Development and Pilot Testing of an Internet-Based Self-Help Intervention for Depression for Indian Users

Feasibility and acceptability of an online group dialectical behavioural therapy skills training in a Transdiagnostic group with Anxiety and Depression

Transdiagnostic approaches offers a paradigm shift in managing psychiatric disorders. Emotion regulation difficulties are a transdiagnostic prevalent across various mood and personality disorders. Dialectical Behavioural Therapy Skills Training (DBT-ST), initially designed as part of treatment for borderline personality disorder, targets emotion regulation and has shown promise in diverse psychiatric conditions. In lower middle-income countries with resource-constrained settings, online delivery of evidence-based interventions holds potential to bridge treatment gaps. This study assesses the feasibility and acceptability of online group DBT skills training for individuals with depression or anxiety disorders in India. Mental health professionals practising in India referred twenty-four eligible participants currently not engaged in psychotherapy. Of these, 18 initiated the 8-week virtual group DBT-ST program, with 12 completing it (66 % female, 18-35 years of age, 5 on concurrent medication). They provided feedback on therapy content's usefulness. Baseline, post-intervention, and one-month follow-up assessments measured changes in emotion regulation difficulties, depression, and anxiety symptoms. Treatment retained 66.7 % of participants, all participants found the intervention beneficial. Repeated measures ANOVA indicates significant reductions in self-reported difficulties in emotion regulation, depression, and anxiety symptoms post-intervention. These findings highlight the promise of transdiagnostic interventions like DBT-ST that merit further evaluations using RCTs with larger sample sizes.

Mobile Behavioral Health Coaching as a Preventive Intervention for Occupational Public Health: Retrospective Longitudinal Study

BACKGROUND

Researchers have recently proposed that behavioral health coaching (BHC) is effective in promoting proactive care among employees. However, to qualify as a preventive workplace intervention, more research is needed to evaluate whether BHC can further elevate well-being among moderately mentally healthy employees.

OBJECTIVE

Using real-world data, this study evaluates the preliminary effectiveness of app-based BHC against a nonrandomized control group with open access to self-help tools in improving well-being (ie, mood levels and perceived stress). The study also explores the active ingredients of BHC and dose-response associations between the number of BHC sessions and well-being improvements.

METHODS

Employees residing across Asia-Pacific countries (N=1025; mean age 30.85, SD 6.97 y) who reported moderately positive mood and medium levels of perceived stress in their first week of using the mental health app Intellect were included in this study. Users who were given access by their organizations to Intellect's BHC services were assigned to the "Coaching" condition (512/1025, 49.95%; mean age 31.09, SD 6.87 y), whereas other employees remained as "Control" participants (513/1025, 50.05%; mean age 30.61, SD 7.06 y). To evaluate effectiveness, monthly scores from the validated mood and stress sliders were aggregated into a composite well-being score and further examined using repeated-measure conditional growth models. Postcoaching items on "Perceived Usefulness of the BHC session" and "Working Alliance with my Coach" were examined as active ingredients of BHC using 1-1-1 multilevel mediation models. Finally, 2-way repeated-measure mixed ANOVA models were conducted to examine dose-response effects on well-being improvements between groups (coaching and control) across time.

RESULTS

Growth curve analyses revealed significant time by group interaction effects for composite well-being, where "Coaching" users reported significantly greater improvements in well-being than "Control" participants across time (composite well-being: F1,391=6.12; ηp2=0.02; P=.01). Among "Coaching" participants, dependent-sample 2-tailed t tests revealed significant improvements in composite well-being from baseline to 11 months (t512=1.98; Cohen d=0.17; P=.049). Improvements in "Usefulness of the BHC session" (β=.078, 95% Cl .043-.118; P<.001) and "Working Alliance" (β=.070, 95% Cl .037-.107; P<.001) fully mediated within-level well-being enhancements over time. Comparing against baseline or first month scores, significant time by group interactions were observed between the second and sixth months, with the largest effect size observed at the fifth month mark (first month vs fifth month: F1,282=15.0; P<.001; ηp2=0.051).

CONCLUSIONS

We found preliminary evidence that BHC is an effective preventive workplace intervention. Mobile-based coaching may be a convenient, cost-effective, and scalable means for organizations and governments to boost public mental health.

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.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Systematic Review Registration

Identifier: CRD42022357408.

Self-guided Cognitive Behavioral Therapy Apps for Depression: Systematic Assessment of Features, Functionality, and Congruence With Evidence

Background

Mental health disorders affect 1 in 10 people globally, of whom approximately 300 million are affected by depression. At least half of the people affected by depression remain untreated. Although cognitive behavioral therapy (CBT) is an effective treatment, access to mental health specialists, habitually challenging, has worsened because of the COVID-19 pandemic. Internet-based CBT is an effective and feasible strategy to increase access to treatment for people with depression. Mental health apps may further assist in facilitating self-management for people affected by depression; however, accessing the correct app may be cumbersome given the large number and wide variety of apps offered by public app marketplaces.

Objective

This study aims to systematically assess the features, functionality, data security, and congruence with evidence of self-guided CBT-based apps targeting users affected by depression that are available in major app stores.

Methods

We conducted a systematic assessment of self-guided CBT-based apps available in Google Play and the Apple App Store. Apps launched or updated since August 2018 were identified through a systematic search in the 42matters database using CBT-related terms. Apps meeting the inclusion criteria were downloaded and assessed using a Samsung Galaxy J7 Pro (Android 9) and iPhone 7 (iOS 13.3.1). Apps were appraised using a 182-question checklist developed by the research team, assessing their general characteristics, technical aspects and quality assurance, and CBT-related features, including 6 evidence-based CBT techniques (ie, psychoeducation, behavioral activation, cognitive restructuring, problem solving, relaxation, and exposure for comorbid anxiety) as informed by a CBT manual, CBT competence framework, and a literature review of internet-based CBT clinical trial protocols. The results were reported as a narrative review using descriptive statistics.

Results

The initial search yielded 3006 apps, of which 98 met the inclusion criteria and were systematically assessed. There were 20 well-being apps; 65 mental health apps, targeting two or more common mental health disorders, including depression; and 13 depression apps. A total of 28 apps offered at least four evidence-based CBT techniques, particularly depression apps. Cognitive restructuring was the most common technique, offered by 79% (77/98) of the apps. Only one-third of the apps offered suicide risk management resources, whereas 17% (17/98) of the apps offered COVID-19–related information. Although most apps included a privacy policy, only a third of the apps presented it before account creation. In total, 82% (74/90) of privacy policies stated sharing data with third-party service providers. Half of the app development teams included academic institutions or health care providers.

Conclusions

Only a few self-guided CBT-based apps offer comprehensive CBT programs or suicide risk management resources. Sharing of users’ data is widespread, highlighting shortcomings in health app market governance. To fulfill their potential, self-guided CBT-based apps should follow evidence-based clinical guidelines, be patient centered, and enhance users’ data security.

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

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

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

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

Smartphone Apps for the Treatment of Mental Disorders: Systematic Review

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Smartteen- a computer assisted cognitive behavior therapy for Indian adolescents with depression- a pilot study

The prevalence of unipolar depression among adolescents in India is high. Cognitive behavior therapies (CBTs) are considered the current gold standard treatment for depression in adolescents; however, their access is limited in India. Given the ubiquity of technology including smartphones and computers, technology can be leveraged to improve access of CBT treatment in India. Our team developed smartteen- a computer application designed to augment in-person CBT for treatment of depression in adolescents. This paper will present results of the pilot evaluation of smartteen (a cCBT) for its feasibility, acceptability and effectiveness in reducing depressive symptoms. Twenty-one adolescents with unipolar depression seeking treatment at a tertiary care hospital were randomly assigned to smartteen (n = 11) and TAU (n = 10). Both groups received twelve weeks of treatment and were assessed at baseline, mid-treatment (6 weeks) and post-treatment (12 weeks) using four clinical measures including BDI-II, CDRS-R, CGI-S and CGAS. smartteen was shown to be feasible and acceptable treatment to adolescents. At 6 weeks, both treatments were effective in reducing depression. At 12 weeks, smartteen was significantly more effective than TAU in reducing depression symptoms and improving functioning on CGAS. Treatment compliance was better in smartteen group. smartten was shown to reduce the time spent by therapist to deliver 12 sessions of CBT treatment for depression. Results indicate that smartteen may be subjected to more rigorous evaluations with larger samples and considered for wider implementation if found effective.

Implementation outcomes and strategies for depression interventions in low- and middle-income countries: a systematic review

BACKGROUND

We systematically reviewed implementation research targeting depression interventions in low- and middle-income countries (LMICs) to assess gaps in methodological coverage.

METHODS

PubMed, CINAHL, PsycINFO, and EMBASE were searched for evaluations of depression interventions in LMICs reporting at least one implementation outcome published through March 2019.

RESULTS

A total of 8714 studies were screened, 759 were assessed for eligibility, and 79 studies met inclusion criteria. Common implementation outcomes reported were acceptability (n = 50; 63.3%), feasibility (n = 28; 35.4%), and fidelity (n = 18; 22.8%). Only four studies (5.1%) reported adoption or penetration, and three (3.8%) reported sustainability. The Sub-Saharan Africa region (n = 29; 36.7%) had the most studies. The majority of studies (n = 59; 74.7%) reported outcomes for a depression intervention implemented in pilot researcher-controlled settings. Studies commonly focused on Hybrid Type-1 effectiveness-implementation designs (n = 53; 67.1), followed by Hybrid Type-3 (n = 16; 20.3%). Only 21 studies (26.6%) tested an implementation strategy, with the most common being revising professional roles (n = 10; 47.6%). The most common intervention modality was individual psychotherapy (n = 30; 38.0%). Common study designs were mixed methods (n = 27; 34.2%), quasi-experimental uncontrolled pre-post (n = 17; 21.5%), and individual randomized trials (n = 16; 20.3).

CONCLUSIONS

Existing research has focused on early-stage implementation outcomes. Most studies have utilized Hybrid Type-1 designs, with the primary aim to test intervention effectiveness delivered in researcher-controlled settings. Future research should focus on testing and optimizing implementation strategies to promote scale-up of evidence-based depression interventions in routine care. These studies should use high-quality pragmatic designs and focus on later-stage implementation outcomes such as cost, penetration, and sustainability.

Examining the initial usability, acceptability and feasibility of a digital mental health intervention for college students in India

Generalised anxiety disorder (GAD) is prevalent among college students in India; however, barriers like stigma, treatment accessibility and cost prevent engagement in treatment. Web- and mobile-based, or digital, mental health interventions have been proposed as a potential solution to increasing treatment access. With the ultimate goal of developing an engaging digital mental health intervention for university students in India, the current study sought to understand students' reactions to a culturally and digitally adapted evidence-based cognitive behavioural therapy (CBT) for GAD intervention. Specifically, through theatre testing and focus groups with a non-clinical sample of 15 college students in India, the present study examined initial usability, acceptability and feasibility of the "Mana Maali Digital Anxiety Program." Secondary objectives comprised identifying students' perceived barriers to using the program and eliciting recommendations. Results indicated high usability, with the average usability rating ranking in the top 10% of general usability scores. Participants offered actionable changes to improve usability and perceived acceptability among peers struggling with mental health issues. Findings highlight the benefits of offering digital resources that circumvent barriers associated with accessing traditional services. Results build on existing evidence that digital interventions can be a viable means of delivering mental healthcare to large, defined populations.

Digital interventions for people living with non-communicable diseases in India: A systematic review of intervention studies and recommendations for future research and development

BACKGROUND

A high burden of non-communicable diseases (NCDs) is contributing to high mortality and morbidity in India. Recent advancements in digital health interventions, including mHealth, eHealth, and telemedicine, have facilitated patient-centered care for NCDs.

OBJECTIVE

This systematic review aims to evaluate the current evidence on digital interventions for people living with NCDs in India and the outcomes of those interventions.

METHODS

We adopted PRISMA guidelines and systematically reviewed articles from MEDLINE, CINAHL, PsycINFO, ERIC, and Scopus databases with following criteria: journal articles presenting digital intervention(s) used by people with at least one of the NCDs, reporting health outcomes following the intervention, studies conducted in India among Indian population.

RESULTS

Among 1669 articles retrieved from multiple sources, only 13 articles met our criteria. Most (n = 7) studies were conducted in southern states of India; eight studies included patients with diabetes, followed by neuropsychiatric disorders and other NCDs. Five studies recruited participants from tertiary hospitals; six interventions used text-messaging for delivering health services, and 10 studies reported randomized controlled trials. All the studies reported positive health outcomes following the intervention, including better self-management, increased patient-provider communication, improved medication adherence, and reduced disease symptoms. Most studies scored moderate to high in quality assessment checklist of Downs and Black.

CONCLUSION

Current evidence suggests a low number of interventions with positive outcomes. Future research should explore avenues of advanced technologies ensuring equitable and sustainable development of digital health interventions for people living with NCDs in India.