Is clinician-supported use of a mindfulness smartphone app a feasible treatment for depression? A mixed-methods feasibility study

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION

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

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

TRIAL REGISTRATION

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

Understanding the Implementation of Informal Meditation Practice in a Smartphone-Based Intervention: A Qualitative Analysis

Objectives

Informal practice (i.e., brief meditation practices incorporated spontaneously into daily activities) may be important for increasing the efficacy and accessibility of meditation-based interventions (MedBIs). However, the facilitators and barriers to engaging in informal practice are largely unknown. The current study aimed to investigate factors associated with the implementation of informal practice.

Method

Participants were drawn from a randomized trial testing the effects of 5- versus 15-min daily meditation practice in a 4-week smartphone-delivered meditation training. Qualitative interviews on informal practice were conducted with 17 participants (mean age: 37.12 years; 82.35% female; 52.94% non-Latinx White) following the intervention. Given that prior knowledge on this topic is limited, inductive content analysis was utilized to characterize participants' experiences in relation to implementing informal practice.

Results

Four overarching categories emerged from the data, namely (a) reported benefits of informal practice, (b) integration of informal practice, (c) perceived barriers to informal practice, and (d) recommended facilitators of informal practice.

Conclusion

This study underscores the importance of addressing barriers and facilitators (e.g., providing personalized app features, reminders, social support, and repeating intervention content) to encourage individuals' informal practice. Findings provide suggestions for methods to increase engagement in informal practice, which may, in turn, increase the accessibility and effectiveness of MedBIs.

Preregistration

The larger trial from which the qualitative interview participants were drawn was preregistered through clinicaltrials.gov (NCT05229406) and the Open Science Framework (https://osf.io/fszvj/?view_only=039b14ccbf8848bd99808c983070b635). The qualitative analyses reported here were not preregistered.

Implementation of digital health interventions in rehabilitation: A scoping review

OBJECTIVE

Digital health interventions have potential to enhance rehabilitation services by increasing accessibility, affordability and scalability. However, implementation of digital interventions in rehabilitation is poorly understood. This scoping review aims to map current strategies, research designs, frameworks, outcomes and determinants used to support and evaluate the implementation of digital interventions in rehabilitation.

DATA SOURCES

Comprehensive searches from inception until October 2022 of MEDLINE, CINAHL, PsycINFO, PEDro, SpeechBITE, NeuroBITE, REHABDATA, WHO International Clinical Trial Registry and the Cochrane Library.

METHODS

Two reviewers screened studies against the eligibility criteria. Implementation science taxonomies and methods, including Powell et al.'s compilation of implementation strategies, were used to guide analysis and synthesis of findings.

RESULTS

The search retrieved 13,833 papers and 23 studies were included. Only 4 studies were randomised controlled trials and 9 studies (39%) were feasibility studies. Thirty-seven discrete implementation strategies were reported across studies. Strategies related to training and educating clinicians (91%), providing interactive assistance (61%), and developing stakeholder interrelationships (43%) were most frequently reported. Few studies adequately described implementation strategies and methods for selecting strategies. Almost all studies measured implementation outcomes and determinants; most commonly, acceptability, compatibility and dose delivered of digital interventions.

CONCLUSION

The rigour of implementation methods in the field is currently poor. Digital interventions require carefully planned and tailored implementation to facilitate successful adoption into rehabilitation practice. To keep pace with rapidly advancing technology, future rehabilitation research should prioritise using implementation science methods to explore and evaluate implementation while testing effectiveness of digital interventions.

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.

What Works to Improve Wellbeing? A Rapid Systematic Review of 223 Interventions Evaluated with the Warwick-Edinburgh Mental Well-Being Scales

INTRODUCTION

The Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS) is a commonly used scale of mental wellbeing focusing entirely on the positive aspect of mental health. It has been widely used in a broad range of clinical and research settings, including to evaluate if interventions, programmes or pilots improve wellbeing. We aimed to systematically review all interventions that used WEMWBS and evaluate which interventions are the most effective at improving wellbeing.

METHODS

Eligible populations included children and adults, with no health or age restrictions. Any intervention study was eligible if the wellbeing outcome was measured using the 7 or 14-item WEMWBS scale assessed both pre- and post-intervention. We identified eligible intervention studies using three approaches: a database search (Medline, EMBASE, CINAHL, PyschInfo and Web of Science from January 2007 to present), grey literature search, and by issuing a call for evidence. Narrative synthesis and random-effects meta-analysis of standardised mean differences in the intervention group were used to summarise intervention effects on WEMWBS score.

RESULTS

We identified 223 interventions across 209 studies, with a total of 53,834 participants across all studies. Five main themes of interventions were synthesised: psychological (n = 80); social (n = 54); arts, culture and environment (n = 29); physical health promotion (n = 18); and other (n = 28). Psychological interventions based on resilience, wellbeing or self-management techniques had the strongest effect on wellbeing. A broad range of other interventions were effective at improving mental wellbeing, including other psychological interventions such as cognitive behavioural therapy, psychoeducation and mindfulness. Medium to strong effects were also seen for person-centred support/advice (social), arts-based, parenting (social) and social prescribing interventions. However, a major limitation of the evidence was that only 75 (36%) of studies included a control group.

CONCLUSIONS

WEMWBS has been widely used to assess wellbeing across a diverse range of interventions, settings and samples. Despite substantial heterogeneity in individual intervention design, delivery and groups targeted, results indicate that a broad range of intervention types can successfully improve wellbeing. Methodological changes, such as greater use of control groups in intervention evaluation, can help future researchers and policy makers further understand what works for mental wellbeing.

“Train your mind for a healthy life”. The medicalization of mediatized mindfulness in the West

The study analyses how the functions and purposes of mindfulness meditation practices are constructed in the narratives of the Headspace mobile application. The quantitative component deployed a semi-automatic, computer assisted text analysis of 964 posts on the Headspace blog, and involved topic modelling and keyword co-occurrence analysis. This step identified dominant topics within the sample, and key term associations, which informed the in-depth qualitative text analysis of the recordings of four Headspace meditation packs, and 45 blog posts written between 2014 and 2018. The analysis focused on identifying the narratives, defined as structured storylines with plots, actors, and attached meanings. The analysis has shown that in the Headspace narratives, the function and purpose of mindfulness is constructed with reference to science and medicine, which also positions the app and the services it offers among scientific achievements, rather than spirituality or alt-med movements. The medical authoritative framework manifests itself in links to research, and referring to problems and solutions in medical or therapeutic terms. Apart from the medicalization of the practice, its healthicization is also manifested in the repetitive encouragement to monitor one’s health and actively improve one’s wellbeing. In effect, the narratives associate taking care of one’s health with the morally desirable behavior. The study concludes that the medicalization and healthicization of mindfulness identified in the app narratives shift the meaning and function of the practice from spiritual growth and enlightenment to a “will to health” and the obligation of constant self-monitoring.