Digital Mental Health Interventions for Depression: Scoping Review of User Engagement

Can an app designed to reduce repetitive negative thinking decrease depression and anxiety in young people? Results from a randomized controlled prevention trial

BACKGROUND AND OBJECTIVES

Rates of mental health disorders are rising among adolescents and young adults. Therefore, scalable methods for preventing psychopathology in these age groups are needed. As repetitive negative thinking (RNT) is a risk factor for depression and anxiety disorders, targeting RNT via smartphone app promises to be an effective, scalable strategy. The current three-arm, parallel group, randomized controlled trial tested whether a self-help app designed to reduce RNT decreased psychopathological symptoms and RNT in adolescents and young adults at risk for mental disorders.

METHOD

A sample of 16-22-year-olds with elevated levels of RNT (N = 365) were randomly allocated to either use a one of two self-help apps designed to reduce RNT for 6 weeks or to a waitlist. The full RNT-focused intervention app encompassed a variety of RNT-reducing strategies, whereas the concreteness training app focused on one of these strategies, namely, concrete thinking.

RESULTS

The apps did not decrease depressive symptoms, anxiety symptoms and RNT relative to the waitlist. However, exploratory analyses using a minimum dose criterion showed that participants who used the full-RNT-focused intervention app more often, reported greater baseline to follow-up decreases in depressive symptoms compared to waitlist.

LIMITATIONS

Include decreased power due to slightly more dropout than expected and limited generalizability due to the mostly female and highly educated sample.

CONCLUSIONS

RNT-focused prevention via a self-help app did not decrease depression and anxiety, presumably due to too little engagement with the app content provided.

Patterns of Skills Review in Smartphone Cognitive Behavioral Therapy for Depression: Observational Study of Intervention Content Use

BACKGROUND

Smartphones could enhance access to effective cognitive behavioral therapy (CBT). Users may frequently and flexibly access bite-size CBT content on personal devices, review and practice skills, and thereby achieve better outcomes.

OBJECTIVE

We explored the distribution of actual interactions participants had with therapeutic content in a trial of smartphone CBT for depression and whether interactions were within assigned treatment modules or revisits to prior module content (ie, between-module interactions).

METHODS

We examined the association between the number of within- and between-module interactions and baseline and end-of-treatment symptom severity during an 8-week, single-arm open trial of a therapist-guided CBT for depression mobile health app.

RESULTS

Interactions were more frequent early in treatment and modestly declined in later stages. Within modules, most participants consistently made more interactions than required to progress to the next module and tended to return to all types of content rather than focus on 1 skill. By contrast, only 15 of 26 participants ever revisited prior module content (median number of revisits=1, mode=0, IQR 0-4). More revisits were associated with more severe end-of-treatment symptom severity after controlling for pretreatment symptom severity (P<.05).

CONCLUSIONS

The results suggest that the frequency of use is an insufficient metric of engagement, lacking the nuance of what users are engaging with and when during treatment. This lens is essential for developing personalized recommendations and yielding better treatment outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05386329; https://clinicaltrials.gov/study/NCT05386329?term=NCT05386329.

Initial Requirements for the Prototyping of an App for a Psychosocial Rehabilitation Project: An Integrative Review

The Psychosocial Rehabilitation Project (PRP) is a tool designed to structure and organize mental health care, guided by the theoretical and practical principles of Psychosocial Rehabilitation (PR). This article aims to identify the initial requirements for the prototyping of a "Psychosocial Rehabilitation Project App". To achieve this, an integrative review was conducted with the research question: what initial requirements are important to compose the prototype of the "Psychosocial Rehabilitation Project App" in mental health? In the search process, 834 articles were identified and exported to the online systematic review application Rayyan QCRI, resulting in 36 eligible articles for this study, along with one app. The reading of this material allowed the elicitation of three themes: privacy and data protection policy; design; and software and programming. The prototyping of the "Psychosocial Rehabilitation Project App" should prioritize data security and protection, simplicity in design, and the integration of technological resources that facilitate the management, construction, monitoring, and evaluation of psychosocial rehabilitation projects by mental health professionals.

Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study

BACKGROUND

Digital mental health is a promising paradigm for individualized, patient-driven health care. For example, cognitive bias modification programs that target interpretation biases (cognitive bias modification for interpretation [CBM-I]) can provide practice thinking about ambiguous situations in less threatening ways on the web without requiring a therapist. However, digital mental health interventions, including CBM-I, are often plagued with lack of sustained engagement and high attrition rates. New attrition detection and mitigation strategies are needed to improve these interventions.

OBJECTIVE

This paper aims to identify participants at a high risk of dropout during the early stages of 3 web-based trials of multisession CBM-I and to investigate which self-reported and passively detected feature sets computed from the participants interacting with the intervention and assessments were most informative in making this prediction.

METHODS

The participants analyzed in this paper were community adults with traits such as anxiety or negative thinking about the future (Study 1: n=252, Study 2: n=326, Study 3: n=699) who had been assigned to CBM-I conditions in 3 efficacy-effectiveness trials on our team's public research website. To identify participants at a high risk of dropout, we created 4 unique feature sets: self-reported baseline user characteristics (eg, demographics), self-reported user context and reactions to the program (eg, state affect), self-reported user clinical functioning (eg, mental health symptoms), and passively detected user behavior on the website (eg, time spent on a web page of CBM-I training exercises, time of day during which the exercises were completed, latency of completing the assessments, and type of device used). Then, we investigated the feature sets as potential predictors of which participants were at high risk of not starting the second training session of a given program using well-known machine learning algorithms.

RESULTS

The extreme gradient boosting algorithm performed the best and identified participants at high risk with macro-F1-scores of .832 (Study 1 with 146 features), .770 (Study 2 with 87 features), and .917 (Study 3 with 127 features). Features involving passive detection of user behavior contributed the most to the prediction relative to other features. The mean Gini importance scores for the passive features were as follows: .033 (95% CI .019-.047) in Study 1; .029 (95% CI .023-.035) in Study 2; and .045 (95% CI .039-.051) in Study 3. However, using all features extracted from a given study led to the best predictive performance.

CONCLUSIONS

These results suggest that using passive indicators of user behavior, alongside self-reported measures, can improve the accuracy of prediction of participants at a high risk of dropout early during multisession CBM-I programs. Furthermore, our analyses highlight the challenge of generalizability in digital health intervention studies and the need for more personalized attrition prevention strategies.

Brief Video-Delivered Intervention to Reduce Anxiety and Improve Functioning in Older Veterans: Pilot Randomized Controlled Trial

BACKGROUND

Older veterans with anxiety disorders encounter multiple barriers to receiving mental health services, including transportation difficulties, physical limitations, and limited access to providers trained to work with older persons. To address both accessibility and the shortage of available providers, evidence-based treatments that can be delivered via guided self-management modalities are a potential solution.

OBJECTIVE

This study aims to determine the feasibility and acceptability of a randomized controlled trial of 2 guided self-management interventions. This study compared the treatment effects of these 2 interventions (relaxation and health psychoeducation) on anxiety symptom severity and functioning in older veterans with anxiety disorders. Our exploratory aims examined factors related to home practices and treatment engagement and perceptions of the practices.

METHODS

Participants were randomized to one of two video-delivered interventions: (1) Breathing, Relaxation, and Education for Anxiety Treatment in the Home Environment (BREATHE)-breathing and progressive relaxation or (2) Healthy Living for Reduced Anxiety-psychoeducation about lifestyle changes. Telephone coaching calls were conducted weekly. Measures of anxiety, depression, and functioning were obtained at baseline, week 4 (end of treatment), week 8, and week 12. Participants completed a semistructured interview at week 12. Analyses included descriptive statistics to summarize measures of intervention engagement; mixed-effects models to characterize symptom change, and qualitative analyses.

RESULTS

Overall, 56 participants (n=48, 86% men; n=23, 41% from ethnic or racial minority groups; mean age 71.36, SD 6.19 y) were randomized. No difference in retention between study arms was found. The Healthy Living group (29/56, 52%) completed significantly more lessons (mean 3.68, SD 0.86) than the BREATHE group (27/56, 48%; mean 2.85, SD 1.43; t53=2.60; P=.01) but did not differ in completion of coaching calls. In the BREATHE group, greater baseline anxiety scores (r=-0.41; P=.03) and greater severity of medical comorbidity (r=-0.50; P=.009) were associated with fewer completed practices. There was no effect of intervention on change in total anxiety scores or functioning. For specific anxiety subtypes, Healthy Living produced a greater decline in somatic anxiety compared with BREATHE. Qualitative analyses found barriers to practicing, including difficulty setting time aside to practice, forgetting, or having other activities that interfered with BREATHE practices. Some participants described adapting their practice routine to fit their daily lives; some also used relaxation skills in everyday situations.

CONCLUSIONS

These findings suggest that a larger randomized controlled trial of guided self-management approaches to treating late-life anxiety is feasible; however, BREATHE was not effective in reducing anxiety compared with Healthy Living. Possible contributing factors may have been the reliance on a single technique. Progressive relaxation was reported to be enjoyable for most participants, but maintaining home practices was challenging. Those with milder anxiety severity and fewer health problems were better able to adhere to practices.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02400723; https://clinicaltrials.gov/study/NCT02400723.

A Personalized, Transdiagnostic Smartphone App (Mello) Targeting Repetitive Negative Thinking for Depression and Anxiety: Qualitative Analysis of Young People's Experience

BACKGROUND

The increasing rates of mental health challenges among young people highlight an urgent need for accessible and effective treatment. However, current mental health systems face unprecedented demand, leaving most young people globally with unmet mental health needs. Smartphones present a promising solution to this issue by offering in-the-moment support through innovative just-in-time adaptive interventions, which provide support based on real-time data.

OBJECTIVE

This study explores young people's experiences with Mello, a just-in-time adaptive intervention that focuses on the transdiagnostic mechanism of repetitive negative thinking (RNT), a significant factor contributing to youth depression and anxiety.

METHODS

Semistructured qualitative interviews were conducted with 15 participants aged 16 to 25 years, all of whom had previously participated in a pilot randomized controlled trial of Mello. Of the 15 participants, 9 (60%) identified as women, 4 (27%) as men (including 1 transgender man), and 2 (13%) as nonbinary. Interviews focused on participants' experiences with the Mello app, factors influencing engagement, perceived benefits and limitations, and suggestions for future improvements. Thematic analysis was used to analyze the data.

RESULTS

The analysis identified three superordinate themes: Mello as a tool for intentional reflection; doing therapy your own way; and barriers to engagement during low mood, anxiety, and RNT. Theme 1 explored young people's experiences of how the app facilitated active management of negative thoughts and supported the development of reflective habits, contrasting with their typical strategies of avoidance or resistance. Theme 2 highlighted the value of the app's self-guided nature, with a particular focus on its flexibility and accessibility, particularly when compared to traditional face-to-face therapy. Finally, theme 3 addressed barriers to engagement, particularly during emotionally difficult times, with participants reporting feeling "stuck" in their negative thoughts. To mitigate these challenges, participants suggested incorporating gamification elements, such as progress-tracking visuals, to enhance motivation and increase engagement with the app.

CONCLUSIONS

Our findings underscored the value of Mello in promoting intentional engagement and reflection with RNT, consistent with prior research that emphasizes the effectiveness of tailored interventions. Although some users valued the self-guided nature of the application, others encountered difficulties with motivation. Future research should explore strategies to enhance engagement for young people with low mood and motivation, such as co-design methodologies, advanced personalization features, and gamification techniques.

Virtual Coach-Guided Online Acceptance and Commitment Therapy for Chronic Pain: Pilot Feasibility Randomized Controlled Trial

BACKGROUND

Veterans are disproportionately affected by chronic pain, with high rates of pain diagnoses (47%-56%) and a 40% higher rate of prevalence of severe pain than nonveterans. This is often accompanied by negative functional outcomes and higher mortality. Combined with research suggesting medical treatments for chronic pain are often insufficient, there is an urgent need for nonmedical pain self-management programs. An interactive online platform to deliver an efficacious treatment for chronic pain such as acceptance and commitment therapy (ACT) could be a valuable option to assist veterans with pain care at home.

OBJECTIVE

This study aims to evaluate the virtual coach-guided Veteran ACT for Chronic Pain (VACT-CP) online program compared to a waitlist and treatment as usual (WL+TAU) control group through a small pilot feasibility randomized controlled trial. The primary aim was to evaluate the feasibility and acceptability of VACT-CP and study procedures, such as ease of recruitment, treatment receptivity, attrition and retention, sustained participation, system usability, and assessment of trial procedures. Secondary aims explored differences in the VACT-CP and WL+TAU groups on pre- and posttest (week 7) outcome measures for pain, mental health, functioning, and ACT processes.

METHODS

Veterans with chronic pain were recruited and randomized to either the VACT-CP (n=20) or the WL+TAU (n=22) group in a parallel group trial design. Self-report surveys were administered to participants at baseline (week 0), at the intervention midpoint (week 3), immediately after the intervention (week 7), and at the 1-month follow-up (week 11). We used Wilcoxon signed rank tests with the intention-to-treat sample to describe changes in secondary outcomes from pre- to postintervention within each group.

RESULTS

Study procedures showed good feasibility related to recruitment, enrollment, randomization, and study completion rates. Participants reported that VACT-CP was easy to use (System Usability Scale: mean 79.6, SD 12.8; median 82.5, IQR 70-87.5); they completed an average of 5 of the 7 total VACT-CP modules with high postintervention satisfaction rates. Qualitative feedback suggested a positive response to program usability, content tailoring, veteran centeredness, and perceived impact on pain management. Although the pilot feasibility trial was not powered to detect differences in clinical outcomes and significant findings should be interpreted with caution, the VACT-CP group experienced significant increases in chronic pain acceptance (P<.001) and decreases in depressive symptoms (P=.03).

CONCLUSIONS

VACT-CP showed encouraging evidence of feasibility, usability, and acceptance, while also providing promising initial results in improving a key process in ACT for chronic pain-chronic pain acceptance-after online program use. A full-scale efficacy trial is needed to assess changes in clinical outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03655132; http://clinicaltrials.gov/ct2/show/NCT03655132.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/45887.

Predictors of adherence to a publicly available self-guided digital mental health intervention

Low adherence to self-guided digital mental health interventions (DMHIs) have raised concerns about their real-world effectiveness. Naturalistic data from self-guided DMHIs are often not available, hindering our ability to assess adherence among real-world users. This study aimed to analyze 3 years of user data from the public launch of an empirically supported 12-session self-guided DMHI, to assess overall program adherence rates and explore predictors of adherence. Data from 984 registered users were analyzed. Results showed that only 14.8% of users completed all 12 modules and 68.6% completed less than half of the modules. Users who were younger, had milder depression, had never seen a mental health provider, and who rejected signing-up for weekly program emails completed significantly more modules. Results add to concerns about the generalizability of controlled research on DMHIs due to lower adherence outside of research trials. This study highlights the potential of user data in identifying key factors that may be related to adherence. By examining adherence patterns among different sub-sets of users, we can pinpoint and focus on individuals who may adhere and benefit more from self-guided programs. Findings could also have implications for guiding intervention personalization for individuals who struggle to complete DMHIs.

Evaluating the Implementation and Clinical Effectiveness of an Innovative Digital First Care Model for Behavioral Health Using the RE-AIM Framework: Quantitative Evaluation

BACKGROUND

In the United States, innovation is needed to address the increasing need for mental health care services and widen the patient-to-provider ratio. Despite the benefits of digital mental health interventions (DMHIs), they have not been effective in addressing patients' behavioral health challenges as stand-alone treatments.

OBJECTIVE

This study evaluates the implementation and effectiveness of precision behavioral health (PBH), a digital-first behavioral health care model embedded within routine primary care that refers patients to an ecosystem of evidence-based DMHIs with strategically placed human support.

METHODS

Patient demographic information, triage visit outcomes, multidimensional patient-reported outcome measure, enrollment, and engagement with the DMHIs were analyzed using data from the electronic health record and vendor-reported data files. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework was used to evaluate the implementation and clinical effectiveness outcomes of PBH.

RESULTS

PBH had a 47.58% reach rate, defined as patients accepting the PBH referral from their behavioral health integrated clinician. PBH patients had high DMHI registration rates (79.62%), high activation rates (76.54%), and high retention rates at 15 days (57.69%) and 30 days (44.58%) compared to literature benchmarks. In total, 74.01% (n=168) of patients showed clinical improvement, 22.47% (n=51) showed no clinical change, and 3.52% (n=8) showed clinical deterioration in symptoms. PBH had high adoption rates, with behavioral health integrated clinicians referring on average 4.35 (SD 0.46) patients to PBH per month and 90%-100% of clinicians (n=12) consistently referring at least 1 patient to PBH each month. A third (32%, n=1114) of patients were offered PBH as a treatment option during their triage visit.

CONCLUSIONS

PBH as a care model with evidence-based DMHIs, human support for patients, and integration within routine settings offers a credible service to support patients with mild to moderate mental health challenges. This type of model has the potential to address real-life access to care problems faced by health care settings.

Blended Psychological Therapy for the Treatment of Psychological Disorders in Adult Patients: Systematic Review and Meta-Analysis

BACKGROUND

Blended therapy (BT) combines digital with face-to-face psychological interventions. BT may improve access to treatment, therapy uptake, and adherence. However, research is scarce on the structure of BT models.

OBJECTIVE

We synthesized the literature to describe BT models used for the treatment of psychological disorders in adults. We investigated whether BT structure, content, and ratio affected treatment efficacy, uptake, and adherence. We also conducted meta-analyses to examine treatment efficacy in intervention-control dyads and associations between treatment outcomes versus BT model structure.

METHODS

PsycINFO, CINAHL, Embase, ProQuest, and MEDLINE databases were searched. Eligibility criteria included articles published in English till March 2023 that described digital and face-to-face elements as part of an intervention plan for treating psychological disorders in adult patients. We developed a coding framework to characterize the BT interventions. A meta-analysis was conducted to calculate effect size (ES; Cohen d and 95% CIs) regarding pre- and posttreatment outcomes in depression and anxiety versus BT structure. The review was registered with PROSPERO and followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

Searches identified 8436 articles, and data were extracted from 29 studies. BT interventions were analyzed and classified according to mode of interaction between digital and face-to-face components (integrated vs sequential), role of the components (core vs supplementary), component delivery (alternate vs case-by-case), and digital materials assignment mode (standardized vs personalized). Most BT interventions (n=24) used a cognitive behavioral therapy approach for anxiety or depression treatment. Mean rates of uptake (91%) and adherence (81%) were reported across individual studies. BT interventions were more effective or noninferior to treatment as usual, with large spread in the data and a moderate to large ES in the treatment of depression (n=9; Cohen d=-1.1, 95% CI -0.6 to -1.6, P<.001, and z score=-4.3). A small, nonsignificant ES was found for anxiety outcomes (n=5; Cohen d=-0.1, 95% CI -0.3 to 0.05, P=.17, and z score=-1.4). Higher ESs were found in blended interventions with supplementary design (depression: n=11, Cohen d=-0.75, 95% CI -0.56 to -0.95; anxiety: n=8, Cohen d=-0.9, 95% CI -0.6 to -1.2); fewer (≤6) face-to-face sessions (depression: n=9, Cohen d=-0.7, 95% CI -0.5 to -0.9; anxiety: n=7, Cohen d=-0.8, 95% CI -0.3 to -1.3); and a lower ratio (≤50%) of face-to-face versus digital sessions (depression: n=5, Cohen d=-0.8, 95% CI -0.6 to -1.1; anxiety: n=4, Cohen d=-0.8, 95% CI 0.006 to -1.6).

CONCLUSIONS

This study confirmed integrated BT models as feasible to deliver. We found BT to be effective in depression treatment, but anxiety treatment results were nonsignificant. Future studies assessing outcomes across different psychological disorders and therapeutic approaches are required.

TRIAL REGISTRATION

PROSPERO CRD42021258977; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=258977.

Clinical Effects of Asynchronous Provider-Guided Practice Sessions During Blended Care Therapy for Anxiety and Depression: Pragmatic Retrospective Cohort Study

BACKGROUND

Blended care therapy models are intended to increase the efficiency and effectiveness of evidence-based psychotherapy by combining synchronous and asynchronous components of care.

OBJECTIVE

This retrospective cohort study evaluated the clinical effects of synchronous video therapy sessions and asynchronous guided practice session elements on anxiety and depression in a blended care therapy program, with a novel focus on asynchronous provider feedback messages.

METHODS

Participants were adults (N=33,492) with clinical symptoms of anxiety (Generalized Anxiety Disorder 7-item scale [GAD-7] score of ≥8) and depression (Patient Health Questionnaire 9-item scale [PHQ-9] score of ≥10) at intake. Symptom trajectories were evaluated via individual growth curve models. Time-varying covariates evaluated effects of synchronous video session attendance and the presence or absence of each asynchronous guided practice session element occurring within 7 days and 8-14 days prior to each clinical outcome assessment. Guided practice session elements included client digital lesson completion, client digital exercise completion, and feedback messages sent by providers.

RESULTS

Approximately 86.6% (29,012/33,492) of clients met criteria for clinical improvement by end of care (median 6, IQR 4-8 synchronous sessions). Synchronous video session attendance and client digital lesson completion in the past 7 days and in the past 8-14 days were each uniquely and significantly associated with lower GAD-7 scores (video session effects: bsession7=-0.82, bsession8-14=-0.58, P values<.001; digital lesson effects: blesson7=-0.18, blesson8-14=-0.26, P values <.001) and PHQ-9 scores (video session effects: bsession7=-0.89, bsession8-14=-0.67, P values <.001; digital lesson effects: blesson7=-0.12, blesson8-14=-0.30, P values <.001). Client digital exercise completion in the past 8-14 days was significantly associated with lower GAD-7 scores (bexercise8-14=-0.10; P<.001) but exercise completion in the 7 days prior to clinical outcome assessment was not (bexercise7=0.00; P=.89). Exercise completion in the past 7 days was significantly associated with lower PHQ-9 scores (bexercise7=-0.16; P<.001) but exercise completion in the past 8-14 days was not (bexercise8-14=-0.05; P=.09). Provider feedback messaging in the past 7 days and in the past 8-14 days was significantly associated with lower GAD-7 and PHQ-9 scores, respectively (GAD-7: bfeedback7=-0.12, P<.001; bfeedback8-14=-0.07, P=.004; PHQ-9: bfeedback7=-0.15, P<.001; bfeedback8-14=-0.08, P=.01).

CONCLUSIONS

Provider feedback between synchronous therapy sessions provided significant benefit for symptom reduction, beyond the effects of client digital engagement and synchronous video sessions. When guided practice sessions are well integrated into care, blended care therapy provides meaningful improvements upon the traditional, synchronous session-only therapy model. Provider guidance and feedback for clients between synchronous sessions support more efficient and effective mental health care overall.

User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review

BACKGROUND

There are numerous mobile health (mHealth) interventions for treatment adherence and self-management; yet, little is known about user engagement or interaction with these technologies.

OBJECTIVE

This systematic review aimed to answer the following questions: (1) How is user engagement defined and measured in studies of mHealth interventions to promote adherence to prescribed medical or health regimens or self-management among people living with a health condition? (2) To what degree are patients engaging with these mHealth interventions? (3) What is the association between user engagement with mHealth interventions and adherence or self-management outcomes? (4) How often is user engagement a research end point?

METHODS

Scientific database (Ovid MEDLINE, Embase, Web of Science, PsycINFO, and CINAHL) search results (2016-2021) were screened for inclusion and exclusion criteria. Data were extracted in a standardized electronic form. No risk-of-bias assessment was conducted because this review aimed to characterize user engagement measurement rather than certainty in primary study results. The results were synthesized descriptively and thematically.

RESULTS

A total of 292 studies were included for data extraction. The median number of participants per study was 77 (IQR 34-164). Most of the mHealth interventions were evaluated in nonrandomized studies (157/292, 53.8%), involved people with diabetes (51/292, 17.5%), targeted medication adherence (98/292, 33.6%), and comprised apps (220/292, 75.3%). The principal findings were as follows: (1) >60 unique terms were used to define user engagement; "use" (102/292, 34.9%) and "engagement" (94/292, 32.2%) were the most common; (2) a total of 11 distinct user engagement measurement approaches were identified; the use of objective user log-in data from an app or web portal (160/292, 54.8%) was the most common; (3) although engagement was inconsistently evaluated, most of the studies (99/195, 50.8%) reported >1 level of engagement due to the use of multiple measurement methods or analyses, decreased engagement across time (76/99, 77%), and results and conclusions suggesting that higher engagement was associated with positive adherence or self-management (60/103, 58.3%); and (4) user engagement was a research end point in only 19.2% (56/292) of the studies.

CONCLUSIONS

The results revealed major limitations in the literature reviewed, including significant variability in how user engagement is defined, a tendency to rely on user log-in data over other measurements, and critical gaps in how user engagement is evaluated (infrequently evaluated over time or in relation to adherence or self-management outcomes and rarely considered a research end point). Recommendations are outlined in response to our findings with the goal of improving research rigor in this area.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022289693; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022289693.

We Have Spent Time, Money, and Effort Making Self-Help Digital Mental Health Interventions: Is Anyone Going to Come to the Party?

Although efficacious psychotherapies exist, a limited number of mental health care providers and significant demand make their accessibility a fundamental problem. Clinical researchers, funders, and investors alike have converged on self-help digital mental health interventions (self-help DMHIs) as a low-cost, low-burden, and broadly scalable solution to the global mental health burden. Consequently, exorbitant financial and time-based resources have been invested in developing, testing, and disseminating these interventions. However, the public's assumed desirability for self-help DMHIs by experts has largely proceeded without question. This commentary critically evaluates whether self-help DMHIs can, and will, reach their purported potential as a solution to the public burden of mental illness, with an emphasis on evaluating their real-world desirability. Our review finds that self-help DMHIs are often perceived as less desirable and credible than in-person treatments, with lower usage rates and, perhaps accordingly, clinical trials testing self-help DMHIs suffering from widespread recruitment challenges. We highlight two fundamental challenges that may be interfering with the desirability of, and engagement in, self-help DMHIs: (1) difficulty competing with technology companies that have advantages in resources, marketing, and user experience design (but may not be delivering evidence-based interventions) and (2) difficulty retaining (vs initially attracting) users. We discuss a range of potential solutions, including highlighting self-help DMHIs in public mental health awareness campaigns; public education about evidence-based interventions that can guide consumers to appropriate self-help DMHI selection; increased financial and expert support to clinical researchers for marketing, design, and user experience in self-help DMHI development; increased involvement of stakeholders in the design of self-help DMHIs; and investing in more research on ways to improve retention (versus initial engagement). We suggest that, through these efforts, self-help DMHIs may fully realize their promise for reducing the global burden of mental illness.

Reflections on Integrating a Therapist-guided CBT Website Into Routine Clinical Practice

Psychotherapy remains a scarce resource for patients, as problems such as provider shortages result in waitlists and lack of timely access. In their academic medical center outpatient clinic, the coauthors piloted use of a therapist-guided CBT website, Good Days Ahead, in routine clinical practice. They reflect on the benefits and challenges of this approach in this guest column.

The Acceptability, Engagement, and Feasibility of Mental Health Apps for Marginalized and Underserved Young People: Systematic Review and Qualitative Study

BACKGROUND

Smartphone apps may provide an opportunity to deliver mental health resources and interventions in a scalable and cost-effective manner. However, young people from marginalized and underserved groups face numerous and unique challenges to accessing, engaging with, and benefiting from these apps.

OBJECTIVE

This study aims to better understand the acceptability (ie, perceived usefulness and satisfaction with an app) and feasibility (ie, the extent to which an app was successfully used) of mental health apps for underserved young people. A secondary aim was to establish whether adaptations can be made to increase the accessibility and inclusivity of apps for these groups.

METHODS

We conducted 2 sequential studies, consisting of a systematic literature review of mental health apps for underserved populations followed by a qualitative study with underserved young male participants (n=20; age: mean 19). Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, an electronic search of 5 databases was conducted in 2021. The search yielded 18,687 results, of which 14 articles met the eligibility criteria.

RESULTS

The included studies comprised a range of groups, including those affected by homelessness, having physical health conditions, living in low- and middle-income countries, and those with sexual and gender minority identities. Establishing and maintaining user engagement was a pervasive challenge across mental health apps and populations, and dropout was a reported problem among nearly all the included studies. Positive subjective reports of usability, satisfaction, and acceptability were insufficient to determine users' objective engagement.

CONCLUSIONS

Despite the significant amount of funding directed to the development of mental health apps, juxtaposed with only limited empirical evidence to support their effectiveness, few apps have been deliberately developed or adapted to meet the heterogeneous needs of marginalized and underserved young people. Before mental health apps are scaled up, a greater understanding is needed of the types of services that more at-risk young people and those in limited-resource settings prefer (eg, standard vs digital) followed by more rigorous and consistent demonstrations of acceptability, effectiveness, and cost-effectiveness. Adopting an iterative participatory approach by involving young people in the development and evaluation process is an essential step in enhancing the adoption of any intervention, including apps, in "real-world" settings and will support future implementation and sustainability efforts to ensure that marginalized and underserved groups are reached.

TRIAL REGISTRATION

PROSPERO CRD42021254241; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=254241.

The Impact of User Engagement With Exposure Components on Posttraumatic Stress Symptoms in an mHealth Mobile App: Secondary Analysis of a Randomized Controlled Trial

Background

Mobile mental health apps are a cost-effective option for managing mental health problems, such as posttraumatic stress disorder (PTSD). The efficacy of mobile health (mHealth) apps depends on engagement with the app, but few studies have examined how users engage with different features of mHealth apps for PTSD.

Objective

This study aims to examine the relationship between app engagement indices and PTSD symptom reduction using data from an unblinded pilot randomized controlled trial of "Renew" (Vertical Design), an exposure-based app for PTSD with and without coaching support. Because exposure is an effective approach for treating PTSD, we expected that engagement with exposure activities would be positively related to symptom reduction, over and above overall app usage.

Methods

Participants were veterans (N=69) with clinically significant PTSD symptoms who were recruited online using Facebook advertisements and invited to use the Renew app as often as they wanted over a 6-week period. Participants completed screening and assessments online but provided informed consent, toured the app, and completed feedback interviews via telephone. We assessed users' self-reported PTSD symptoms before and after a 6-week intervention period and collected app usage data using a research-instrumented dashboard. To examine overall app engagement, we used data on the total time spent in the app, the number of log-in days, and the number of points that the user gained in the app. To examine engagement with exposure components, we used data on total time spent completing exposure activities (both in vivo and imaginal), the number of in vivo exposure activities completed, and the number of characters written in response to imaginal exposure prompts. We used hierarchical regression analyses to test the effect of engagement indices on change in PTSD symptoms.

Results

Usage varied widely. Participants spent an average of 166.09 (SD 156.52) minutes using Renew, over an average of 14.7 (SD 10.71) mean log-in days. Engagement with the exposure components of the app was positively associated with PTSD symptom reduction (F6,62=2.31; P=.04). Moreover, this relationship remained significant when controlling for overall engagement with the app (ΔF3,62=4.42; P=.007). The number of characters written during imaginal exposure (β=.37; P=.009) and the amount of time spent completing exposure activities (β=.36; P=.03) were significant contributors to the model.

Conclusions

To our knowledge, this is the first study to show a relationship between symptom improvement and engagement with the active therapeutic components of an mHealth app (ie, exposure) for PTSD. This relationship held when controlling for overall app use, which suggests that it was engagement with exposure, specifically, that was associated with symptom change. Future work to identify ways of promoting greater engagement with self-guided exposure may help improve the effectiveness of mHealth apps for PTSD.

Is a brief mindfulness ecological momentary intervention more efficacious than a self-monitoring app for social anxiety disorder? A randomized controlled trial

Despite their proliferation, limited knowledge exists regarding possible benefits of brief mindfulness ecological momentary interventions (MEMIs) for social anxiety disorder (SAD). Propositions that MEMIs could alleviate SAD symptoms and related clinical outcomes remain untested. This trial evaluated a 14-day MEMI for SAD. Participants with self-reported SAD were randomized to MEMI (n = 96) or self-monitoring app (SM; n = 95). Whereas MEMI instructed mindfulness exercises, SM prompted only self-monitoring five times daily for 14 days. Participants completed state-level self-reports of depression, anxiety, and mindfulness pre-post-mindfulness practice and SAD symptoms, worry, depression severity, repetitive negative thinking, and trait mindfulness at pre-randomization, post-intervention, and 1-month follow-up (1MFU). Hierarchical linear modeling was conducted. The MEMI yielded statistically significantly larger improvements in momentary depression, anxiety, and mindfulness (Cohen's d = -0.10-0.11). Although no between-group effects emerged in alleviating SAD fear and avoidance, excessive worry, depression severity, repetitive negative thinking, and trait mindfulness (-0.13-0.15), within-group effects were significantly small-to-large from pre-post and pre-1MFU (-4.62-0.67). A significant reduction in depression severity occurred in MEMI (-0.63--0.60) but not SM (-0.31--0.29). Brief MEMI and SM yielded nondifferent sustained effects on SAD, comorbid symptoms, and risk factors, highlighting its potential value within stepped-care delivery settings.

A service-user digital intervention to collect real-time safety information on acute, adult mental health wards: the WardSonar mixed-methods study

Background

Acute inpatient mental health services report high levels of safety incidents. The application of patient safety theory has been sparse, particularly concerning interventions that proactively seek patient perspectives.

Objective(s)

Develop and evaluate a theoretically based, digital monitoring tool to collect real-time information from patients on acute adult mental health wards about their perceptions of ward safety.

Design

Theory-informed mixed-methods study. A prototype digital monitoring tool was developed from a co-design approach, implemented in hospital settings, and subjected to qualitative and quantitative evaluation.

Setting and methods

Phase 1: scoping review of the literature on patient involvement in safety interventions in acute mental health care; evidence scan of digital technology in mental health contexts; qualitative interviews with mental health patients and staff about perspectives on ward safety. This, alongside stakeholder engagement with advisory groups, service users and health professionals, informed the development processes. Most data collection was virtual. Phase 1 resulted in the technical development of a theoretically based digital monitoring tool that collected patient feedback for proactive safety monitoring. Phase 2: implementation of the tool in six adult acute mental health wards across two UK NHS trusts; evaluation via focused ethnography and qualitative interviews. Statistical analysis of WardSonar data and routine ward data involving construction of an hour-by-hour data set per ward, permitting detailed analysis of the use of the WardSonar tool.

Participants

A total of 8 patients and 13 mental health professionals participated in Phase 1 interviews; 33 staff and 34 patients participated in Phase 2 interviews.

Interventions

Patients could use a web application (the WardSonar tool) to record real-time perceptions of ward safety. Staff could access aggregated, anonymous data to inform timely interventions.

Results

Coronavirus disease 2019 restrictions greatly impacted the study. Stakeholder engagement permeated the project. Phase 1 delivered a theory-based, collaboratively designed digital tool for proactive patient safety monitoring. Phase 2 showed that the tool was user friendly and broadly acceptable to patients and staff. The aggregated safety data were infrequently used by staff. Feasibility depended on engaged staff and embedding use of the tool in ward routines. There is strong evidence that an incident leads to increased probability of further incidents within the next 4 hours. This puts a measure on the extent to which social/behavioural contagion persists. There is weak evidence to suggest that an incident leads to a greater use of the WardSonar tool in the following hour, but none to suggest that ward atmosphere predicts future incidents. Therefore, how often patients use the tool seems to send a stronger signal about potential incidents than patients' real-time reports about ward atmosphere.

Limitations

Implementation was limited to two NHS trusts. Coronavirus disease 2019 impacted design processes including stakeholder engagement; implementation; and evaluation of the monitoring tool in routine clinical practice. Higher uptake could enhance validity of the results.

Conclusions

WardSonar has the potential to provide a valuable route for patients to communicate safety concerns. The WardSonar monitoring tool has a strong patient perspective and uses proactive real-time safety monitoring rather than traditional retrospective data review.

Future work

The WardSonar tool can be refined and tested further in a post Coronavirus disease 2019 context.

Study registration

This study is registered as ISRCTN14470430.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR128070) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 14. See the NIHR Funding and Awards website for further award information.

Individuals' attitudes toward digital mental health apps and implications for adoption in Portugal: web-based survey

BACKGROUND

The literature is consensual regarding the academic community exhibiting higher levels of mental disorder prevalence than the general population. The potential of digital mental health apps for improving access to resources to cope with these issues is ample. However, studies have yet to be performed in Portugal on individuals' attitudes and perceptions toward digital mental health applications or their preferences and decision drivers on obtaining mental health care, self-assessment, or treatment.

OBJECTIVE

This study aims to understand the determinants of digital mental health applications use in the Portuguese academic community of Porto, along with potential adoption barriers and enablers.

METHODS

A cross-sectional, web-based survey was delivered via dynamic email to the University of Porto's academic community. Data collection occurred between September 20 and October 20, 2022. We used structural equation modeling to build three models, replicating a peer-reviewed and published study and producing a newly full mediation model shaped by the collected data. We tested the relationships between use of digital mental health apps and perceived stress, perceived need to seek help for mental health, perceived stigma, past use of mental health services, privacy concerns, and social influence.

RESULTS

Of the 539 participants, 169 (31.4%) reported having used digital mental health apps. Perceived stress and a latent variable, comprising perceptions of mental health problems and coping strategies, were positively associated with mental health app use, while privacy concerns regarding one's information being accessible to others were negatively associated. Perceived stigma, need to seek help, and close relationships did not have a statistically significant direct effect.

CONCLUSIONS

These findings can inform product and policy development of new, better-targeted digital mental health app interventions, with implications for researchers and academia, industry, and policymakers. Our study concludes that, to maximize adherence to these apps, they should have low to no financial charges, demonstrate evidence of their helpfulness and focus on the timely delivery of care. We also conclude that to foster digital mental health app use, there is a need to improve mental health literacy, namely regarding self-awareness of one's conditions, acceptable stress levels, and overall behavior towards mental health.

TRIAL REGISTRATION

RR2-10.2196/41040.

The impact of mindfulness apps on psychological processes of change: a systematic review

Mindfulness-based interventions (MBIs) have demonstrated therapeutic efficacy for various psychological conditions, and smartphone apps that facilitate mindfulness practice can enhance the reach and impact of MBIs. The goal of this review was to summarize the published evidence on the impact of mindfulness apps on the psychological processes known to mediate transdiagnostic symptom reduction after mindfulness practice. A literature search from January 1, 1993, to August 7, 2023 was conducted on three databases, and 28 randomized controlled trials involving 5963 adults were included. Across these 28 studies, 67 outcome comparisons were made between a mindfulness app group and a control group. Between-group effects tended to favor the mindfulness app group over the control group in three psychological process domains: repetitive negative thinking, attention regulation, and decentering/defusion. Findings were mixed in other domains (i.e., awareness, nonreactivity, non-judgment, positive affect, and acceptance). The range of populations examined, methodological concerns across studies, and problems with sustained app engagement likely contributed to mixed findings. However, effect sizes tended to be moderate to large when effects were found, and gains tended to persist at follow-up assessments two to six months later. More research is needed to better understand the impact of these apps on psychological processes of change. Clinicians interested in integrating apps into care should consider app-related factors beyond evidence of a clinical foundation and use app databases to identify suitable apps for their patients, as highlighted at the end of this review.

Measuring digital intervention user experience with a novel ecological momentary assessment (EMA) method, CORTO

Digital interventions often suffer from low usage, which may reflect insufficient attention to user experience. Moreover, the existing evaluation methods have limited applicability in the remote study of user experience of complex interventions that have expansive content and that are used over an extensive period of time. To alleviate these challenges, we describe here a novel qualitative Ecological Momentary Assessment (EMA) method: the CORTO method (Contextual, One-item, Repeated, Timely, Open-ended). We used it to gather digital intervention user experience data from Finnish adults (n = 184) who lived with interview-confirmed major depressive disorder (MDD) and took part in a randomized controlled trial (RCT) that studied the efficacy of a novel 12-week game-based digital intervention for depression. A second dataset on user experience was gathered with retrospective interviews (n = 22). We inductively coded the CORTO method and retrospective interview data, which led to four user experience categories: (1) contextual use, (2) interaction-elicited emotional experience, (3) usability, and (4) technical issues. Then, we used the created user experience categories and Template Analysis to analyze both datasets together, and reported the results qualitatively. Finally, we compared the two datasets with each other. We found that the data generated with the CORTO method offered more insights into usability and technical categories than the interview data that particularly illustrated the contextual use. The emotional valence of the interview data was more positive compared with the CORTO data. Both the CORTO and interview data detected 55 % of the micro-level categories; 20 % of micro-level categories were only detected by the CORTO data and 25 % only by the interview data. We found that the during-intervention user experience measurement with the CORTO method can provide intervention-specific insights, and thereby further the iterative user-centered intervention development. Overall, these findings highlight the impact of evaluation methods on the categories and qualities of insights acquired in intervention research.

Improving Veteran Engagement with Virtual Care Technologies: a Veterans Health Administration State of the Art Conference Research Agenda

Although the availability of virtual care technologies in the Veterans Health Administration (VHA) continues to expand, ensuring engagement with these technologies among Veterans remains a challenge. VHA Health Services Research & Development convened a Virtual Care State of The Art (SOTA) conference in May 2022 to create a research agenda for improving virtual care access, engagement, and outcomes. This article reports findings from the Virtual Care SOTA engagement workgroup, which comprised fourteen VHA subject matter experts representing VHA clinical care, research, administration, and operations. Workgroup members reviewed current evidence on factors and strategies that may affect Veteran engagement with virtual care technologies and generated key questions to address evidence gaps. The workgroup agreed that although extensive literature exists on factors that affect Veteran engagement, more work is needed to identify effective strategies to increase and sustain engagement. Workgroup members identified key priorities for research on Veteran engagement with virtual care technologies through a series of breakout discussion groups and ranking exercises. The top three priorities were to (1) understand the Veteran journey from active service to VHA enrollment and beyond, and when and how virtual care technologies can best be introduced along that journey to maximize engagement and promote seamless care; (2) utilize the meaningful relationships in a Veteran's life, including family, friends, peers, and other informal or formal caregivers, to support Veteran adoption and sustained use of virtual care technologies; and (3) test promising strategies in meaningful combinations to promote Veteran adoption and/or sustained use of virtual care technologies. Research in these priority areas has the potential to help VHA refine strategies to improve virtual care user engagement, and by extension, outcomes.

Longitudinal outcomes of a therapist-supported digital mental health intervention for depression and anxiety symptoms: A retrospective cohort study

PURPOSE

This study examined treatment outcomes (depression and anxiety symptoms) up to 24 months after completion of a therapist-supported digital mental health intervention (DMHI).

METHODS

The sample consisted of 380 participants who participated in an eight-week DMHI from February 6, 2017 to May 20, 2019. Participants reported depression and anxiety symptoms at eight timepoints from baseline to 24 months. Mixed-effects modelling was used to investigate symptom changes over time. The proportion of participants meeting criteria for treatment response, clinically significant change, and remission of depression and anxiety symptoms were calculated, including proportions demonstrating each outcome sustained up to each timepoint.

RESULTS

Multivariate analyses yielded statistically significant reductions in depression (β = -5.40) and anxiety (β = -3.31) symptoms from baseline to end of treatment (8 weeks). Symptom levels remained significantly reduced from baseline through 24 months. The proportion of participants meeting criteria for clinical treatment outcomes remained constant over 24 months, although there were linear decreases in the proportions experiencing sustained clinical outcomes.

CONCLUSIONS

Treatment gains were made for depression and anxiety symptoms at the end of treatment and up to 24 months. Future studies should determine the feasibility of integrating post-treatment programmes into DMHIs to address symptom deterioration.

Assumptions, Perceptions, and Experiences of Behavioral Health Providers Using Telemedicine: Qualitative Study

BACKGROUND

The urgent and reactive implementation of telemedicine during the pandemic does not represent a long-term, strategic, and proactive approach to optimizing this technology. The assumptions, perceptions, and experiences of the behavioral health providers using telemedicine can inform system-wide and institutional-level strategies to promote longitudinal maintenance of care delivery, which can reduce the use of high-cost care due to new symptom onset and symptom exacerbation related to service interruptions.

OBJECTIVE

We aim to identify the assumptions, perspectives, and experiences of behavioral health clinicians and providers using telemedicine to inform the development of an optimized, sustainable approach to telemedicine implementation.

METHODS

This qualitative study applies the domains of the Consolidated Framework for Implementation Research (CFIR) to structure data collection and analysis from behavioral health providers using telemedicine via an audiovisual connection in the New England region. In total, 12 providers across levels of care were recruited for a 60-minute interview, developed from the CFIR interview guide. Atlas Ti Qualitative Software (version 23; ATLAS.ti Scientific Software Development GmbH) was used to coordinate and facilitate coding among 3 reviewers. Deductive coding was provided from the CFIR interview guide, allowing for data to be categorized by domain and construct. Constructs were analyzed for descriptive themes and tabulated for response frequency. Uncoded data were reviewed and coded in vivo to explore variables contributing to participant perceptions of experience with telemedicine use. Descriptive themes, then analytical themes, were identified. Analytical themes and tabulated frequency of response data were summarized. Finally, a sentiment analysis was completed to derive tone and meaning from the data.

RESULTS

Results are reported within the CFIR domains: intervention characteristic, outer setting, inner setting, characteristics of individuals, and process. The findings with ≥90% agreement include "best practice standards were not known"; "telemedicine was believed to be efficient and time-saving for the patient and provider, maximizing productivity and thus increasing access to care"; "telemedicine provided an additional option for patients to access services, promoting sustained continuity and timeliness of care"; "participants did not identify any clear goals related to telemedicine use"; "demonstrated positive affective responses to telemedicine use"; "expressed high efficacy with telemedicine utilization"; and "strong leadership support."

CONCLUSIONS

These findings support the development of interstate compacts advancing licensure across state lines; payment parity across modalities of care to ensure the financial vitality of behavioral health services; improved dissemination of telehealth training and resources, and telehealth training in academic programs of the health professions; seamless, dynamic workflows to accommodate the changing needs of patient and care continuity; emergency response protocols; and community partnerships to provide private spaces needed for a therapeutic encounter. Future research exploring the patient's experience with telemedicine is needed for all stakeholders to be represented in developing a sustainable, integrated system.

Artificial intelligence in mental healthcare: an overview and future perspectives

Artificial intelligence is disrupting the field of mental healthcare through applications in computational psychiatry, which leverages quantitative techniques to inform our understanding, detection, and treatment of mental illnesses. This paper provides an overview of artificial intelligence technologies in modern mental healthcare and surveys recent advances made by researchers, focusing on the nascent field of digital psychiatry. We also consider the ethical implications of artificial intelligence playing a greater role in mental healthcare.

Selecting and describing control conditions in mobile health randomized controlled trials: a proposed typology

Hundreds of randomized controlled trials (RCTs) have tested the efficacy of mobile health (mHealth) tools for a wide range of mental and behavioral health outcomes. These RCTs have used a variety of control condition types which dramatically influence the scientific inferences that can be drawn from a given study. Unfortunately, nomenclature across mHealth RCTs is inconsistent and meta-analyses commonly combine control conditions that differ in potentially important ways. We propose a typology of control condition types in mHealth RCTs. We define 11 control condition types, discuss key dimensions on which they differ, provide a decision tree for selecting and identifying types, and describe the scientific inferences each comparison allows. We propose a five-tier comparison strength gradation along with four simplified categorization schemes. Lastly, we discuss unresolved definitional, ethical, and meta-analytic issues related to the categorization of control conditions in mHealth RCTs.

The engagement problem: A review of engagement with digital mental health interventions and recommendations for a path forward

Purpose of the review

Digital mental health interventions (DMHIs) are an effective and accessible means of addressing the unprecedented levels of mental illness worldwide. Currently, however, patient engagement with DMHIs in real-world settings is often insufficient to see clinical benefit. In order to realize the potential of DMHIs, there is a need to better understand what drives patient engagement.

Recent findings

We discuss takeaways from the existing literature related to patient engagement with DMHIs and highlight gaps to be addressed through further research. Findings suggest that engagement is influenced by patient-, intervention- and systems-level factors. At the patient-level, variables such as sex, education, personality traits, race, ethnicity, age and symptom severity appear to be associated with engagement. At the intervention-level, integrating human support, gamification, financial incentives and persuasive technology features may improve engagement. Finally, although systems-level factors have not been widely explored, the existing evidence suggests that achieving engagement will require addressing organizational and social barriers and drawing on the field of implementation science.

Summary

Future research clarifying the patient-, intervention- and systems-level factors that drive engagement will be essential. Additionally, to facilitate improved understanding of DMHI engagement, we propose the following: (a) widespread adoption of a minimum necessary 5-element engagement reporting framework; (b) broader application of alternative clinical trial designs; and (c) directed efforts to build upon an initial parsimonious conceptual model of DMHI engagement.

Feasibility and Preliminary Efficacy of Digital Interventions for Depressive Symptoms in Working Adults: Multiarm Randomized Controlled Trial

BACKGROUND

Depressive symptoms are highly prevalent and have broad-ranging negative implications. Digital interventions are increasingly available in the workplace context, but supporting evidence is limited.

OBJECTIVE

This study aimed to evaluate the feasibility, acceptability, and preliminary efficacy of 3 digital interventions for depressive symptoms in a sample of UK-based working adults experiencing mild to moderate symptoms.

METHODS

This was a parallel, multiarm, pilot randomized controlled trial. Participants were allocated to 1 of 3 digital interventions or a waitlist control group and had 3 weeks to complete 6 to 8 short self-guided sessions. The 3 interventions are available on the Unmind mental health app for working adults and draw on behavioral activation, cognitive behavioral therapy, and acceptance and commitment therapy. Web-based assessments were conducted at baseline, postintervention (week 3), and at 1-month follow-up (week 7). Participants were recruited via Prolific, a web-based recruitment platform, and the study was conducted entirely on the web. Feasibility and acceptability were assessed using objective engagement data and self-reported feedback. Efficacy outcomes were assessed using validated self-report measures of mental health and functioning and linear mixed models with intention-to-treat principles.

RESULTS

In total, 2003 individuals were screened for participation, of which 20.22% (405/2003) were randomized. A total of 92% (373/405) of the participants were retained in the study, 97.4% (295/303) initiated their allocated intervention, and 66.3% (201/303) completed all sessions. Moreover, 80.6% (229/284) of the participants rated the quality of their allocated intervention as excellent or good, and 79.6% (226/284) of the participants were satisfied or very satisfied with their intervention. All active groups showed improvements in well-being, functioning, and depressive and anxiety symptoms compared with the control group, which were maintained at 4 weeks. Hedges g effect sizes for depressive symptoms ranged from -0.53 (95% CI -0.25 to -0.81) to -0.74 (95% CI -0.45 to -1.03).

CONCLUSIONS

All interventions were feasible and acceptable, and the preliminary efficacy findings indicated that their use may improve depressive symptoms, well-being, and functioning. The predefined criteria for a definitive trial were met.

TRIAL REGISTRATION

International Standard Randomised Controlled Trial Number (ISRCTN) ISRCTN13067492; https://www.isrctn.com/ISRCTN13067492.