assessing College Students' Perceptions of and Intentions to Use a Mobile App for Mental Health

Background: College students face high rates of depression, anxiety, and suicide. Therefore, the focus of this study was to examine college students' intention to use a mental health app provided by the university, called MySSP, through use of the unified theory of acceptance and use of technology (UTAUT). Materials and Methods: An online survey was developed based on responses to focus groups previously conducted by the authors regarding MySSP. A multiple linear regression was conducted to test the associations between the UTAUT variables and behavioral intention. In addition, moderation analyses were conducted to explore the effects of depression, anxiety, stigma, and quality of life as moderators. Results: Results suggest that performance expectancy (PE) (t = 3.088, p = 0.003) and social influence (SI) (t = -2.163, p = 0.03) were the only significant predictors of behavioral intention. The only significant moderator was stigma in the relationship between effort expectancy and behavioral intention (b = -1.6081, standard error (SE) = 0.7454, confidence interval (CI): -3.0691 to -0.1472) as well as facilitating conditions (FCs) and behavioral intention (b = -2.2292, SE = 0.8580, CI: -3.9110 to -0.5475). Conclusions: This study provides an initial exploration of college students' intentions to use MySSP. The results suggest that successful interventions include features related to PE (usefulness) and SI (norms), which should be focused on when developing and testing apps for mental health. Additionally, the stigma of mental health has significant negative impacts on the adoption of mental health apps and should be considered in implementation of mental health interventions geared toward college students.

Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial

BACKGROUND

The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes.

OBJECTIVE

This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy.

METHODS

We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics.

RESULTS

A higher engagement rate was associated with higher weight loss at 8 weeks (r=-0.59; P<.001) and 24 weeks (r=-0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R² 0.416, SD 0.006). The prediction of short-term weight change (mean R² 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R² 0.590, SD 0.011).

CONCLUSIONS

Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306.

Patients' adherence to smartphone apps in the management of bipolar disorder: a systematic review

Background

Despite an increasing number of available mental health apps in the bipolar disorder field, these tools remain scarcely implemented in everyday practice and are quickly discontinued by patients after downloading. The aim of this study is to explore adherence characteristics of bipolar disorder patients to dedicated smartphone interventions in research studies.

Methods

A systematic review following PRISMA guidelines was conducted. Three databases (EMBASE, PsychInfo and MEDLINE) were searched using the following keywords: "bipolar disorder" or "mood disorder" or “bipolar” combined with “digital” or “mobile” or “phone” or “smartphone” or “mHealth” or “ehealth” or "mobile health" or “app” or “mobile-health”.

Results

Thirteen articles remained in the review after exclusion criteria were applied. Of the 118 eligible studies, 39 did not provide adherence characteristics. Among the selected papers, study length, sample size and definition of measures of adherence were strongly heterogeneous. Activity rates ranged from 58 to 91.6%.

Conclusion

The adherence of bipolar patients to apps is understudied. Standardised measures of adherence should be defined and systematically evaluated in future studies dedicated to these tools.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40345-021-00224-6.

A Clinician-Controlled Just-in-time Adaptive Intervention System (CBT+) Designed to Promote Acquisition and Utilization of Cognitive Behavioral Therapy Skills in Bulimia Nervosa: Development and Preliminary Evaluation Study

Background

Cognitive behavioral therapy (CBT) for bulimia nervosa (BN) is most effective when patients demonstrate adequate skill utilization (ie, the frequency with which a patient practices or uses therapeutic skills) and skill acquisition (ie, the ability to successfully perform a skill learned in treatment). However, rates of utilization and acquisition of key treatment skills (eg, regular eating, urge management skills, and mood management skills) by the end of the treatment are frequently low; as a result, outcomes from CBT for BN are affected. Just-in-time adaptive interventions (JITAIs) may improve skill acquisition and utilization by delivering real-time interventions during algorithm-identified opportunities for skill practice.

Objective

In this manuscript, we describe a newly developed JITAI system called CBT+ that is designed to facilitate the acquisition and utilization of CBT for BN treatment skills when used as a treatment augmentation. We also present feasibility, acceptability, and preliminary outcomes data from a small proof-of-concept pilot trial (n=5 patients and n=3 clinicians) designed to identify opportunities for iterative development of CBT+ ahead of a larger ongoing randomized controlled trial.

Methods

A total of 5 individuals with BN received 16 sessions of outpatient CBT for BN while using the CBT+ app. Data were collected from patients and clinicians to evaluate the feasibility (eg, app use and user adherence), acceptability (eg, qualitative patient and clinician feedback, including usefulness ratings of CBT+ on a 6-point Likert scale ranging from 1=extremely useless to 6=extremely useful), and preliminary outcomes (eg, improvements in skill utilization and acquisition and BN symptoms) of the CBT+ system.

Results

Patients reported that CBT+ was a relatively low burden (eg, quick and easy-to-use self-monitoring interface), and adherence to in-app self-monitoring was high (mean entries per day 3.13, SD 1.03). JITAIs were perceived as useful by both patients (median rating 5/6) and clinicians (median rating 5/6) for encouraging the use of CBT skills. Large improvements in CBT skills and clinically significant reductions in BN symptoms were observed post treatment. Although preliminary findings indicated that the CBT+ system was acceptable to most patients and clinicians, the overall study dropout was relatively high (ie, 2/5, 40% patients), which could indicate some moderate concerns regarding feasibility.

Conclusions

CBT+, the first-ever JITAI system designed to facilitate the acquisition and utilization of CBT for BN treatment skills when used as a treatment augmentation, was shown to be feasible and acceptable. The results indicate that the CBT+ system should be subjected to more rigorous evaluations with larger samples and should be considered for wider implementation if found effective. Areas for iterative improvement of the CBT+ system ahead of a randomized controlled trial are also discussed.

Engagement and Effectiveness of a Healthy-Coping Intervention via Chatbot for University Students During the COVID-19 Pandemic: Mixed Methods Proof-of-Concept Study

BACKGROUND

University students are increasingly reporting common mental health problems, such as stress, anxiety, and depression, and they frequently face barriers to seeking psychological support because of stigma, cost, and availability of mental health services. This issue is even more critical in the challenging time of the COVID-19 pandemic. Digital mental health interventions, such as those delivered via chatbots on mobile devices, offer the potential to achieve scalability of healthy-coping interventions by lowering cost and supporting prevention.

OBJECTIVE

The goal of this study was to conduct a proof-of-concept evaluation measuring the engagement and effectiveness of Atena, a psychoeducational chatbot supporting healthy coping with stress and anxiety, among a population of university students.

METHODS

In a proof-of-concept study, 71 university students were recruited during the COVID-19 pandemic; 68% (48/71) were female, they were all in their first year of university, and their mean age was 20.6 years (SD 2.4). Enrolled students were asked to use the Atena psychoeducational chatbot for 4 weeks (eight sessions; two per week), which provided healthy-coping strategies based on cognitive behavioral therapy, positive psychology, and mindfulness techniques. The intervention program consisted of conversations combined with audiovisual clips delivered via the Atena chatbot. Participants were asked to complete web-based versions of the 7-item Generalized Anxiety Disorder scale (GAD-7), the 10-item Perceived Stress Scale (PSS-10), and the Five-Facet Mindfulness Questionnaire (FFMQ) at baseline and postintervention to assess effectiveness. They were also asked to complete the User Engagement Scale-Short Form at week 2 to assess engagement with the chatbot and to provide qualitative comments on their overall experience with Atena postintervention.

RESULTS

Participants engaged with the Atena chatbot an average of 78 (SD 24.8) times over the study period. A total of 61 out of 71 (86%) participants completed the first 2 weeks of the intervention and provided data on engagement (10/71, 14% attrition). A total of 41 participants out of 71 (58%) completed the full intervention and the postintervention questionnaires (30/71, 42% attrition). Results from the completer analysis showed a significant decrease in anxiety symptoms for participants in more extreme GAD-7 score ranges (t39=0.94; P=.009) and a decrease in stress symptoms as measured by the PSS-10 (t39=2.00; P=.05) for all participants postintervention. Participants also improved significantly in the describing and nonjudging facets, based on their FFMQ subscale scores, and asked for some improvements in the user experience with the chatbot.

CONCLUSIONS

This study shows the benefit of deploying a digital healthy-coping intervention via a chatbot to support university students experiencing higher levels of distress. While findings collected during the COVID-19 pandemic show promise, further research is required to confirm conclusions.

Intelligent Cognitive Assistants for Attitude and Behavior Change Support in Mental Health: State-of-the-Art Technical Review

Intelligent cognitive assistant (ICA) technology is used in various domains to emulate human behavior expressed through synchronous communication, especially written conversation. Due to their ability to use individually tailored natural language, they present a powerful vessel to support attitude and behavior change. Behavior change support systems are emerging as a crucial tool in digital mental health services, and ICAs exceed in effective support, especially for stress, anxiety and depression (SAD), where ICAs guide people’s thought processes and actions by analyzing their affective and cognitive phenomena. Currently, there is no comprehensive review of such ICAs from a technical standpoint, and existing work is conducted exclusively from a psychological or medical perspective. This technical state-of-the-art review tried to discern and systematize current technological approaches and trends as well as detail the highly interdisciplinary landscape of intersections between ICAs, attitude and behavior change, and mental health, focusing on text-based ICAs for SAD. Ten papers with systems, fitting our criteria, were selected. The systems varied significantly in their approaches, with the most successful opting for comprehensive user models, classification-based assessment, personalized intervention, and dialogue tree conversational models.

Atrial fibrillation self-management: a mobile telephone app scoping review and content analysis

Atrial fibrillation (AF) affects over 1.4 million people in the UK, resulting in a five-fold increased stroke risk and a three to four times greater risk of severe, disabling stroke. Atrial fibrillation, a chronic disease, requires monitoring, medication, and lifestyle measures. A self-management approach supported by mobile health (mHealth) may empower AF self-care. To assess the need to develop new mHealth self-management interventions for those with AF this review aimed to identify commercially available AF self-management apps, analyse, and synthesize (i) characteristics, (ii) functions, (iii) privacy/security, (iv) incorporated behaviour change techniques (BCTs), and (v) quality and usability. We searched app stores for 'atrial fibrillation' and 'anticoagulation', and included apps focused on AF self-management in the review. We examined app functions, privacy statements against best practice recommendations, the inclusion of BCTs using the App Behaviour Change Scale, and app quality/usability using the Mobile App Rating Scale. From an initial search of 555 apps, five apps were included in the review. Common functions were educational content, medication trackers, and communication with healthcare professionals. Apps contained limited BCTs, lacked intuitive functions and were difficult to use. Privacy policies were difficult to read. App quality rated from poor to acceptable and no app had been evaluated in a clinical trial. The review reports a lack of commercially available AF self-management apps of sufficient standard for use in healthcare settings. This highlights the need for clinically validated mHealth interventions incorporating evidence-based BCTs to support AF self-management.

Effectiveness of Mobile App-Based Psychological Interventions for College Students: A Systematic Review of the Literature

Serious mental health disorders are increasing among college students and university counseling services are often overburdened. Mobile applications for mental health have been growing exponentially in the last decade and they are emerging in university settings as a promising tool to promote and intervene in college students' mental health. Additionally, considering the recent covid-19 pandemic, mHealth interventions, due to its nature and possibilities, may play an important role in these institutions. Our main objectives are to explore mhealth interventions in universities, regarding its conceptual framework, acceptability and efficacy outcomes and understand its impact and contributions to address treatment delivery and psychological difficulties resulting from covid-19 pandemic. The literature search was conducted in scientific databases, namely, Web of Science, Pubmed, and Scopus. A search in app stores was not conducted, thus regarding commercially available apps, only those found in our database search were included in our review. We selected studies with mobile applications addressing psychological interventions for college students. A total of 2,158 participants were included in the 8 selected studies and most interventions were delivered through mobile apps only and based in cognitive behavioral therapy. Results suggested that college students accept and adhere to these interventions and preliminary evidence of efficacy was demonstrated in different disorders, such as stress, anxiety, depression and risky behaviors such as alcohol and tobacco abuse and sexual knowledge. We conclude that universities, particularly college counseling services, may benefit from mhealth interventions, not only to address college students' mental health but to decrease some of its difficulties related to lack of human resources. Specifically in covid-19 pandemic context, these interventions may contribute significantly by promoting and delivering psychological interventions at a safe distance.

Smartphone ownership and use of mental health applications by psychiatric inpatients

Little is known about the use of mental health smartphone applications during the greatest period of vulnerability - immediately following discharge from a psychiatric inpatient unit. Currently, no data are available regarding smartphone ownership or technology literacy of individuals who receive inpatient psychiatric treatment. The goal of this study was to determine psychiatric inpatients' smartphone ownership, current uses of, and interest in utilizing apps to aid in mental health treatment after discharge. A single time point self-report survey was given to patients prior to discharge from a psychiatric inpatient unit at a major academic hospital in a metropolitan area of the United States. Of the 101 survey respondents, 82.8% indicated that they own a smartphone, and over 70% indicated that they use smartphone apps, can access the internet from their phones, and use social media. While only 25.3% reported that they currently use a mental health app, a majority of respondents (53.2%) expressed interest in using such apps in the future, and almost 60% would use those apps to track their mental health. Our data suggest that there is significant untapped potential for utilizing smartphone applications for psychiatric monitoring and treatment following discharge from an inpatient psychiatric unit.

MyEDCare: Evaluation of a Smartphone-Based Emergency Department Discharge Process

BACKGROUND

Poor comprehension and low compliance with post-ED (emergency department) care plans increase the risk of unscheduled ED return visits and adverse outcomes. Despite the growth of personal health records to support transitions of care, technological innovation's focus on the ED discharge process has been limited. Recent literature suggests that digital communication incorporated into post-ED care can improve patient satisfaction and care quality.

OBJECTIVES

We evaluated the feasibility of utilizing MyEDCare, a text message and smartphone-based electronic ED discharge process at two urban EDs.

METHODS

MyEDCare sends text messages to patients' smartphones at the time of discharge, containing a hyperlink to a Health Insurance Portability and Accountability Act (HIPAA)-compliant website, to deliver patient-specific ED discharge instructions. Content includes information on therapeutics, new medications, outpatient care scheduling, return precautions, as well as results of laboratory and radiological diagnostic testing performed in the ED. Three text messages are sent to patients: at the time of ED discharge with the nurse assistance for initial access of content, as well as 2 and 29 days after ED discharge. MyEDCare was piloted in a 9-month pilot period in 2019 at two urban EDs in an academic medical center. We evaluated ED return visits, ED staff satisfaction, and patient satisfaction using ED Consumer Assessment of Healthcare Providers and Systems (ED-CAHPS) patient satisfaction scores.

RESULTS

MyEDCare enrolled 27,713 patients discharged from the two EDs, accounting for 43% of treat-and-release ED patients. Of the treat-and-release patients, 27% completed MyEDCare discharge process, accessing the online content at the time of ED discharge. Patients discharged via MyEDCare had fewer 72-hour, 9-day, and 30-day unscheduled return ED visits and reported higher satisfaction related to nursing care.

CONCLUSION

EDs and urgent care facilities may consider developing a HIPAA-compliant, text message, and smartphone-based discharge process, including the transmission of test results, to improve patient-centered outcomes.

Development of a Resource Guide to Support the Engagement of Mental Health Providers and Patients With Digital Health Tools: Multimethod Study

BACKGROUND

As mental illness continues to affect 1 in 5 individuals, and the need for support has increased during the COVID-19 pandemic, the promise of digital mental health tools remains largely unrealized due to a lack of uptake by patients and providers. Currently, most efforts on supporting the uptake of digital mental health tools remain fragmented across organizations and geography. There is a critical need to synthesize these efforts in order to provide a coordinated strategy of supporting the adoption of digital mental health tools.

OBJECTIVE

The specific aim of this project is to develop a web-based resource document to support the engagement of mental health providers and patients in the use of digital mental health tools.

METHODS

The web-based resource was developed using a multimethod approach. A grey literature review was conducted in 2019 to identify relevant toolkits that are available in the public domain. This was supplemented with an environmental scan where individuals with expertise in the development, acquisition, implementation, and evaluation of digital mental health tools were invited to contribute additional tools or documents not identified in the grey literature search. An engagement workshop was held with stakeholders to explore how the resource document should be developed and delivered. These findings were collectively used to develop the final iteration of the resource document.

RESULTS

Based on a gray literature review and environmental scan with 27 experts, 25 resources were identified and included in the resource guide. These resources were developed for patients and providers by organizations from 5 countries. An engagement workshop was held with 14 stakeholders, and barriers related to cultural sensitivity, sustainability, and accessibility of the toolkit were identified. The final iteration of the resource document was developed by the research team using findings from the gray literature review, environmental scan, and engagement workshop. The contents of the 45-page resource guide are directed at mental health care providers, administrators, and patients (inclusive of families and caregivers).

CONCLUSIONS

The use of a multimethod approach led to the development of a resource guide that builds on existing evidence on digital mental health tools and was co-designed with stakeholders and end-users. The resource guide is now publicly available online for free and is being promoted through digital health and mental health websites. Future work should explore how this document can be integrated into clinical care delivery and pathways.

Chatbot-Based Assessment of Employees' Mental Health: Design Process and Pilot Implementation

BACKGROUND

Stress, burnout, and mental health problems such as depression and anxiety are common, and can significantly impact workplaces through absenteeism and reduced productivity. To address this issue, organizations must first understand the extent of the difficulties by mapping the mental health of their workforce. Online surveys are a cost-effective and scalable approach to achieve this but typically have low response rates, in part due to a lack of interactivity. Chatbots offer one potential solution, enhancing engagement through simulated natural human conversation and use of interactive features.

OBJECTIVE

The aim of this study was to explore if a text-based chatbot is a feasible approach to engage and motivate employees to complete a workplace mental health assessment. This paper describes the design process and results of a pilot implementation.

METHODS

A fully automated chatbot ("Viki") was developed to evaluate employee risks of suffering from depression, anxiety, stress, insomnia, burnout, and work-related stress. Viki uses a conversation style and gamification features to enhance engagement. A cross-sectional analysis was performed to gain first insights of a pilot implementation within a small to medium-sized enterprise (120 employees).

RESULTS

The response rate was 64.2% (77/120). In total, 98 employees started the assessment, 77 of whom (79%) completed it. The majority of participants scored in the mild range for anxiety (20/40, 50%) and depression (16/28, 57%), in the moderate range for stress (10/22, 46%), and at the subthreshold level for insomnia (14/20, 70%) as defined by their questionnaire scores.

CONCLUSIONS

A chatbot-based workplace mental health assessment seems to be a highly engaging and effective way to collect anonymized mental health data among employees with response rates comparable to those of face-to-face interviews.

Comprehensively addressing postpartum maternal health: a content and image review of commercially available mobile health apps

BACKGROUND

The United States is currently facing a maternal morbidity and mortality crisis, with the highest rates of any resource-rich nation. In efforts to address this, new guidelines for postpartum care suggest that mobile health (mHealth) apps can help provide complementary clinical support for new mothers during the postpartum period. However, to date no study has evaluated the quality of existing mHealth tools targeted to this time period in terms of sufficiency of maternal health information, inclusivity of people of color, and app usability.

METHODS

Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards were used to review the peripartum apps from the Apple and Google Play stores in either the Health/Fitness, Medical, or Education categories. Apps were evaluated for extent and quality of maternal health information and inclusivity of people of color using an a priori coding scheme. App usability was evaluated using the Mobile Application Rating Scale (MARS) score.

RESULTS

Of the 301 apps from the Apple and Google Play stores, 25 met criteria for final evaluation. Of the 30 maternal health topics coded for, the median number addressed by apps was 19.5 (65%). Peripartum behaviors were more frequently addressed than peripartum outpatient care topics and peripartum acute health risks. The coverage of maternal health information and inclusivity of people of color in app imagery both correlated positively with the MARS usability score of the app. Only 8 apps (32%) portrayed greater than 24% images of people of color- the percent of non-white Americans according to 2019 census estimates. There was no correlation between MARS usability score and number of app users, as estimated by number of ratings for the app available on the app store. In addition, apps with evidence-based maternal health information had greater MARS engagement, information, and aesthetics scores. However, presence of evidence-based information did not correlate with greater numbers of app users.

CONCLUSIONS

Current commercially available peripartum apps range widely in quality. Overall current app offerings generally do not provide adequate maternal health information and are not optimally accessible to the target users in terms of inclusivity of women of color or app usability. Apps delivering evidence-based information and more usable design are more likely to meet these standards but are not more likely to be downloaded by users.

Machine learning prediction of blood alcohol concentration: a digital signature of smart-breathalyzer behavior

Excess alcohol use is an important determinant of death and disability. Machine learning (ML)-driven interventions leveraging smart-breathalyzer data may help reduce these harms. We developed a digital phenotype of long-term smart-breathalyzer behavior to predict individuals' breath alcohol concentration (BrAC) levels trained on data from a smart breathalyzer. We analyzed roughly one million datapoints from 33,452 users of a commercial smart-breathalyzer device, collected between 2013 and 2017. For validation, we analyzed the associations between state-level observed smart-breathalyzer BrAC levels and impaired-driving motor vehicle death rates. Behavioral, geolocation-based, and time-series-derived features were fed to an ML algorithm using training (70% of the cohort), development (10% of the cohort), and test (20% of the cohort) sets to predict the likelihood of a BrAC exceeding the legal driving limit (0.08 g/dL). States with higher average BrAC levels had significantly higher alcohol-related driving death rates, adjusted for the number of users per state B (SE) = 91.38 (15.16), p < 0.01. In the independent test set, the ML algorithm predicted the likelihood of a given user-initiated BrAC sample exceeding BrAC ≥ 0.08 g/dL, with an area under the curve (AUC) of 85%. Highly predictive features included users' prior BrAC trends, subjective estimation of their BrAC (or AUC = 82% without the self-estimate), engagement and self-monitoring, time since the last measure, and hour of the day. In conclusion, an ML algorithm successfully quantified a digital phenotype of behavior, predicting naturalistic BrAC levels exceeding 0.08 g/dL (a threshold associated with alcohol-related harm) with good discrimination capability. This result establishes a foundation for future research on precision behavioral medicine digital health interventions using smart breathalyzers and passive monitoring approaches.

Bridging the ‘digital divide’ in psychological therapies: Engagement with the SlowMo mobile app for paranoia in psychosis (Preprint)

Background

Marginalized groups are more likely to experience problems with technology-related access, motivation, and skills. This is known as the “digital divide.” Technology-related exclusion is a potential barrier to the equitable implementation of digital health. SlowMo therapy was developed with an inclusive, human-centered design to optimize accessibility and bridge the “digital divide.” SlowMo is an effective, blended digital psychological therapy for paranoia in psychosis.

Objective

This study explores the “digital divide” and mobile app engagement in the SlowMo randomized controlled trial.

Methods

Digital literacy was assessed at baseline, and a multidimensional assessment of engagement (ie, adherence [via system analytics and self-report] and self-reported user experience) was conducted at 12 weeks after therapy. Engagement was investigated in relation to demographics (ie, gender, age, ethnicity, and paranoia severity).

Results

Digital literacy data demonstrated that technology use and confidence were lower in Black people and older people (n=168). The engagement findings indicated that 80.7% (96/119) of therapy completers met the a priori analytics adherence criteria. However, analytics adherence did not differ by demographics. High rates of user experience were reported overall (overall score: mean 75%, SD 17.1%; n=82). No differences in user experience were found for ethnicity, age, or paranoia severity, although self-reported app use, enjoyment, and usefulness were higher in women than in men.

Conclusions

This study identified technology-related inequalities related to age and ethnicity, which did not influence engagement with SlowMo, suggesting that the therapy design bridged the “digital divide.” Intervention design may moderate the influence of individual differences on engagement. We recommend the adoption of inclusive, human-centered design to reduce the impact of the “digital divide” on therapy outcomes.

Trial Registration

ISRCTN Registry ISRCTN32448671; https://www.isrctn.com/ISRCTN32448671

A Multiple Health Behavior Change, Self-Monitoring Mobile App for Adolescents: Development and Usability Study of the Health4Life App

BACKGROUND

The link between chronic diseases and the Big 6 lifestyle risk behaviors (ie, poor diet, physical inactivity, smoking, alcohol use, sedentary recreational screen time, and poor sleep) is well established. It is critical to target these lifestyle risk behaviors, as they often co-occur and emerge in adolescence. Smartphones have become an integral part of everyday life, and many adolescents already use mobile apps to monitor their lifestyle behaviors and improve their health. Smartphones may be a valuable platform for engaging adolescents with interventions to prevent key chronic disease risk behaviors.

OBJECTIVE

The aim of this paper is to describe the development, usability, and acceptability of the Health4Life app, a self-monitoring smartphone app for adolescents that concurrently targets the Big 6 lifestyle behaviors.

METHODS

The development of the Health4Life app was an iterative process conducted in collaboration with adolescents and experts. The development process consisted of three stages: scoping the literature; end user consultations, which included a web-based survey (N=815; mean age 13.89, SD 0.89 years) and a focus group (N=12) among adolescents; and app development and beta testing. Following this development work, 232 adolescents were asked to rate the usability and acceptability of the app.

RESULTS

The process resulted in a self-monitoring smartphone app that allows adolescent users to track and set goals for the Big 6 health behaviors, using in-app rewards and notifications to enhance engagement. The overall adolescent feedback was positive in terms of user-friendly design, content, relevance, and helpfulness. Commonly identified areas for improvement were to increase interactive features and display recorded health behaviors differently to improve interpretability.

CONCLUSIONS

The Health4Life app is a co-designed, self-monitoring smartphone app for adolescents that concurrently targets the Big 6 lifestyle behaviors. Adolescents rated the app as highly acceptable and usable. The app has the potential to efficiently and effectively modify important risk factors for chronic disease among young people and is currently being evaluated in a world-first trial of 6640 secondary school students in 71 schools across Australia.

Promoting Graduate Student Mental Health During COVID-19: Acceptability, Feasibility, and Perceived Utility of an Online Single-Session Intervention

The COVID-19 outbreak has simultaneously increased the need for mental health services and decreased their availability. Brief online self-help interventions that can be completed in a single session could be especially helpful in improving access to care during the crisis. However, little is known about the uptake, acceptability, and perceived utility of these interventions outside of clinical trials in which participants are compensated. Here, we describe the development, deployment, acceptability ratings, and pre-post effects of a single-session intervention, the Common Elements Toolbox (COMET), adapted for the COVID-19 crisis to support graduate and professional students. Participants (n = 263), who were not compensated, were randomly assigned to two of three modules: behavioral activation, cognitive restructuring, and gratitude. Over 1 week, 263 individuals began and 189 individuals (72%) completed the intervention. Participants reported that the intervention modules were acceptable (93% endorsing), helpful (88%), engaging (86%), applicable to their lives (87%), and could help them manage COVID-related challenges (88%). Participants reported pre- to post-program improvements in secondary control (i.e., the belief that one can control their reactions to objective events; d av = 0.36, d z = 0.50, p < 0.001) and in the perceived negative impact of the COVID-19 crisis on their quality of life (d av = 0.22, d z = 0.25, p < 0.001). On average, differences in their perceived ability to handle lifestyle changes resulting from the pandemic were positive, but small and at the level of a non-significant trend (d av = 0.13, d z = 0.14, p = 0.066). Our results highlight the acceptability and utility of an online intervention for supporting individuals through the COVID-19 crisis.

Postsecondary Student Engagement With a Mental Health App and Online Platform (Thought Spot): Qualitative Study of User Experience

BACKGROUND

There is growing interest in using mobile apps and online tools to support postsecondary student mental health, but most of these solutions have suboptimal user engagement in real-world settings. Poor engagement can limit long-term effectiveness and usefulness of these tools. Previous literature has proposed several theories that link factors such as low usability and poor user-centered design to app disengagement. However, few studies provide direct evidence showing what factors contribute to suboptimal user engagement in the context of mobile mental health apps for postsecondary students.

OBJECTIVE

This study focuses on understanding postsecondary students' attitudes and behaviors when using Thought Spot, a co-designed mental health app and online platform, to understand factors related to engagement and user experience.

METHODS

Students who were given access to Thought Spot for 6 months during a randomized trial of the intervention were invited to participate in one-on-one semistructured interviews. The interviews explored participants' overall experiences and perceptions of the app, along with factors that affected their usage of various features. All interviews were recorded, and template analysis was used to analyze transcripts.

RESULTS

User satisfaction was mixed among users of Thought Spot. The degree of engagement with the app appeared to be affected by factors that can be grouped into 5 themes: (1) Students valued detailed, inclusive, and relevant content; (2) Technical glitches and a lack of integration with other apps affected the overall user experience and satisfaction with the app; (3) Using the app to support peers or family can increase engagement; (4) Crowdsourced information from peers about mental health resources drove user engagement, but was difficult to obtain; and (5) Users often turned to the app when they had an immediate need for mental health information, rather than using it to track mental health information over time.

CONCLUSIONS

Content, user experience, user-centeredness, and peer support are important determinants of user engagement with mobile mental health apps among postsecondary students. In this study, participants disengaged when the app did not meet their expectations on these determinants. Future studies on user engagement should further explore the effectiveness of different features and the relative importance of various criteria for high-quality apps. Further focus on these issues may inform the creation of interventions that increase student engagement and align with their mental health needs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03412461; https://clinicaltrials.gov/ct2/show/NCT03412461.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/resprot.6446.

Scoping review: Development and assessment of evaluation frameworks of mobile health apps for recommendations to consumers

Objective

The study sought to review the different assessment items that have been used within existing health app evaluation frameworks aimed at individual, clinician, or organizational users, and to analyze the scoring and evaluation methods used in these frameworks.

Materials and Methods

We searched multiple bibliographic databases and conducted backward searches of reference lists, using search terms that were synonyms of “health apps,” “evaluation,” and “frameworks.” The review covered publications from 2011 to April 2020. Studies on health app evaluation frameworks and studies that elaborated on the scaling and scoring mechanisms applied in such frameworks were included.

Results

Ten common domains were identified across general health app evaluation frameworks. A list of 430 assessment criteria was compiled across 97 identified studies. The most frequently used scaling mechanism was a 5-point Likert scale. Most studies have adopted summary statistics to generate the total scoring of each app, and the most popular approach taken was the calculation of mean or average scores. Other frameworks did not use any scaling or scoring mechanism and adopted criteria-based, pictorial, or descriptive approaches, or “threshold” filter.

Discussion

There is wide variance in the approaches to evaluating health apps within published frameworks, and this variance leads to ongoing uncertainty in how to evaluate health apps.

Conclusions

A new evaluation framework is needed that can integrate the full range of evaluative criteria within one structure, and provide summative guidance on health app rating, to support individual app users, clinicians, and health organizations in choosing or recommending the best health app.

Assessing the usability and user engagement of Thought Spot - A digital mental health help-seeking solution for transition-aged youth

OBJECTIVE

To evaluate the perceived usability of and user engagement with a digital platform (Thought Spot) designed to enhance mental health and wellness help-seeking among transition-aged youth (TAY; 17-29-years old).

MATERIALS AND METHODS

Survey responses and usage patterns were collected as part of a randomized controlled trial evaluating the efficacy of Thought Spot. Participants given Thought Spot completed an adapted Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire to measure perceived usability of the platform. User engagement patterns on Thought Spot were examined using analytics data collected throughout the study (March 2018-June 2019).

RESULTS

A total of 131 transition-aged participants completed the USE questionnaire and logged on to Thought Spot at least once. Ease of learning scored higher than ease of use, usefulness and satisfaction. Participants identified numerous strengths and challenges related to usability, visual appeal, functionality and usefulness of the content. In terms of user engagement, most participants stopped using the platform after 3 weeks. Participants searched and were interested in a variety of resources, including mental health, counselling and social services.

DISCUSSION

Participants reported mixed experiences while using Thought Spot and exhibited low levels of long-term user engagement. User satisfaction, the willingness to recommend Thought Spot to others, and the willingness for future use appeared to be influenced by content relevance, ease of learning, available features, and other contextual factors. Analysis of the types of resources viewed and searches conducted by TAY end-users provided insight into their behaviour and needs.

CONCLUSION

Users had mixed perceptions about the usability of Thought Spot, which may have contributed to the high attrition rate. User satisfaction and engagement appears to be influenced by content relevance, ease of learning, and the types of features available. Further investigation to understand the contextual factors that affect TAYs' adoption and engagement with digital mental health tools is required.

Designing an mHealth Intervention for People With Visible Differences Based on Acceptance and Commitment Therapy: Participatory Study Gaining Stakeholders' Input

Background

Given their growing popularity, mobile health (mHealth) apps may offer a viable method of delivering psychological interventions for people with an atypical appearance (ie, visible difference) who struggle with appearance-related distress. Acceptance and Commitment Therapy (ACT), a third-wave cognitive behavioral approach, has been used effectively in mHealth and is being increasingly applied clinically to common psychosocial difficulties associated with visible differences. We planned to design an ACT-based mHealth intervention (ACT It Out) for this population.

Objective

The aim of this study is to gain key stakeholder input from user representatives and psychological clinicians to optimize the intervention’s design for future development and uptake. To do so, we explored considerations relating to mHealth as a delivery platform for adults with visible differences and elicited stakeholders’ design preferences and ideas based on initial author-created content.

Methods

Within a participatory design framework, we used a mix of qualitative methods, including usability sessions and a focus group in a face-to-face workshop, and interviews and textual feedback collected remotely, all analyzed using template analysis. A total of 6 user representatives and 8 clinicians were recruited for this study.

Results

Our findings suggest that there are likely to be strengths and challenges of mHealth as an intervention platform for the study population, with key concerns being user safeguarding and program adherence. Participants expressed design preferences toward relatable human content, interactive and actionable features, flexibility of use, accessibility, and engaging content.

Conclusions

The findings offer valuable design directions for ACT It Out and related interventions, emphasizing the need to carefully guide users through the intervention while acknowledging the limited time and space that mHealth affords.

Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Background

Digital mental health interventions (DMHIs), which deliver mental health support via technologies such as mobile apps, can increase access to mental health support, and many studies have demonstrated their effectiveness in improving symptoms. However, user engagement varies, with regard to a user’s uptake and sustained interactions with these interventions.

Objective

This systematic review aims to identify common barriers and facilitators that influence user engagement with DMHIs.

Methods

A systematic search was conducted in the SCOPUS, PubMed, PsycINFO, Web of Science, and Cochrane Library databases. Empirical studies that report qualitative and/or quantitative data were included.

Results

A total of 208 articles met the inclusion criteria. The included articles used a variety of methodologies, including interviews, surveys, focus groups, workshops, field studies, and analysis of user reviews. Factors extracted for coding were related to the end user, the program or content offered by the intervention, and the technology and implementation environment. Common barriers included severe mental health issues that hampered engagement, technical issues, and a lack of personalization. Common facilitators were social connectedness facilitated by the intervention, increased insight into health, and a feeling of being in control of one’s own health.

Conclusions

Although previous research suggests that DMHIs can be useful in supporting mental health, contextual factors are important determinants of whether users actually engage with these interventions. The factors identified in this review can provide guidance when evaluating DMHIs to help explain and understand user engagement and can inform the design and development of new digital interventions.

A Therapeutic Relational Agent for Reducing Problematic Substance Use (Woebot): Development and Usability Study

Background

Misuse of substances is common, can be serious and costly to society, and often goes untreated due to barriers to accessing care. Woebot is a mental health digital solution informed by cognitive behavioral therapy and built upon an artificial intelligence–driven platform to deliver tailored content to users. In a previous 2-week randomized controlled trial, Woebot alleviated depressive symptoms.

Objective

This study aims to adapt Woebot for the treatment of substance use disorders (W-SUDs) and examine its feasibility, acceptability, and preliminary efficacy.

Methods

American adults (aged 18-65 years) who screened positive for substance misuse without major health contraindications were recruited from online sources and flyers and enrolled between March 27 and May 6, 2020. In a single-group pre/postdesign, all participants received W-SUDs for 8 weeks. W-SUDs provided mood, craving, and pain tracking and modules (psychoeducational lessons and psychotherapeutic tools) using elements of dialectical behavior therapy and motivational interviewing. Paired samples t tests and McNemar nonparametric tests were used to examine within-subject changes from pre- to posttreatment on measures of substance use, confidence, cravings, mood, and pain.

Results

The sample (N=101) had a mean age of 36.8 years (SD 10.0), and 75.2% (76/101) of the participants were female, 78.2% (79/101) were non-Hispanic White, and 72.3% (73/101) were employed. Participants’ W-SUDs use averaged 15.7 (SD 14.2) days, 12.1 (SD 8.3) modules, and 600.7 (SD 556.5) sent messages. About 94% (562/598) of all completed psychoeducational lessons were rated positively. From treatment start to end, in-app craving ratings were reduced by half (87/101, 86.1% reporting cravings in the app; odds ratio 0.48, 95% CI 0.32-0.73). Posttreatment assessment completion was 50.5% (51/101), with better retention among those who initially screened higher on substance misuse. From pre- to posttreatment, confidence to resist urges to use substances significantly increased (mean score change +16.9, SD 21.4; P<.001), whereas past month substance use occasions (mean change −9.3, SD 14.1; P<.001) and scores on the Alcohol Use Disorders Identification Test-Concise (mean change −1.3, SD 2.6; P<.001), 10-item Drug Abuse Screening Test (mean change −1.2, SD 2.0; P<.001), Patient Health Questionnaire-8 item (mean change 2.1, SD 5.2; P=.005), Generalized Anxiety Disorder-7 (mean change −2.3, SD 4.7; P=.001), and cravings scale (68.6% vs 47.1% moderate to extreme; P=.01) significantly decreased. Most participants would recommend W-SUDs to a friend (39/51, 76%) and reported receiving the service they desired (41/51, 80%). Fewer felt W-SUDs met most or all of their needs (22/51, 43%).

Conclusions

W-SUDs was feasible to deliver, engaging, and acceptable and was associated with significant improvements in substance use, confidence, cravings, depression, and anxiety. Study attrition was high. Future research will evaluate W-SUDs in a randomized controlled trial with a more diverse sample and with the use of greater study retention strategies.

Trial Registration

ClinicalTrials.gov NCT04096001; http://clinicaltrials.gov/ct2/show/NCT04096001.

"Smartphone Apps Are Cool, But Do They Help Me?": A Qualitative Interview Study of Adolescents' Perspectives on Using Smartphone Interventions to Manage Nonsuicidal Self-Injury

Nonsuicidal self-injury (NSSI) is a major mental health problem associated with negative psychosocial outcomes and it most often starts in early adolescence. Despite this, adolescents are rarely involved in informing the development of interventions designed to address their mental health problems. This study aimed to (1) assess adolescents' needs and preferences about future interventions that are delivered through smartphones and (2) develop a framework with implications for designing engaging digital mental health interventions. Fifteen adolescent girls, aged 12-18 years, who met diagnostic criteria for a current NSSI disorder and were in contact with mental health services, participated in semi-structured interviews. Following a reflexive thematic analysis approach, this study identified two main themes: (1) Experiences of NSSI (depicts the needs of young people related to their everyday experiences of managing NSSI) and (2) App in Context (portrays preferences of young people about smartphone interventions and reflects adolescents' views on how technology itself can improve or hinder engaging with these interventions). Adolescent patients expressed interest in using smartphone mental health interventions if they recognize them as helpful, relevant for their life situation and easy to use. The developed framework suggests that digital mental health interventions are embedded in three contexts (i.e., person using the intervention, mental health condition, and technology-related factors) which together need to inform the development of engaging digital resources. To achieve this, the cooperation among people with lived experience, mental health experts, and human computer interaction professionals is vital.

Mobile Apps for Foot Measurement in Pedorthic Practice: Scoping Review

BACKGROUND

As the use of smartphones increases globally across various fields of research and technology, significant contributions to the sectors related to health, specifically foot health, can be observed. Numerous smartphone apps are now being used for providing accurate information about various foot-related properties. Corresponding to this abundance of foot scanning and measuring apps available in app stores, there is a need for evaluating these apps, as limited information regarding their evidence-based quality is available.

OBJECTIVE

The aim of this review was to assess the measurement techniques and essential software quality characteristics of mobile foot measurement apps, and to determine their potential as commercial tools used by foot care health professionals, to assist in measuring feet for custom shoes, and for individuals to enhance their awareness of foot health and hygiene to ultimately prevent foot-related problems.

METHODS

An electronic search across Android and iOS app stores was performed between July and August 2020 to identify apps related to foot measurement and general foot health. The selected apps were rated by three independent raters, and all discrepancies were resolved by discussion among raters and other investigators. Based on previous work on app rating tools, a modified rating scale tool was devised to rate the selected apps. The internal consistency of the rating tool was tested with a group of three people who rated the selected apps over 2-3 weeks. This scale was then used to produce evaluation scores for the selected foot measurement apps and to assess the interrater reliability.

RESULTS

Evaluation inferences showed that all apps failed to meet even half of the measurement-specific criteria required for the proper manufacturing of custom-made footwear. Only 23% (6/26) of the apps reportedly used external scanners or advanced algorithms to reconstruct 3D models of a user's foot that could possibly be used for ordering custom-made footwear (shoes, insoles/orthoses), and medical casts to fit irregular foot sizes and shapes. The apps had varying levels of performance and usability, although the overall measurement functionality was subpar with a mean of 1.93 out of 5. Apps linked to online shops and stores (shoe recommendation) were assessed to be more usable than other apps but lacked some features (eg, custom shoe sizes and shapes). Overall, the current apps available for foot measurement do not follow any specific guidelines for measurement purposes.

CONCLUSIONS

Most commercial apps currently available in app stores are not viable for use as tools in assisting foot care health professionals or individuals to measure their feet for custom-made footwear. Current apps lack software quality characteristics and need significant improvements to facilitate proper measurement, enhance awareness of foot health, and induce motivation to prevent and cure foot-related problems. Guidelines similar to the essential criteria items introduced in this study need to be developed for future apps aimed at foot measurement for custom-made or individually fitted footwear and to create awareness of foot health.

Step-by-step: Feasibility randomised controlled trial of a mobile-based intervention for depression among populations affected by adversity in Lebanon

BACKGROUND

E-mental health interventions may help to bridge the mental health treatment gap. Evidence on their effectiveness is compelling in high-income countries. Not enough evidence has been generated on their use with communities affected by adversity in low- and middle-income countries. The World Health Organization (WHO), the National Mental Health Programme (NMMP) at Ministry of Public Health (MoPH) in Lebanon and other partners have adapted a WHO intervention called Step-by-Step for use with Lebanese and displaced people living in Lebanon. Step-by-Step is a minimally guided, internet-based intervention for adults with depression. In this study, a feasibility randomised controlled trial (RCT) and a qualitative process evaluation were conducted to explore the feasibility and the acceptability of the research methods, and the intervention, in preparation for two fully powered trials to assess the effectiveness and cost-effectiveness of Step-by-Step in Lebanon.

METHOD

Participants were recruited through social media. Inclusion criteria were: being able to understand and speak Arabic or English; access to an internet connected device; aged over 18; living in Lebanon; scores above cut-off on the Patient Health Questionnaire and the WHO Disability Assessment Schedule 2.0. Participants were randomly assigned to the intervention or enhanced care as usual. They completed post-assessments eight weeks after baseline, and follow-up assessments another three months later. Primary outcomes were depression and level of functioning, secondary outcomes were anxiety, post-traumatic stress, and well-being. Qualitative interviews were conducted to evaluate the feasibility and acceptability of the research procedures and the intervention.

RESULTS

A total of N = 138 participants, including 33 Syrians, were recruited and randomised into two equal groups. The dropout rate was higher in the control group (73% post- and 82% follow-up assessment) than in the intervention group (63% post- and 72% follow-up assessment). The intervention was perceived as relevant, acceptable and beneficial to those who completed it. Suggestions were made to further adapt the content and to make the intervention more engaging. Statistical analyses were conducted despite the small sample size. Complete cases analysis showed a statistically significant symptom reduction in depression, anxiety, disability, and post-traumatic stress, and statistically significant improvement in well-being and functioning. Intention-to-treat analysis revealed non-significant effects.

CONCLUSION

The research design, methods and procedures are feasible and acceptable in the context of Lebanon and can be applied in the RCTs. Preliminary findings suggest that Step-by-Step may be effective in reducing symptoms of depression and anxiety and improving functioning and well-being.

Characterization of polycystic ovary syndrome among Flo app users around the world

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex and multi-faceted endocrine disorder that affects 5-20% of women. Literature is limited regarding potentially differing PCOS phenotypes among women around the world.

OBJECTIVE

To use Flo app technology to understand the multifaceted characteristics of PCOS across several countries and identify contributing risk factors to the development of this condition.

STUDY DESIGN

Flo is a widely used female health and wellbeing app with period tracking functionality that provides a globally representative and medically unbiased perspective on PCOS symptomatology. A chatbot dialog on PCOS was subsequently administered on the Flo application (app) to users from 142 countries (with at least 100 respondents) who have the app running in English during September-October 2019.

RESULTS

For analyses, we selected the five countries with the greatest number of respondents: US (n = 243,238), UK (n = 68,325), India (n = 40,092), Philippines (n = 35,131), and Australia (n = 29,926). Bloating was the most frequently reported symptom among PCOS-positive women and appeared to be the main predictor of PCOS in our model (odds ratio 3·76 [95% CI 3·60-3·94]; p < 0·0001). Additional top predictors of PCOS are high blood cholesterol and glucose levels. As BMI increased, the percentage of women who reported a physician-confirmed PCOS diagnosis also increased. However, women in India did not follow this trend.

CONCLUSION

Our findings are based on the largest known PCOS dataset and indicate that symptoms are more complex than previously understood. The most frequently reported symptoms (bloating, facial hirsutism, irregular cycles, hyperpigmentation, and baldness) are broader than those included in the Rotterdam criteria. Future work should reevaluate and refine the criteria utilized in PCOS diagnosis.

Does cognitive impairment in bipolar disorder impact on a SIMPLe app use?

BACKGROUND

Smartphone apps are becoming increasingly used by service users in mental health care and research for diverse aims. However, it is well-known the high prevalence of cognitive impairment in some people suffering from severe mental illnesses such as bipolar disorder (BD), which impacts on their psychosocial functioning and quality of life. In this context, the main aim of this paper is to investigate through exploratory analyses the role of specific cognitive deficits in the retention, engagement, and usability of a psychoeducational smartphone app in a group of patients with BD.

METHODS

51 remitted BD patients were asked to use the app for 3 months. Baseline and 3-months follow-up clinical and usability assessments were conducted. Twenty-seven independent results from a comprehensive neurocognitive test of the same participants were retrieved separately of the 2 years before or after the use of the app. Post-hoc exploratory analyses were carried out using Spearman correlations to identify significant cognitive deficits domains influencing the usability and retention with the app.

RESULTS

There were no statistically significant cognitive variables associated with the use, reported usability or retention with the app. Some variables associated with executive functions, verbal and visual memory correlated significantly with previous use of smartphones.

LIMITATIONS

Post-hoc analysis with a limited sample size.

CONCLUSION

These preliminary results suggests that patients with BD and mild cognitive deficits do not present any limitation in using mental health apps. In our case, the adoption of a user-centred design in the development process of the app could have mitigated the participants' difficulties when using the app.

How technology can enhance treatment: A scoping review of clinical interventions for anxiety and obsessive-compulsive spectrum disorders

OBJECTIVES

Researchers are increasingly investigating how technology could be used to improve the efficacy of treatment for anxiety and obsessive-compulsive (OC) spectrum disorders. A broad range of technologies, disorders and therapeutic processes have been examined in the literature. This review summarizes the evidence for using technology in clinical interventions for anxiety and OC-spectrum disorders and highlights research gaps that should be addressed to improve the evidence base.

METHODS

A scoping review was conducted based on systematic searches of three databases. Broadly, the criteria included interventions that had integrated technology into clinical contexts to enhance treatment for anxiety and OC-spectrum disorders. All records were double-screened by two reviewers, and data were extracted on the characteristics of interventions, symptom outcomes, and implementation factors.

RESULTS

Searches returned 2,475 studies, of which 117 were eligible for inclusion in this review. Although almost all studies reported pre-post-symptom reductions, only one quarter of the controlled studies demonstrated additive effect of technology-based interventions in between-group analyses. We noted a trend in underreporting implementation factors.

CONCLUSIONS

Technology-based interventions can improve the efficacy of treatment for anxiety and OC-spectrum disorders, but there are challenges to achieving this goal. Based on a review of the included studies, we provide four specific recommendations to improve the quality and likelihood of success of future research projects.

PRACTITIONER POINTS

Technology-based adjuvants are unlikely to improve the efficacy of treatment for anxiety or OC-spectrum disorders based on their novelty or convenience alone. A subset of studies gives hope that specific innovations can improve treatment when targeting a therapeutic process that has been problematic. Clinicians seeking to improve the efficacy of their treatment should first define client-specific therapeutic factors (e.g., homework compliance) that could be leveraged, then apply a specific innovation to address this factor.

Smartphone apps for depression and anxiety: a systematic review and meta-analysis of techniques to increase engagement

Meta-analyses have shown that digital mental health apps can be efficacious in reducing symptoms of depression and anxiety. However, real-world usage of apps is typically not sustained over time, and no studies systematically examine which features increase sustained engagement with apps or the relationship between engagement features and clinical efficacy. We conducted a systematic search of the literature to identify empirical studies that (1) investigate standalone apps for depression and/or anxiety in symptomatic participants and (2) report at least one measure of engagement. Features intended to increase engagement were categorized using the persuasive system design (PSD) framework and principles of behavioral economics. Twenty-five studies with 4159 participants were included in the analysis. PSD features were commonly used, whereas behavioral economics techniques were not. Smartphone apps were efficacious in treating symptoms of anxiety and depression in randomized controlled trials, with overall small-to-medium effects (g = 0.2888, SE = 0.0999, z(15) = 2.89, p = 0.0119, Q(df = 14) = 41.93, p < 0.0001, I2 = 66.6%), and apps that employed a greater number of engagement features as compared to the control condition had larger effect sizes (β = 0.0450, SE = 0.0164, t(15) = 2.7344, p = 0.0161). We observed an unexpected negative association between PSD features and engagement, as measured by completion rate (β = -0.0293, SE = 0.0121, t(17) = 02.4142, p = 0.0281). Overall, PSD features show promise for augmenting app efficacy, though engagement, as reflected in study completion, may not be the primary factor driving this association. The results suggest that expanding the use of PSD features in mental health apps may increase clinical benefits and that other techniques, such as those informed by behavioral economics, are employed infrequently.

Acceptability, Validity, and Engagement With a Mobile App for Frequent, Continuous Multiyear Assessment of Youth Health Behaviors (mNCANDA): Mixed Methods Study

BACKGROUND

Longitudinal studies of many health behaviors often rely on infrequent self-report assessments. The measurement of psychoactive substance use among youth is expected to improve with more frequent mobile assessments, which can reduce recall bias. Researchers have used mobile devices for longitudinal research, but studies that last years and assess youth continuously at a fine-grained, temporal level (eg, weekly) are rare. A tailored mobile app (mNCANDA [mobile National Consortium on Alcohol and Neurodevelopment in Adolescence]) and a brief assessment protocol were designed specifically to provide a feasible platform to elicit responses to health behavior assessments in longitudinal studies, including NCANDA (National Consortium on Alcohol and Neurodevelopment in Adolescence).

OBJECTIVE

This study aimed to determine whether an acceptable mobile app system could provide repeatable and valid assessment of youth's health behaviors in different developmental stages over extended follow-up.

METHODS

Participants were recruited (n=534; aged 17-28 years) from a larger longitudinal study of neurodevelopment. Participants used mNCANDA to register reports of their behaviors for up to 18 months. Response rates as a function of time measured using mNCANDA and participant age were modeled using generalized estimating equations to evaluate response rate stability and age effects. Substance use reports captured using mNCANDA were compared with responses from standardized interviews to assess concurrent validity. Reactivity was assessed by evaluating patterns of change in substance use after participants initiated weekly reports via mNCANDA. Quantitative feedback about the app was obtained from the participants. Qualitative interviews were conducted with a subset of participants who used the app for at least one month to obtain feedback on user experience, user-derived explanations of some quantitative results, and suggestions for system improvements.

RESULTS

The mNCANDA protocol adherence was high (mean response rate 82%, SD 27%) and stable over time across all age groups. The median time to complete each assessment was 51 s (mean response time 1.14, SD 1.03 min). Comparisons between mNCANDA and interview self-reports on recent (previous 30 days) alcohol and cannabis use days demonstrate close agreement (eg, within 1 day of reported use) for most observations. Models used to identify reactivity failed to detect changes in substance use patterns subsequent to enrolling in mNCANDA app assessments (P>.39). Most participants (64/76, 84%) across the age range reported finding the mNCANDA system acceptable. Participants provided recommendations for improving the system (eg, tailoring signaling times).

CONCLUSIONS

mNCANDA provides a feasible, multi-year, continuous, fine-grained (eg, weekly) assessment of health behaviors designed to minimize respondent burden and provides acceptable regimes for long-term self-reporting of health behaviors. Fine-grained characterization of variability in behaviors over relatively long periods (eg, up to 18 months) may, through the use of mNCANDA, improve our understanding of the relationship between substance use exposure and neurocognitive development.

Patient and physician perspectives of a smartphone application for depression: a qualitative study

BACKGROUND

Despite an increasing number of smartphone apps, such therapeutic tools have not yet consistently demonstrated their efficacy and many suffer from low retention rates. To ensure the development of efficient apps associated with high adherence, we aimed to identify, through a user-centred design approach, patient and physician expectations of a hypothetical app dedicated to depression.

METHODS

We conducted semi-structured interviews with physicians (psychiatrists and general practitioners) and patients who had experienced a major depressive episode during the last 12 months using the focus group method. The interviews were audio recorded, transcribed and analysed using qualitative content analysis to define codes, categories and emergent themes.

RESULTS

A total of 26 physicians and 24 patients were included in the study. The focus groups showed balanced sex and age distributions. Most participants owned a smartphone (83.3% of patients, 96.1% of physicians) and were app users (79.2% of patients and 96.1% of physicians). The qualitative content analysis revealed 3 main themes: content, operating characteristics and barriers to the use of the app. Expected content included the data collected by the app, aiming to provide information about the patient, data provided by the app, gathering psychoeducation elements, therapeutic tools and functionalities to help with the management of daily life and features expected for this tool. The "operating characteristics" theme gathered aims considered for the app, its potential target users, considered modalities of use and considerations around its accessibility and security of use. Finally, barriers to the use of the app included concerns about potential app users, its accessibility, safety, side-effects, utility and functioning. All themes and categories were the same for patients and physicians.

CONCLUSIONS

Physician and patient expectations of a hypothetical smartphone app dedicated to depression are high and confirmed the important role it could play in depression care. The key points expected by the users for such a tool are an easy and intuitive use and a personalised content. They are also waiting for an app that gives information about depression, offers a self-monitoring functionality and helps them in case of emergency.

Psychiatric Advance Directives and Artificial Intelligence: A Conceptual Framework for Theoretical and Ethical Principles

The patient's decision-making abilities are often altered in psychiatric disorders. The legal framework of psychiatric advance directives (PADs) has been made to provide care to patients in these situations while respecting their free and informed consent. The implementation of artificial intelligence (AI) within Clinical Decision Support Systems (CDSS) may result in improvements for complex decisions that are often made in situations covered by PADs. Still, it raises theoretical and ethical issues this paper aims to address. First, it goes through every level of possible intervention of AI in the PAD drafting process, beginning with what data sources it could access and if its data processing competencies should be limited, then treating of the opportune moments it should be used and its place in the contractual relationship between each party (patient, caregivers, and trusted person). Second, it focuses on ethical principles and how these principles, whether they are medical principles (autonomy, beneficence, non-maleficence, justice) applied to AI or AI principles (loyalty and vigilance) applied to medicine, should be taken into account in the future of the PAD drafting process. Some general guidelines are proposed in conclusion: AI must remain a decision support system as a partner of each party of the PAD contract; patients should be able to choose a personalized type of AI intervention or no AI intervention at all; they should stay informed, i.e., understand the functioning and relevance of AI thanks to educational programs; finally, a committee should be created for ensuring the principle of vigilance by auditing these new tools in terms of successes, failures, security, and relevance.

Participant Engagement in a Transmedia Storytelling Web-Based App Intervention for Mental Health of Latina Women: Qualitative Analysis

BACKGROUND

Stigma, fear, and lack of knowledge regarding treatment options or where to get help create delays for Latina women in accessing needed mental health help. Story-based media interventions hold appeal for Latina women. Thus, we drew upon the Social Cognitive Theory by Bandura to create an evidence-based, transmedia storytelling web-based app for mental health called Catalina: Confronting My Emotions to connect Latina women to a curated set of mental health resources. Understanding how Latina women perceive various aspects of the web-based app will help design future expansions.

OBJECTIVE

A previously published analysis led to the development of a category on how participants related to the lead character (Catalina) in the story line of the web-based app as a real person. However, the purpose of this analysis was to gain an understanding of participants' experiences with the extension of the dramatic story line of the web-based app beyond Catalina to a Latina nurse-therapist character named Veronica, who was featured prominently in the app's interactive content and bonus videos.

METHODS

Qualitative analyses were conducted with interview data from a community-based sample of 28 English-speaking Latina women aged between 21 and 50 years who scored above the threshold for anxiety (Generalized Anxiety Disorder-7) and/or depression (Patient Health Questionnaire-9) but were not suicidal at screening. Data were collected 72 hours after participants engaged with our transmedia storytelling web-based app for mental health. Grounded theory methodology guided the analysis and interpretation of data that had been collected telephonically, recorded, and transcribed with identifiers removed. Analyses included initial and focused coding using process codes (gerund form of verbs in codes focused on action), informed by symbolic interactionism, and the development of categories with properties through constant comparison, memo writing, and the use of charts and diagrams.

RESULTS

Our participants experienced a multiphase process that was most heavily related to Veronica, the Latina nurse-therapist character in our web-based app, who led them through a process to a place of action. We conceptualized this process as moving from passive viewer to active participant of a transmedia storytelling web-based app intervention. Overall, 3 new conceptual categories provided insight into women's experiences, including encountering a trustworthy nurse-therapist character, taking in messages that dispel old beliefs, and preparing when and how to take action. Each category has nuanced properties that reflect participants' experiences.

CONCLUSIONS

Active engagement with our web-based app led our sample to successfully transition from the viewpoint of the observer to the viewpoint of the experiencer, moving from a passive position of watching to active engagement that involved imagining, thinking, reflecting, and acting. Careful development of dramatic material for health-related web-based apps using transmedia story extension and bonus videos needs to be based on input from the target group from the start of development through evaluation and testing.

Screening accuracy of a 14-day smartphone ambulatory assessment of depression symptoms and mood dynamics in a general population sample: Comparison with the PHQ-9 depression screening

Introduction

Major depression affects over 300 million people worldwide, but cases are often detected late or remain undetected. This increases the risk of symptom deterioration and chronification. Consequently, there is a high demand for low threshold but clinically sound approaches to depression detection. Recent studies show a great willingness among users of mobile health apps to assess daily depression symptoms. In this pilot study, we present a provisional validation of the depression screening app Moodpath. The app offers a 14-day ambulatory assessment (AA) of depression symptoms based on the ICD-10 criteria as well as ecologically momentary mood ratings that allow the study of short-term mood dynamics.

Materials and methods

N = 113 Moodpath users were selected through consecutive sampling and filled out the Patient Health Questionnaire (PHQ-9) after completing 14 days of AA with 3 question blocks (morning, midday, and evening) per day. The psychometric properties (sensitivity, specificity, accuracy) of the ambulatory Moodpath screening were assessed based on the retrospective PHQ-9 screening result. In addition, several indicators of mood dynamics (e.g. average, inertia, instability), were calculated and investigated for their individual and incremental predictive value using regression models.

Results

We found a strong linear relationship between the PHQ-9 score and the AA Moodpath depression score (r = .76, p < .001). The app-based screening demonstrated a high sensitivity (.879) and acceptable specificity (.745). Different indicators of mood dynamics covered substantial amounts of PHQ-9 variance, depending on the number of days with mood data that were included in the analyses.

Discussion

AA and PHQ-9 shared a large proportion of variance but may not measure exactly the same construct. This may be due to the differences in the underlying diagnostic systems or due to differences in momentary and retrospective assessments. Further validation through structured clinical interviews is indicated. The results suggest that ambulatory assessed mood indicators are a promising addition to multimodal depression screening tools. Improving app-based AA screenings requires adapted screening algorithms and corresponding methods for the analysis of dynamic processes over time.

Considerations in Designing Digital Peer Support for Mental Health: Interview Study Among Users of a Digital Support System (Buddy Project)

BACKGROUND

Peer support is an approach to cope with mental illness, and technology provides a way to facilitate peer support. However, there are barriers to seeking support in offline and technology-mediated contexts.

OBJECTIVE

This study aims to uncover potential ways to design digital mental health peer support systems and to outline a set of principles for future designers to consider as they embark on designing these systems. By learning how existing systems are used by people in daily life and by centering their experiences, we can better understand how to design mental health peer support technologies that foreground people's needs. One existing digital peer support system is Buddy Project, the case study in this paper.

METHODS

This paper reports on an interview study with Buddy Project users (N=13). Data were analyzed using the constant comparative approach.

RESULTS

Individuals matched through Buddy Project developed supportive friendships with one another, leading them to become each other's peer supporters in their respective journeys. It was not only the mental health peer support that was important to participants but also being able to connect over other parts of their lives and identities. The design of Buddy Project provided a sense of anonymity and separation from pre-existing ties, making it easier for participants to disclose struggles; moreover, the pairs appreciated being able to browse each other's social media pages before connecting. Buddy Project has an explicit mission to prevent suicide and demonstrates this mission across its online platforms, which helps reduce the stigma around mental health within the peer support space. Pairs were matched based on shared interests and identities. This choice aided the pairs in developing meaningful, compatible, and supportive relationships with each other, where they felt seen and understood. However, the pairs were concerned that matching based on a shared mental health diagnosis may lead to sharing unhealthy coping mechanisms or comparing themselves and the severity of their experiences with their peers.

CONCLUSIONS

The results of this study shed light on desirable features of a digital mental health peer support system: matching peers based on interests and identities that they self-identify with; having an explicit mental health-related mission coupled with social media and other web-based presences to signal that discussing mental health is safe within the peer support ecosystem; and not matching peers based on a broad mental health diagnosis. However, if the diagnosis is important, this matching should account for illness severity and educate peers on how to provide support while avoiding suggesting unhelpful coping mechanisms; allowing for some degree of anonymity and control over how peers present themselves to each other; and providing relevant information and tools to potential peers to help them decide if they would like to embark on a relationship with their matched peer before connecting with them.

The emergence of digital mental health in low-income and middle-income countries: A review of recent advances and implications for the treatment and prevention of mental disorders

In low-income and middle-income countries (LMICs), emerging digital mental health interventions should be accompanied by regular and comprehensive assessment of available scientific evidence. This review aims to support efforts to monitor progress in digital mental health research, ensuring new evidence can guide researchers, clinicians, policymakers and program managers positioned to adopt and implement these digitally-enabled treatments. In accordance with PRISMA guidelines, an electronic database search from 2016 to 2020 yielded 37 digital intervention studies for detection, diagnosis, prevention, treatment, and/or management of a broad range of mental disorders in 13 LMICs. This date range was selected to update previous reviews. Most studies involved online interventions and many reported feasibility and acceptability, reflected by participant satisfaction or program adherence. About half the studies (N = 23) reported clinical benefits based on changes in mental health. For depression and mood disorders, some digital interventions showed improvements in depressive symptoms, quality of life, treatment adherence, and recovery. However, sample sizes were small and studies focused primarily on adults. Further limiting generalizability was the lack of consistency in clinical assessment and measurement tools between studies. No studies reported worsening symptoms, negative acceptability or dissatisfaction with digital interventions, suggesting possible publication bias. While digital interventions show promise, it remains difficult to conclude that digital interventions are effective from these studies, as it is prudent to exercise caution before drawing conclusions about clinical effectiveness. This review reflects continued growth in digital mental health research in LMICs and further highlights the need for rigorous evaluation of effectiveness and cost-effectiveness.

Toward dynamic phenotypes and the scalable measurement of human behavior

Precision psychiatry demands the rapid, efficient, and temporally dense collection of large scale and multi-omic data across diverse samples, for better diagnosis and treatment of dynamic clinical phenomena. To achieve this, we need approaches for measuring behavior that are readily scalable, both across participants and over time. Efforts to quantify behavior at scale are impeded by the fact that our methods for measuring human behavior are typically developed and validated for single time-point assessment, in highly controlled settings, and with relatively homogeneous samples. As a result, when taken to scale, these measures often suffer from poor reliability, generalizability, and participant engagement. In this review, we attempt to bridge the gap between gold standard behavioral measurements in the lab or clinic and the large-scale, high frequency assessments needed for precision psychiatry. To do this, we introduce and integrate two frameworks for the translation and validation of behavioral measurements. First, borrowing principles from computer science, we lay out an approach for iterative task development that can optimize behavioral measures based on psychometric, accessibility, and engagement criteria. Second, we advocate for a participatory research framework (e.g., citizen science) that can accelerate task development as well as make large-scale behavioral research more equitable and feasible. Finally, we suggest opportunities enabled by scalable behavioral research to move beyond single time-point assessment and toward dynamic models of behavior that more closely match clinical phenomena.

Use of Asynchronous Virtual Mental Health Resources for COVID-19 Pandemic-Related Stress Among the General Population in Canada: Cross-Sectional Survey Study

BACKGROUND

The COVID-19 pandemic has resulted in profound mental health impacts among the general population worldwide. As many in-person mental health support services have been suspended or transitioned online to facilitate physical distancing, there have been numerous calls for the rapid expansion of asynchronous virtual mental health (AVMH) resources. These AVMH resources have great potential to provide support for people coping with negative mental health impacts associated with the pandemic; however, literature examining use prior to COVID-19 illustrates that the uptake of these resources is consistently low.

OBJECTIVE

The aim of this paper is to examine the use of AVMH resources in Canada during the COVID-19 pandemic among the general population and among a participant subgroup classified as experiencing an adverse mental health impact related to the pandemic.

METHODS

Data from this study were drawn from the first wave of a large multiwave cross-sectional monitoring survey, distributed from May 14 to 29, 2020. Participants (N=3000) were adults living in Canada. Descriptive statistics were used to characterize the sample, and bivariate cross-tabulations were used to examine the relationships between the use of AVMH resources and self-reported indicators of mental health that included a range of emotional and coping-related responses to the pandemic. Univariate and fully adjusted multivariate logistic regression models were used to examine associations between sociodemographic and health-related characteristics and use of AVMH resources in the subgroup of participants who reported experiencing one or more adverse mental health impacts identified in the set of self-reported mental health indicators.

RESULTS

Among the total sample, 2.0% (n=59) of participants reported accessing AVMH resources in the prior 2 weeks to cope with stress related to the COVID-19 pandemic, with the highest rates of use among individuals who reported self-harm (n=5, 10.4%) and those who reported coping "not well" with COVID-19-related stress (n=22, 5.5%). Within the subgroup of 1954 participants (65.1% of the total sample) who reported an adverse mental health impact related to COVID-19, 54 (2.8%) reported use of AVMH resources. Individuals were more likely to have used AVMH resources if they had reported receiving in-person mental health supports, were connecting virtually with a mental health worker or counselor, or belonged to a visible minority group.

CONCLUSIONS

Despite substantial government investment into AVMH resources, uptake is low among both the general population and individuals who may benefit from the use of these resources as a means of coping with the adverse mental health impacts of the COVID-19 pandemic. Further research is needed to improve our understanding of the barriers to use.

Engagement with smartphone-delivered behavioural activation interventions: a study of the MoodMission smartphone application

BACKGROUND

Despite increased research interest in smartphone mental health applications (MHapps), few studies have examined user engagement and its determinants. MoodMission is a MHapp that targets low mood and anxiety via evidence-based techniques including behavioural activation (BA).

AIMS

The present study aimed to investigate (i) whether BA interventions delivered with visual psychoeducation had greater engagement than BA interventions delivered with solely written psychoeducation, (ii) whether BA interventions targeting mastery would have greater engagement than those targeting pleasure, and (iii) the relationship between level of engagement and MHapp benefit.

METHOD

Participants downloaded MoodMission and completed activities and within-app evaluations over a 30-day period. Data from 238 MoodMission users were analysed via multi-level modelling and linear regression.

RESULTS

The average number of app-based activities completed was 5.46 and the average self-reported engagement level was in the low to moderate range. As hypothesized, higher levels of engagement significantly predicted more positive activity appraisal.

CONCLUSIONS

The results suggest that BA technique beliefs are involved in MHapp engagement and future research examining user appraisals of techniques is warranted.

mHealth applications to support caregiver needs and engagement during stroke recovery: A content review

Caregiving in stroke results in severe physical, psychological, and social impacts on the caregiver. Over the past few years, researchers have explored the use of mHealth technologies to support healthcare-related activities due to their ability to provide real-time care at any given place or time. The purpose of this content review is to investigate mHealth apps in supporting stroke caregiving engagement based on three aspects: motivation, value, and satisfaction. We searched app stores and repositories for apps related to stroke caregiving published up to September 2020. Extracted apps were reviewed and filtered using inclusion criteria, and then downloaded onto compatible devices to determine eligibility. Results were compared with evidence-based frameworks to identify the ability of these apps in engaging and supporting the caregiver. Forty-seven apps were included in this review that enabled caregivers to support their needs, such as adjustment to new roles and relationships, involvement in care and caring for oneself using several different functionalities. These functionalities include information resources, risk assessment, remote monitoring, data sharing, reminders and so on. However, no single app was identified that focuses on all aspects of stroke caregiving. We also identified several challenges faced by users through their reviews and the factors associated with value and satisfaction. Our findings can add to the knowledge of existing mHealth technologies and their functionalities to support stroke caregiving needs, and the importance of considering user engagement in the design. They can be used by developers and researchers looking to design better mHealth apps for stroke caregiving.

Engagement With a Behavior Change App for Alcohol Reduction: Data Visualization for Longitudinal Observational Study

Background

Behavior change apps can develop iteratively, where the app evolves into a complex, dynamic, or personalized intervention through cycles of research, development, and implementation. Understanding how existing users engage with an app (eg, frequency, amount, depth, and duration of use) can help guide further incremental improvements. We aim to explore how simple visualizations can provide a good understanding of temporal patterns of engagement, as usage data are often longitudinal and rich.

Objective

This study aims to visualize behavioral engagement with Drink Less, a behavior change app to help reduce hazardous and harmful alcohol consumption in the general adult population of the United Kingdom.

Methods

We explored behavioral engagement among 19,233 existing users of Drink Less. Users were included in the sample if they were from the United Kingdom; were 18 years or older; were interested in reducing their alcohol consumption; had a baseline Alcohol Use Disorders Identification Test score of 8 or above, indicative of excessive drinking; and had downloaded the app between May 17, 2017, and January 22, 2019 (615 days). Measures of when sessions begin, length of sessions, time to disengagement, and patterns of use were visualized with heat maps, timeline plots, k-modes clustering analyses, and Kaplan-Meier plots.

Results

The daily 11 AM notification is strongly associated with a change in engagement in the following hour; reduction in behavioral engagement over time, with 50.00% (9617/19,233) of users disengaging (defined as no use for 7 or more consecutive days) 22 days after download; identification of 3 distinct trajectories of use, namely engagers (4651/19,233, 24.18% of users), slow disengagers (3679/19,233, 19.13% of users), and fast disengagers (10,903/19,233, 56.68% of users); and limited depth of engagement with 85.076% (7,095,348/8,340,005) of screen views occurring within the Self-monitoring and Feedback module. In addition, a peak of both frequency and amount of time spent per session was observed in the evenings.

Conclusions

Visualizations play an important role in understanding engagement with behavior change apps. Here, we discuss how simple visualizations helped identify important patterns of engagement with Drink Less. Our visualizations of behavioral engagement suggest that the daily notification substantially impacts engagement. Furthermore, the visualizations suggest that a fixed notification policy can be effective for maintaining engagement for some users but ineffective for others. We conclude that optimizing the notification policy to target both effectiveness and engagement is a worthwhile investment. Our future goal is to both understand the causal effect of the notification on engagement and further optimize the notification policy within Drink Less by tailoring to contextual circumstances of individuals over time. Such tailoring will be informed from the findings of our micro-randomized trial (MRT), and these visualizations were useful in both gaining a better understanding of engagement and designing the MRT.

Design Features for Improving Mobile Health Intervention User Engagement: Systematic Review and Thematic Analysis

Background

Well-designed mobile health (mHealth) interventions support a positive user experience; however, a high rate of disengagement has been reported as a common concern regarding mHealth interventions. To address this issue, it is necessary to summarize the design features that improve user engagement based on research over the past 10 years, during which time the popularity of mHealth interventions has rapidly increased due to the use of smartphones.

Objective

The aim of this review was to answer the question “Which design features improve user engagement with mHealth interventions?” by summarizing published literature with the purpose of guiding the design of future mHealth interventions.

Methods

This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) checklist. Databases, namely, PubMed, Web of Science, Cochrane Library, Ovid EMBASE, and Ovid PsycINFO, were searched for English and Chinese language papers published from January 2009 to June 2019. Thematic analysis was undertaken to assess the design features in eligible studies. The Mixed Methods Appraisal Tool was used to assess study quality.

Results

A total of 35 articles were included. The investigated mHealth interventions were mainly used in unhealthy lifestyle (n=17) and chronic disease (n=10) prevention programs. Mobile phone apps (n=24) were the most common delivery method. Qualitative (n=22) and mixed methods (n=9) designs were widely represented. We identified the following 7 themes that influenced user engagement: personalization (n=29), reinforcement (n=23), communication (n=20), navigation (n=17), credibility (n=16), message presentation (n=16), and interface aesthetics (n=7). A checklist was developed that contained these 7 design features and 29 corresponding specific implementations derived from the studies.

Conclusions

This systematic review and thematic synthesis identified useful design features that make an mHealth intervention more user friendly. We generated a checklist with evidence-based items to enable developers to use our findings easily. Future evaluations should use more robust quantitative approaches to elucidate the relationships between design features and user engagement.

Visual and Personalized Quality of Life Assessment App for People With Severe Mental Health Problems: Qualitative Evaluation

BACKGROUND

QoL-ME is a digital visual personalized quality of life assessment app for people with severe mental health problems. Research reveals that e-mental health apps frequently suffer from low engagement and fall short of expectations regarding their impact on patients' daily lives. Studies often indicate that e-mental health apps ought to respect the needs and preferences of end users to achieve optimal user engagement.

OBJECTIVE

The aim of this study was to explore the experiences of users regarding the usability and functionality of QoL-ME and whether the app is actionable and beneficial for patients.

METHODS

End users (n=8) of QoL-ME contributed to semistructured interviews. An interview guide was used to direct the interviews. All interviews were audiorecorded and transcribed verbatim. Transcriptions were analyzed and coded thematically.

RESULTS

Analysis revealed 3 main themes: (1) benefit, (2) actionability, and (3) characteristics of the QoL-ME. The first theme reveals that the QoL-ME app was beneficial for the majority of respondents, primarily by prompting them to reflect on their quality of life. The current version is not yet actionable; the actionability of the QoL-ME app may be improved by enabling users to view their scores over time and by supplying practical advice for quality of life improvements. Overall, participants had positive experiences with the usability, design, and content of the app.

CONCLUSIONS

The QoL-ME app can be beneficial to users as it provides them with insight into their quality of life and elicits reflection. Incorporating more functionalities that facilitate self-management, such as advice and strategies for improving areas that are lacking, will likely make the app actionable. Patients positively regarded the usability, design, and contents of the QoL-ME app.

Usage and Acceptability of the iBobbly App: Pilot Trial for Suicide Prevention in Aboriginal and Torres Strait Islander Youth

BACKGROUND

The proliferation of mental health apps purporting to target and improve psychological wellbeing is ever-growing and also concerning: Few apps have been rigorously evaluated, and, indeed, the safety of the vast majority of them has not been determined. Over 10,000 self-help apps exist but most are not used much after being downloaded. Gathering and analyzing usage data and the acceptability of apps are critical to inform consumers, researchers, and app developers.

OBJECTIVE

This paper presents pilot usage and acceptability data from the iBobbly suicide prevention app, an app distributed through a randomized controlled trial.

METHODS

Aboriginal and Torres Strait Islander participants from the Kimberley region of Western Australia completed a survey measuring their technology use in general (n=13), and data on their experiences with and views of the iBobbly app were also collected in semistructured interviews (n=13) and thematically analyzed. Finally, engagement with the app, such as the number of sessions completed and time spent on various acceptance-based therapeutic activities, was analyzed (n=18). Both groups were participants in the iBobbly app pilot randomized controlled trial (n=61) completed in 2015.

RESULTS

Regression analysis indicated that app use improved psychological outcomes, although only minimally, and effects were not significant. However, results of the thematic analysis indicated that the iBobbly app was deemed effective, acceptable, and culturally appropriate by those interviewed.

CONCLUSIONS

There is a scarcity of randomized controlled trials and eHealth interventions in Indigenous communities, while extremely high rates of psychological distress and suicide persist. In this environment, studies that can add evidence from mixed-methods approaches are important. While the regression analysis in this study did not indicate a significant effect of app use on psychological wellbeing, this was predictable considering the small sample size (n=18) and typically brief app use. The results on engagement with the iBobbly app were however positive. This study showed that Indigenous youth are early and frequent users of technology in general, and they regarded the iBobbly app to be culturally safe and of therapeutic value. Qualitative analyses demonstrated that iBobbly app use was associated with self-reported improvements in psychological wellbeing, mental health literacy, and reductions in shame. Importantly, participants reported that they would recommend other similar apps if available to their peers.

College student veterans' experience with a mindfulness- and acceptance-based mobile app intervention for PTSD: A qualitative study

This study aimed to explore college student military veterans' experience with a mindfulness- and acceptance-based smartphone app intervention. Upon the 4-week participation in the intervention, 23 student veterans took part in semi-structured interviews. In the thematic analysis of the interview transcripts, three main themes emerged: (1) generating momentum of app use; (2) optimizing the functions and benefits of the app; and (3) resolving to deepen the practice of mindfulness and acceptance. Considering the low engagement rates of several previous app-based studies, our results provide a useful framework for incorporating human feedback and support in enhancing users' engagement with the app.