Standalone smartphone apps for mental health-a systematic review and meta-analysis

Systematic review and meta-analysis of standalone digital interventions for cognitive symptoms in people without dementia

Cognitive symptoms are prevalent across neuropsychiatric disorders, increase distress and impair quality of life. Self-guided digital interventions offer accessibility, scalability, and may overcome the research-to-practice treatment gap. Seventy-six trials with 5214 participants were identified. A random-effects meta-analysis investigated the effects of all digital self-guided interventions, compared to controls, at post-treatment. We found a small-to-moderate positive pooled effect on cognition (k = 71; g = -0.51, 95%CI -0.64 to -0.37; p < 0.00001) and mental health (k = 30; g = -0.41, 95%CI -0.60 to -0.22; p < 0.0001). Positive treatment effects on fatigue (k = 8; g = -0.27, 95%CI -0.53 to -0.02; p = 0.03) and quality of life (k = 22; g = -0.17, 95%CI -0.34 to -0.00; p = 0.04) were only marginally significant. No significant benefit was found for performance on activities of daily living. Results were independent of control groups, treatment duration, risk of bias and delivery format. Self-guided digital transdiagnostic interventions may benefit at least a subset of patients in the short run, yet their impact on non-cognitive outcomes remains uncertain.

The effectiveness of smartphone app-based interventions for insomnia and sleep disturbances: A meta-analysis of randomized controlled trials

There is growing enthusiasm towards the role of smartphone app-based interventions in the management of insomnia and related sleep problems. A considerable number of apps designed to address insomnia have been developed in recent years, and randomized controlled trials (RCTs) have begun to explore their efficacy. We conducted a meta-analysis investigating the effectiveness of apps for insomnia and sleep disturbances. From 19 RCTs, we identified significant pooled effect sizes for the primary outcomes of self-reported insomnia (g = 0.60; 05 % CI = 0.44, 0.76; NNT = 4.8) and sleep disturbances (g = 0.70; 95 % CI = 0.58, 0.83; NNT = 4.1) in favour of apps over control conditions. These effects remained robust when restricting the analyses to trials that delivered a placebo control, received a lower risk of bias rating, and had a larger sample size. Significant pooled effects in favour of apps were also observed for secondary outcomes of night time awakenings (g = 0.56), total sleep time (g = 0.33), and sleep onset latency (g = 0.32), but non-significant effects emerged for daytime sleepiness, dysfunctional beliefs about sleep, sleep efficiency, sleep hygiene, and wake after sleep onset. The pooled dropout rate from app conditions was 13.1 % (95 % CI = 8.3, 20.0), which was significantly higher than control conditions (OR = 1.78, 95 % CI = 1.39, 2.28). Findings suggest that stand-alone app-based interventions can effectively address insomnia and sleep disturbances, and may play an important role in the management of these symptoms.

RegulEm, an unified protocol based-app for the treatment of emotional disorders: a parallel mixed methods usability and quality study

BACKGROUND

Interest in mental health smartphone applications has grown in recent years. Despite their effectiveness and advantages, special attention needs to be paid to two aspects to ensure app engagement: to include patients and professionals in their design and to guarantee their usability. The aim of this study was to analyse the perceived usability and quality of the preliminary version of RegulEm, an app based in the Unified Protocol, as part of the second stage of the app development.

METHODS

A parallel mixed methods study was used with 7 professionals and 4 users who were previously involved in the first stage of the development of the app. MARS, uMARS and SUS scales were used, and two focus groups were conducted. Descriptive statistical analysis and a thematic content analysis were performed in order to gather as much information as possible on RegulEm's usability and quality as well as suggestions for improvement.

RESULTS

RegulEm's usability was perceived through the SUS scale scores as good by users (75 points) and excellent by professionals (84.64 points), while its quality was perceived through the uMARS and MARS scales as good by both groups, with 4 and 4.14 points out of 5. Different areas regarding RegulEm's usability and suggestions for improvement were identified in both focus groups and 20% of the suggestions proposed were implemented in the refined version of RegulEm.

CONCLUSION

RegulEm's usability and quality were perceived as good by users and professionals and different identified areas have contributed to its refinement. This study provides a more complete picture of RegulEm's usability and quality prior analysing its effectiveness, implementation and cost-effectiveness in Spanish public mental health units.

Efficacy of Gamified Digital Mental Health Interventions for Pediatric Mental Health Conditions: A Systematic Review and Meta-Analysis

Importance

Anxiety, depression, and attention-deficit/hyperactivity disorder (ADHD) affect up to 20% of children and adolescents. Despite demonstrated efficacy, evidence-based treatments for these conditions are often inaccessible; innovative solutions are essential to meet the demand for pediatric mental health care.

Objective

To examine the efficacy and moderators of gamified DMHIs for anxiety, depression, and ADHD in randomized clinical trials (RCTs) for children and adolescents.

Data Sources

A systematic search of PubMed, PsycInfo, and Web of Science was conducted for RCTs published before March 20, 2024.

Study Selection

RCTs that evaluated the efficacy of gamified DMHIs for treating pediatric ADHD, depression, or anxiety were included. Studies were excluded if they did not use a gamified DMHI, provide sufficient data for effect sizes, or were unavailable in English.

Data Extraction and Synthesis

Efficacy data were extracted from rating scales for ADHD, depression, and anxiety. Extracted moderator variables included participant characteristics (eg, age and sex), intervention characteristics (eg, delivery modality and time limit), and trial design characteristics (eg, outcome measure and risk of bias).

Main Outcomes and Measures

The primary outcome was change in ADHD, depression, or anxiety severity in the treatment group compared to the control group. Hedges g quantified treatment effects.

Results

The search strategy identified 27 RCTs that included 2911 participants across ADHD, depression, and anxiety disorders. There were modest significant effects of gamified DMHIs on ADHD (g, 0.28; 95% CI, 0.09 to 0.48) and depression (g, 0.28; 95% CI, 0.08 to 0.47) but small, nonsignificant effects for anxiety disorders (g, 0.07; 95% CI, -0.02 to 0.17). Moderator analyses revealed that DMHIs for ADHD delivered on a computer and those RCTs that had a greater preponderance of male participants produced larger treatment effects. DMHIs for depressive disorders that used preset time limits for gamified DMHIs also exhibited larger treatment effects.

Conclusions and Relevance

The findings suggest a benefit of gamified DMHIs for youth with ADHD or depressive disorder. Pediatricians and other health care professionals have new information about novel, accessible, and efficacious options for pediatric mental health care.

Engagement, Acceptability, and Effectiveness of the Self-Care and Coach-Supported Versions of the Vira Digital Behavior Change Platform Among Young Adults at Risk for Depression and Obesity: Pilot Randomized Controlled Trial

BACKGROUND

Adolescence and early adulthood are pivotal stages for the onset of mental health disorders and the development of health behaviors. Digital behavioral activation interventions, with or without coaching support, hold promise for addressing risk factors for both mental and physical health problems by offering scalable approaches to expand access to evidence-based mental health support.

OBJECTIVE

This 2-arm pilot randomized controlled trial evaluated 2 versions of a digital behavioral health product, Vira (Ksana Health Inc), for their feasibility, acceptability, and preliminary effectiveness in improving mental health in young adults with depressive symptoms and obesity risk factors.

METHODS

A total of 73 participants recruited throughout the United States were randomly assigned to use Vira either as a self-guided product (Vira Self-Care) or with support from a health coach (Vira+Coaching) for 12 weeks. The Vira smartphone app used passive sensing of behavioral data related to mental health and obesity risk factors (ie, activity, sleep, mobility, and language patterns) and offered users personalized insights into patterns of behavior associated with their daily mood. Participants completed self-reported outcome measures at baseline and follow-up (12 weeks). All study procedures were completed via digital communications.

RESULTS

Both versions of Vira showed strong user engagement, acceptability, and evidence of effectiveness in improving mental health and stress. However, users receiving coaching exhibited more sustained engagement with the platform and reported greater reductions in depression (Cohen d=0.45, 95% CI 0.10-0.82) and anxiety (Cohen d=0.50, 95% CI 0.13-0.86) compared to self-care users. Both interventions also resulted in reduced stress (Vira+Coaching: Cohen d=-1.05, 95% CI -1.57 to --0.50; Vira Self-Care: Cohen d=-0.78, 95% CI -1.33 to -0.23) and were perceived as useful and easy to use. Coached users also reported reductions in sleep-related impairment (Cohen d=-0.51, 95% CI -1.00 to -0.01). Moreover, participants increased their motivation for and confidence in making behavioral changes, with greater improvements in confidence among coached users.

CONCLUSIONS

An app-based intervention using passive mobile sensing to track behavior and deliver personalized insights into behavior-mood associations demonstrated feasibility, acceptability, and preliminary effectiveness for reducing depressive symptoms and other mental health problems in young adults. Future directions include (1) optimizing the interventions, (2) conducting a fully powered trial that includes an active control condition, and (3) testing mediators and moderators of outcome effects.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05638516; https://clinicaltrials.gov/study/NCT05638516.

Smartphone-Based Hand Function Assessment: Systematic Review

BACKGROUND

Hand function assessment heavily relies on specific task scenarios, making it challenging to ensure validity and reliability. In addition, the wide range of assessment tools, limited and expensive data recording, and analysis systems further aggravate the issue. However, smartphones provide a promising opportunity to address these challenges. Thus, the built-in, high-efficiency sensors in smartphones can be used as effective tools for hand function assessment.

OBJECTIVE

This review aims to evaluate existing studies on hand function evaluation using smartphones.

METHODS

An information specialist searched 8 databases on June 8, 2023. The search criteria included two major concepts: (1) smartphone or mobile phone or mHealth and (2) hand function or function assessment. Searches were limited to human studies in the English language and excluded conference proceedings and trial register records. Two reviewers independently screened all studies, with a third reviewer involved in resolving discrepancies. The included studies were rated according to the Mixed Methods Appraisal Tool. One reviewer extracted data on publication, demographics, hand function types, sensors used for hand function assessment, and statistical or machine learning (ML) methods. Accuracy was checked by another reviewer. The data were synthesized and tabulated based on each of the research questions.

RESULTS

In total, 46 studies were included. Overall, 11 types of hand dysfunction-related problems were identified, such as Parkinson disease, wrist injury, stroke, and hand injury, and 6 types of hand dysfunctions were found, namely an abnormal range of motion, tremors, bradykinesia, the decline of fine motor skills, hypokinesia, and nonspecific dysfunction related to hand arthritis. Among all built-in smartphone sensors, the accelerometer was the most used, followed by the smartphone camera. Most studies used statistical methods for data processing, whereas ML algorithms were applied for disease detection, disease severity evaluation, disease prediction, and feature aggregation.

CONCLUSIONS

This systematic review highlights the potential of smartphone-based hand function assessment. The review suggests that a smartphone is a promising tool for hand function evaluation. ML is a conducive method to classify levels of hand dysfunction. Future research could (1) explore a gold standard for smartphone-based hand function assessment and (2) take advantage of smartphones' multiple built-in sensors to assess hand function comprehensively, focus on developing ML methods for processing collected smartphone data, and focus on real-time assessment during rehabilitation training. The limitations of the research are 2-fold. First, the nascent nature of smartphone-based hand function assessment led to limited relevant literature, affecting the evidence's completeness and comprehensiveness. This can hinder supporting viewpoints and drawing conclusions. Second, literature quality varies due to the exploratory nature of the topic, with potential inconsistencies and a lack of high-quality reference studies and meta-analyses.

Cognitive Behavioral Therapy for Insomnia Self-Management Mobile Apps: A Review of Efficacy and Quality

Cognitive behavioral therapy for insomnia (CBT-I) is the recommended treatment for insomnia, yet multiple barriers limit utilization. Digital CBT-I may present a solution, though related reviews have focused on Internet-based delivery rather than app use. The high utilization of health apps and prevalence of sleep apps indicate the need to equip clinicians with app-specific research. Toward this end, we reviewed efficacy and quality data on self-management CBT-I smartphone apps, revealing efficacy research on eleven apps, five of which were publicly available. While preliminary, these efficacy studies showed consistent positive findings. When examining quantitative quality indicators for the five publicly available apps, two had consistent data. Overall, two apps, CBTi Coach and Insomnia Coach, had positive, empirical findings across all efficacy and quality assessment approaches. We provide recommendations to guide clinician decision making regarding CBT-I self-management apps based on the literature and publicly available methods of app evaluations.

Effects of a self-guided digital mental health self-help intervention for Syrian refugees in Egypt: A pragmatic randomized controlled trial

BACKGROUND

Digital mental health interventions for smartphones, such as the World Health Organization (WHO) Step-by-Step (SbS) program, are potentially scalable solutions to improve access to mental health and psychosocial support in refugee populations. Our study objective was to evaluate the effectiveness of SbS as self-guided intervention with optional message-based contact-on-demand (COD) support on reducing psychological distress, functional impairment, symptoms of posttraumatic stress disorder (PTSD), and self-identified problems in a sample of Syrian refugees residing in Egypt.

METHODS AND FINDINGS

We conducted a 2-arm pragmatic randomized controlled trial. A total of 538 Syrians residing in Egypt with elevated levels of psychological distress (Kessler Psychological Distress Scale; K10 > 15) and reduced psychosocial functioning (WHODAS 2.0 > 16) were randomized into SbS + CAU (N = 266) or CAU only (N = 272). Primary outcomes were psychological distress (Hopkins Symptom Checklist 25) and impaired functioning (WHO Disability Assessment Schedule 2.0) at 3-month follow-up. Secondary outcomes were symptoms of PTSD (PTSD Checklist for DSM-5 short form, PCL-5 short) and self-identified problems (Psychological Outcomes Profiles Scale, PSYCHLOPS). Intention-to-treat (ITT) analyses showed significant but small effects of condition on psychological distress (mean difference: -0.15; 95% CI: -0.28, -0.02; p = .02) and functioning (mean difference: -2.04; 95% CI: -3.87, -0.22; p = .02) at 3-month follow-up. There were no significant differences between groups on symptoms of PTSD and self-identified problems. Remission rates did not differ between conditions on any of the outcomes. COD was used by 9.4% of participants for a median of 1 contact per person. The main limitations are high intervention dropout and low utilization of COD support.

CONCLUSIONS

The trial provides a real-world implementation case, showing small positive effects of a digital, potentially scalable and self-guided mental health intervention for Syrian refugees in Egypt in reducing psychological distress and improving overall functioning. Further user-centered adaptations are required to improve adherence and effectiveness while maintaining scalability.

TRIAL REGISTRATION

German Register for Clinical Studies DRKS00023505.

Efficacy of digital mental health interventions for PTSD symptoms: A systematic review of meta-analyses

BACKGROUND

The present systematic review aimed to synthesize the results of meta-analyses which examine the effects of digital mental health interventions (DMHIs) on post-traumatic stress disorder (PTSD) symptoms, and investigate whether intervention characteristics (i.e., technique, timeframe, and therapeutic guidance) and methodological characteristics including outcome measures and sample inclusion criteria (age, gender, socioeconomic status, country, comorbidity) moderate the efficacy of digital interventions.

METHODS

A systematic search of various sources (ECSCOhost PsycInfo, PubMed, Web of Science, Scopus, EBSCOhost ERIC, Google Scholar, ProQuest Dissertations & Theses) including five peer-reviewed journals was conducted to identify relevant meta-analyses up to December 2023, and 11 meta-analyses were included in the final review.

RESULTS

Overall, our review elucidates that DMHIs are appropriate for alleviating PTSD symptoms in adults, with more consistent evidence supporting the efficacy of cognitive behavioral therapy (CBT)-based, compared to non-CBT-based, interventions when compared to control conditions. However, we found inconclusive evidence that the efficacy of DMHIs varied according to intervention timeframe, therapeutic guidance, or sample characteristics.

LIMITATIONS

A relatively limited number of different populations was sampled across meta-analyses. Further, while our review focused on PTSD symptoms to indicate the efficacy of digital interventions, other indices of effectiveness were not examined.

CONCLUSION

Our findings indicate the clinical utility of DMHIs for managing PTSD symptoms particularly when CBT-based intervention techniques are employed.

Comparative effectiveness of remote digital gamified and group CBT skills training interventions for anxiety and depression among college students: Results of a three-arm randomised controlled trial

Digital interventions can enhance access to healthcare in under-resourced settings. However, guided digital interventions may be costly for low- and middle-income countries, despite their effectiveness. In this randomised control trial, we evaluated the effectiveness of two digital interventions designed to address this issue: (1) a Cognitive Behavioral Therapy Skills Training (CST) intervention that increased scalability by using remote online group administration; and (2) the SuperBetter gamified self-guided CBT skills training app, which uses other participants rather than paid staff as guides. The study was implemented among anxious and/or depressed South African undergraduates (n = 371) randomised with equal allocation to Remote Group CST, SuperBetter, or a MoodFlow mood monitoring control. Symptoms were assessed with the Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9). Intention-to-treat analysis found effect sizes at the high end of prior digital intervention trials, including significantly higher adjusted risk differences (ARD; primary outcome) in joint anxiety/depression remission at 3-months and 6-months for Remote Group CST (ARD = 23.3-18.9%, p = 0.001-0.035) and SuperBetter (ARD = 12.7-22.2%, p = 0.047-0.006) than MoodFlow and mean combined PHQ-9/GAD-7 scores (secondary outcome) significantly lower for Remote Group CST and SuperBetter than MoodFlow. These results illustrate how innovative delivery methods can increase the scalability of standard one-on-one guided digital interventions. PREREGISTRATION INTERNATIONAL STANDARD RANDOMISED CONTROLLED TRIAL NUMBER (ISRTCN) SUBMISSION #: 47,089,643.

A Chatbot-Delivered Stress Management Coaching for Students (MISHA App): Pilot Randomized Controlled Trial

BACKGROUND

Globally, students face increasing mental health challenges, including elevated stress levels and declining well-being, leading to academic performance issues and mental health disorders. However, due to stigma and symptom underestimation, students rarely seek effective stress management solutions. Conversational agents in the health sector have shown promise in reducing stress, depression, and anxiety. Nevertheless, research on their effectiveness for students with stress remains limited.

OBJECTIVE

This study aims to develop a conversational agent-delivered stress management coaching intervention for students called MISHA and to evaluate its effectiveness, engagement, and acceptance.

METHODS

In an unblinded randomized controlled trial, Swiss students experiencing stress were recruited on the web. Using a 1:1 randomization ratio, participants (N=140) were allocated to either the intervention or waitlist control group. Treatment effectiveness on changes in the primary outcome, that is, perceived stress, and secondary outcomes, including depression, anxiety, psychosomatic symptoms, and active coping, were self-assessed and evaluated using ANOVA for repeated measure and general estimating equations.

RESULTS

The per-protocol analysis revealed evidence for improvement of stress, depression, and somatic symptoms with medium effect sizes (Cohen d=-0.36 to Cohen d=-0.60), while anxiety and active coping did not change (Cohen d=-0.29 and Cohen d=0.13). In the intention-to-treat analysis, similar results were found, indicating reduced stress (β estimate=-0.13, 95% CI -0.20 to -0.05; P<.001), depressive symptoms (β estimate=-0.23, 95% CI -0.38 to -0.08; P=.003), and psychosomatic symptoms (β estimate=-0.16, 95% CI -0.27 to -0.06; P=.003), while anxiety and active coping did not change. Overall, 60% (42/70) of the participants in the intervention group completed the coaching by completing the postintervention survey. They particularly appreciated the quality, quantity, credibility, and visual representation of information. While individual customization was rated the lowest, the target group fitting was perceived as high.

CONCLUSIONS

Findings indicate that MISHA is feasible, acceptable, and effective in reducing perceived stress among students in Switzerland. Future research is needed with different populations, for example, in students with high stress levels or compared to active controls.

TRIAL REGISTRATION

German Clinical Trials Register DRKS 00030004; https://drks.de/search/en/trial/DRKS00030004.

Off-body Sleep Analysis for Predicting Adverse Behavior in Individuals with Autism Spectrum Disorder

Poor sleep quality in Autism Spectrum Disorder (ASD) individuals is linked to severe daytime behaviors. This study explores the relationship between a prior night's sleep structure and its predictive power for next-day behavior in ASD individuals. The motion was extracted using a low-cost near-infrared camera in a privacy-preserving way. Over two years, we recorded overnight data from 14 individuals, spanning over 2,000 nights, and tracked challenging daytime behaviors, including aggression, self-injury, and disruption. We developed an ensemble machine learning algorithm to predict next-day behavior in the morning and the afternoon. Our findings indicate that sleep quality is a more reliable predictor of morning behavior than afternoon behavior the next day. The proposed model attained an accuracy of 74% and a F1 score of 0.74 in target-sensitive tasks and 67% accuracy and 0.69 F1 score in target-insensitive tasks. For 7 of the 14, better-than-chance balanced accuracy was obtained (p-value<0.05), with 3 showing significant trends (p-value<0.1). These results suggest off-body, privacy-preserving sleep monitoring as a viable method for predicting next-day adverse behavior in ASD individuals, with the potential for behavioral intervention and enhanced care in social and learning settings.

How are Conversations via an On-Demand Peer-To-Peer Emotional Well-Being App Associated with Emotional Improvement?

Non-clinical, on-demand peer-to-peer (PtP) support apps have become increasingly popular over the past several years. Although not as pervasive as general self-help apps, these PtP support apps are usually free and instantly connect individuals through live texting with a non-clinical volunteer who has been minimally trained to listen and offer support. To date, there is little empirical work that examines whether and how using an on-demand PtP support app improves emotional well-being. Applying regression and multilevel models to N = 1000+ PtP conversations, this study examined whether individuals experience emotional improvement following a conversation on a PtP support app (HearMe) and whether dyadic characteristics of the conversation - specifically, verbal and emotional synchrony - are associated with individuals' emotional improvement. We found that individuals reported emotional improvement following a conversation on the PtP support app and that verbal (but not emotional) synchrony was associated with the extent of individuals' emotional improvement. Our results suggest that online PtP support apps are a viable source of help. We discuss cautions and considerations when applying our findings to enhance the delivery of support provision on PtP apps.

Mobile apps to reduce depressive symptoms and alcohol use in youth: A systematic review and meta-analysis: A systematic review

Background

Among youth, symptoms of depression, anxiety, and alcohol use are associated with considerable illness and disability. Youth face many personal and health system barriers in accessing mental health care. Mobile applications (apps) offer youth potentially accessible, scalable, and anonymous therapy and other support. Recent systematic reviews on apps to reduce mental health symptoms among youth have reported uncertain effectiveness, but analyses based on the type of app-delivered therapy are limited.

Objectives

We conducted this systematic review with youth co-researchers to ensure that this review addressed the questions that were most important to them. The objective of this review is to synthesize the best available evidence on the effectiveness of mobile apps for the reduction of depressive symptoms (depression, generalized anxiety, psychological distress) and alcohol use among youth.

Search Methods

We conducted electronic searches of the following bibliographic databases for studies published between January 1, 2008, and July 1, 2022: MEDLINE (via Ovid), Embase (via Ovid), PsycINFO (via Ovid), CINAHL (via EBSCOHost), and CENTRAL (via the Cochrane Library). The search used a combination of indexed terms, free text words, and MeSH headings. We manually screened the references of relevant systematic reviews and included randomized controlled trials (RCTs) for additional eligible studies, and contacted authors for full reports of identified trial registries or protocols.

Selection Criteria

We included RCTs conducted among youth aged 15-24 years from any setting. We did not exclude populations on the basis of gender, socioeconomic status, geographic location or other personal characteristics. We included studies which assessed the effectiveness of app-delivered mental health support or therapy interventions that targeted the management of depressive disorders and/or alcohol use disorders. We excluded apps that targeted general wellness, apps which focused on prevention of psychological disorders and apps that targeted bipolar disorder, psychosis, post-traumatic stress disorder, attention-deficit hyperactivity disorder, substance use disorders (aside from alcohol), and sleep disorders. Eligible comparisons included usual care, no intervention, wait-list control, alternative or controlled mobile applications. We included studies which reported outcomes on depressive symptoms, anxiety symptoms, alcohol use and psychological distress over any follow-up period.

Data Collection and Analysis

We standardized the PICO definitions (population, intervention, comparison, and outcome) of each included study and grouped studies by the type of therapy or support offered by the app. Whenever app design and clinical homogeneity allowed, we meta-analyzed outcomes using a random-effects model. Outcome data measured using categorical scales were synthesized using odds ratios. Outcome data measured using continuous scales were synthesized as the standardized mean difference. We assessed the methodological quality of each included study using the Cochrane Risk of Bias 2.0 tool and we assessed certainty of the evidence using the GRADE approach.

Main Results

From 5280 unique citations, we included 36 RCTs published in 37 reports and conducted in 15 different countries (7984 participants). Among the 36 included trials, we assessed two with an overall low risk of bias, 8 trials with some concern regarding risk of bias, and 26 trials with a high risk of bias. Interventions varied in the type of therapy or supports offered. The most common intervention designs employed mindfulness training, cognitive behavioral therapy (CBT), or a combination of the two (mindfulness + CBT). However, other interventions also included self-monitoring, medication reminders, cognitive bias modification or positive stimulation, dialectical behavioral therapy, gamified health promotion, or social skill building. Mindfulness apps led to short term improvements in depressive symptoms when compared to a withheld control (SMD = -0.36; 95% CI [-0.63, -0.10]; p = 0.007, n = 3 RCTs, GRADE: very low certainty) and when compared to an active control (SMD = -0.27; 95% CI [-0.53, -0.01]; p = 0.04, n = 2 RCTs, GRADE: very low). Apps delivering this type of support also significantly improved symptoms of anxiety when compared to a withheld control (SMD = -0.35; 95% CI [-0.60, -0.09]; p = 0.008, n = 3 RCTs, GRADE: very low) but not when compared to an active control (SMD = -0.24; 95% CI [-0.50, 0.02]; p = 0.07, n = 2 RCTs, GRADE: very low). Mindfulness apps showed improvements in psychological stress that approached statistical significance among participants receiving the mindfulness mobile apps compared to those in the withheld control (SMD = -0.27; 95% CI [-0.56, 0.03]; p = .07, n = 4 RCTs, GRADE: very low). CBT apps also led to short-term improvements in depressive symptoms when compared to a withheld control (SMD = -0.40; 95% CI [-0.80, 0.01]; p = 0.05, n = 2 RCTs, GRADE: very low) and when compared to an active control (SMD = -0.59; 95% CI [-0.98, -0.19]; p = 0.003, n = 2 RCTs, GRADE: very low). CBT-based apps also improved symptoms of anxiety compared to a withheld control (SMD = -0.51; 95% CI [-0.94, -0.09]; p = 0.02, n = 3 RCTs, GRADE: very low) but not when compared to an active control (SMD = -0.26; 95% CI [-1.11, 0.59]; p = 0.55, n = 3 RCTs, GRADE: very low). Apps which combined mindfulness and CBT did not significantly improve symptoms of depression (SMD = -0.20; 95% CI [-0.42, 0.02]; p = 0.07, n = 2 RCTs, GRADE: very low) or anxiety (SMD = -0.21; 95% CI [-0.49, 0.07]; p = 0.14, n = 2 RCTs, GRADE: very low). However, these apps did improve psychological distress (SMD = -0.43; 95% CI [-0.74, -0.12]; p = 0.006, n = 2 RCTs, GRADE: very low). The results of trials on apps to reduce alcohol use were inconsistent. We did not identify any harms associated with the use of apps to manage mental health concerns. All effectiveness results had a very low certainty of evidence rating using the GRADE approach, meaning that apps which deliver therapy or other mental health support may reduce symptoms of depression, anxiety and psychological distress but the evidence is very uncertain.

Authors' Conclusions

We reviewed evidence from 36 trials conducted among youth. According to our meta-analyses, the evidence is very uncertain about the effect of apps on depression, anxiety, psychological distress, and alcohol use. Very few effects were interpreted to be of clinical importance. Most of the RCTs were small studies focusing on efficacy for youth at risk for depressive symptoms. Larger trials are needed to evaluate effectiveness and allow for further analysis of subgroup differences. Longer trials are also needed to better estimate the clinical importance of these apps over the long term.

Evidence for Bidirectional, Cross-Lagged Associations Between Alliance and Psychological Distress in an Unguided Mobile-Health Intervention

Bidirectional associations between changes in symptoms and alliance are established for in-person psychotherapy. Alliance may play an important role in promoting engagement and effectiveness within unguided mobile health (mHealth) interventions. Using models disaggregating alliance and psychological distress into within- and between-person components (random intercept cross-lagged panel model), we report bidirectional associations between alliance and distress over the course of a 4-week smartphone-based meditation intervention (n=302, 80.0% elevated depression/anxiety). Associations were stable across time with effect sizes similar to those observed for psychotherapy (βs=-.13 to -.14 and -.09 to -.10, for distress to alliance and alliance to distress, respectively). Alliance may be worth measuring to improve the acceptability and effectiveness of mHealth tools. Further empirical and theoretical work characterizing the role and meaning of alliance in unguided mHealth is warranted.

Evaluation of the internet-based intervention "Selfapy" in participants with unipolar depression and the impact on quality of life: a randomized, parallel group study

PURPOSE

Depressive disorders cause a major burden of disease worldwide and often lead to a loss of social functioning. Patients suffering from depressive disorders report a lower quality of life (QOL) than people without a history of mental health issues. Internet-based interventions (IBIs) based on cognitive behavioral therapy (CBT) are effective in reducing symptom severity but data on their impact on quality of life in clinically depressed patients so far is scarce.

METHODS

Selfapy is a CBT-based IBI for depressive disorders. 401 participants (332 female, mean age 37 (SD = 11) with a diagnosis of major depressive disorder (MDD) or dysthymia were enrolled in a randomized, parallel, three-arm trial comparing a therapist-guided Selfapy intervention with an unguided Selfapy intervention and a waiting list control. QOL was measured using the WHOQOL-BREF at baseline, post-treatment (12 weeks) and at 24-week follow-up. The effects of the interventions on QOL were calculated using linear mixed effects models.

RESULTS

At post-treatment (12 weeks) the guided and unguided intervention groups reported an increase in QOL on physical and psychological health domains compared to controls (significant group*time interaction). The gain in QOL was maintained over the follow-up period only for psychological health. QOL decreased in the social relationships and environment domains over the course of treatment and during the follow-up treatment for all participants. There were no differences between the guided and the unguided intervention.

CONCLUSION

Selfapy proved to positively affect psychological and physical QOL in a sample of participants suffering from depressive disorders and can therefore be considered an effective and highly scalable therapeutic tool. The pattern of results might partly be attributable to effects of the COVID-19 pandemic and public health measures that coincided with the trial.

TRIAL REGISTRATION

German Clinical Trials Register (DRKS): DRKS00017191. Registered June 14th, 2019, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00017191 .

A Novel Blended Transdiagnostic Intervention (eOrygen) for Youth Psychosis and Borderline Personality Disorder: Uncontrolled Single-Group Pilot Study

BACKGROUND

Integrating innovative digital mental health interventions within specialist services is a promising strategy to address the shortcomings of both face-to-face and web-based mental health services. However, despite young people's preferences and calls for integration of these services, current mental health services rarely offer blended models of care.

OBJECTIVE

This pilot study tested an integrated digital and face-to-face transdiagnostic intervention (eOrygen) as a blended model of care for youth psychosis and borderline personality disorder. The primary aim was to evaluate the feasibility, acceptability, and safety of eOrygen. The secondary aim was to assess pre-post changes in key clinical and psychosocial outcomes. An exploratory aim was to explore the barriers and facilitators identified by young people and clinicians in implementing a blended model of care into practice.

METHODS

A total of 33 young people (aged 15-25 years) and 18 clinicians were recruited over 4 months from two youth mental health services in Melbourne, Victoria, Australia: (1) the Early Psychosis Prevention and Intervention Centre, an early intervention service for first-episode psychosis; and (2) the Helping Young People Early Clinic, an early intervention service for borderline personality disorder. The feasibility, acceptability, and safety of eOrygen were evaluated via an uncontrolled single-group study. Repeated measures 2-tailed t tests assessed changes in clinical and psychosocial outcomes between before and after the intervention (3 months). Eight semistructured qualitative interviews were conducted with the young people, and 3 focus groups, attended by 15 (83%) of the 18 clinicians, were conducted after the intervention.

RESULTS

eOrygen was found to be feasible, acceptable, and safe. Feasibility was established owing to a low refusal rate of 25% (15/59) and by exceeding our goal of young people recruited to the study per clinician. Acceptability was established because 93% (22/24) of the young people reported that they would recommend eOrygen to others, and safety was established because no adverse events or unlawful entries were recorded and there were no worsening of clinical and social outcome measures. Interviews with the young people identified facilitators to engagement such as peer support and personalized therapy content, as well as barriers such as low motivation, social anxiety, and privacy concerns. The clinician focus groups identified evidence-based content as an implementation facilitator, whereas a lack of familiarity with the platform was identified as a barrier owing to clinicians' competing priorities, such as concerns related to risk and handling acute presentations, as well as the challenge of being understaffed.

CONCLUSIONS

eOrygen as a blended transdiagnostic intervention has the potential to increase therapeutic continuity, engagement, alliance, and intensity. Future research will need to establish the effectiveness of blended models of care for young people with complex mental health conditions and determine how to optimize the implementation of such models into specialized services.

Algorithmic surveillance in the era of the mental health appsphere

Digital mental health applications, also known as mHealth apps, are designed to help users manage their mental health using technology such as mobile devices and smartphones. However, there has been little critical engagement surrounding their impact on marginalized communities, and Black people in Canada. This article aims to explore how state and private actors conceptualize the digitalization of mental health access, leading to the creation and implementation of these apps. It is important to consider the links and interconnections between the platform and the app, and to be cautious and curious before adopting yet another app that claims to manage and mitigate moods and address mental health needs. We should be considering the implications of what comes with this access and apparent ease of use.

Effects on voice hearing distress and social functioning of unguided application of a smartphone app - A randomized controlled trial

Background

Temstem is a smartphone app developed with and for clinical voice hearing individuals with the aim to reduce their voice hearing distress and improve social functioning.

Methods

A randomized controlled trial with adult outpatients suffering from distressing and frequent auditory verbal hallucinations (AVH) was conducted. Participants were randomized to unguided 'Temstem+AVH monitoring' or unguided 'AVH monitoring only' (control condition). Assessments were performed at baseline, post-intervention (week 5-6), and follow-up (week 9-10). Primary outcomes were voice hearing distress and social functioning, as measured with Experience Sampling Method (ESM), consisting of multiple daily questionnaires during six days. In addition, voices and mood were self-monitored with help of a daily reflective questionnaire. Analyses were linear regression models (intention-to-treat).

Results

44 Participants were allocated to Temstem and 45 to the control condition. No significant differences between the groups were found on both primary outcomes.

Conclusion

Our results do not support the effectiveness of stand-alone use of Temstem versus symptom monitoring on voice hearing distress or social functioning in voice hearing individuals. In order to potentially improve effectiveness of an mHealth tool in a population of people with frequent and distressing voices, we recommend to involve persons with lived experience in all stages of development and research; to thoroughly test the (technological) usability before performing an RCT; to test whether guidance of a therapist is needed to optimize effectiveness; and to provide prompts to remind the user to actually use the tool.

Transdiagnostic Ecological Momentary Intervention for Improving Self-Esteem in Youth Exposed to Childhood Adversity: The SELFIE Randomized Clinical Trial

Importance

Targeting low self-esteem in youth exposed to childhood adversity is a promising strategy for preventing adult mental disorders. Ecological momentary interventions (EMIs) allow for the delivery of youth-friendly, adaptive interventions for improving self-esteem, but robust trial-based evidence is pending.

Objective

To examine the efficacy of SELFIE, a novel transdiagnostic, blended EMI for improving self-esteem plus care as usual (CAU) compared with CAU only.

Design, Setting, and Participants

This was a 2-arm, parallel-group, assessor-blinded, randomized clinical trial conducted from December 2018 to December 2022. The study took place at Dutch secondary mental health services and within the general population and included youth (aged 12-26 years) with low self-esteem (Rosenberg Self-Esteem Scale [RSES] <26) exposed to childhood adversity.

Interventions

A novel blended EMI (3 face-to-face sessions, email contacts, app-based, adaptive EMI) plus CAU or CAU only.

Main Outcomes and Measures

The primary outcome was RSES self-esteem at postintervention and 6-month follow-up. Secondary outcomes included positive and negative self-esteem, schematic self-beliefs, momentary self-esteem and affect, general psychopathology, quality of life, observer-rated symptoms, and functioning.

Results

A total of 174 participants (mean [SD] age, 20.7 [3.1] years; 154 female [89%]) were included in the intention-to-treat sample, who were primarily exposed to childhood emotional abuse or neglect, verbal or indirect bullying, and/or parental conflict. At postintervention, 153 participants (87.9%) and, at follow-up, 140 participants (80.5%), provided primary outcome data. RSES self-esteem was, on average, higher in the experimental condition (blended EMI + CAU) than in the control condition (CAU) across both postintervention and follow-up as a primary outcome (B = 2.32; 95% CI, 1.14-3.50; P < .001; Cohen d-type effect size [hereafter, Cohen d] = 0.54). Small to moderate effect sizes were observed suggestive of beneficial effects on positive (B = 3.85; 95% CI, 1.83-5.88; P < .001; Cohen d = 0.53) and negative (B = -3.78; 95% CI, -6.59 to -0.98; P = .008; Cohen d = -0.38) self-esteem, positive (B = 1.58; 95% CI, 0.41-2.75; P = .008; Cohen d = 0.38) and negative (B = -1.71; 95% CI, -2.93 to -0.48; P = .006; Cohen d = -0.39) schematic self-beliefs, momentary self-esteem (B = 0.29; 95% CI, 0.01-0.57; P = .04; Cohen d = 0.24), momentary positive affect (B = 0.23; 95% CI, 0.01-0.45; P = .04; Cohen d = 0.20), momentary negative affect (B = -0.33; 95% CI, -0.59 to -0.03, P = .01, Cohen d = -0.27), general psychopathology (B = -17.62; 95% CI, -33.03 to -2.21; P = .03; Cohen d = -0.34), and quality of life (B = 1.16; 95% CI, 0.18-2.13; P = .02; Cohen d = 0.33) across postintervention and follow-up. No beneficial effects on symptoms and functioning were observed.

Conclusions and Relevance

A transdiagnostic, blended EMI demonstrated efficacy on the primary outcome of self-esteem and signaled beneficial effects on several secondary outcomes. Further work should focus on implementing this novel EMI in routine public mental health provision.

Trial Registration

Dutch Trial Register Identifier:NL7129(NTR7475).

Additive effects of adjunctive app-based interventions for mental disorders - A systematic review and meta-analysis of randomised controlled trials

Background

It is uncertain whether app-based interventions add value to existing mental health care.

Objective

To examine the incremental effects of app-based interventions when used as adjunct to mental health interventions.

Methods

We searched PubMed, PsycINFO, Scopus, Web of Science, and Cochrane Library databases on September 15th, 2023, for randomised controlled trials (RCTs) on mental health interventions with an adjunct app-based intervention compared to the same intervention-only arm for adults with mental disorders or respective clinically relevant symptomatology. We conducted meta-analyses on symptoms of different mental disorders at postintervention. PROSPERO, CRD42018098545.

Results

We identified 46 RCTs (4869 participants). Thirty-two adjunctive app-based interventions passively or actively monitored symptoms and behaviour, and in 13 interventions, the monitored data were sent to a therapist. We found additive effects on symptoms of depression (g = 0.17; 95 % CI 0.02 to 0.33; k = 7 comparisons), anxiety (g = 0.80; 95 % CI 0.06 to 1.54; k = 3), mania (g = 0.2; 95 % CI 0.02 to 0.38; k = 4), smoking cessation (g = 0.43; 95 % CI 0.29 to 0.58; k = 10), and alcohol use (g = 0.23; 95 % CI 0.08 to 0.39; k = 7). No significant effects were found on symptoms of depression within a bipolar disorder (g = -0.07; 95 % CI -0.37 to 0.23, k = 4) and eating disorders (g = -0.02; 95 % CI -0.44 to 0.4, k = 3). Studies on depression, mania, smoking, and alcohol use had a low heterogeneity between the trials. For other mental disorders, only single studies were identified. Only ten studies had a low risk of bias, and 25 studies reported insufficient statistical power.

Discussion

App-based interventions may be used to enhance mental health interventions to further reduce symptoms of depression, anxiety, mania, smoking, and alcohol use. However, the effects were small, except for anxiety, and limited due to study quality. Further high-quality research with larger sample sizes is warranted to better understand how app-based interventions can be most effectively combined with established interventions to improve outcomes.

Attrition in Conversational Agent-Delivered Mental Health Interventions: Systematic Review and Meta-Analysis

BACKGROUND

Conversational agents (CAs) or chatbots are computer programs that mimic human conversation. They have the potential to improve access to mental health interventions through automated, scalable, and personalized delivery of psychotherapeutic content. However, digital health interventions, including those delivered by CAs, often have high attrition rates. Identifying the factors associated with attrition is critical to improving future clinical trials.

OBJECTIVE

This review aims to estimate the overall and differential rates of attrition in CA-delivered mental health interventions (CA interventions), evaluate the impact of study design and intervention-related aspects on attrition, and describe study design features aimed at reducing or mitigating study attrition.

METHODS

We searched PubMed, Embase (Ovid), PsycINFO (Ovid), Cochrane Central Register of Controlled Trials, and Web of Science, and conducted a gray literature search on Google Scholar in June 2022. We included randomized controlled trials that compared CA interventions against control groups and excluded studies that lasted for 1 session only and used Wizard of Oz interventions. We also assessed the risk of bias in the included studies using the Cochrane Risk of Bias Tool 2.0. Random-effects proportional meta-analysis was applied to calculate the pooled dropout rates in the intervention groups. Random-effects meta-analysis was used to compare the attrition rate in the intervention groups with that in the control groups. We used a narrative review to summarize the findings.

RESULTS

The systematic search retrieved 4566 records from peer-reviewed databases and citation searches, of which 41 (0.90%) randomized controlled trials met the inclusion criteria. The meta-analytic overall attrition rate in the intervention group was 21.84% (95% CI 16.74%-27.36%; I2=94%). Short-term studies that lasted ≤8 weeks showed a lower attrition rate (18.05%, 95% CI 9.91%- 27.76%; I2=94.6%) than long-term studies that lasted >8 weeks (26.59%, 95% CI 20.09%-33.63%; I2=93.89%). Intervention group participants were more likely to attrit than control group participants for short-term (log odds ratio 1.22, 95% CI 0.99-1.50; I2=21.89%) and long-term studies (log odds ratio 1.33, 95% CI 1.08-1.65; I2=49.43%). Intervention-related characteristics associated with higher attrition include stand-alone CA interventions without human support, not having a symptom tracker feature, no visual representation of the CA, and comparing CA interventions with waitlist controls. No participant-level factor reliably predicted attrition.

CONCLUSIONS

Our results indicated that approximately one-fifth of the participants will drop out from CA interventions in short-term studies. High heterogeneities made it difficult to generalize the findings. Our results suggested that future CA interventions should adopt a blended design with human support, use symptom tracking, compare CA intervention groups against active controls rather than waitlist controls, and include a visual representation of the CA to reduce the attrition rate.

TRIAL REGISTRATION

PROSPERO International Prospective Register of Systematic Reviews CRD42022341415; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022341415.

[Apps for tinnitus? A systematic review on quality, intervention components, and behavior change techniques]

BACKGROUND

Various smartphone applications (apps) for people with tinnitus are available and promise tinnitus relief. Yet, it is difficult for people suffering from tinnitus and healthcare professionals to estimate their quality, potential, or risks. The current study aims to generate an overview of available tinnitus apps in the German language and to offer orientation for research and healthcare providers.

METHOD

The most prominent stores were searched systematically (November 2020-April 2021; Google Play Store and Apple App Store). Apps specifically developed for tinnitus were evaluated by two independent raters using multiple approaches: a) a quality screening was performed using the German version of the Mobile App Rating Scale (MARS-G), b) intervention components were assessed using a newly developed list of categories, and c) implemented strategies for active tinnitus management were analyzed using behavior change techniques (BCTs).

RESULTS

The search yielded 1073 apps, of which 21 apps were analyzed. The apps' overall quality as assessed by MARS‑G was average (M = 3.37, SD = 039). A lot of apps offered sounds (n = 18) and information (n = 9) or assessed tinnitus characteristics (n = 13). Out of 93 BCTs, 24 were identified at least once. Only one app was evaluated in non-randomized trials.

CONCLUSION

Although a variety of apps are available, most of them focus on a few intervention components (e.g., sounds or information). Therefore, apps do not exploit their potential to impart important evidence-based content for tinnitus management. The app evaluation using multiple approaches points out potential for improvement.

Development and Evaluation of a Smartphone-Based Chatbot Coach to Facilitate a Balanced Lifestyle in Individuals With Headaches (BalanceUP App): Randomized Controlled Trial

BACKGROUND

Primary headaches, including migraine and tension-type headaches, are widespread and have a social, physical, mental, and economic impact. Among the key components of treatment are behavior interventions such as lifestyle modification. Scalable conversational agents (CAs) have the potential to deliver behavior interventions at a low threshold. To our knowledge, there is no evidence of behavioral interventions delivered by CAs for the treatment of headaches.

OBJECTIVE

This study has 2 aims. The first aim was to develop and test a smartphone-based coaching intervention (BalanceUP) for people experiencing frequent headaches, delivered by a CA and designed to improve mental well-being using various behavior change techniques. The second aim was to evaluate the effectiveness of BalanceUP by comparing the intervention and waitlist control groups and assess the engagement and acceptance of participants using BalanceUP.

METHODS

In an unblinded randomized controlled trial, adults with frequent headaches were recruited on the web and in collaboration with experts and allocated to either a CA intervention (BalanceUP) or a control condition. The effects of the treatment on changes in the primary outcome of the study, that is, mental well-being (as measured by the Patient Health Questionnaire Anxiety and Depression Scale), and secondary outcomes (eg, psychosomatic symptoms, stress, headache-related self-efficacy, intention to change behavior, presenteeism and absenteeism, and pain coping) were analyzed using linear mixed models and Cohen d. Primary and secondary outcomes were self-assessed before and after the intervention, and acceptance was assessed after the intervention. Engagement was measured during the intervention using self-reports and usage data.

RESULTS

A total of 198 participants (mean age 38.7, SD 12.14 y; n=172, 86.9% women) participated in the study (intervention group: n=110; waitlist control group: n=88). After the intervention, the intention-to-treat analysis revealed evidence for improved well-being (treatment: β estimate=-3.28, 95% CI -5.07 to -1.48) with moderate between-group effects (Cohen d=-0.66, 95% CI -0.99 to -0.33) in favor of the intervention group. We also found evidence of reduced somatic symptoms, perceived stress, and absenteeism and presenteeism, as well as improved headache management self-efficacy, application of behavior change techniques, and pain coping skills, with effects ranging from medium to large (Cohen d=0.43-1.05). Overall, 64.8% (118/182) of the participants used coaching as intended by engaging throughout the coaching and completing the outro.

CONCLUSIONS

BalanceUP was well accepted, and the results suggest that coaching delivered by a CA can be effective in reducing the burden of people who experience headaches by improving their well-being.

TRIAL REGISTRATION

German Clinical Trials Register DRKS00017422; https://trialsearch.who.int/Trial2.aspx?TrialID=DRKS00017422.

Small Steps over time: A longitudinal usability test of an automated interactive text messaging intervention to support self-management of depression and anxiety symptoms

BACKGROUND

Digital mental health interventions (DMHIs) offer potential solutions for addressing mental health care gaps, but often suffer from low engagement. Text messaging is one promising medium for increasing access and sustaining user engagement with DMHIs. This paper examines the Small Steps SMS program, an 8-week, automated, adaptive text message-based intervention for depression and anxiety.

METHODS

We conducted an 8-week longitudinal usability test of the Small Steps SMS program, recruiting 20 participants who met criteria for major depressive disorder and/or generalized anxiety disorder. Participants used the automated intervention for 8 weeks and completed symptom severity and usability self-report surveys after 4 and 8 weeks of intervention use. Participants also completed individual interviews to provide feedback on the intervention.

RESULTS

Participants responded to automated messages on 70 % of study days and with 85 % of participants sending responses to messages in the 8th week of use. Usability surpassed established cutoffs for software that is considered acceptable. Depression symptom severity decreased significantly over the usability test, but reductions in anxiety symptoms were not significant. Participants noted key areas for improvement including addressing message volume, aligning message scheduling to individuals' availability, and increasing the customizability of content.

LIMITATIONS

This study does not contain a control group.

CONCLUSIONS

An 8-week automated interactive text messaging intervention, Small Steps SMS, demonstrates promise with regard to being a feasible, usable, and engaging method to deliver daily mental health support to individuals with symptoms of anxiety and depression.

Use and Engagement With Low-Intensity Cognitive Behavioral Therapy Techniques Used Within an App to Support Worry Management: Content Analysis of Log Data

BACKGROUND

Low-intensity cognitive behavioral therapy (LICBT) has been implemented by the Improving Access to Psychological Therapies services across England to manage excessive worry associated with generalized anxiety disorder and support emotional well-being. However, barriers to access limit scalability. A solution has been to incorporate LICBT techniques derived from an evidence-based protocol within the Iona Mind Well-being app for Worry management (IMWW) with support provided through an algorithmically driven conversational agent.

OBJECTIVE

This study aims to examine engagement with a mobile phone app to support worry management with specific attention directed toward interaction with specific LICBT techniques and examine the potential to reduce symptoms of anxiety.

METHODS

Log data were examined with respect to a sample of "engaged" users who had completed at least 1 lesson related to the Worry Time and Problem Solving in-app modules that represented the "minimum dose." Paired sample 2-tailed t tests were undertaken to examine the potential for IMWW to reduce worry and anxiety, with multivariate linear regressions examining the extent to which completion of each of the techniques led to reductions in worry and anxiety.

RESULTS

There was good engagement with the range of specific LICBT techniques included within IMWW. The vast majority of engaged users were able to interact with the cognitive behavioral therapy model and successfully record types of worry. When working through Problem Solving, the conversational agent was successfully used to support the user with lower levels of engagement. Several users engaged with Worry Time outside of the app. Forgetting to use the app was the most common reason for lack of engagement, with features of the app such as completion of routine outcome measures and weekly reflections having lower levels of engagement. Despite difficulties in the collection of end point data, there was a significant reduction in severity for both anxiety (t53=5.5; P<.001; 95% CI 2.4-5.2) and low mood (t53=2.3; P=.03; 95% CI 0.2-3.3). A statistically significant linear model was also fitted to the Generalized Anxiety Disorder-7 (F2,51=6.73; P<.001), while the model predicting changes in the Patient Health Questionnaire-8 did not reach significance (F2,51=2.33; P=.11). This indicates that the reduction in these measures was affected by in-app engagement with Worry Time and Problem Solving.

CONCLUSIONS

Engaged users were able to successfully interact with the LICBT-specific techniques informed by an evidence-based protocol although there were lower completion rates of routine outcome measures and weekly reflections. Successful interaction with the specific techniques potentially contributes to promising data, indicating that IMWW may be effective in the management of excessive worry. A relationship between dose and improvement justifies the use of log data to inform future developments. However, attention needs to be directed toward enhancing interaction with wider features of the app given that larger improvements were associated with greater engagement.

Digital thErapy For Improved tiNnitus carE Study (DEFINE): Protocol for a randomised controlled trial

Tinnitus is a common health condition, affecting approximately 15% of the UK population. The tinnitus treatment with the strongest evidence base is Cognitive Behavioural Therapy (CBT), with standard tinnitus therapy typically augmented with education, relaxation and other techniques. Availability of CBT and conventional tinnitus therapy more broadly is limited for tinnitus sufferers. The DEFINE trial aims to assess whether smartphone-delivered tinnitus therapy, the Oto app, is as effective as current standard care, one-to-one therapist-delivered tinnitus treatment for the treatment of tinnitus in adults. The trial is registered in the ISRCTN Registry: ISRCTN99577932. DEFINE is an open-label, non-inferiority, prospective, parallel design, randomised-controlled trial. Recruitment, interventions and assessments will be remote, enabling UK-wide participant involvement. 198 participants aged 18 years or more will be recruited via social media advertisement or via primary care physicians. A screening process will identify those with tinnitus that impacts health-related quality of life, and following consent smartphone-based audiometry will be performed. Randomisation 1:1 to the Oto app or one-to-one therapist-led tinnitus therapy will be performed centrally by computer, matching groups for age, sex and hearing level. Following participant allocation, the Oto app will be provided for immediate use, or a one-to-one remote therapy appointment booked to occur within approximately 1 week, with up to 6 sessions delivered. Participant outcomes will be collected at 4,12, 26 and 52 weeks via questionnaire and phone call. The primary outcome is the change in Tinnitus Functional Index (TFI) total score measured at 26 weeks following allocation. Adverse events will be recorded. A health economic evaluation in the form of a cost-utility analysis will be performed using data from participant submitted EuroQol 5D-5L and Health Utilities Index Mark 3 scores and resource use data. Trial results will be made publicly available, including a plain English summary.

Effectiveness of mobile application interventions for stroke survivors: systematic review and meta-analysis

BACKGROUND

Although smartphone usage is ubiquitous, and a vast amount of mobile applications have been developed for chronic diseases, mobile applications amongst stroke survivors remain unclear.

OBJECTIVE

This systematic review and meta-analysis aimed to determine the effectiveness of mobile applications on medication adherence, functional outcomes, cardiovascular risk factors, quality of life and knowledge on stroke in stroke survivors.

METHODS

A review of the literature was conducted using key search terms in PubMed, EMBASE, Cochrane and Web of Science databases until 16 March 2023 to identify eligible randomized controlled trials (RCTs) or controlled clinical trial (CCTs) of mobile application interventions among stroke survivors. Two reviewers independently screened the literature in accordance with the eligibility criteria and collected data from the articles included. Outcomes included medication adherence,functional outcomes,cardiovascular risk factors, quality of life,and knowledge of stroke.

RESULTS

Twenty-three studies involving 2983 participants across nine countries were included in this review. Sixteen trials involved health care professionals in app use, and seven trials reported measures to ensure app-based intervention adherence. Mobile applications targeting stroke survivors primarily encompassed three areas: rehabilitation, education and self-care. The participants in the studies primarily included young and middle-aged stroke survivors. Meta-analysis results demonstrated that mobile application intervention significantly improved trunk control ability (mean differences [MD] 3.00, 95% CI [1.80 to 4.20]; P < 0.00001), Fugl-Meyer assessment of upper extremity (MD 9.81, 95% CI [8.72 to 10.90]; P < 0.00001), low-density lipoprotein cholesterol (MD - 0.33, 95% CI [- 0.54 to - 0.11]; P = 0.003) and glycosylated haemoglobin A1c (HbA1c)<7 levels (MD 1.95, 95% CI [1.17 to 3.25]; P = 0.01). However, the mobile application intervention did not differ significantly in medication adherence, 10-min walk test (10 MWT), Barthel index, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, body mass index, smoking, health-related quality of life and knowledge of stroke.

CONCLUSION

Our study suggested that mobile application interventions may have a potential benefit to stroke survivors, but clinical effectiveness should be established. More studies using rigorous designs are warranted to understand their usefulness. Future research should also involve more older adult stroke survivors.

Real-time personalized feedback in mHealth for adolescents

Mobile Health (mHealth) interventions have the potential to improve early identification, prevention, and treatment of mental health problems. Grow It! is a multiplayer smartphone app designed for youth aged 12-25, allowing them to monitor their emotions and engage in daily challenges based on Cognitive Behavioral Therapy (CBT) principles. Recently, a personalized mood profile was added to improve the app. We investigated whether real-time personalized feedback on mood enhances app engagement, user experience, and the effects on affective and cognitive well-being. Sample A (N = 1269, age = 18.60 SD = 3.39, 80.6% girls, 95.4% Dutch) played the original app without feedback on their mood, and an independent Sample B (N = 386, age = 16.04 SD = 3.21, 67.6% girls, 82.9% Dutch) received the renewed version with personalized real-time feedback on their mood. Participants who received personal feedback did not have higher app engagement (t(1750,400) = 1.39, P = .206, d = 0.07; t(692,905) = 0.36, P = .971, d = 0.0) nor higher user experience (t(177,596) = 0.21, P = .831, d = 0.02; (t(794) = 1.28, P = .202, d = 0.12; χ2 (659,141) = 2.83, P = .091). Players of the renewed version (Sample B) experienced significant improvements in affective (t(175) = 3.01, P = .003, d = 0.23) and cognitive well-being (t(175) = 3.48, P = <.001, d = 0.26) over the course of three weeks. The renewed version Grow It! has the potential to enhance youths' affective and cognitive well-being. However, adding real-time insights did not seem to affect app engagement nor user experience.

From research to routine care: A historical review of internet-based cognitive behavioral therapy for adult mental health problems in Sweden

This narrative historical review examines the development of internet-based cognitive behavioral therapy (ICBT) in Sweden, describing its progression within both academic and routine care settings. The review encompasses key publications, significant scientific findings, and contextual factors in real-world settings. Over 25 years ago, Sweden emerged as a pioneering force in internet-delivered treatment research for mental health. Since then, Swedish universities, in collaboration with research partners, have produced substantial research demonstrating the efficacy of ICBT across various psychological problems, including social anxiety disorder, panic disorder, generalized anxiety disorder, and depression. Although research conducted in clinical settings has been less frequent than in academic contexts, it has confirmed the effectiveness of therapist-supported ICBT programs for mild-to-moderate mental health problems in routine care. Early on, ICBT was provided as an option for patients at both the primary care level and in specialized clinics, using treatment programs developed by both public and private providers. The development of a national platform for delivering internet-based treatment and the use of procurement in selecting ICBT programs and providers are factors that have shaped the current routine care landscape. However, gaps persist in understanding how to optimize the integration of digital treatment in routine care, warranting further research and the use of specific implementation frameworks and outcomes. This historical perspective on the research and delivery of ICBT in Sweden over two decades offers insights for the international community into the development and broad dissemination of a specific digital mental health intervention within a national context.

Feasibility, Adherence, and Effectiveness of Blended Psychotherapy for Severe Mental Illnesses: Scoping Review

BACKGROUND

Blended psychotherapy (bPT) combines face-to-face psychotherapy with digital interventions to enhance the effectiveness of mental health treatment. The feasibility and effectiveness of bPT have been demonstrated for various mental health issues, although primarily for patients with higher levels of functioning.

OBJECTIVE

This scoping review aims to investigate the feasibility, adherence, and effectiveness of bPT for the treatment of patients with severe mental illnesses (SMIs).

METHODS

Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines, we conducted searches in PubMed, MEDLINE, Embase, PsycINFO, and PsycArticles for studies published until March 23, 2023.

RESULTS

Out of 587 screened papers, we incorporated 25 studies encompassing 23 bPT interventions, involving a total of 2554 patients with SMI. The intervention formats and research designs exhibited significant variation. Our findings offer preliminary evidence supporting the feasibility of bPT for SMI, although there is limited research on adherence. Nevertheless, the summarized studies indicated promising attrition rates, spanning from 0% to 37%, implying a potential beneficial impact of bPT on adherence to SMI treatment. The quantity of evidence on the effects of bPT for SMI was limited and challenging to generalize. Among the 15 controlled trials, 4 concluded that bPT interventions were effective compared with controls. However, it is noteworthy that 2 of these studies used the same study population, and the control groups exhibited significant variations.

CONCLUSIONS

Overall, our review suggests that while bPT appears promising as a treatment method, further research is necessary to establish its effectiveness for SMI. We discuss considerations for clinical implementation, directions, and future research.

A Personalized, Transdiagnostic Smartphone Intervention (Mello) Targeting Repetitive Negative Thinking in Young People With Depression and Anxiety: Pilot Randomized Controlled Trial

BACKGROUND

Repetitive negative thinking (RNT) is a key transdiagnostic mechanism underpinning depression and anxiety. Using "just-in-time adaptive interventions" via smartphones may disrupt RNT in real time, providing targeted and personalized intervention.

OBJECTIVE

This pilot randomized controlled trial evaluates the feasibility, acceptability, and preliminary clinical outcomes and mechanisms of Mello-a fully automated, personalized, transdiagnostic, and mechanistic smartphone intervention targeting RNT in young people with depression and anxiety.

METHODS

Participants with heightened depression, anxiety, and RNT were recruited via social media and randomized to receive Mello or a nonactive control over a 6-week intervention period. Assessments were completed via Zoom sessions at baseline and at 3 and 6 weeks after baseline.

RESULTS

The findings supported feasibility and acceptability, with high rates of recruitment (N=55), uptake (55/64, 86% of eligible participants), and retention (52/55, 95% at 6 weeks). Engagement was high, with 90% (26/29) and 59% (17/29) of the participants in the Mello condition still using the app during the third and sixth weeks, respectively. Greater reductions in depression (Cohen d=0.50), anxiety (Cohen d=0.61), and RNT (Cohen d=0.87) were observed for Mello users versus controls. Mediation analyses suggested that changes in depression and anxiety were accounted for by changes in RNT.

CONCLUSIONS

The results indicate that mechanistic, targeted, and real-time technology-based solutions may provide scalable and effective interventions that advance the treatment of youth mental ill health.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12621001701819; http://tinyurl.com/4d3jfj9f.

User-Centered Design of a Gamified Mental Health App for Adolescents in Sub-Saharan Africa: Multicycle Usability Testing Study

BACKGROUND

There is an urgent need for scalable psychological treatments to address adolescent depression in low-resource settings. Digital mental health interventions have many potential advantages, but few have been specifically designed for or rigorously evaluated with adolescents in sub-Saharan Africa.

OBJECTIVE

This study had 2 main objectives. The first was to describe the user-centered development of a smartphone app that delivers behavioral activation (BA) to treat depression among adolescents in rural South Africa and Uganda. The second was to summarize the findings from multicycle usability testing.

METHODS

An iterative user-centered agile design approach was used to co-design the app to ensure that it was engaging, culturally relevant, and usable for the target populations. An array of qualitative methods, including focus group discussions, in-depth individual interviews, participatory workshops, usability testing, and extensive expert consultation, was used to iteratively refine the app throughout each phase of development.

RESULTS

A total of 160 adolescents from rural South Africa and Uganda were involved in the development process. The app was built to be consistent with the principles of BA and supported by brief weekly phone calls from peer mentors who would help users overcome barriers to engagement. Drawing on the findings of the formative work, we applied a narrative game format to develop the Kuamsha app. This approach taught the principles of BA using storytelling techniques and game design elements. The stories were developed collaboratively with adolescents from the study sites and included decision points that allowed users to shape the narrative, character personalization, in-app points, and notifications. Each story consists of 6 modules ("episodes") played in sequential order, and each covers different BA skills. Between modules, users were encouraged to work on weekly activities and report on their progress and mood as they completed these activities. The results of the multicycle usability testing showed that the Kuamsha app was acceptable in terms of usability and engagement.

CONCLUSIONS

The Kuamsha app uniquely delivered BA for adolescent depression via an interactive narrative game format tailored to the South African and Ugandan contexts. Further studies are currently underway to examine the intervention's feasibility, acceptability, and efficacy in reducing depressive symptoms.

Feasibility, acceptability and preliminary efficacy of a mental health self-management app in clinicians working during the COVID-19 pandemic: A pilot randomised controlled trial

COVID-19 affected the well-being of healthcare workers (HCWs) globally. Mental health app interventions (MHAIs) may offer appropriate and accessible means to support HCWs' mental health. We conducted a pilot randomised controlled crossover trial involving 34 clinicians randomised to either a MHAI or a waitlisted group. After one month, outcome assessments were repeated and the waitlisted group then crossed over to the MHAI; they again completed outcome assessments after a month. The primary outcomes were feasibility, assessed with the Systems Usability Scale (SUS), and acceptability, assessed with the Client Satisfaction Questionnaire (CSQ). Secondary outcomes included efficacy for various mental health parameters. The SUS and CSQ scores indicated above average feasibility and acceptability. There was a significant difference in anxiety from baseline to 1-month follow-up between the groups, with greater improvement in the MHAI group. The groups differed in resilience and patient-related burnout from baseline to 1-month follow-up, with a trend towards significance, with greater improvements in the MHAI group. Anxiety and acute stress disorder severity improved significantly from pre- to post-intervention. We demonstrated that MHAIs hold potential for improving well-being of HCWs, although these findings will need to be replicated in adequately powered trials.

App-Based Interventions for Moderate to Severe Depression: A Systematic Review and Meta-Analysis

Importance

Mobile mental health applications (apps) for moderate to severe depression are proliferating, likely owing to their capacity to overcome the limitations of conventional psychotherapy, but research on the potential moderators of treatment efficacy is lacking.

Objective

To examine the treatment efficacy associated with mobile app interventions for moderate to severe depression and identify the potential moderators associated with better treatment outcomes.

Data Sources

PubMed, Embase, and PsycINFO were searched from their inception to January 22, 2023.

Study Selection

Only randomized clinical trials evaluating mobile app treatments in adults with moderate to severe depression that published their results in English were included in the analysis.

Data Extraction and Synthesis

Three independent researchers extracted and assessed relevant studies, their risk of bias, the characteristics of the population and study design, and the components of the intervention program following the Preferred Reporting Items for Systematic Reviews and Meta-analyses reporting guidelines. A fixed-effects model was used for data analysis, and exploratory post hoc meta-regression and subgroup analyses were also conducted. Data were analyzed from February 16 to March 25, 2023.

Main Outcomes and Measures

The main outcome was changes in depression symptom severity from before to after treatment, measured by standardized depression assessment instruments. Secondary outcomes included study-, intervention-, and patient-level factors associated with app efficacy.

Results

Of 2128 studies identified, 13 studies evaluating 16 intervention apps with 1470 participants with moderate to severe depression were included in the analysis. The overall pooled effect size of mobile app interventions vs both active and inactive control groups was 0.50 (95% CI, 0.40 to 0.61). Interventions with in-app notifications were associated with significantly lower treatment outcomes (standardized mean difference [SMD], 0.45; 95% CI, 0.29-0.60) than interventions without (SMD, 0.71; 95% CI, 0.54-0.87; P = .02). In addition, app interventions delivered for less than 8 weeks were associated with a significantly greater effect size (SMD, 0.77; 95% CI, 0.59-0.96) than interventions delivered for 8 weeks or longer (SMD, 0.43; 95% CI, 0.30-0.57; P = .004).

Conclusions and Relevance

In this systematic review and meta-analysis, the feasibility and efficacy of mobile app interventions were supported in treating moderate and severe depression, and practical implications were also provided for developing effective app-based interventions in clinical practice.

Implementing digital mental health interventions at scale: one-year evaluation of a national digital CBT service in Ireland

BACKGROUND

In recent years, exponential growth in digital innovations and internet access has provided opportunities to deliver health services at a much greater scale than previously possible. Evidence-based technology-enabled interventions can provide cost-effective, accessible, and resource-efficient solutions for addressing mental health issues. This study evaluated the first year of a supported digital cognitive behavioral therapy (CBT) service provided by the national health service in Ireland, which has been accessible to individuals who receive a referral from one of five referring groups: General Practitioners, Primary Care Psychology, Counselling Primary Care, Community Mental Health, and Jigsaw (a nationwide youth mental health service).

METHODS

A retrospective, observational study examining data from the service between April 2021 to April 2022 was conducted. Descriptive statistics on referrals, account activations, user demographics, program usage, and user satisfaction were extracted, and pre-to-post clinical outcomes for depression measured by the Patient Health Questionnaire-9 and for anxiety measured by the Generalised Anxiety Disorder-7 were analysed using linear mixed effect models.

RESULTS

There were 5,298 referrals and 3,236 (61%) account activations within the year. Most users were female (72.9%) and aged between 18 and 44 years (75.4%). The CBT programs were associated with significant reductions in both depression (β = 3.34, 95% CI [3.03, 3.65], p < 0.001) and anxiety (β = 3.64, 95% CI [3.36, 3.93], p < 0.001), with large effect sizes (Cohen's d > 0.8). Time spent using the programs was also found to be a predictor of the variability in these clinical outcomes (p < 0.001), and accounting for this resulted in significantly better model fits (p < 0.001). User satisfaction ratings were also very high, exceeding 94%.

CONCLUSIONS

Efforts to improve the representation of male and older adult users are warranted. However, overall, the results demonstrate how digital CBT can be provided at scale and lead to symptom reductions with large effect sizes for patients seeking help for depression and anxiety. The findings substantiate the continued use and expansion of this service in Ireland and the more widespread implementation of similar services in other international public healthcare settings.

Efficacy, Safety, and Evaluation Criteria of mHealth Interventions for Depression: Systematic Review

BACKGROUND

Depression is a significant public health issue that can lead to considerable disability and reduced quality of life. With the rise of technology, mobile health (mHealth) interventions, particularly smartphone apps, are emerging as a promising approach for addressing depression. However, the lack of standardized evaluation tools and evidence-based principles for these interventions remains a concern.

OBJECTIVE

In this systematic review and meta-analysis, we aimed to evaluate the efficacy and safety of mHealth interventions for depression and identify the criteria and evaluation tools used for their assessment.

METHODS

A systematic review and meta-analysis of the literature was carried out following the recommendations of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. Studies that recruited adult patients exhibiting elevated depressive symptoms or those diagnosed with depressive disorders and aimed to assess the effectiveness or safety of mHealth interventions were eligible for consideration. The primary outcome of interest was the reduction of depressive symptoms, and only randomized controlled trials (RCTs) were included in the analysis. The risk of bias in the original RCTs was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials.

RESULTS

A total of 29 RCTs were included in the analysis after a comprehensive search of electronic databases and manual searches. The efficacy of mHealth interventions in reducing depressive symptoms was assessed using a random effects meta-analysis. In total, 20 RCTs had an unclear risk of bias and 9 were assessed as having a high risk of bias. The most common element in mHealth interventions was psychoeducation, followed by goal setting and gamification strategies. The meta-analysis revealed a significant effect for mHealth interventions in reducing depressive symptoms compared with nonactive control (Hedges g=-0.62, 95% CI -0.87 to -0.37, I2=87%). Hybrid interventions that combined mHealth with face-to-face sessions were found to be the most effective. Three studies compared mHealth interventions with active controls and reported overall positive results. Safety analyses showed that most studies did not report any study-related adverse events.

CONCLUSIONS

This review suggests that mHealth interventions can be effective in reducing depressive symptoms, with hybrid interventions achieving the best results. However, the high level of heterogeneity in the characteristics and components of mHealth interventions indicates the need for personalized approaches that consider individual differences, preferences, and needs. It is also important to prioritize evidence-based principles and standardized evaluation tools for mHealth interventions to ensure their efficacy and safety in the treatment of depression. Overall, the findings of this study support the use of mHealth interventions as a viable method for delivering mental health care.

TRIAL REGISTRATION

PROSPERO CRD42022304684; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304684.

Evaluating the effectiveness and cost-effectiveness of a digital, app-based intervention for depression (VMood) in community-based settings in Vietnam: Protocol for a stepped-wedge randomized controlled trial

The COVID-19 pandemic has amplified mental health problems and highlighted inequitable gaps in care worldwide. In response there has been an explosion of digital interventions such as smartphone applications ("apps") to extend care. The objective of this trial is to evaluate the effectiveness and cost-effectiveness of a digital depression intervention (VMood), delivered via a smartphone app. VMood is adapted from an in-person intervention that was delivered by non-specialist providers and shown to be effective in the Vietnamese context in our previous trial (2016-2019). A stepped-wedge, randomized controlled trial will be conducted across eight provinces in Vietnam. Adults aged 18 years and over will be recruited through community-based primary care centres and screened for depression using the embedded Patient Health Questionnaire-9 (primary outcome measure). Participants scoring 10-19, indicating depression caseness, will be randomly allocated to the intervention or control group until the target of 336 is reached. Secondary outcome measures will examine the effect of the intervention on commonly co-occuring anxiety, quality of life and work productivity, along with use of alcohol and tobacco products. Assessments will be administered through an online survey platform (REDCap) at baseline, and at every 3 months until 3 months post-intervention. Intervention-group participants will receive VMood for a 3-month period, with online support provided by social workers. Control-group participants will receive a limited version of the app until they cross into the intervention group. Generalized Linear Mixed-effect Models for clustered measures will be used for all outcomes data. We will conduct a cost-effectiveness analysis alongside the trial to capture VMood's costs and benefits. This trial will provide evidence on the effectiveness and cost-effectiveness of a digital mental health intervention adapted from an in-person intervention. This trial will also contribute important information to the growing and promising field of digital mental health. Trail regulation. Registered at ClinicalTrials.gov, identifier [NCT05783531].

Exploring putative therapeutic mechanisms of change in a hybrid compassion-focused, ecological momentary intervention: Findings from the EMIcompass trial

Compassion-focused interventions represent a promising transdiagnostic approach, but the mechanisms involved in hybrid delivery combining face-to-face sessions and an ecological momentary intervention remain unexplored. The current study aimed at exploring associations of putative mechanisms with clinical outcomes at post-intervention/follow-up and mediation of outcome at follow-up by preceding pre-to post-intervention changes in putative mechanisms. The compassion-focused EMIcompass intervention was applied in an exploratory randomized controlled trial (treatment as usual (TAU) vs. TAU + EMIcompass) with youth with early mental health problems. Data was collected before randomization, at post-intervention and at four-week follow-up. We recruited N = 92 participants, N = 46 were allocated to the experimental condition. After control for baseline levels of the target outcomes, baseline-to post-intervention improvement in adaptive emotion regulation was associated with lower levels of clinical outcomes (e.g. psychological distress b = -1.15; 95%CI = -1.92 to -0.39) across time points. We could not detect indirect effects, but we observed associations of change in self-compassion and adaptive emotion regulation with outcomes at follow-up in the mediation analysis (e.g., β = -0.35, 95%CI = -0.52 to -0.16). If successfully targeted by interventions, self-compassion and emotion regulation may be promising putative therapeutic mechanisms of change.

Digital Therapeutics as a New Therapeutic Modality: A Review from the Perspective of Clinical Pharmacology

The promise of transforming digital technologies into treatments is what drives the development of digital therapeutics (DTx), generally known as software applications embedded within accessible technologies-such as smartphones-to treat, manage, or prevent a pathological condition. Whereas DTx solutions that successfully demonstrate effectiveness and safety could drastically improve the life of patients in multiple therapeutic areas, there is a general consensus that generating therapeutic evidence for DTx presents challenges and open questions. We believe there are three main areas where the application of clinical pharmacology principles from the drug development field could benefit DTx development: the characterization of the mechanism of action, the optimization of the intervention, and, finally, its dosing. We reviewed DTx studies to explore how the field is approaching these topics and to better characterize the challenges associated with them. This leads us to emphasize the role that the application of clinical pharmacology principles could play in the development of DTx and to advocate for a development approach that merges such principles from development of traditional therapeutics with important considerations from the highly attractive and fast-paced world of digital solutions.

Efficacy of a Brief Blended Cognitive Behavioral Therapy Program for the Treatment of Depression and Anxiety in University Students: Uncontrolled Intervention Study

BACKGROUND

Blended cognitive behavioral therapy (bCBT)-the combination of cognitive behavioral therapy and digital mental health applications-has been increasingly used to treat depression and anxiety disorders. As a resource-efficient treatment approach, bCBT appears promising for addressing the growing need for mental health care services, for example, as an early intervention before the chronification of symptoms. However, further research on the efficacy and feasibility of integrated bCBT interventions is needed.

OBJECTIVE

This study aimed to evaluate the efficacy of a novel bCBT program comprising short (25 min), weekly face-to-face therapy sessions combined with a smartphone-based digital health app for treating mild to moderate symptoms of depression or anxiety.

METHODS

This prospective uncontrolled trial comprised 2 measurement points (before and after treatment) and 2 intervention groups. We recruited university students with mild to moderate symptoms of depression or anxiety. On the basis of the primary symptoms, participants were assigned to either a depression intervention group (n=67 completers) or an anxiety intervention group (n=33 completers). Participants in each group received 6 weekly individual psychotherapy sessions via videoconference and completed modules tailored to their respective symptoms in the smartphone-based digital health app.

RESULTS

The depression group displayed medium to large improvements in the symptoms of depression (Cohen d=-0.70 to -0.90; P<.001). The anxiety group experienced significant improvements in the symptoms of generalized anxiety assessed with the Generalized Anxiety Disorder-7 scale with a large effect size (Cohen d=-0.80; P<.001) but not in symptoms of anxiety assessed with the Beck Anxiety Inventory (Cohen d=-0.35; P=.06). In addition, both groups experienced significant improvements in their perceived self-efficacy (Cohen d=0.50; P<.001 in the depression group and Cohen d=0.71; P<.001 in the anxiety group) and quality of life related to psychological health (Cohen d=0.87; P<.001 in the depression group and Cohen d=0.40; P=.03 in the anxiety group). Work and social adjustment of patients improved significantly in the depression group (Cohen d=-0.49; P<.001) but not in the anxiety group (Cohen d=-0.06; P=.72). Patients' mental health literacy improved in the anxiety group (Cohen d=0.45; P=.02) but not in the depression group (Cohen d=0.21; P=.10). Patient satisfaction with the bCBT program and ratings of the usability of the digital app were high in both treatment groups.

CONCLUSIONS

This study provides preliminary evidence for the feasibility and efficacy of a novel brief bCBT intervention. The intervention effects were generalized across a broad spectrum of patient-reported outcomes. Hence, the newly developed bCBT intervention appears promising for treating mild to moderate depression and anxiety in young adults.

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.

Efficacy of stand-alone digital mental health applications for anxiety and depression: A meta-analysis of randomized controlled trials

BACKGROUND

Anxiety and depressive disorders affect 20% of the population, cause functional impairment, and represent a leading cause of disability. Although evidence-based treatments exist, the shortage of trained clinicians and high demand for mental health services have resulted in limited access to evidence-based care. Digital mental health applications (DMHA) present innovative, scalable, and sustainable solutions to address disparities in mental health care.

METHODS

The present study used meta-analytic techniques to evaluate the therapeutic effect of DMHAs in randomized controlled trials (RCTs) for individuals experiencing anxiety and/or depressive symptoms. Search terms were selected based on concepts related to digital mental health applications, mental health/wellness, intervention type, trial design, and anxiety and/or depression symptoms/diagnosis outcomes to capture all potentially eligible results. Potential demographic, DMHA, and trial design characteristics were examined as moderators of therapeutic effects.

RESULTS

Random effects meta-analyses found that stand-alone DMHAs produced a modest reduction in anxiety (g = 0.31) and depressive (g = 0.35) symptom severity. Several moderators influenced the therapeutic effects of DMHAs for anxiety and/or depressive symptoms including treatment duration, participant inclusion criteria, and outcome measures.

LIMITATIONS

Minimal information was available on DMHA usability and participant engagement with DMHAs within RCTs.

CONCLUSIONS

While DMHAs have the potential to be scalable and sustainable solutions to improve access and availability of evidence-based mental healthcare, moderator analyses highlight the considerations for implementation of DMHAs in practice. Further research is needed to understand factors that influence therapeutic effects of DMHAs and investigate strategies to optimize its implementation and overcome the extant research-to-practice gap.

A Comparison of the Readiness of Youth Service Agencies to Implement a Technology-Based Toolkit to Support Treatment Delivery

Implementation initiatives and technology-based resources aim to address barriers to Evidence-Based Practice (EBP) use by creating generalizable techniques that can be used for a variety of youth-serving agencies. However, research has not carefully examined unique differences between agency types or individual programs in readiness to use such technologies and implementation strategies. The current study explored differences between community mental health clinics and child advocacy centers on organizational cultural factors (e.g., ability to change and commitment for change) to implement a novel technology-based toolkit to support delivery of Trauma Focused Cognitive Behavioral Therapy (TF-CBT). Results indicated that TF-CBT providers from child advocacy centers reported greater commitment to change and more support to use the technology-based system than those from community mental health centers. Findings suggest that implementation initiatives should address the needs of individual agencies and service settings and adaptations should be explored to best meet the needs of these settings.

Wearable and Mobile Technologies for the Evaluation and Treatment of Obsessive-Compulsive Disorder: Scoping Review

BACKGROUND

Smartphones and wearable biosensors can continuously and passively measure aspects of behavior and physiology while also collecting data that require user input. These devices can potentially be used to monitor symptom burden; estimate diagnosis and risk for relapse; predict treatment response; and deliver digital interventions in patients with obsessive-compulsive disorder (OCD), a prevalent and disabling psychiatric condition that often follows a chronic and fluctuating course and may uniquely benefit from these technologies.

OBJECTIVE

Given the speed at which mobile and wearable technologies are being developed and implemented in clinical settings, a continual reappraisal of this field is needed. In this scoping review, we map the literature on the use of wearable devices and smartphone-based devices or apps in the assessment, monitoring, or treatment of OCD.

METHODS

In July 2022 and April 2023, we conducted an initial search and an updated search, respectively, of multiple databases, including PubMed, Embase, APA PsycINFO, and Web of Science, with no restriction on publication period, using the following search strategy: ("OCD" OR "obsessive" OR "obsessive-compulsive") AND ("smartphone" OR "phone" OR "wearable" OR "sensing" OR "biofeedback" OR "neurofeedback" OR "neuro feedback" OR "digital" OR "phenotyping" OR "mobile" OR "heart rate variability" OR "actigraphy" OR "actimetry" OR "biosignals" OR "biomarker" OR "signals" OR "mobile health").

RESULTS

We analyzed 2748 articles, reviewed the full text of 77 articles, and extracted data from the 25 articles included in this review. We divided our review into the following three parts: studies without digital or mobile intervention and with passive data collection, studies without digital or mobile intervention and with active or mixed data collection, and studies with a digital or mobile intervention.

CONCLUSIONS

Use of mobile and wearable technologies for OCD has developed primarily in the past 15 years, with an increasing pace of related publications. Passive measures from actigraphy generally match subjective reports. Ecological momentary assessment is well tolerated for the naturalistic assessment of symptoms, may capture novel OCD symptoms, and may also document lower symptom burden than retrospective recall. Digital or mobile treatments are diverse; however, they generally provide some improvement in OCD symptom burden. Finally, ongoing work is needed for a safe and trusted uptake of technology by patients and providers.

Conducting a systematic review and evaluation of commercially available mobile applications (apps) on a health-related topic: the TECH approach and a step-by-step methodological guide

OBJECTIVES

To provide an overview of the methodological considerations for conducting commercial smartphone health app reviews (mHealth reviews), with the aim of systematising the process and supporting high-quality evaluations of mHealth apps.

DESIGN

Synthesis of our research team's experiences of conducting and publishing various reviews of mHealth apps available on app stores and hand-searching the top medical informatics journals (eg, The Lancet Digital Health, npj Digital Medicine, Journal of Biomedical Informatics and the Journal of the American Medical Informatics Association) over the last five years (2018-2022) to identify other app reviews to contribute to the discussion of this method and supporting framework for developing a research (review) question and determining the eligibility criteria.

RESULTS

We present seven steps to support rigour in conducting reviews of health apps available on the app market: (1) writing a research question or aims, (2) conducting scoping searches and developing the protocol, (3) determining the eligibility criteria using the TECH framework, (4) conducting the final search and screening of health apps, (5) data extraction, (6) quality, functionality and other assessments and (7) analysis and synthesis of findings. We introduce the novel TECH approach to developing review questions and the eligibility criteria, which considers the Target user, Evaluation focus, Connectedness and the Health domain. Patient and public involvement and engagement opportunities are acknowledged, including co-developing the protocol and undertaking quality or usability assessments.

CONCLUSION

Commercial mHealth app reviews can provide important insights into the health app market, including the availability of apps and their quality and functionality. We have outlined seven key steps for conducting rigorous health app reviews in addition to the TECH acronym, which can support researchers in writing research questions and determining the eligibility criteria. Future work will include a collaborative effort to develop reporting guidelines and a quality appraisal tool to ensure transparency and quality in systematic app reviews.

Opportunities and challenges to enhance the value and uptake of Chief Nursing Informatics Officer (CNIO) Roles in Canada: A Qualitative Study

Clinician informatics leadership has been identified as an essential component of addressing the 'implementation to benefits realization gap' that exists for many digital health technologies. Chief Medical Informatics Officers (CMIOs), and Chief Nursing Informatics Officers (CNIOs) are well-positioned to ensure the success of these initiatives. However, while the CMIO role is fairly well-established in Canada, there is limited uptake of CNIO roles in the country. The main objective of this work is to build on the current progress of the CMIO role and explore how the CNIO role can be best positioned for uptake and value across healthcare organizations in Canada. A qualitative study was conducted. Ten clinician leaders in CMIO, CNIO, and related roles in Canada were interviewed about the value of these roles and strategies for supporting the uptake of the role. This study provides the foundation for future initiatives for supporting and showcasing the value of the CNIO in a digitally enabled healthcare organization.

A systematic review and meta-analysis of digital interventions targeted at individuals with borderline personality disorder (BPD), emotionally unstable personality disorder (EUPD), and related symptoms

OBJECTIVES

The present review investigates the impact of digital interventions for individuals with features of borderline personality disorder (BPD)/emotional unstable personality disorder (EUPD) as digital interventions show promise as therapeutic tools in underserved groups. BPD/EUPD features are identified as clinically relevant, yet previous reviews on the use of digital interventions fail to include subthreshold symptomatology.

METHODS

Five online databases were searched for terminology in three categories: BPD/EUPD and related symptoms, mental-health interventions, and digital technology. Additionally, four relevant journals and two trial registers were searched for additional papers meeting the inclusion criteria.

RESULTS

Twelve articles met all inclusion criteria. Meta-analyses revealed statistically significant differences in symptom measures between intervention and control groups at postintervention and decreases in BPD/EUPD symptomatology and well-being from pre- to postintervention. Service users' engagement, satisfaction, and acceptability of interventions were high. Results support the previous literature on the value of using digital interventions in populations with BPD/EUPD.

CONCLUSION

Overall, it was identified that digital interventions show promise for successful implementation with this population.