Digital therapeutics for mental health: Is attrition the Achilles heel?

Smartband-based smoking detection and real-time brief mindfulness intervention: findings from a feasibility clinical trial

BACKGROUND

Smartbands can be used to detect cigarette smoking and deliver real time smoking interventions. Brief mindfulness interventions have been found to reduce smoking.

OBJECTIVE

This single arm feasibility trial used a smartband to detect smoking and deliver brief mindfulness exercises.

METHODS

Daily smokers who were motivated to reduce their smoking wore a smartband for 60 days. For 21 days, the smartband monitored, detected and notified the user of smoking in real time. After 21 days, a 'mindful smoking' exercise was triggered by detected smoking. After 28 days, a 'RAIN' (recognize, allow, investigate, nonidentify) exercise was delivered to predicted smoking. Participants received mindfulness exercises by text message and online mindfulness training. Feasibility measures included treatment fidelity, adherence and acceptability.

RESULTS

Participants (N=155) were 54% female, 76% white non-Hispanic, and treatment starters (n=115) were analyzed. Treatment fidelity cutoffs were met, including for detecting smoking and delivering mindfulness exercises. Adherence was mixed, including moderate smartband use and low completion of mindfulness exercises. Acceptability was mixed, including high helpfulness ratings and mixed user experiences data. Retention of treatment starters was high (81.9%).

CONCLUSIONS

Findings demonstrate the feasibility of using a smartband to track smoking and deliver quit smoking interventions contingent on smoking.

Leveraging Personal Technologies in the Treatment of Schizophrenia Spectrum Disorders: Scoping Review

BACKGROUND

Digital mental health is a rapidly growing field with an increasing evidence base due to its potential scalability and impacts on access to mental health care. Further, within underfunded service systems, leveraging personal technologies to deliver or support specialized service delivery has garnered attention as a feasible and cost-effective means of improving access. Digital health relevance has also improved as technology ownership in individuals with schizophrenia has improved and is comparable to that of the general population. However, less digital health research has been conducted in groups with schizophrenia spectrum disorders compared to other mental health conditions, and overall feasibility, efficacy, and clinical integration remain largely unknown.

OBJECTIVE

This review aims to describe the available literature investigating the use of personal technologies (ie, phone, computer, tablet, and wearables) to deliver or support specialized care for schizophrenia and examine opportunities and barriers to integrating this technology into care.

METHODS

Given the size of this review, we used scoping review methods. We searched 3 major databases with search teams related to schizophrenia spectrum disorders, various personal technologies, and intervention outcomes related to recovery. We included studies from the full spectrum of methodologies, from development papers to implementation trials. Methods and reporting follow the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

This search resulted in 999 studies, which, through review by at least 2 reviewers, included 92 publications. Included studies were published from 2010 to 2023. Most studies examined multitechnology interventions (40/92, 43%) or smartphone apps (25/92, 27%), followed by SMS text messaging (16/92, 17%) and internet-based interventions (11/92, 12%). No studies used wearable technology on its own to deliver an intervention. Regarding the stage of research in the field, the largest number of publications were pilot studies (32/92, 35%), followed by randomized control trials (RCTs; 20/92, 22%), secondary analyses (16/92, 17%), RCT protocols (16/92, 17%), development papers (5/92, 5%), and nonrandomized or quasi-experimental trials (3/92, 3%). Most studies did not report on safety indices (55/92, 60%) or privacy precautions (64/92, 70%). Included studies tend to report consistent positive user feedback regarding the usability, acceptability, and satisfaction with technology; however, engagement metrics are highly variable and report mixed outcomes. Furthermore, efficacy at both the pilot and RCT levels report mixed findings on primary outcomes.

CONCLUSIONS

Overall, the findings of this review highlight the discrepancy between the high levels of acceptability and usability of these digital interventions, mixed efficacy results, and difficulties with sustained engagement. The discussion highlights common patterns that may underscore this observation in the field; however, as this was a scoping review, a more in-depth systematic review or meta-analysis may be required to better understand the trends outlined in this review.

Electronic interventions in primary care to address substance use: A systematic review

The present systematic review aims to identify electronic interventions for addressing substance use and understand their effectiveness in primary care settings. A systematic search was carried out in the Web of Science, PubMed/MEDLINE, Scopus, and Cochrane Library. The search included the keywords "electronic intervention", "substance use", "primary care" and synonyms. To determine the quality and recommendation of the analyzed interventions, the efficacy results reported by the studies were considered, as well as the Mixed Methods Appraisal Tool (MMAT) assessment and the GRADE Evidence Assessment. Twenty-one electronic interventions in Primary Care were identified: internet, mobile or tablet applications, text messages, emails, automated telephone calls, or electronic self-reports. These interventions had diverse components, incorporating theories that have proven effective in face-to-face interventions as their theoretical frameworks. Some of them were complementary to in-person treatment, while others replaced it. Six interventions (28.5 %) displayed high quality: HealthCall, AB-CASI, Quit Genius, eCHECKUP-TOGO, CBI, and TES. Another nine interventions (42.8 %) were found to have moderate-high quality: Alcohol y Salud, IVR-BI, Program of Wallace et al., Let's Talk About Smoking, SMSalud, ESCAPE, AAC-ASPIRE, iQuit, and Programa VIH. One intervention (4.7 %) had moderate-low quality: Vive sin tabaco ¡Decídete! The remaining five interventions (23.8 %) were found to have very low quality: Connection to health, cSBI, Teen Well Check, the program of Helzer et al. (2008), and Down your drink. The programs with the highest recommendation for addressing alcohol-related issues are HealthCall and AB-CASI; for tobacco use, it is Quit Genius; for cannabis use, it is eCHECKUP-TOGO; for addressing both legal and illegal substances, it is CBI and TES. Finally, for specific illicit drug use, the only recommended program is CBI. This last intervention, CBI, is of the highest quality and, therefore, can be considered a model intervention for dissemination in the primary care setting.

Design of Digital Mental Health Platforms for Family Member Cocompletion: Scoping Review

BACKGROUND

The COVID-19 pandemic placed an additional mental health burden on individuals and families, resulting in widespread service access problems. Digital mental health interventions suggest promise for improved accessibility. Recent reviews have shown emerging evidence for individual use and early evidence for multiusers. However, attrition rates remain high for digital mental health interventions, and additional complexities exist when engaging multiple family members together.

OBJECTIVE

As such, this scoping review aims to detail the reported evidence for digital mental health interventions designed for family use with a focus on the build and design characteristics that promote accessibility and engagement and enable cocompletion by families.

METHODS

A systematic literature search of MEDLINE, Embase, PsycINFO, Web of Science, and CINAHL databases was conducted for articles published in the English language from January 2002 to March 2024. Eligible records included empirical studies of digital platforms containing some elements designed for cocompletion by related people as well as some components intended to be completed without therapist engagement. Platforms were included in cases in which clinical evidence had been documented.

RESULTS

Of the 9527 papers reviewed, 85 (0.89%) met the eligibility criteria. A total of 24 unique platforms designed for co-use by related parties were identified. Relationships between participants included couples, parent-child dyads, family caregiver-care recipient dyads, and families. Common platform features included the delivery of content via structured interventions with no to minimal tailoring or personalization offered. Some interventions provided live contact with therapists. User engagement indicators and findings varied and included user experience, satisfaction, completion rates, and feasibility. Our findings are more remarkable for what was absent in the literature than what was present. Contrary to expectations, few studies reported any design and build characteristics that enabled coparticipation. No studies reported on platform features for enabling cocompletion or considerations for ensuring individual privacy and safety. None examined platform build or design characteristics as moderators of intervention effect, and none offered a formative evaluation of the platform itself.

CONCLUSIONS

In this early era of digital mental health platform design, this novel review demonstrates a striking absence of information about design elements associated with the successful engagement of multiple related users in any aspect of a therapeutic process. There remains a large gap in the literature detailing and evaluating platform design, highlighting a significant opportunity for future cross-disciplinary research. This review details the incentive for undertaking such research; suggests design considerations when building digital mental health platforms for use by families; and offers recommendations for future development, including platform co-design and formative evaluation.

The Potential for Digital Phenotyping in Understanding Mindfulness App Engagement Patterns: A Pilot Study

Background: Low app engagement is a central barrier to digital mental health efficacy. With mindfulness-based mental health apps growing in popularity, there is a need for new understanding of factors influencing engagement. This study utilized digital phenotyping to understand real-time patterns of engagement around app-based mindfulness. Different engagement metrics are presented that measure both the total number of app-based activities participants completed each week, as well as the proportion of days that participants engaged with the app each week. Method: Data were derived from two iterations of a four-week study exploring app engagement in college students (n = 169). This secondary analysis investigated the relationships between general and mindfulness-based app engagement with passive data metrics (sleep duration, home time, and screen duration) at a weekly level, as well as the relationship between demographics and engagement. Additional clinically focused analysis was performed on three case studies of participants with high mindfulness activity completion. Results: Demographic variables such as gender, race/ethnicity, and age lacked a significant association with mindfulness app-based engagement. Passive data variables such as sleep and screen duration were significant predictors for different metrics of general and mindfulness-based app engagement at a weekly level. There was a significant interaction effect for screen duration between the number of mindfulness activities completed and whether or not the participant received a mindfulness notification. K-means clusters analyses using passive data features to predict mindfulness activity completion had low performance. Conclusions: While there are no simple solutions to predicting engagement with mindfulness apps, utilizing digital phenotyping approaches at a population and personal level offers new potential. The signal from digital phenotyping warrants more investigation; even small increases in engagement with mindfulness apps may have a tremendous impact given their already high prevalence of engagement, availability, and potential to engage patients across demographics.

A Review of Current Digital Mental Health Care Applications for Anxiety Symptoms and Future Prospects

OBJECTIVE

Since the impact of the coronavirus disease-2019 pandemic, the need for efficiency in medical services has become more urgent than ever. The digital treatment market is rapidly growing worldwide and digital therapeutics (DTx), a major part of the digital medical services, is also emerging as a new paradigm for treatment, with its industry growing rapidly as well. Increasing research is done on the effectiveness of mobile DTx in improving mental health conditions such as insomnia, panic, and depression.

METHODS

This review paper investigates 1) the functions and characteristics of mobile digital mental health care applications for the treatment of anxiety symptoms, 2) extracts common attributes of the applications, and 3) compares them with existing traditional treatment mechanisms.

RESULTS

Among the 20,000 mental health management applications that have been developed so far, 8 applications that are relatively widely used were selected and reviewed. Check-in, self-help tips, quick relief, journal, courses for practice are common features of the digital mental health care applications for anxiety and are also widely used feature in the cognitive behavioral therapy.

CONCLUSION

Based on this review, we have proposed the essential elements and directions for the development of a Korean digital mental health care applications for anxiety disorders.

Not missing at random: Missing data are associated with clinical status and trajectories in an electronic monitoring longitudinal study of bipolar disorder

There is limited information on the association between participants' clinical status or trajectories and missing data in electronic monitoring studies of bipolar disorder (BD). We collected self-ratings scales and sensor data in 145 adults with BD. Using a new metric, Missing Data Ratio (MDR), we assessed missing self-rating data and sensor data monitoring activity and sleep. Missing data were lowest for participants in the midst of a depressive episode, intermediate for participants with subsyndromal symptoms, and highest for participants who were euthymic. Over a mean ± SD follow-up of 246 ± 181 days, missing data remained unchanged for participants whose clinical status did not change throughout the study (i.e., those who entered the study in a depressive episode and did not improve, or those who entered the study euthymic and remained euthymic). Conversely, when participants' clinical status changed during the study (e.g., those who entered the study euthymic and experienced the occurrence of a depressive episode), missing data for self-rating scales increased, but not for sensor data. Overall missing data were associated with participants' clinical status and its changes, suggesting that these are not missing at random.

The Digital Navigator: Standardizing Human Technology Support in App-Integrated Clinical Care

Background: Mental health apps offer scalable care, yet clinical adoption is hindered by low user engagement and integration challenges into clinic workflows. Human support staff called digital navigators, trained in mental health technology, could enhance care access and patient adherence and remove workflow burdens from clinicians. While the potential of this role is clear, training staff to become digital navigators and assessing their impact are primary challenges. Methods: We present a detailed manual/framework for implementation of the Digital Navigator within a short-term, cognitive-behavioral therapy-focused hybrid clinic. We analyze patient engagement, satisfaction, and digital phenotyping data quality outcomes. Data from 83 patients, for the period spanning September 2022 to September 2023, included Digital Navigator satisfaction, correlated with demographics, mindLAMP app satisfaction, engagement, and passive data quality. Additionally, average passive data across 33 clinic patients from November 2023 to January 2024 were assessed for missingness. Results: Digital Navigator satisfaction averaged 18.8/20. Satisfaction was not influenced by sex, race, gender, or education. Average passive data quality across 33 clinic patients was 0.82 at the time this article was written. Digital Navigator satisfaction scores had significant positive correlation with both clinic app engagement and perception of that app. Conclusions: Results demonstrate preliminary support and patient endorsement for the Digital Navigator role and positive outcomes around digital engagement and digital phenotyping data quality. Through sharing training resources and standardizing the role, we aim to enable clinicians and researchers to adapt and utilize the Digital Navigator for their own needs.

A multicenter randomized controlled feasibility trial of a digital self-management intervention for adults with epilepsy

OBJECTIVE

Self-management interventions may enhance health-related quality of life (HRQoL) in epilepsy. However, several barriers often impair their implementation in the real world. Digital interventions may help to overcome some of these barriers. Considering this, the Helpilepsy Plus Prototype was developed as a prototype smartphone-delivered self-care treatment program for adults with epilepsy.

METHODS

The 12-week Helpilepsy Plus Prototype was evaluated through a randomized controlled feasibility trial with a waiting-list control (WLC) group. Outcome measurement at baseline and at 12 weeks assessed adherence to the prototype intervention and changes in epilepsy-related outcomes. The primary endpoint was patient autonomy measured with EASE, and secondary endpoints included HRQoL measured with QOLIE-31, health literacy measured with HLQ, anxiety, and depression symptoms measured with HADS. Semi-structured interviews were conducted with a heterogeneous sample of participants to assess user-friendliness and usefulness. The prototype program was delivered through the Neuroventis Platform (Neuroventis, BV, Overijse, Belgium), a certified medical device (under EU/MDD Class I, and EU/MDR grace period).

RESULTS

Ninety-two patients were included (46 in the intervention group, 46 in WLC). Most participants (63%, 58/92 women, median age 30 years) had pharmacoresistant epilepsy (61%, 56/92). Only 22% of participants (10/46) in the intervention group completed at least half of all intervention sessions. No significant differences between the intervention group and WLC were observed. Although there was a larger proportion of patients in the intervention group with meaningful improvements in HRQoL compared to WLC (19/46 versus 11/46), the difference was not significant (p = 0.119). Qualitative feedback showed that participants would appreciate more personalization, such as adaptation of the content to their current epilepsy knowledge level, a more interactive interface, shorter text sections, and interaction through reminders and notifications.

SIGNIFICANCE

Digital interventions should allow sufficient scope for personalization and interaction to increase patient engagement and enable benefits from self-care apps. Feedback loops allow the participatory development of tailored interventions.

PLAIN LANGUAGE SUMMARY

In this study, we investigated the effectiveness of an app-based self-help intervention. Study participants were either randomly assigned to a group that had access to the app or a group that received access to the app after the end of the study. Although a larger proportion of participants in the intervention group showed a relevant improvement in quality of life, the difference between the two groups was not statistically significant. Less than one-fifth of participants in the intervention group attended at least half of all intervention sessions; patient feedback showed that patients required more personalization and interactive options.

Digital Mental Health for Schizophrenia and Other Severe Mental Illnesses: An International Consensus on Current Challenges and Potential Solutions

BACKGROUND

Digital approaches may be helpful in augmenting care to address unmet mental health needs, particularly for schizophrenia and severe mental illness (SMI).

OBJECTIVE

An international multidisciplinary group was convened to reach a consensus on the challenges and potential solutions regarding collecting data, delivering treatment, and the ethical challenges in digital mental health approaches for schizophrenia and SMI.

METHODS

The consensus development panel method was used, with an in-person meeting of 2 groups: the expert group and the panel. Membership was multidisciplinary including those with lived experience, with equal participation at all stages and coproduction of the consensus outputs and summary. Relevant literature was shared in advance of the meeting, and a systematic search of the recent literature on digital mental health interventions for schizophrenia and psychosis was completed to ensure that the panel was informed before the meeting with the expert group.

RESULTS

Four broad areas of challenge and proposed solutions were identified: (1) user involvement for real coproduction; (2) new approaches to methodology in digital mental health, including agreed standards, data sharing, measuring harms, prevention strategies, and mechanistic research; (3) regulation and funding issues; and (4) implementation in real-world settings (including multidisciplinary collaboration, training, augmenting existing service provision, and social and population-focused approaches). Examples are provided with more detail on human-centered research design, lived experience perspectives, and biomedical ethics in digital mental health approaches for SMI.

CONCLUSIONS

The group agreed by consensus on a number of recommendations: (1) a new and improved approach to digital mental health research (with agreed reporting standards, data sharing, and shared protocols), (2) equal emphasis on social and population research as well as biological and psychological approaches, (3) meaningful collaborations across varied disciplines that have previously not worked closely together, (4) increased focus on the business model and product with planning and new funding structures across the whole development pathway, (5) increased focus and reporting on ethical issues and potential harms, and (6) organizational changes to allow for true communication and coproduction with those with lived experience of SMI. This study approach, combining an international expert meeting with patient and public involvement and engagement throughout the process, consensus methodology, discussion, and publication, is a helpful way to identify directions for future research and clinical implementation in rapidly evolving areas and can be combined with measurements of real-world clinical impact over time. Similar initiatives will be helpful in other areas of digital mental health and similarly fast-evolving fields to focus research and organizational change and effect improved real-world clinical implementation.

Effects of Serious Games in Older Adults With Mild Cognitive Impairment

OBJECTIVE

The rising prevalence of mild cognitive impairment (MCI) has spurred interest in innovative cognitive rehabilitation approaches, including serious games. This review summarizes randomized clinical trials (RCTs) exploring the impact of serious games on MCI patients.

METHODS

We conducted a comprehensive data search using key terms such as "gamification," "digital therapy," "cognition," "mild cognitive impairment," and "Alzheimer's disease." We exclusively considered published RCTs, excluding animal studies and basic research.

RESULTS

We identified eight RCTs. Four RCTs examined the effects of serious games using cognitive training for MCI patients. Notably, one study found that non-specific training (Nintendo Wii) significantly enhanced cognitive function and quality of life compared to cognition-specific computer training (CoTras). Among the remaining three RCTs, one specifically demonstrated that personalized serious game-based cognitive training yielded superior cognitive outcomes and reduced depressive symptoms. One RCT focused on serious games incorporating physical exercise, highlighting the effectiveness of kinetic-based exergaming in enhancing overall cognition. Three RCT focused on combined cognitive training and physical exercise. A double-blind RCT revealed that progressive resistance training or standalone physical exercise outperformed the combined approach in improving executive function and global cognition. Two additional RCTs reported positive outcomes, including improvements in cognitive function and electroencephalogram patterns associated with game-based interventions.

CONCLUSION

Serious games, whether focusing on cognitive training, physical exercise, or a combination of both, have potential to improve cognitive and functional outcomes in individuals with MCI. Further research and standardization of protocols are needed to better understand the full potential of serious games in MCI.

Feasibility and Acceptability of Digital Behavioral Interventions Among Black and Hispanic Patients With Inflammatory Bowel Disease: A Randomized Pilot Study

The use of digital behavioral interventions was tested among patients with inflammatory bowel disease with a predominately low-income, Black/Hispanic background who had elevated symptoms of anxiety/depression. Both mood-tracking and cognitive behavioral self-management applications were feasible and acceptable to use, with opportunities for improvement identified.

Interdisciplinary perspectives on digital technologies for global mental health

Digital Mental Health Technologies (DMHTs) have the potential to close treatment gaps in settings where mental healthcare is scarce or even inaccessible. For this, DMHTs need to be affordable, evidence-based, justice-oriented, user-friendly, and embedded in a functioning digital infrastructure. This viewpoint discusses areas crucial for future developments of DMHTs. Drawing back on interdisciplinary scholarship, questions of health equity, consumer-, patient- and developer-oriented legislation, and requirements for successful implementation of technologies across the globe are discussed. Economic considerations and policy implications complement these aspects. We discuss the need for cultural adaptation specific to the context of use and point to several benefits as well as pitfalls of DMHTs for research and healthcare provision. Nonetheless, to circumvent technology-driven solutionism, the development and implementation of DMHTs require a holistic, multi-sectoral, and participatory approach.

Integrated Digital Mental Health Care: A Vision for Addressing Population Mental Health Needs

The unmet need for mental health care continues to rise across the world. This article synthesizes the evidence supporting the components of a hypothetical model of integrated digital mental health care to meet population-wide mental health needs. This proposed model integrates two approaches to broadening timely access to effective care: integrated, primary care-based mental health services and digital mental health tools. The model solves for several of the key challenges historically faced by digital health, through promoting digital literacy and access, the curation of evidence-based digital tools, integration into clinical practice, and electronic medical record integration. This model builds upon momentum toward the integration of mental health services within primary care and aligns with the principles of the Collaborative Care Model. Finally, the authors present the major next steps toward implementation of integrated digital mental health care at scale.

Predictors of users' adherence to a fully automated digital intervention to manage insomnia complaints

OBJECTIVE

Fully automated digital interventions show promise for disseminating evidence-based strategies to manage insomnia complaints. However, an important concept often overlooked concerns the extent to which users adopt the recommendations provided in these programs into their daily lives. Our objectives were evaluating users' adherence to the behavioral recommendations provided by an app, and exploring whether users' perceptions of the app had an impact on their adherence behavior.

MATERIAL AND METHODS

Case series study of individuals completing a fully automated insomnia management program, conducted by a virtual agent, during December 2020 to September 2022. Primary outcome was self-reported adherence to the behavioral recommendations provided. Perceptions of the app and of the virtual agent were measured with the Acceptability E-Scale and ECA-Trust Questionnaire. Insomnia was evaluated with the Insomnia Severity Index at baseline (phase 1), after 7 days of sleep monitoring (phase 2) and post-intervention (phase 3).

RESULTS

A total of 824 users were included, 62.7% female, mean age 51.85 (±12.55) years. Of them, 32.7% reported having followed at least one recommendation. Users' trust in the virtual agent and acceptance of the app were related to a pre-intervention effect in insomnia severity (phase 2). In turn, larger pre-intervention improvements predicted better adherence. Mediational analyses showed that higher levels of trust in the virtual agent and better acceptance of the app exerted statistically significant positive effects on adherence (β = 0.007, 95% CI, 0.001-0.017 and β = 0.003, 95% CI 0.0004-0.008, respectively).

DISCUSSION

Users' adherence is motivated by positive perceptions of the app's features and pre-intervention improvements.

CONCLUSIONS

Determinants of adherence should be assessed, and targeted, to increase the impact of fully automated digital interventions.

User engagement in a randomised controlled trial for a digital health intervention for early psychosis (Actissist 2.0 trial)

Digital Health Interventions (DHIs) can help support people with mental health problems. Achieving satisfactory levels of patient engagement is a crucial, yet often underexplored, pre-requisite for health improvement. Actissist is a co-produced DHI delivered via a smartphone app for people with early psychosis, based on Cognitive Behaviour Therapy principles. This study describes and compares engagement patterns among participants in the two arms of the Actissist 2.0 randomised controlled trial. Engagement frequency and duration were measured among participants using the Actissist app in the intervention arm (n = 87) and the ClinTouch symptom monitoring only app used as the control condition (n = 81). Overall, 47.1 % of Actissist and 45.7 % of ClinTouch users completed at least a third of scheduled alerts while active in the study. The mean frequency (77.1 versus 60.2 total responses) and the median duration (80 versus 75 days until last response) of engagement were not significantly higher among Actissist users compared to ClinTouch users. Older age, White ethnicity, using their own smartphone device and, among Actissist users, an increased sense of therapeutic alliance were significantly associated with increased engagement. Through exploiting detailed usage data, this study identifies possible participant-level and DHI-level predictors of engagement to inform the practical implementation of future DHIs.

Specifying the Efficacy of Digital Therapeutic Tools for Depression and Anxiety: Retrospective, 2-Cohort, Real-World Analysis

BACKGROUND

Depression and anxiety are the main sources of work and social disabilities as well as health-related problems around the world. Digital therapeutic solutions using cognitive behavioral therapy have demonstrated efficacy in depression and anxiety. A common goal of digital health apps is to increase user digital engagement to improve outcomes. However, there is a limited understanding of the association between digital platform components and clinical outcomes.

OBJECTIVE

The aim of the study is to investigate the contribution of specific digital engagement tools to mental health conditions. We hypothesized that participation in coaching sessions and breathing exercises would be associated with a reduction in depression and anxiety.

METHODS

Depression and general anxiety symptoms were evaluated in real-world data cohorts using the digital health platform for digital intervention and monitoring change. This retrospective real-world analysis of users on a mobile platform-based treatment followed two cohorts of people: (1) users who started with moderate levels of depression and completed at least 2 depression assessments (n=519) and (2) users who started with moderate levels of anxiety and completed at least 2 anxiety assessments (n=474). Levels of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) were tracked throughout the first 16 weeks. A piecewise mixed-effects model was applied to model the trajectories of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 mean scores in 2 segments (1-6 weeks and 7-16 weeks). Finally, simple slope analysis was used for the interpretation of the interactions probing the moderators: coaching sessions and breathing exercises in both depression and anxiety cohorts.

RESULTS

Analysis revealed a significant decrease in depression symptoms (β=-.37, 95% CI -0.46 to 0.28; P≤.001) during the period of weeks 1-6 of app use, which was maintained during the period of 7-16 weeks. Coach interaction significantly moderated the reduction in depression symptoms during the period of weeks 1-6 (β=-.03, 95% CI -0.05 to -0.001; P=.02). A significant decrease in anxiety symptoms (β=-.41, 95% CI -0.50 to -0.33; P≤.001) was revealed during the period of 1-6 weeks, which was maintained during the period of 7-16 weeks. Breathing exercises significantly moderated the reduction in anxiety symptoms during the period of 1-6 weeks (β=-.07, 95% CI -0.14 to -0.01; P=.04).

CONCLUSIONS

This study demonstrated general improvement followed by a period of stability of depression and anxiety symptoms associated with cognitive behavioral therapy-based digital intervention. Interestingly, engagement with a coaching session but not a breathing exercise was associated with a reduction in depression symptoms. Moreover, breathing exercise but not engagement with a coaching session was associated with a reduction of anxiety symptoms. These findings emphasize the importance of using a personalized approach to behavioral health during digital health interventions.

Working towards a ready to implement digital literacy program

Background

As healthcare continues to expand online and digital care offerings multiply, the importance of digital inclusion and equity is now better recognized. Yet despite impressive regional grassroots efforts, today there remain few readily deployable programs designed to support patient digital literacy.

Methods

Digital Outreach for Obtaining Resources and Skills (DOORs) is one such digital literacy program that has evolved over the last 5 years to meet the rising demand. Through community partnerships, the DOORs curriculum and delivery has been updated to make the program more accessible and applicable as Coronavirus Disease 2019 (COVID-19) changes healthcare. Participants' experience in the most updated iteration of DOORS was assessed through surveys and semi-structured interviews.

Results

Improvements to DOORs include an updated DOORs curriculum, updated facilitator manual, an online platform with a learning management system, standardized training, patient-facing educational handouts, consolidation of all DOORs materials into a single package that is ready to be shared with other groups, implementation of a single-session intervention model, and Spanish translation. Participants reported improved confidence on 72% of the digital skills assessed. Thematic analysis resulted in three themes: awareness of divide, patient-centered design, and expanded skills and confidence.

Conclusions

Combined, these changes and participant outcomes better position DOORS to meet the rising need for digital literacy and offers a scalable model for teams across the world.

Assessing Patient Adherence to and Engagement With Digital Interventions for Depression in Clinical Trials: Systematic Literature Review

BACKGROUND

New approaches to the treatment of depression are necessary for patients who do not respond to current treatments or lack access to them because of barriers such as cost, stigma, and provider shortage. Digital interventions for depression are promising; however, low patient engagement could limit their effectiveness.

OBJECTIVE

This systematic literature review (SLR) assessed how participant adherence to and engagement with digital interventions for depression have been measured in the published literature, what levels of adherence and engagement have been reported, and whether higher adherence and increased engagement are linked to increased efficacy.

METHODS

We focused on a participant population of adults (aged ≥18 years) with depression or major depressive disorder as the primary diagnosis and included clinical trials, feasibility studies, and pilot studies of digital interventions for treating depression, such as digital therapeutics. We screened 756 unique records from Ovid MEDLINE, Embase, and Cochrane published between January 1, 2000, and April 15, 2022; extracted data from and appraised the 94 studies meeting the inclusion criteria; and performed a primarily descriptive analysis. Otsuka Pharmaceutical Development & Commercialization, Inc (Princeton, New Jersey, United States) funded this study.

RESULTS

This SLR encompassed results from 20,111 participants in studies using 47 unique web-based interventions (an additional 10 web-based interventions were not described by name), 15 mobile app interventions, 5 app-based interventions that are also accessible via the web, and 1 CD-ROM. Adherence was most often measured as the percentage of participants who completed all available modules. Less than half (44.2%) of the participants completed all the modules; however, the average dose received was 60.7% of the available modules. Although engagement with digital interventions was measured differently in different studies, it was most commonly measured as the number of modules completed, the mean of which was 6.4 (means ranged from 1.0 to 19.7) modules. The mean amount of time participants engaged with the interventions was 3.9 (means ranged from 0.7 to 8.4) hours. Most studies of web-based (34/45, 76%) and app-based (8/9, 89%) interventions found that the intervention group had substantially greater improvement for at least 1 outcome than the control group (eg, care as usual, waitlist, or active control). Of the 14 studies that investigated the relationship between engagement and efficacy, 9 (64%) found that increased engagement with digital interventions was significantly associated with improved participant outcomes. The limitations of this SLR include publication bias, which may overstate engagement and efficacy, and low participant diversity, which reduces the generalizability.

CONCLUSIONS

Patient adherence to and engagement with digital interventions for depression have been reported in the literature using various metrics. Arriving at more standardized ways of reporting adherence and engagement would enable more effective comparisons across different digital interventions, studies, and populations.

The Impact of a Gamified Mobile Mental Health App (eQuoo) on Resilience and Mental Health in a Student Population: Large-Scale Randomized Controlled Trial

BACKGROUND

With many digital mental health interventions failing to engage clients for enough time to demonstrate substantive changes to their well-being and with only 2% of all digital solutions on app stores having undergone randomized controlled trials, the rising demand for mental health prevention and early intervention care is not being met. Young adults in particular struggle to find digital well-being apps that suit their needs.

OBJECTIVE

This study explored the effects of eQuoo, an evidence-based mental health game that teaches psychological skills through gamification, on resilience, depression, anxiety, and attrition in a student population.

METHODS

In total, 1165 students from 180 universities in the United Kingdom participated in a 5-week, 3-armed randomized controlled trial. Participants were randomly allocated into 1 of 3 groups: eQuoo users, users of a treatment-as-usual evidence-based cognitive behavioral health app called Sanvello, and a no-intervention waitlist. The Rugged Resilience Scale, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-8 were administered to all participants at baseline and every 7 days until completion.

RESULTS

A repeated measures-ANOVA revealed statistically significant increases in resilience scores in the test group (P<.001) compared with both control groups (Sanvello: P=.10 and waitlist: P=.82) over 5 weeks. The app also significantly decreased anxiety and depression scores (both P<.001). With 64.5% (251/389) adherence, the eQuoo group retained 42% more participants than the control groups.

CONCLUSIONS

Digital health interventions such as eQuoo are effective, scalable, and low-cost solutions for supporting young adults and are available on all leading mobile platforms. Further investigation could clarify the extent to which specific elements of the eQuoo app (including gamification) led to better outcomes.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS) DRKS00027638; https://drks.de/search/en/trial/DRKS00027638.

Leveraging machine learning to examine engagement with a digital therapeutic

Digital Therapeutics (DTx) are evidence-based software-driven interventions for the prevention, management, and treatment of medical disorders or diseases. DTx offer the unique ability to capture rich objective data about when and how a patient engages with a treatment. Not only can one measure the quantity of patient interactions with a digital treatment with high temporal precision, but one can also assess the quality of these interactions. This is particularly useful for treatments such as cognitive interventions, where the specific manner in which a patient engages may impact likelihood of treatment success. Here, we present a technique for measuring the quality of user interactions with a digital treatment in near-real time. This approach produces evaluations at the level of a roughly four-minute gameplay session (mission). Each mission required users to engage in adaptive and personalized multitasking training. The training included simultaneous presentation of a sensory-motor navigation task and a perceptual discrimination task. We trained a machine learning model to classify user interactions with the digital treatment to determine if they were "using it as intended" or "not using it as intended" based on labeled data created by subject matter experts (SME). On a held-out test set, the classifier was able to reliably predict the SME-derived labels (Accuracy = .94; F1 Score = .94). We discuss the value of this approach and highlight exciting future directions for shared decision-making and communication between caregivers, patients and healthcare providers. Additionally, the output of this technique can be useful for clinical trials and personalized intervention.

Asynchronous Technologies in Mental Health Care and Education

Purpose of review

Patients, providers, and trainees should understand the current types of asynchronous technologies that can be used to enhance the delivery and accessibility of mental health care. Asynchronous telepsychiatry (ATP) removes the need for real time communication between the clinician and patient, which improves efficiency and enables quality specialty care. ATP can be applied as distinct consultative and supervisory models in clinician-to-clinician, clinician-to-patient, and patient-to-mobile health settings.

Recent findings

This review is based on research literature and the authors' clinical and medical training, using experiences with asynchronous telepsychiatry from before, during, and after the COVID-19 pandemic. Our studies demonstrate that ATP provides positive outcomes in the clinician-to-patient model with demonstrated feasibility, outcomes and patient satisfaction. One author's medical education experience in the Philippines during COVID-19 highlights the potential to utilize asynchronous technology in areas with limitations to online learning. We emphasize the need to teach media skills literacy around mental health to students, coaches, therapists, and clinicians when advocating for mental well-being. Several studies have demonstrated the feasibility of incorporating asynchronous e-tools such as self-guided multimedia and artificial intelligence for data collection at the clinician-to-clinician and patient-to-mobile health level. In addition, we offer fresh perspectives on recent trends in asynchronous telehealth in wellness, applying concepts such as "tele-exercise" and "tele-yoga."

Summary

Asynchronous technologies continue to be integrated into mental health care services and research. Future research must ensure that the design and the usability of this technology puts the patient and provider first.

Digital cognitive behavioral therapy for insomnia on depression and anxiety: a systematic review and meta-analysis

Despite research into the development of digital cognitive behavioral therapy for insomnia (dCBT-I), research into the outcomes of dCBT-I on insomnia and the associated clinical conditions of depression and anxiety have been limited. The PubMed, PsycINFO (Ovid), Embase, and Cochrane databases were searched for randomized controlled trials (RCTs) on adult patients with insomnia also having reported measures of depressive or anxiety symptoms. In total, 2504 articles were identified after duplicate removal, and 22 RCTs were included in the final meta-analysis. At the post-treatment assessment, the dCBT-I group had a small to moderate effect in alleviating depressive (standardized mean difference (SMD) = -0.42; 95% CI: -0.56, -0.28; p < 0.001; k = 21) and anxiety symptoms (SMD = -0.29; 95% CI: -0.40, -0.19; p < 0.001; k = 18), but had a large effect on sleep outcome measures (SMD = -0.76; 95% CI: -0.95, -0.57; p < 0.001; k = 22). When considering treatment adherence, the treatment effects of those in the high adherent groups identified a more robust outcome, showing greater effect sizes than those in the low adherent groups for depression, anxiety, and sleep outcomes. Furthermore, additional subgroup analysis on studies that have used the fully automated dCBT-I treatment without the support of human therapists reported significant treatment effects for depression, anxiety, and sleep outcomes. The results demonstrated that digital intervention for insomnia yielded significant effects on alleviating depressive and anxiety symptoms as well as insomnia symptoms. Specifically, the study demonstrated significant effects on the above symptoms when considering treatment adherence and implementing fully automated dCBT-I.

Efficacy of a Mobile-Based Multidomain Intervention to Improve Cognitive Function and Health-Related Outcomes Among Older Korean Adults with Subjective Cognitive Decline

BACKGROUND

Subjective cognitive decline (SCD) is a self-reported experience of declining cognitive function showing normal performance in cognitive assessments, which is a known risk factor for dementia. Recent studies highlight the importance of nonpharmacological multidomain interventions that can target multiple risk factors of dementia in older adults.

OBJECTIVE

This study investigated the efficacy of the Silvia program, a mobile-based multidomain intervention, to improve cognitive function and health-related outcomes of older adults with SCD. We compare its effects to a conventional paper-based multidomain program on various health indicators related to risk factors of dementia.

METHODS

This prospective randomized controlled trial involved 77 older adults with SCD recruited from the Dementia Prevention and Management Center in Gwangju, South Korea during May to October 2022. Participants were randomly assigned to either the mobile- or paper-based group. Interventions were administered for 12 weeks, where pre- and post-assessments were conducted.

RESULTS

The K-RBANS total score did not show significant differences between groups. The mobile group showed better improvement in K-PRMQ scores and PSS scores than the paper group. Differences within groups showed that mobile-based interventions significantly improved K-PRMQ, STAI-X-1, PSS, and EQ-5D-5 L scores, while paper-based interventions significantly improved PSS, and EQ-5D-5 L scores. Patient adherence rate was 76.6%.

CONCLUSION

Overall, the Silvia program was effective for improving self-reported memory failures, stress, anxiety, and health-related quality of life in older adults with SCD. However, longer periods of administration for more than 12 weeks may be needed to achieve significant improvements in cognitive function by objective measures.

An exploratory analysis of the effect size of the mobile mental health Application, mindLAMP

Objectives

Despite the proliferation of mobile mental health apps, evidence of their efficacy around anxiety or depression is inadequate as most studies lack appropriate control groups. Given that apps are designed to be scalable and reusable tools, insights concerning their efficacy can also be assessed uniquely through comparing different implementations of the same app. This exploratory analysis investigates the potential to report a preliminary effect size of an open-source smartphone mental health app, mindLAMP, on the reduction of anxiety and depression symptoms by comparing a control implementation of the app focused on self-assessment to an intervention implementation of the same app focused on CBT skills.

Methods

A total of 328 participants were eligible and completed the study under the control implementation and 156 completed the study under the intervention implementation of the mindLAMP app. Both use cases offered access to the same in-app self-assessments and therapeutic interventions. Multiple imputations were utilized to impute the missing Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9 survey scores of the control implementation.

Results

Post hoc analysis revealed small effect sizes of Hedge's g = 0.34 for Generalized Anxiety Disorder-7 and Hedge's g = 0.21 for Patient Health Questionnaire-9 between the two groups.

Conclusions

mindLAMP shows promising results in improving anxiety and depression outcomes in participants. Though our results mirror the current literature in assessing mental health apps' efficacy, they remain preliminary and will be used to inform a larger, well-powered study to further elucidate the efficacy of mindLAMP.

Smartphone app engagement and clinical outcomes in a hybrid clinic

Despite the growing prevalence of mental health-related smartphone apps, low real-world engagement has prevented these apps from transforming the mental health landscape. Integrating mental health apps into more traditional therapeutic models appears to support better clinical outcomes, but also raises questions about the relationship between app engagement, the app itself, and the coach or clinician. This study explores patient app engagement patterns and the associated clinical outcomes gathered from piloting a digital clinic. Patients with anxiety or depression completed eight clinical visits and coach visits over a median of 83 days with a standard deviation of 17.25 days. Between clinical visits, patients completed therapeutic activities on the mindLAMP app. Mean PHQ-9 and GAD-7 scores decreased from the intake visit to both visit 4 and visit 8. Patients had high app engagement, but engagement did not correlate with outcomes. From intake visit to visit 4, the interaction effects indicate significant differences in the change of both PHQ-9 and GAD-7 depending on participants' average app satisfaction and clinician/coach satisfaction (as measured by WAI-SR) with engagement. Overall, results support the feasibility of incorporating an app into a hybrid clinic.