A Mobile App-Based Intervention for Depression: End-User and Expert Usability Testing Study

Resilience eDBT: Development and Usability Evaluation of a Dialectical Behavior Therapy Skills Training App for Eating Disorders

OBJECTIVE

Dialectical behavior therapy (DBT) is an evidence-based treatment for disorders characterized by recurrent binge eating. Yet, access to specialized treatment like DBT remains limited. To increase the accessibility of DBT, we developed a DBT skills training app (Resilience: eDBT) for the management of eating disorder (ED) symptoms. This paper delineates the developmental process of Resilience and tests its usability.

METHODS

Descriptive information on the development and features of Resilience is provided, including its framework, content structure and delivery formats, functionality, data storage procedure, and privacy protocols. Usability was assessed via a mixed methods approach in 10 symptomatic individuals. Qualitative data were organized based on an existing framework, which included six themes: usability, visual design, user engagement, content, therapeutic persuasiveness, and therapeutic alliance.

RESULTS

Resilience demonstrated good usability via a Systems Usability Scale score of 85.5, which exceeded the recommended cutoff of 68. Positive aspects of the app, according to interview data, were the ease of use and the visual design, while the addition of peer support was suggested as an opportunity for improvement.

DISCUSSION

A novel DBT-based app may serve as an acceptable, low-intensity option or adjunct to traditional treatment for targeting ED symptoms that emerge in daily life. However, notable limitations include the small sample size and the single time point at which the usability assessment was conducted.

Acceptability of Digital Mental Health Interventions for Depression and Anxiety: Systematic Review

BACKGROUND

Depression and anxiety disorders are common, and treatment often includes psychological interventions. Digital health interventions, delivered through technologies such as web-based programs and mobile apps, are increasingly used in mental health treatment. Acceptability, the extent to which an intervention is viewed positively, has been identified as contributing to patient adherence and engagement with digital health interventions. Acceptability, therefore, impacts the benefit derived from using digital health interventions in treatment. Understanding the acceptability of digital mental health interventions among patients with depression or anxiety disorders is essential to maximize the effectiveness of their treatment.

OBJECTIVE

This review investigated the acceptability of technology-based interventions among patients with depression or anxiety disorders.

METHODS

A systematic review was performed based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and PROSPERO (International Prospective Register of Systematic Reviews) guidelines. We searched PubMed, Web of Science, and Ovid in May 2022. Studies were included if they evaluated digital interventions for the treatment of depression or anxiety disorders and investigated their acceptability among adult patients. Studies were excluded if they targeted only specific populations (eg, those with specific physical health conditions), investigated acceptability in healthy individuals or patients under the age of 18 years, involved no direct interaction between patients and technologies, used technology only as a platform for traditional care (eg, videoconferencing), had patients using technologies only in clinical or laboratory settings, or involved virtual reality technologies. Acceptability outcome data were narratively synthesized by the direction of acceptability using vote counting. Included studies were evaluated using levels of evidence from the Oxford Centre for Evidence-Based Medicine. The risk of bias was assessed using a tool designed for this review and GRADE (Grading of Recommendations, Assessment, Development, and Evaluation).

RESULTS

A total of 143 articles met the inclusion criteria, comprising 67 (47%) articles on interventions for depression, 65 (45%) articles on interventions for anxiety disorders, and 11 (8%) articles on interventions for both. Overall, 90 (63%) were randomized controlled trials, 50 (35%) were other quantitative studies, and 3 (2%) were qualitative studies. Interventions used web-based programs, mobile apps, and computer programs. Cognitive behavioral therapy was the basis of 71% (102/143) of the interventions. Digital mental health interventions were generally acceptable among patients with depression or anxiety disorders, with 88% (126/143) indicating positive acceptability, 8% (11/143) mixed results, and 4% (6/143) insufficient information to categorize the direction of acceptability. The available research evidence was of moderate quality.

CONCLUSIONS

Digital mental health interventions seem to be acceptable to patients with depression or anxiety disorders. Consistent use of validated measures for acceptability would enhance the quality of evidence. Careful design of acceptability as an evaluation outcome can further improve the quality of evidence and reduce the risk of bias.

TRIAL REGISTRATION

Open Science Framework Y7MJ4; https://doi.org/10.17605/OSF.IO/SPR8M.

Data Visualization Preferences in Remote Measurement Technology for Individuals Living With Depression, Epilepsy, and Multiple Sclerosis: Qualitative Study

BACKGROUND

Remote measurement technology (RMT) involves the use of wearable devices and smartphone apps to measure health outcomes in everyday life. RMT with feedback in the form of data visual representations can facilitate self-management of chronic health conditions, promote health care engagement, and present opportunities for intervention. Studies to date focus broadly on multiple dimensions of service users' design preferences and RMT user experiences (eg, health variables of perceived importance and perceived quality of medical advice provided) as opposed to data visualization preferences.

OBJECTIVE

This study aims to explore data visualization preferences and priorities in RMT, with individuals living with depression, those with epilepsy, and those with multiple sclerosis (MS).

METHODS

A triangulated qualitative study comparing and thematically synthesizing focus group discussions with user reviews of existing self-management apps and a systematic review of RMT data visualization preferences. A total of 45 people participated in 6 focus groups across the 3 health conditions (depression, n=17; epilepsy, n=11; and MS, n=17).

RESULTS

Thematic analysis validated a major theme around design preferences and recommendations and identified a further four minor themes: (1) data reporting, (2) impact of visualization, (3) moderators of visualization preferences, and (4) system-related factors and features.

CONCLUSIONS

When used effectively, data visualizations are valuable, engaging components of RMT. Easy to use and intuitive data visualization design was lauded by individuals with neurological and psychiatric conditions. Apps design needs to consider the unique requirements of service users. Overall, this study offers RMT developers a comprehensive outline of the data visualization preferences of individuals living with depression, epilepsy, and MS.

Digital Psychotherapies for Adults Experiencing Depressive Symptoms: Systematic Review and Meta-Analysis

BACKGROUND

Depression affects 5% of adults and it is a major cause of disability worldwide. Digital psychotherapies offer an accessible solution addressing this issue. This systematic review examines a spectrum of digital psychotherapies for depression, considering both their effectiveness and user perspectives.

OBJECTIVE

This review focuses on identifying (1) the most common types of digital psychotherapies, (2) clients' and practitioners' perspectives on helpful and unhelpful aspects, and (3) the effectiveness of digital psychotherapies for adults with depression.

METHODS

A mixed methods protocol was developed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The search strategy used the Population, Intervention, Comparison, Outcomes, and Study Design (PICOS) framework covering 2010 to 2024 and 7 databases were searched. Overall, 13 authors extracted data, and all aspects of the review were checked by >1 reviewer to minimize biases. Quality appraisal was conducted for all studies. The clients' and therapists' perceptions on helpful and unhelpful factors were identified using qualitative narrative synthesis. Meta-analyses of depression outcomes were conducted using the standardized mean difference (calculated as Hedges g) of the postintervention change between digital psychotherapy and control groups.

RESULTS

Of 3303 initial records, 186 records (5.63%; 160 studies) were included in the review. Quantitative studies (131/160, 81.8%) with a randomized controlled trial design (88/160, 55%) were most common. The overall sample size included 70,720 participants (female: n=51,677, 73.07%; male: n=16,779, 23.73%). Digital interventions included "stand-alone" or non-human contact interventions (58/160, 36.2%), "human contact" interventions (11/160, 6.8%), and "blended" including stand-alone and human contact interventions (91/160, 56.8%). What clients and practitioners perceived as helpful in digital interventions included support with motivation and accessibility, explanation of task reminders, resources, and learning skills to manage symptoms. What was perceived as unhelpful included problems with usability and a lack of direction or explanation. A total of 80 studies with 16,072 participants were included in the meta-analysis, revealing a moderate to large effect in favor of digital psychotherapies for depression (Hedges g=-0.61, 95% CI -0.75 to -0.47; Z=-8.58; P<.001). Subgroup analyses of the studies with different intervention delivery formats and session frequency did not have a statistically significant effect on the results (P=.48 and P=.97, respectively). However, blended approaches revealed a large effect size (Hedges g=-0.793), while interventions involving human contact (Hedges g=-0.42) or no human contact (Hedges g=-0.40) had slightly smaller effect sizes.

CONCLUSIONS

Digital interventions for depression were found to be effective regardless of format and frequency. Blended interventions have larger effect size than those involving human contact or no human contact. Digital interventions were helpful especially for diverse ethnic groups and young women. Future research should focus on understanding the sources of heterogeneity based on intervention and population characteristics.

TRIAL REGISTRATION

PROSPERO CRD42021238462; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=238462.

Investigating mobile persuasive design for mental wellness: A cross-domain analysis

BACKGROUND

Global mental health issues have increased the demand for digital mental health support. Mobile apps with persuasive technology play a vital role in enhancing mental well-being.

OBJECTIVE

Analysing and Comparing persuasive intervention design across various app categories, this study aims to inspire innovative design approaches for improving the persuasiveness of mental wellness apps during their development.

METHODS

We retrieved a total of 100 mobile apps from five distinct categories (20 for each): Mental wellness, Social media, Entertainment, Fitness & Physical health and News & Information from Apple Store and Google Play. Two researchers examined and coded the apps to identify the persuasive features employed within each category using the Persuasive Systems Design (PSD) Framework, while a third researcher participated in discussions to resolve discrepancies. Kendall's Rank Correlation Coefficient was performed to determine the relationship between persuasive features and effectiveness.

RESULTS

Trustworthiness (n = 81), Liking (n = 78), Surface credibility (n = 71), Reminders (n = 63), and Reduction (n = 57) were the most widely implemented persuasive features. Dialogue support and system credibility support features were heavily used across different app types, while social support features were less commonly employed, particularly in mental health apps. A positive correlation was found between Surface credibility, Trustworthiness, Liking, Reminders, Self-monitoring, Expertise features and apps' effectiveness.

CONCLUSION

Through a cross-domain analysis using the PSD framework to investigate persuasive feature implementations, the findings from this study offer design suggestions to create innovative and effective mobile apps promoting mental well-being.

Evaluating the Usability of an mHealth App for Empowering Cancer Survivors With Disabilities: Heuristic Evaluation and Usability Testing

BACKGROUND

More than 18 million cancer survivors are living in the United States. The effects of cancer and its treatments can have cognitive, psychological, physical, and social consequences that many survivors find incredibly disabling. Posttreatment support is often unavailable or underused, especially for survivors living with disabilities. This leaves them to deal with new obstacles and struggles on their own, oftentimes feeling lost during this transition. Mobile health (mHealth) interventions have been shown to effectively aid cancer survivors in dealing with many of the aftereffects of cancer and its treatments; these interventions hold immense potential for survivors living with disabilities. We developed a prototype for WeCanManage, an mHealth-delivered self-management intervention to empower cancer survivors living with disabilities through problem-solving, mindfulness, and self-advocacy training.

OBJECTIVE

Our study conducted a heuristic evaluation of the WeCanManage high-fidelity prototype and assessed its usability among cancer survivors with known disabilities.

METHODS

We evaluated the prototype using Nielsen's 10 principles of heuristic evaluation with 22 human-computer interaction university students. On the basis of the heuristic evaluation findings, we modified the prototype and conducted usability testing on 10 cancer survivors with a variety of known disabilities, examining effectiveness, efficiency, usability, and satisfaction, including a completion of the modified System Usability Scale (SUS).

RESULTS

The findings from the heuristic evaluation were mostly favorable, highlighting the need for a help guide, addressing accessibility concerns, and enhancing the navigation experience. After usability testing, the average SUS score was 81, indicating a good-excellent design. The participants in the usability testing sample expressed positive reactions toward the app's design, educational content and videos, and the available means of connecting with others. They identified areas for improvement, such as improving accessibility, simplifying navigation within the community forums, and providing a more convenient method to access the help guide.

CONCLUSIONS

Overall, usability testing showed positive results for the design of WeCanManage. The course content and features helped participants feel heard, understood, and less alone.

Understanding the perspectives and needs of multiple stakeholders: Identifying key elements of a digital health intervention to protect against environmental hazards

AirRater is a free environmental health smartphone app developed and available in Australia that collects individual health data and disseminates environmental hazard information to populations. Following previous evaluations with app users, the aim of this study was to better understand how clinicians, government agency and non-government advocacy group representatives perceive an app designed to reduce the impacts of environmental hazards on individual and public health. Nine government agency and non-government advocacy group representatives, along with 11 clinicians based in Australia participated in a semi-structured interview or focus group to explore perspectives on AirRater. Interview and focus group data were transcribed and analysed using the qualitative data analysis software NVivo. Results indicate that for clinicians, apps like AirRater can add value as an educational, patient self-management and diagnostic tool. For government and peak bodies, apps can add value by addressing environmental health literacy and monitoring and forecasting gaps, as well as supporting advocacy efforts and public health surveillance. We conclude that environmental health smartphone apps can support a range of stakeholders to achieve shared goals and priorities related to individual and public health outcomes. Further research is needed to better understand how apps could be embedded into clinical practice and policy settings.

Design and development of a mobile-based self-care application for patients with depression and anxiety disorders

BACKGROUND AND AIM

Depression and anxiety can cause social, behavioral, occupational, and functional impairments if not controlled and managed. Mobile-based self-care applications can play an essential and effective role in controlling and reducing the effects of anxiety disorders and depression. The aim of this study was to design and develop a mobile-based self-care application for patients with depression and anxiety disorders with the goal of enhancing their mental health and overall well-being.

MATERIALS AND METHODS

In this study we designed a mobile-based application for self -management of depression and anxiety disorders. In order to design this application, first the education- informational needs and capabilities were identified through a systematic review. Then, according to 20 patients with depression and anxiety, this education-informational needs and application capabilities were approved. In the next step, the application was designed.

RESULTS

In the first step, 80 education-information needs and capabilities were identified. Finally, in the second step, of 80 education- informational needs and capabilities, 68 needs and capabilities with a mean greater than and equal to 3.75 (75%) were considered in application design. Disease control and management, drug management, nutrition and diet management, recording clinical records, communicating with physicians and other patients, reminding appointments, how to improve lifestyle, quitting smoking and reducing alcohol consumption, educational content, sedation instructions, introducing health care centers for depression and anxiety treatment and recording activities, personal goals and habits in a diary were the most important features of this application.

CONCLUSION

The designed application can encourage patients with depression and stress to perform self-care processes and access necessary information without searching the Internet.

A Series of Personalized Virtual Light Therapy Interventions for Fatigue: Feasibility Randomized Crossover Trial for N-of-1 Treatment

BACKGROUND

Fatigue is one of the most common symptoms treated in primary care and can lead to deficits in mental health and functioning. Light therapy can be an effective treatment for symptoms of fatigue; however, the feasibility, scalability, and individual-level heterogeneity of light therapy for fatigue are unknown.

OBJECTIVE

This study aimed to evaluate the feasibility, acceptability, and effectiveness of a series of personalized (N-of-1) interventions for the virtual delivery of bright light (BL) therapy and dim light (DL) therapy versus usual care (UC) treatment for fatigue in 60 participants.

METHODS

Participants completed satisfaction surveys comprising the System Usability Scale (SUS) and items assessing satisfaction with the components of the personalized trial. Symptoms of fatigue were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS) daily, PROMIS weekly, and ecological momentary assessment (EMA) questionnaires delivered 3 times daily. Comparisons of fatigue between the BL, DL, and UC treatment periods were conducted using generalized linear mixed model analyses between participants and generalized least squares analyses within individual participants.

RESULTS

Participants rated the usability of the personalized trial as acceptable (average SUS score=78.9, SD 15.6), and 92% (49/53) of those who completed satisfaction surveys stated that they would recommend the trial to others. The levels of fatigue symptoms measured using the PROMIS daily fatigue measure were lower or improved in the BL (B=-1.63, 95% CI -2.63 to -0.63) and DL (B=-1.44, 95% CI -2.50 to -0.38) periods relative to UC. The treatment effects of BL and DL on the PROMIS daily measure varied among participants. Similar findings were demonstrated for the PROMIS weekly and EMA measures of fatigue symptoms.

CONCLUSIONS

The participant scores on the SUS and satisfaction surveys suggest that personalized N-of-1 trials of light therapy for fatigue symptoms are both feasible and acceptable. Both interventions produced significant (P<.05) reductions in participant-reported PROMIS and EMA fatigue symptoms relative to UC. However, the heterogeneity of these treatment effects across participants indicated that the effect of light therapy was not uniform. This heterogeneity along with high ratings of usability and satisfaction support the use of personalized N-of-1 research designs in evaluating the effect of light therapy on fatigue for each patient. Furthermore, the results of this trial provide additional support for the use of a series of personalized N-of-1 research trials.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04707846; https://clinicaltrials.gov/ct2/show/NCT04707846.

User-Centered Design of a Digitally Enabled Care Pathway in a Large Health System: Qualitative Interview Study

BACKGROUND

Major depressive disorder (MDD) is a leading cause of disability worldwide. Management of chronic conditions such as MDD can be improved by enhanced patient engagement, measurement-based care (MBC), and shared decision-making (SDM). A user-centered design approach can improve the understanding of the patient journey and care team workflows and thus aid the development of digital health care innovations optimized for the needs of patients living with MDD and their primary care teams.

OBJECTIVE

This study aims to use qualitative research methods for the user-centered design of a digitally enabled MDD care platform, PathwayPlatform, intended to enhance patient engagement, MBC, and SDM.

METHODS

Insights were gathered through 2 stages of qualitative interviews by a study team with expertise in qualitative research and user-centered design methods. Thematic analysis was used to generate an overarching understanding of a set of shared experiences, thoughts, or behaviors across a broad qualitative data set, including transcripts of interviews, to allow both inductive and deductive insights to emerge. Thematic analysis of interviews was supported by Dedoose (SocioCultural Research Consultants, LLC), a qualitative data analysis software tool that enables systematized coding. Findings and insights were presented based on code frequency, salience, and relevance to the research project.

RESULTS

In stage 1, interviews were conducted with 20 patients living with MDD and 15 health care providers from September 2018 to January 2019 to understand the experiences with and perceptions about the initial functionality of the Pathway app while also exploring the perceptions about potential additional features and functionality. Feedback about care team workflows and treatment approaches was collected in stage-2 interviews with 36 health care providers at 8 primary care sites. Inductive and deductive thematic analyses revealed several themes related to app functionality, patient-provider engagement, workflow integration, and patient education. Both patients and their care teams perceived the remote tracking of patient-reported outcomes via digital tools to be clinically useful and reliable and to promote MBC and SDM. However, there was emphasis on the need to enhance the flow of real-time data shared with the care team, improve trend visualizations, and integrate the data within the existing clinical workflow and educational programs for patients and their care teams. User feedback was incorporated into the iterative development of the Pathway app.

CONCLUSIONS

Ongoing communication with patients living with MDD and their care teams provided an opportunity for user-centric developmental iterations of the Pathway Platform. Key insights led to further development of the patient-facing and care team-facing visit preparation features, collaborative goal-setting and goal-tracking features, patient-reported outcome summaries, and trend visualizations. The result is an enhanced digital platform with the potential to improve treatment outcomes and provide patients living with MDD additional support throughout their treatment journey.

Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms

Introduction

Personalization is a much-discussed approach to improve adherence and outcomes for Digital Mental Health interventions (DMHIs). Yet, major questions remain open, such as (1) what personalization is, (2) how prevalent it is in practice, and (3) what benefits it truly has.

Methods

We address this gap by performing a systematic literature review identifying all empirical studies on DMHIs targeting depressive symptoms in adults from 2015 to September 2022. The search in Pubmed, SCOPUS and Psycinfo led to the inclusion of 138 articles, describing 94 distinct DMHIs provided to an overall sample of approximately 24,300 individuals.

Results

Our investigation results in the conceptualization of personalization as purposefully designed variation between individuals in an intervention's therapeutic elements or its structure. We propose to further differentiate personalization by what is personalized (i.e., intervention content, content order, level of guidance or communication) and the underlying mechanism [i.e., user choice, provider choice, decision rules, and machine-learning (ML) based approaches]. Applying this concept, we identified personalization in 66% of the interventions for depressive symptoms, with personalized intervention content (32% of interventions) and communication with the user (30%) being particularly popular. Personalization via decision rules (48%) and user choice (36%) were the most used mechanisms, while the utilization of ML was rare (3%). Two-thirds of personalized interventions only tailored one dimension of the intervention.

Discussion

We conclude that future interventions could provide even more personalized experiences and especially benefit from using ML models. Finally, empirical evidence for personalization was scarce and inconclusive, making further evidence for the benefits of personalization highly needed.

Systematic Review Registration

Identifier: CRD42022357408.

A qualitative exploration of university student perspectives on mindfulness-based stress reduction exercises via smartphone app in Bangladesh

PURPOSE

Mental health problems are proliferating, and access to mental health care is difficult due to barriers imposed by the COVID-19 pandemic in low-income countries such as Bangladesh. University students are susceptible to mental health concerns, given their unique stressors (i.e., academic pressure, new social environment). Mindfulness techniques can promote mental health , yet their acceptability has not been examined among Bangladeshi university students. These techniques can be used on a digital app, to decrease barriers to use.Qualitative methods were used to examine the acceptability of mindfulness among university students in Bangladesh. In-depth interviews (n = 12) were conducted to examine student reactions to linguistically (Bangla) and culturally adapted mindfulness exercises. Thematic analysis generated three themes (1) previous experience with mindfulness (2) positive responses to and (3) improvements to mindfulness exercises.

RESULTS

The results showed favourable attitudes towards the mindfulness content; students expressed positive psychological and physiological reactions. Students welcomed the concept of using these exercises on an app and felt it could overcomepast barriers to help-seeking.

CONCLUSIONS

This evidence suggests the value of exploring the acceptability of an app with mindfulness exercises for mental health promotion through a larger-scale pilot study in university students in Bangladesh.

Adaptation of the trauma group intervention 'Teaching Recovery Techniques' for online delivery: A participatory design and usability study

Background

Video-telehealth delivery of trauma-based care is promising and may help address structural and perceptual barriers to receiving support. However, existing evidence relies heavily on samples from adult populations. There is potential to transfer existing child and adolescent trauma interventions to a video-telehealth delivery format; but, this requires careful consideration. The aim of this project was to adapt a group-based intervention called Teaching Recovery Techniques for online delivery and investigate the usability of the new intervention format.

Methods

A qualitative needs assessment was performed (n = 3 intervention leaders, 4 youth), followed by participatory workshops and advisory panel consultation to generate adaptation recommendations. Usability testing was performed in two cycles; the first tested the adapted manual with intervention leaders (n = 5), and the second tested newly developed digital resources with youth (n = 5).

Results

The needs assessment uncovered a number of issues that, when generating recommendations, were distilled into three topics: safety, participation and learning. Recommendations included safety rules, an emergency response protocol, communication strategies, and guidance on group composition and intervention delivery. Usability testing indicated acceptability but highlighted the need for more detailed and explicit guidance, particularly on safety processes.

Discussion

The present study demonstrates the potential for delivery format to affect intervention feasibility and acceptability, and provides recommendations that can be used to guide the transfer of other group-based mental health interventions to an online format. The young people, parents and professionals involved in the project provided rich and varied perspectives, which illustrated the value of broad stakeholder engagement.

A Series of Virtual Interventions for Chronic Lower Back Pain: A Feasibility Pilot Study for a Series of Personalized (N-of-1) Trials

Chronic lower back pain (CLBP) affects 25% of U.S. adults and is associated with high costs due to physician visits and reduced productivity. Research shows that massage and yoga can be effective nonpharmacological treatments for CLBP, but the feasibility, scalability, individual treatment, and adverse-event heterogeneity of these treatments are unknown. The current study evaluated the feasibility and acceptability of a series of personalized (N-of-1) interventions for virtual delivery of massage and yoga or usual-care treatment for CLBP in 57 participants. We hypothesized that this study would provide valuable information about implementing a virtual, personalized platform for randomized controlled trials of personalized (N-of-1) interventions among individuals with CLBP. The study will do so by determining participants' ratings of usability and satisfaction with the virtual, personalized intervention delivery system and, in the long term, identifying ways to integrate these personalized trials into patient care. Of the 57 participants enrolled, two withdrew from the study and were not eligible to receive the primary outcome assessment. Thirty-seven of the remaining 55 participants (67.3%) completed satisfaction surveys comprising the System Usability Scale (SUS) and items assessing satisfaction with the components of the personalized trial. Participants rated the usability of the personalized trial as excellent (average SUS score = 85.8), 95% were satisfied with the personalized trial overall, and 100% stated they would recommend the trial to others. These results suggest that personalized trials of massage and yoga are highly feasible and acceptable to participants with CLBP.

A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

Due to the development of sensing technology people can easily track their health in various ways, and the interest in personal healthcare data is increasing. Individuals are interested in controlling their wellness, which requires self-awareness and an understanding of various health conditions. Self-generated health data are easily accessed through mobile devices, and data visualization is commonly used in applications. A systematic literature review was conducted to better understand the role of visualizations and learn how to develop effective ones. Thirteen papers were analyzed for types of data, characteristics of visualizations, and effectiveness for healthcare management. The papers were selected because they represented research on personal health data and visualization in a non-clinical setting, and included health data tracked in everyday life. This paper suggests six levels for categorizing the efficacy of visualizations that take into account cognitive and physical changes in users. Recommendations for future work on conducting evaluations are also identified. This work provides a foundation for personal healthcare data as more applications are developed for mobile and wearable devices.

System Usability Scale Benchmarking for Digital Health Apps: Meta-analysis

Background

The System Usability Scale (SUS) is a widely used scale that has been used to quantify the usability of many software and hardware products. However, the SUS was not specifically designed to evaluate mobile apps, or in particular digital health apps (DHAs).

Objective

The aim of this study was to examine whether the widely used SUS distribution for benchmarking (mean 68, SD 12.5) can be used to reliably assess the usability of DHAs.

Methods

A search of the literature was performed using the ACM Digital Library, IEEE Xplore, CORE, PubMed, and Google Scholar databases to identify SUS scores related to the usability of DHAs for meta-analysis. This study included papers that published the SUS scores of the evaluated DHAs from 2011 to 2021 to get a 10-year representation. In total, 117 SUS scores for 114 DHAs were identified. R Studio and the R programming language were used to model the DHA SUS distribution, with a 1-sample, 2-tailed t test used to compare this distribution with the standard SUS distribution.

Results

The mean SUS score when all the collected apps were included was 76.64 (SD 15.12); however, this distribution exhibited asymmetrical skewness (–0.52) and was not normally distributed according to Shapiro-Wilk test (P=.002). The mean SUS score for “physical activity” apps was 83.28 (SD 12.39) and drove the skewness. Hence, the mean SUS score for all collected apps excluding “physical activity” apps was 68.05 (SD 14.05). A 1-sample, 2-tailed t test indicated that this health app SUS distribution was not statistically significantly different from the standard SUS distribution (P=.98).

Conclusions

This study concludes that the SUS and the widely accepted benchmark of a mean SUS score of 68 (SD 12.5) are suitable for evaluating the usability of DHAs. We speculate as to why physical activity apps received higher SUS scores than expected. A template for reporting mean SUS scores to facilitate meta-analysis is proposed, together with future work that could be done to further examine the SUS benchmark scores for DHAs.

Efficacy of a transdiagnostic cognitive-behavioral intervention for eating disorder psychopathology delivered through a smartphone app: a randomized controlled trial

BACKGROUND

Although effective treatments exist for diagnostic and subthreshold-level eating disorders (EDs), a significant proportion of affected individuals do not receive help. Interventions translated for delivery through smartphone apps may be one solution towards reducing this treatment gap. However, evidence for the efficacy of smartphones apps for EDs is lacking. We developed a smartphone app based on the principles and techniques of transdiagnostic cognitive-behavioral therapy for EDs and evaluated it through a pre-registered randomized controlled trial.

METHODS

Symptomatic individuals (those who reported the presence of binge eating) were randomly assigned to the app (n = 197) or waiting list (n = 195). Of the total sample, 42 and 31% exhibited diagnostic-level bulimia nervosa and binge-eating disorder symptoms, respectively. Assessments took place at baseline, 4 weeks, and 8 weeks post-randomization. Analyses were intention-to-treat. The primary outcome was global levels of ED psychopathology. Secondary outcomes were other ED symptoms, impairment, and distress.

RESULTS

Intervention participants reported greater reductions in global ED psychopathology than the control group at post-test (d = -0.80). Significant effects were also observed for secondary outcomes (d's = -0.30 to -0.74), except compensatory behavior frequency. Symptom levels remained stable at follow-up. Participants were largely satisfied with the app, although the overall post-test attrition rate was 35%.

CONCLUSION

Findings highlight the potential for this app to serve as a cost-effective and easily accessible intervention for those who cannot receive standard treatment. The capacity for apps to be flexibly integrated within current models of mental health care delivery may prove vital for addressing the unmet needs of people with EDs.

Screening Depressive Symptoms and Incident Major Depressive Disorder Among Chinese Community Residents Using a Mobile App-Based Integrated Mental Health Care Model: Cohort Study

Background

Depression is associated with significant morbidity and human capital costs globally. Early screening for depressive symptoms and timely depressive disorder case identification and intervention may improve health outcomes and cost-effectiveness among affected individuals. China’s public and academic communities have reached a consensus on the need to improve access to early screening, diagnosis, and treatment of depression.

Objective

This study aims to estimate the screening prevalence and associated factors of subthreshold depressive symptoms among Chinese residents enrolled in the cohort study using a mobile app–based integrated mental health care model and investigate the 12-month incidence rate and related factors of major depressive disorder (MDD) among those with subthreshold depressive symptoms.

Methods

Data were drawn from the Depression Cohort in China (DCC) study. A total of 4243 community residents aged 18 to 64 years living in Nanshan district, Shenzhen city, in Guangdong province, China, were encouraged to participate in the DCC study when visiting the participating primary health care centers, and 4066 (95.83%) residents who met the DCC study criteria were screened for subthreshold depressive symptoms using the Patient Health Questionnaire-9 at baseline. Of the 4066 screened residents, 3168 (77.91%) with subthreshold depressive symptoms were referred to hospitals to receive a psychiatric diagnosis of MDD within 12 months. Sleep duration, anxiety symptoms, well-being, insomnia symptoms, and resilience were also investigated. The diagnosis of MDD was provided by trained psychiatrists using the Mini-International Neuropsychiatric Interview. Univariate and multivariate logistic regression models were performed to explore the potential factors related to subthreshold depressive symptoms at baseline, and Cox proportional hazards models were performed to explore the potential factors related to incident MDD.

Results

Anxiety symptoms (adjusted odds ratio [AOR] 1.63, 95% CI 1.42-1.87) and insomnia symptoms (AOR 1.13, 95% CI 1.05-1.22) were associated with an increased risk of subthreshold depressive symptoms, whereas well-being (AOR 0.93, 95% CI 0.87-0.99) was negatively associated with depressive symptoms. During the follow-up period, the 12-month incidence rate of MDD among participants with subthreshold depressive symptoms was 5.97% (189/3168). After incorporating all significant variables from the univariate analyses, the multivariate Cox proportional hazards model reported that a history of comorbidities (adjusted hazard ratio [AHR] 1.49, 95% CI 1.04-2.14) and anxiety symptoms (AHR 1.13, 95% CI 1.09-1.17) were independently associated with an increased risk of incident MDD. The 5-item World Health Organization Well-Being Index was associated with a decreased risk of incident MDD (AHR 0.90, 95% CI 0.86-0.94).

Conclusions

Elevated anxiety symptoms and unfavorable general well-being were significantly associated with subthreshold depressive symptoms and incident MDD among Chinese residents in Shenzhen. Early screening for subthreshold depressive symptoms and related factors may be helpful for identifying populations at high risk of incident MDD.

Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives

BACKGROUND

Remote measurement technologies (RMT) such as mobile health devices and apps are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, although little is known about visualization design preferences from the perspectives of those living with chronic conditions.

OBJECTIVE

The aim of this review was to explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health.

METHODS

In this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, Association for Computing Machinery Computer-Human Interface proceedings, and the Cochrane Library) for original papers published between January 2007 and September 2021 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised, and extracted data underwent thematic synthesis.

RESULTS

We identified 35 eligible publications from 31 studies representing 12 conditions. Coded data coalesced into 3 themes: desire for data visualization, impact of visualizations on condition management, and visualization design considerations. Data visualizations were viewed as an integral part of users' experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting both between and within conditions.

CONCLUSIONS

When used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not "one-size-fits-all," and it is important to engage with potential users during visualization design to understand when, how, and with whom the visualizations will be used to manage health.

Motivations Toward Using Digital Health and Exploring the Possibility of Using Digital Health for Mental Health in Bangladesh University Students: Cross-sectional Questionnaire Study

Background

Digital health is efficacious for the management and prevention of mental health (MH) problems. It is particularly helpful for the young adult population, who appreciate the autonomy digital health provides, and in low-income countries, where the prevalence of MH problems is high but the supply of professionals trained in MH is low.

Objective

The objectives of this study are 2-fold: to determine whether university students in Bangladesh find using digital health for MH promotion acceptable and to examine motivational factors for using digital health for MH.

Methods

This study used a cross-sectional survey to examine the likelihood that university students in Bangladesh (n=311) would use different forms of digital health platforms for MH promotion and assessed drivers of intention to use and actual use of digital health generally and digital health for MH through the lens of the Technology Acceptance Model. The results provided evidence that the university student population in Bangladesh is likely to use digital health to promote their MH.

Results

Social influence (adjusted odds ratio [aOR] 1.68, 95% CI 1.40-2.01; P<.001), ease of use (aOR 1.85, 95% CI 1.35-2.53; P<.001), and perceived usefulness (aOR 4.12, 95% CI 1.79-9.51; P=.001) of digital health were found to be significant drivers of the intention to use general digital health, and having an intention to use digital health (aOR 2.10, 95% CI 1.17-3.78; P=.01) had the greatest influence on actual use of digital health. Social influence (aOR 1.71, 95% CI 1.43-2.04; P<.001), perceived usefulness (aOR 8.92, 95% CI 4.18-19.04; P<.001), and use of general digital health (aOR 2.16, 95% CI 1.18-3.97; P=.01) were associated with higher intention to use digital health for MH. The use of general digital health (aOR 4.19, 95% CI 2.37-7.41; P<.001) was associated with the actual use of digital health for MH, as were greater non–stigma-related barriers to using traditional clinical MH services (aOR 2.05, 95% CI 1.10-3.80; P=.02).

Conclusions

Overall, we see that the use of digital health for MH is acceptable in this population and can be helpful for students who perceive barriers to receiving traditional care. We also gain insight into how to promote the intention to use digital health, which in turn promotes the actual use of digital health.

A self-guided and monitored digital problem-solving intervention for patients with symptoms of depression or anxiety on the waiting list for treatment in routine psychiatric care: feasibility study

BACKGROUND

There is often a waiting period for people who seek psychiatric treatment for depression or anxiety. As this delay risks worsening symptoms, an alternative could be to provide an intervention that requires minimal resources during the waiting period.

AIMS

The aim was to investigate if a digital problem-solving intervention delivered in a self-guided format with automated features is feasible to provide for patients on the waiting list in routine psychiatric care.

METHOD

A total of 12 patients with symptoms of depression or anxiety on the waiting list for treatment in routine psychiatric care were given access to a self-guided and monitored digital problem-solving intervention over 4 weeks. Primary outcome measures were treatment credibility and usability. Secondary outcome measures were behavioural engagement, symptoms of depression and anxiety, and negative effects.

RESULTS

A majority of participants rated the intervention as both credible and usable. The intervention was used at least once by nine out of 12 individuals, with an average of 11 logins. The participants did, on average, initiate 2.8 problem-solving attempts and 10.1 solutions. A few participants reached a clinically relevant symptom improvement of depression and anxiety. No serious negative effects were reported.

CONCLUSIONS

The credibility and usability of the intervention was perceived as good, and the behavioural engagement with the intervention was deemed sufficient compared with similar self-guided interventions. A self-guided and monitored digital problem-solving intervention may be a beneficial option for patients waiting for or receiving treatment in routine psychiatric care, and should be further evaluated.

COVID-19 smart surveillance: Examination of Knowledge of Apps and mobile thermometer detectors (MTDs) in a high-risk society

BACKGROUND

Technological innovations gained momentum and supported COVID-19 intelligence surveillance among high-risk populations globally. We examined technology surveillance using mobile thermometer detectors (MTDs), knowledge of App, and self-efficacy as a means of sensing body temperature as a measure of COVID-19 risk mitigation. In a cross-sectional survey, we explored COVID-19 risk mitigation, mobile temperature detectable by network syndromic surveillance mobility, detachable from clinicians, and laboratory diagnoses to elucidate the magnitude of community monitoring.

MATERIALS AND METHODS

In a cross-sectional survey, we create in-depth comprehension of risk mitigation, mobile temperature Thermometer detector, and other variables for surveillance and monitoring among 850 university students and healthcare workers. An applied structural equation model was adopted for analysis with Amos v.24. We established that mobile usability knowledge of APP could effectively aid in COVID-19 intelligence risk mitigation. Moreover, both self-efficacy and mobile temperature positively strengthened data visualization for public health decision-making.

RESULTS

The algorithms utilize a validated point-of-center test to ascertain the HealthCode scanning system for a positive or negative COVID-19 notification. The MTD is an alternative personal self-testing procedure used to verify temperature rates based on previous SARS-CoV-2 and future mobility digital health. Personal self-care of MTD mobility and knowledge of mHealth apps can specifically manage COVID-19 mitigation in high or low terrestrial areas. We found mobile usability, mobile self-efficacy, and app knowledge were statistically significant to COVID-19 mitigation. Additionally, interaction strengthened the positive relationship between self-efficacy and COVID-19. Data aggregation is entrusted with government database agencies, using natural language processing and machine learning mechanisms to validate and analyze.

CONCLUSION

The study shows that temperature thermometer detectors, mobile usability, and knowledge of App enhanced COVID-19 risk mitigation in a high or low-risk environment. The standardizing dataset is necessary to ensure privacy and security preservation of data ethics.

User experience and acceptance of patients and healthy adults testing a personalized self-management app for depression: A non-randomized mixed-methods feasibility study

Objective

Previous studies have shown positive treatment outcomes of e-mental health applications targeting depression. However, few applications provide personalized features. The aim of the present study is to ask for the user experience and acceptance of patients with depression and healthy adults, who tested the self-management app Self-administered Psycho Therapy SystemS over a period of 5 days. The results serve as a source for evidence-based recommendations for developers and clinicians.

Methods

A total of 110 participants (41 patients and 69 healthy controls) tested the app Self-administered Psycho Therapy SystemS over a period of 5 days and completed evaluation sheets developed for the purpose of this study. Quantitative measures were asked with 5-point Likert-scaled items (range: −2 to + 2) for the perceived quality of the programme and its components, its practicality (both referred to as user experience) and its acceptance. Student’s t-tests and Pearson correlations were calculated for group comparisons and associations, respectively. Open text fields were analysed by applying a qualitative structuring content analysis.

Results

The perceived quality of the total programme was rated with M = 0.96 (SD = 0.82), the practicality was M = 0.84 (SD = 0.08) and the acceptance was M = 0.25 (SD = 1.04). Patients rated perceived quality of the total programme and acceptance higher than healthy adults, while there was no difference in practicality. Acceptance was associated with increased depression scores (r = 0.33, p = .01), higher scores of perceived quality of the total programme (r = 0.48, p< .001) and of practicality (r = 0.45, p < .001). Feedback of both groups regarding usability, therapeutic content and personalization revealed a strong wish for guidance and insights into mood progress, opportunities for choice of interventions and features of customization for individualized treatment.

Conclusions

Patients with depression accepted the app Self-administered Psycho Therapy SystemS more than healthy adults and gave higher ratings in quality. User experience of all users shows a need for features of guidance, choice and personalization that clinicians and developers of future apps should pay attention to.

Digital Therapeutic Alliance With Fully Automated Mental Health Smartphone Apps: A Narrative Review

Fully automated mental health smartphone apps show strong promise in increasing access to psychological support. Therefore, it is crucial to understand how to make these apps effective. The therapeutic alliance (TA), or the relationship between healthcare professionals and clients, is considered fundamental to successful treatment outcomes in face-to-face therapy. Thus, understanding the TA in the context of fully automated apps would bring us insights into building effective smartphone apps which engage users. However, the concept of a digital therapeutic alliance (DTA) in the context of fully automated mental health smartphone apps is nascent and under-researched, and only a handful of studies have been published in this area. In particular, no published review paper examined the DTA in the context of fully automated apps. The objective of this review was to integrate the extant literature to identify research gaps and future directions in the investigation of DTA in relation to fully automated mental health smartphone apps. Our findings suggest that the DTA in relation to fully automated smartphone apps needs to be conceptualized differently to traditional face-to-face TA. First, the role of bond in the context of fully automated apps is unclear. Second, human components of face-to-face TA, such as empathy, are hard to achieve in the digital context. Third, some users may perceive apps as more non-judgmental and flexible, which may further influence DTA formation. Subdisciplines of computer science, such as affective computing and positive computing, and some human-computer interaction (HCI) theories, such as those of persuasive technology and human-app attachment, can potentially help to foster a sense of empathy, build tasks and goals and develop bond or an attachment between users and apps, which may further contribute to DTA formation in fully automated smartphone apps. Whilst the review produced a relatively limited quantity of literature, this reflects the novelty of the topic and the need for further research.

Engagement with mobile health interventions for depression: A systematic review

BACKGROUND

Depressive disorders are a major public health problem, and many people face barriers to accessing evidence-based mental health treatment. Mobile health (mHealth) interventions may circumvent logistical barriers to in-person care (e.g., cost, transportation), however the symptoms of depression (low motivation, concentration difficulties) may make it difficult for people with the disorder to engage with mHealth.

OBJECTIVE

The aim of this systematic review is to examine assessment and reporting of engagement in clinical trials of mHealth interventions for depression, including objective engagement (e.g., number of times program is used), subjective engagement (e.g., qualitative data on users' experiences), and associations between engagement and other clinically important variables (e.g., symptom improvement, participant characteristics).

METHODS

Three electronic databases (PsycINFO, Web of Science, PubMed) were searched in February 2020 using search terms for mHealth and depression. Studies were included in the review if they tested a mHealth intervention designed for people with depressive disorders or elevated depression symptoms.

RESULTS

Thirty studies met inclusion criteria and were reviewed. Most studies reported objective engagement (N = 23, 76.7%), approximately half reported subjective engagement (N = 16, 53.3%), and relatively few examined associations between engagement and clinical improvement, participant characteristics, or other clinically relevant variables (N = 13, 43.3%).

CONCLUSIONS

Although most studies in this small but rapidly growing literature report at least one measure of engagement, there is substantial heterogeneity. Intentional, theory-driven, and consistent measurement of engagement with mHealth interventions for depression may advance the field's understanding of effective engagement to facilitate clinical improvement, identify dose-response relationships, and maximize generalizability for underserved populations.

What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review

Background:

Despite the growing popularity of mobile app interventions, specific engagement components of mobile apps have not been well studied.

Methods:

The objectives of this scoping review are to determine which components of mobile health intervention apps encouraged or hindered engagement, and examine how studies measured engagement.

Results:

A PubMed search on March 5, 2020 yielded 239 articles that featured the terms engagement, mobile app/mobile health, and adult. After applying exclusion criteria, only 54 studies were included in the final analysis.

Discussion:

Common app components associated with increased engagement included: personalized content/feedback, data visualization, reminders/push notifications, educational information/material, logging/self-monitoring functions, and goal-setting features. On the other hand, social media integration, social forums, poor app navigation, and technical difficulties appeared to contribute to lower engagement rates or decreased usage. Notably, the review revealed a great variability in how engagement with mobile health apps is measured due to lack of established processes.

Conclusion:

There is a critical need for controlled studies to provide guidelines and standards to help facilitate engagement and its measurement in research and clinical trial work using mobile health intervention apps.

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.

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.

Usability Evaluation of a Cognitive-Behavioral App-Based Intervention for Binge Eating and Related Psychopathology: A Qualitative Study

Despite their promise as a scalable intervention modality for binge eating and related problems, reviews show that engagement of app-based interventions is variable. Issues with usability may account for this. App developers should undertake usability testing so that any problems can be identified and fixed prior to dissemination. We conducted a qualitative usability evaluation of a newly-developed app for binge eating in 14 individuals with a diagnostic- or subthreshold-level binge eating symptoms. Participants completed a semi-structured interview and self-report measures. Qualitative data were organized into six themes: usability, visual design, user engagement, content, therapeutic persuasiveness, and therapeutic alliance. Qualitative and quantitative results indicated that the app demonstrated good usability. Key advantages reported were its flexible content-delivery formats, level of interactivity, easy-to-understand information, and ability to track progress. Concerns with visual aesthetics and lack of professional feedback were raised. Findings will inform the optimal design of app-based interventions for eating disorder symptoms.

A Clinical Journey Mobile Health App for Perioperative Patients: Cross-sectional Study

Background

Mobile eHealth apps are important tools in personal health care management. The Patient Journey app was developed to inform patients with musculoskeletal disorders during their perioperative period. The app contains timely information, video exercises, and functional tasks. Although the Patient Journey app and other health apps are widely used, little research is available on how patients appreciate these apps.

Objective

The primary aim of this study was to evaluate the user-friendliness of the Patient Journey app in terms of its usability and the attitudes of users toward the app. The secondary aim was to evaluate positive and negative user experiences.

Methods

A web-based questionnaire was sent to 2114 patients scheduled for surgery for a musculoskeletal disorder. Primary outcomes were usability (measured with the System Usability Scale) and user attitudes regarding the Patient Journey app (assessed with the second part of the eHealth Impact Questionnaire). The secondary outcomes were evaluated with multiple choice questions and open-ended questions, which were analyzed via inductive thematic content analyses.

Results

Of the 940 patients who responded, 526 used the Patient Journey app. The usability of the app was high (System Usability Scale: median 85.0, IQR 72.5-92.5), and users had a positive attitude toward the Information and Presentation provided via the app (eHealth Impact Questionnaire: median 78.0, IQR 68.8-84.4). The app did not adequately improve the users’ confidence in discussing health with others (eHealth Impact Questionnaire: median 63.9, IQR 50.0-75.0) or motivation to manage health (eHealth Impact Questionnaire: median 61.1, IQR 55.6-72.2). Three core themes emerged regarding positive and negative user experiences: (1) content and information, (2) expectations and experiences, and (3) technical performance. Users experienced timely information and instructions positively and found that the app prepared and guided them optimally through the perioperative period. Negative user experiences were overly optimistic information, scarcely presented information about pain (medication), lack of reference data, insufficient information regarding clinical course deviations and complications, and lack of interaction with clinicians.

Conclusions

The Patient Journey app is a usable, informative, and presentable tool to inform patients with musculoskeletal disorders during their perioperative period. The qualitative analyses identified aspects that can further improve the user experiences of the app.

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.

Leveraging the Power of Nondisruptive Technologies to Optimize Mental Health Treatment: Case Study

Regular assessment of the effectiveness of behavioral interventions is a potent tool for improving their relevance to patients. However, poor provider and patient adherence characterize most measurement-based care tools. Therefore, a new approach for measuring intervention effects and communicating them to providers in a seamless manner is warranted. This paper provides a brief overview of the available research evidence on novel ways to measure the effects of behavioral treatments, integrating both objective and subjective data. We highlight the importance of analyzing therapeutic conversations through natural language processing. We then suggest a conceptual framework for capitalizing on data captured through directly collected and nondisruptive methodologies to describe the client's characteristics and needs and inform clinical decision-making. We then apply this context in exploring a new tool to integrate the content of therapeutic conversations and patients' self-reports. We present a case study of how both subjective and objective measures of treatment effects were implemented in cognitive-behavioral treatment for depression and anxiety and then utilized in treatment planning, delivery, and termination. In this tool, called Eleos, the patient completes standardized measures of depression and anxiety. The content of the treatment sessions was evaluated using nondisruptive, independent measures of conversation content, fidelity to the treatment model, and the back-and-forth of client-therapist dialogue. Innovative applications of advances in digital health are needed to disseminate empirically supported interventions and measure them in a noncumbersome way. Eleos appears to be a feasible, sustainable, and effective way to assess behavioral health care.

Acceptability and Co-Development of an Online Cognitive Bias Modification Intervention for Emerging Adults With Hazardous Alcohol Use and Social Anxiety: A Mixed Methods Study

BACKGROUND

Approach bias modification (ApBM) and interpretation bias modification (IBM) are two promising adjunct treatments for alcohol use and social anxiety, respectively. However, the acceptability of combining ApBM and IBM into one program for people who experience both of these disorders is unknown. The present study describes the codevelopment of a new, hybrid ApBM + IBM program and provides insight into the perceptions of acceptability from service providers and emerging adults.

METHODS

Service providers (n = 14) and emerging adults aged 18 to 25 years with lived experience of hazardous alcohol use and heightened social anxiety (n = 15) were recruited via online advertisements and through existing networks. All participants were shown a beta version of the program and asked to complete qualitative and quantitative questions to ascertain feedback on the program's acceptability and suggestions for improvement.

RESULTS

Themes emerged relating to the ApBM + IBM program's quality and usefulness, appropriateness, motivation and engagement, and potential clinical value. The program was well received and deemed acceptable for the target age group. It was rated particularly highly with regard to the overall quality and ease of use. Emerging adults had fewer suggestions for how the intervention might be revised; however, there were suggestions from both groups regarding the need for a compelling rationale at the outset of treatment and a suggestion to include a motivational interviewing and psychoeducational-based module prior to the first training session, to increase user buy-in and engagement.

CONCLUSIONS

The current findings reflect positively on the acceptability of a hybrid ApBM + IBM for emerging adults with co-occurring hazardous alcohol use and social anxiety. Service providers and emerging adults identified a number of ways to improve the design and implementation of the program, which will likely improve adherence to, and outcomes of, the intervention when added as an adjunct to treatment as usual.

Use of the Healthy Lifestyle Coaching Chatbot App to Promote Stair-Climbing Habits Among Office Workers: Exploratory Randomized Controlled Trial

Background

Lack of time for exercise is common among office workers given their busy lives. Because of occupational restrictions and difficulty in taking time off, it is necessary to suggest effective ways for workers to exercise regularly. Sustaining lifestyle habits that increase nonexercise activity in daily life can solve the issue of lack of exercise time. Healthy Lifestyle Coaching Chatbot is a messenger app based on the habit formation model that can be used as a tool to provide a health behavior intervention that emphasizes the importance of sustainability and involvement.

Objective

This study aimed to assess the efficacy of the Healthy Lifestyle Coaching Chatbot intervention presented via a messenger app aimed at stair-climbing habit formation for office workers.

Methods

From February 1, 2018, to April 30, 2018, a total of 106 people participated in the trial after online recruitment. Participants were randomly assigned to the intervention group (n=57) or the control group (n=49). The intervention group received cues and intrinsic and extrinsic rewards for the entire 12 weeks. However, the control group did not receive intrinsic rewards for the first 4 weeks and only received all rewards as in the intervention group from the fifth to twelfth week. The Self-Report Habit Index (SRHI) of participants was evaluated every week, and the level of physical activity was measured at the beginning and end of the trial. SPSS Statistics version 21 (IBM Corp) was used for statistical analysis.

Results

After 4 weeks of intervention without providing the intrinsic rewards in the control group, the change in SRHI scores was 13.54 (SD 14.99) in the intervention group and 6.42 (SD 9.42) in the control group, indicating a significant difference between the groups (P=.04). When all rewards were given to both groups, from the fifth to twelfth week, the change in SRHI scores of the intervention and control groups was comparable at 12.08 (SD 10.87) and 15.88 (SD 13.29), respectively (P=.21). However, the level of physical activity showed a significant difference between the groups after 12 weeks of intervention (P=.045).

Conclusions

This study provides evidence that intrinsic rewards are important to enhance the sustainability and effectiveness of an intervention. The Healthy Lifestyle Coaching Chatbot program can be a cost-effective method for healthy habit formation.

Trial Registration

Clinical Research Information Service KCT0004009; https://tinyurl.com/w4oo7md

Smartphone Apps for the Treatment of Mental Disorders: Systematic Review

BACKGROUND

Smartphone apps are an increasingly popular means for delivering psychological interventions to patients suffering from a mental disorder. In line with this popularity, there is a need to analyze and summarize the state of the art, both from a psychological and technical perspective.

OBJECTIVE

This study aimed to systematically review the literature on the use of smartphones for psychological interventions. Our systematic review has the following objectives: (1) analyze the coverage of mental disorders in research articles per year; (2) study the types of assessment in research articles per mental disorder per year; (3) map the use of advanced technical features, such as sensors, and novel software features, such as personalization and social media, per mental disorder; (4) provide an overview of smartphone apps per mental disorder; and (5) provide an overview of the key characteristics of empirical assessments with rigorous designs (ie, randomized controlled trials [RCTs]).

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for systematic reviews were followed. We performed searches in Scopus, Web of Science, American Psychological Association PsycNET, and Medical Literature Analysis and Retrieval System Online, covering a period of 6 years (2013-2018). We included papers that described the use of smartphone apps to deliver psychological interventions for known mental disorders. We formed multidisciplinary teams, comprising experts in psychology and computer science, to select and classify articles based on psychological and technical features.

RESULTS

We found 158 articles that met the inclusion criteria. We observed an increasing interest in smartphone-based interventions over time. Most research targeted disorders with high prevalence, that is, depressive (31/158,19.6%) and anxiety disorders (18/158, 11.4%). Of the total, 72.7% (115/158) of the papers focused on six mental disorders: depression, anxiety, trauma and stressor-related, substance-related and addiction, schizophrenia spectrum, and other psychotic disorders, or a combination of disorders. More than half of known mental disorders were not or very scarcely (<3%) represented. An increasing number of studies were dedicated to assessing clinical effects, but RCTs were still a minority (25/158, 15.8%). From a technical viewpoint, interventions were leveraging the improved modalities (screen and sound) and interactivity of smartphones but only sparingly leveraged their truly novel capabilities, such as sensors, alternative delivery paradigms, and analytical methods.

CONCLUSIONS

There is a need for designing interventions for the full breadth of mental disorders, rather than primarily focusing on most prevalent disorders. We further contend that an increasingly systematic focus, that is, involving RCTs, is needed to improve the robustness and trustworthiness of assessments. Regarding technical aspects, we argue that further exploration and innovative use of the novel capabilities of smartphones are needed to fully realize their potential for the treatment of mental health disorders.

Apps for Depression: Are They Ready to Work?

PURPOSE OF REVIEW

To summarize the latest evidence about mobile phone applications for the management of depression.

RECENT FINDINGS

Depression apps are very heterogeneous, given the absence of standards for their development, description, and evaluation. Randomized clinical trials show the effectiveness of some of these applications in reducing depressive symptoms. Attrition is an important issue whose evaluation is limited by the frequent use of incentives in the studies. The number of mobile applications for depression far exceeds the number of studies evaluating their efficacy and feasibility. Despite the limitations of the digital market, there are a small number of apps that have demonstrated sufficient effectiveness and tolerability to think of short-term clinical use. However, there are still barriers at different levels that may delay the implementation of these interventions in daily clinical practice.

Usability Evaluations of Mobile Mental Health Technologies: Systematic Review

Background

Many mobile health (mHealth) apps for mental health have been made available in recent years. Although there is reason to be optimistic about their effect on improving health and increasing access to care, there is a call for more knowledge concerning how mHealth apps are used in practice.

Objective

This study aimed to review the literature on how usability is being addressed and measured in mHealth interventions for mental health problems.

Methods

We conducted a systematic literature review through a search for peer-reviewed studies published between 2001 and 2018 in the following electronic databases: EMBASE, CINAHL, PsycINFO, PubMed, and Web of Science. Two reviewers independently assessed all abstracts against the inclusion and exclusion criteria, following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines.

Results

A total of 299 studies were initially identified based on the inclusion keywords. Following a review of the title, abstract, and full text, 42 studies were found that fulfilled the criteria, most of which evaluated usability with patients (n=29) and health care providers (n=11) as opposed to healthy users (n=8) and were directed at a wide variety of mental health problems (n=24). Half of the studies set out to evaluate usability (n=21), and the remainder focused on feasibility (n=10) or acceptability (n=10). Regarding the maturity of the evaluated systems, most were either prototypes or previously tested versions of the technology, and the studies included few accounts of sketching and participatory design processes. The most common reason referred to for developing mobile mental health apps was the availability of mobile devices to users, their popularity, and how people in general became accustomed to using them for various purposes.

Conclusions

This study provides a detailed account of how evidence of usability of mHealth apps is gathered in the form of usability evaluations from the perspective of computer science and human-computer interaction, including how users feature in the evaluation, how the study objectives and outcomes are stated, which research methods and techniques are used, and what the notion of mobility features is for mHealth apps. Most studies described their methods as trials, gathered data from a small sample size, and carried out a summative evaluation using a single questionnaire, which indicates that usability evaluation was not the main focus. As many studies described using an adapted version of a standard usability questionnaire, there may be a need for developing a standardized mHealth usability questionnaire.

Young People's Response to Six Smartphone Apps for Anxiety and Depression: Focus Group Study

BACKGROUND

Suicide is one of the most frequent causes of death in young people worldwide. Depression lies at the root of this issue, a condition that has a significant negative impact on the lives of those who experience it and on society more generally. However, 80% of affected young people do not obtain professional help for depression and other mental health issues. Therefore, a key challenge is to find innovative and appealing ways to engage young people in learning to manage their mental health. Research suggests that young people prefer to access anonymous Web-based programs rather than get face-to-face help, which has led to the development of numerous smartphone apps. However, the evidence indicates that not all of these apps are effective in engaging the interest of young people who are most in need of help.

OBJECTIVE

The study aimed to investigate young people's response to six currently available smartphone apps for mental health and to identify features that young people like and dislike in such apps.

METHODS

Focus groups were conducted with 23 young people aged 13 to 25 years in which they viewed and used six smartphone apps for mental health. A general inductive approach following a realist paradigm guided data analysis.

RESULTS

The results revealed that young people value autonomy and the opportunity to personalize experiences with these apps above other things. Finding a balance between simplicity and informativeness is also an important factor.

CONCLUSIONS

App developers need to consider using participant-design frameworks to ensure that smartphone apps are providing what young people want in a mental health app. Solutions to the need for personalization and increasing user engagement are also crucially needed.