A systematic review of the impact of adherence on the effectiveness of e-therapies

Dose-Response Effects of Patient Engagement on Health Outcomes in an mHealth Intervention: Secondary Analysis of a Randomized Controlled Trial

Background

The dose–response relationship between patient engagement and long-term intervention effects in mobile health (mHealth) interventions are understudied. Studies exploring long-term and potentially changing relationships between patient engagement and health outcomes in mHealth interventions are needed.

Objective

This study aims to examine dose–response relationships between patient engagement and 3 psychosocial outcomes in an mHealth intervention, Run4Love, using repeated measurements of outcomes at baseline and 3, 6, and 9 months.

Methods

This study is a secondary analysis using longitudinal data from the Run4Love trial, a randomized controlled trial with 300 people living with HIV and elevated depressive symptoms to examine the effects of a 3-month mHealth intervention on reducing depressive symptoms and improving quality of life (QOL). We examined the relationships between patient engagement and depressive symptoms, QOL, and perceived stress in the intervention group (N=150) using 4–time-point outcome measurements. Patient engagement was assessed using the completion rate of course assignments and frequency of items completed. Cluster analysis was used to categorize patients into high- and low-engagement groups. Generalized linear mixed effects models were conducted to investigate the dose–response relationships between patient engagement and outcomes.

Results

The cluster analysis identified 2 clusters that were distinctively different from each other. The first cluster comprised 72 participants with good compliance to the intervention, completing an average of 74% (53/72) of intervention items (IQR 0.22). The second cluster comprised 78 participants with low compliance to the intervention, completing an average of 15% (11/72) of intervention items (IQR 0.23). Results of the generalized linear mixed effects models showed that, compared with the low-engagement group, the high-engagement group had a significant reduction in more depressive symptoms (β=−1.93; P=.008) and perceived stress (β=−1.72; P<.001) and an improved QOL (β=2.41; P=.01) over 9 months. From baseline to 3, 6, and 9 months, the differences in depressive symptoms between the 2 engagement groups were 0.8, 1.6, 2.3, and 3.7 points, respectively, indicating widening between-group differences over time. Similarly, between-group differences in QOL and perceived stress increased over time (group differences in QOL: 0.9, 1.9, 4.7, and 5.1 points, respectively; group differences in the Perceived Stress Scale: 0.9, 1.4, 2.3, and 3.0 points, respectively).

Conclusions

This study revealed a positive long-term dose–response relationship between patient engagement and 3 psychosocial outcomes among people living with HIV and elevated depressive symptoms in an mHealth intervention over 9 months using 4 time-point repeat measurement data. The high- and low-engagement groups showed significant and widening differences in depressive symptoms, QOL, and perceived stress at the 3-, 6-, and 9-month follow-ups. Future mHealth interventions should improve patient engagement to achieve long-term and sustained intervention effects.

Trial Registration

Chinese Clinical Trial Registry ChiCTR-IPR-17012606; https://www.chictr.org.cn/showproj.aspx?proj=21019

There's an app for that, but nobody's using it: Insights on improving patient access and adherence to digital therapeutics in Germany

Background

Mobile health applications and their subset digital therapeutics—defined as evidence-based software interventions to prevent, manage, or treat a medical condition—offer great potential to improve patient care. However, such solutions often struggle to reach widespread adoption.

Objective

This study seeks to explore healthcare stakeholders’ roles and potential for fostering patient access and adherence to evidence-based digital therapeutics and thereby improve health outcomes from the perspective of digital therapeutics developers and distributors.

Methods

Semi-structured qualitative and semiquantitative interviews were conducted with 19 experts from developers and distributors of digital therapeutics in Germany to discuss their perceived relevance of different healthcare stakeholders and strategies in promoting patient access and adherence to digital therapeutics.

Results

Healthcare professionals were found to have the greatest potential to promote both access and patient adherence to digital therapeutics, followed by health insurers, pharmaceutical companies, and patients themselves. In terms of patient access, healthcare professionals have potential due to their ability to prescribe digital therapeutics. Other stakeholders’ potential stems from their capacity to influence healthcare professionals prescription decision. In terms of patient adherence, only healthcare professionals are of high relevance by onboarding patients and monitoring digital therapeutics use. Most healthcare stakeholders currently do not fully leverage their potential. Further educating healthcare professionals and simplifying processes for them, empowering patients to seek treatment with digital therapeutics, and designing digital therapeutics’ product features for better adherence can help improve patient access and adherence.

Conclusions

Established healthcare stakeholders and digital therapeutics developers both need to take action to improve patient access and adherence to digital therapeutics. Several macro-level changes can support these efforts, including broader information dissemination, improved financial incentives, simplified prescription and activation processes, and a wider adoption of blended care and pay-for-performance payment models.

Prospective trial registration and publication rates of randomized clinical trials in digital health: A cross-sectional analysis of global trial registries

Objectives

We sought to examine the prevalence of prospective registration and publication rates in digital health trials.

Materials and Methods

We included 417 trials that enrolled participants in 2012 and were registered in any of the 17 WHO data provider registries. The evaluation of the prospective trial registration was based on the actual difference between the registration and enrollment dates. We identified existing publications through an automated PubMed search by every trial registration number as well as a pragmatic search in PubMed and Google based on extracted metadata from the trial registries.

Results

The prospective registration and publication rates were at (38.4%) and (65.5%), respectively. We identified a statistically significant ( p < 0.001) “Selective Registration Bias” with 95.7% of trials published within a year after registration, were registered retrospectively. We reported a statistically significant relationship ( p = 0.003) between prospective registration and funding sources, with industry-funded trials having the lowest compliance with prospective registration at (14.3%). The lowest non-publication rates were in the Middle East (26.7%) and Europe (28%), and the highest were in Asia (56.5%) and the U.S. (42.5%). We found statistically significant differences ( p < 0.001) between trial location and funding sources with the highest percentage of industry-funded trials in Asia (17.4%) and the U.S. (3.3%).

Conclusion

The adherence of investigators to the best practices of trial registration and result dissemination is still evolving in digital health trials. Further research is required to identify contributing factors and mitigation strategies to low compliance rate with trial publication and prospective registration in digital health trials.

A Nurse-Led mHealth Self-Management Program (mChemotherapy) for Breast Cancer Patients Undergoing Chemotherapy: Study Protocol of a Randomized Controlled Pilot Study

Background

The global pandemic has caused breast cancer (BC) patients who are receiving chemotherapy to face more challenges in taking care of themselves than usual. A novel nurse-led mHealth program (mChemotherapy) is designed to foster self-management for this population. The aim of the pilot study is to determine the feasibility, usability, and acceptability of an mChemotherapy program for breast cancer patients undergoing chemotherapy. The objective also is to evaluate the preliminary effects of this program on adherence to app usage, self-efficacy, quality of life, symptom burden, and healthcare utilization among this group of patients.

Methods

This is a single-blinded randomized controlled pilot study that includes one intervention group (mChemotherapy group) and one control group (routine care group). Ninety-four breast cancer patients who commence chemotherapy in a university-affiliated hospital will be recruited. Based on the Individual and Family Self-management Theory, this 6-week mChemotherapy program, which includes a combination of self-regulation activities and nurse-led support, will be provided. Data collection will be conducted at baseline, week 3 (T1), and week 6 (T2). A general linear model will be utilized for identifying the between-group, within-group, and interaction effects. Qualitative content analysis will be adopted to analyze, extract, and categorize the interview transcripts.

Discussions

Breast cancer patients receiving chemotherapy are a population that often experiences a heavy symptom burden. During the pandemic, they have had difficulties in self-managing the side effects of chemotherapy due to the lack of face-to-face professional support. An mChemotherapy program will be adopted through a self-regulation process and with the provision of nurse-led real-time professional support for these patients. If proven effective, BC patients who engage in this program will be more likely to take an active role in managing their symptoms, take responsibility for their own health, and subsequently improve their self-efficacy and adherence to the use of the app.

Technology-supported strategies for promoting user engagement with digital mental health interventions: A systematic review

Background

Although digital mental health interventions (DMHIs) offer a potential solution for increasing access to mental health treatment, their integration into real-world settings has been slow. A key reason for this is poor user engagement. A growing number of studies evaluating strategies for promoting engagement with DMHIs means that a review of the literature is now warranted. This systematic review is the first to synthesise evidence on technology-supported strategies for promoting engagement with DMHIs.

Methods

MEDLINE, EmbASE, PsycINFO and PubMed databases were searched from 1 January 1995 to 1 October 2021. Experimental or quasi-experimental studies examining the effect of technology-supported engagement strategies deployed alongside DMHIs were included, as were secondary analyses of such studies. Title and abstract screening, full-text coding and quality assessment were performed independently by two authors. Narrative synthesis was used to summarise findings from the included studies.

Results

24 studies (10,266 participants) were included. Engagement strategies ranged from reminders, coaching, personalised information and peer support. Most strategies were disseminated once a week, usually via email or telephone. There was some empirical support for the efficacy of technology-based strategies towards promoting engagement. However, findings were mixed regardless of strategy type or study aim.

Conclusions

Technology-supported strategies appear to increase engagement with DMHIs; however, their efficacy varies widely by strategy type. Future research should involve end-users in the development and evaluation of these strategies to develop a more cohesive set of strategies that are acceptable and effective for target audiences, and explore the mechanism(s) through which such strategies promote engagement.

Impact of guidance on intervention adherence in computerised interventions for mental health problems: a meta-analysis

Web-based interventions are increasingly used for the prevention, treatment and aftercare of mental disorders. A crucial factor to the efficacy of such online programmes is adherence to the intervention content and procedure. It has been frequently suggested that adherence in web-based interventions is low and little is known about which factors influence adherence. To increase intervention uptake and completion, studies increasingly include interventions with some form of guidance. Guided interventions have been shown to have higher efficacy, however, evidence for the impact on adherence is limited and mixed. This meta-analysis explored the impact of human guidance on intervention completion in web-based mental health interventions. A total of 22 studies were included with interventions primarily targeting symptoms of depression and anxiety disorders. Results showed that guidance significantly increases the average amount of intervention completion [g = 0.29, 95% confidence interval (CI) 0.18-0.40] and the proportion of intervention completers [log odds ratio (OR) = 0.50, 95% CI 0.34-0.66] with small effects. On average, full completion rates were 12% higher in guided intervention groups. This meta-analysis demonstrated that guidance in web-based mental health interventions does increase adherence, but more research is required to better understand the specific mechanisms between guidance, adherence and outcomes.

Artificially intelligent chatbots in digital mental health interventions: a review

INTRODUCTION

Increasing demand for mental health services and the expanding capabilities of artificial intelligence (AI) in recent years has driven the development of digital mental health interventions (DMHIs). To date, AI-based chatbots have been integrated into DMHIs to support diagnostics and screening, symptom management and behavior change, and content delivery.

AREAS COVERED

We summarize the current landscape of DMHIs, with a focus on AI-based chatbots. Happify Health's AI chatbot, Anna, serves as a case study for discussion of potential challenges and how these might be addressed, and demonstrates the promise of chatbots as effective, usable, and adoptable within DMHIs. Finally, we discuss ways in which future research can advance the field, addressing topics including perceptions of AI, the impact of individual differences, and implications for privacy and ethics.

EXPERT OPINION

Our discussion concludes with a speculative viewpoint on the future of AI in DMHIs, including the use of chatbots, the evolution of AI, dynamic mental health systems, hyper-personalization, and human-like intervention delivery.

Estimating the impact of engagement with digital health interventions on patient outcomes in randomized trials

OBJECTIVE

Guidance is needed on studying engagement and treatment effects in digital health interventions, including levels required for benefit. We evaluated multiple analytic approaches for understanding the association between engagement and clinical outcomes.

MATERIALS AND METHODS

We defined engagement as intervention participants' response rate to interactive text messages, and considered moderation, standard regression, mediation, and a modified instrumental variable (IV) analysis to investigate the relationship between engagement and clinical outcomes. We applied each approach to two randomized controlled trials featuring text message content in the intervention: REACH (Rapid Encouragement/Education and Communications for Health), which targeted diabetes, and VERB (Vanderbilt Emergency Room Bundle), which targeted hypertension.

RESULTS

In REACH, the treatment effect on hemoglobin A1c was estimated to be -0.73% (95% CI: [-1.29, -0.21]; P = 0.008), and in VERB, the treatment effect on systolic blood pressure was estimated to be -10.1 mmHg (95% CI: [-17.7, -2.8]; P = 0.007). Only the IV analyses suggested an effect of engagement on outcomes; the difference in treatment effects between engagers and non-engagers was -0.29% to -0.51% in the REACH study and -1.08 to -3.25 mmHg in the VERB study.

DISCUSSION

Standard regression and mediation have less power than a modified IV analysis, but the IV approach requires specification of assumptions. This is the first review of the strengths and limitations of various approaches to evaluating the impact of engagement on outcomes.

CONCLUSIONS

Understanding the role of engagement in digital health interventions can help reveal when and how these interventions achieve desired outcomes.

Factors predicting engagement of older adults with a coach-supported eHealth intervention promoting lifestyle change, and associations between engagement and changes in cardiovascular and dementia risk: secondary analysis of an 18-month multinational randomized controlled trial

Background

Digital health interventions could help to prevent age-related diseases, but little is known about how older adults engage with such interventions, especially in the long term, or whether engagement is associated with changes in clinical, behavioral, or biological outcomes in this population. Disparities in engagement levels with digital health interventions may exist among older people and be associated with health inequalities.

Objective

This study aimed to describe older adults’ engagement with an eHealth intervention, identify factors associated with engagement, and examine associations between engagement and changes in cardiovascular and dementia risk factors (blood pressure, cholesterol, BMI, physical activity, diet, and cardiovascular and dementia risk scores).

Methods

This was a secondary analysis of the 18-month randomized controlled Healthy Ageing Through Internet Counselling in the Elderly trial of a tailored internet-based intervention encouraging behavior changes, with remote support from a lifestyle coach, to reduce cardiovascular and cognitive decline risk in 2724 individuals aged ≥65 years, recruited offline in the Netherlands, Finland, and France. Engagement was assessed via log-in frequency, number of lifestyle goals set, measurements entered and messages sent to coaches, and percentage of education materials read. Clinical and biological data were collected during in-person visits at baseline and 18 months. Lifestyle data were self-reported on a web-based platform.

Results

Of the 1389 intervention group participants, 1194 (85.96%) sent at least one message. They logged in a median of 29 times, and set a median of 1 goal. Higher engagement was associated with significantly greater improvement in biological and behavioral risk factors, with evidence of a dose-response effect. Compared with the control group, the adjusted mean difference (95% CI) in 18-month change in the primary outcome, a composite z-score comprising blood pressure, BMI, and cholesterol, was −0.08 (−0.12 to −0.03), −0.04 (−0.08 to 0.00), and 0.00 (−0.08 to 0.08) in the high, moderate, and low engagement groups, respectively. Low engagers showed no improvement in any outcome measures compared with the control group. Participants not using a computer regularly before the study engaged much less with the intervention than those using a computer up to 7 (adjusted odds ratio 5.39, 95% CI 2.66-10.95) or ≥7 hours per week (adjusted odds ratio 6.58, 95% CI 3.21-13.49). Those already working on or with short-term plans for lifestyle improvement at baseline, and with better cognition, engaged more.

Conclusions

Greater engagement with an eHealth lifestyle intervention was associated with greater improvement in risk factors in older adults. However, those with limited computer experience, who tended to have a lower level of education, or who had poorer cognition engaged less. Additional support or forms of intervention delivery for such individuals could help minimize potential health inequalities associated with the use of digital health interventions in older people.

Engagement in Digital Mental Health Interventions: Can Monetary Incentives Help?

Digital mental health interventions (DMHI) are scalable and cost-effective strategies for increasing access to mental health care; however, dropout rates associated with digital interventions are high, particularly for open-access digital interventions. While some studies have focused on predictors of dropout from digital mental health programs, few studies have focused on engagement features that might improve engagement. In this perspective article, we discuss whether monetary incentives (MI) are one avenue to increasing user engagement in DMHI. We begin by reviewing the literature on the effects of MI for behavior change in health domains (e.g., dietary behaviors, substance use, and medication adherence). Then, drawing on a pilot study we conducted to test the effects of different levels of MI on usage and improvement in subjective well-being among users of a DMHI (Happify), we discuss the potential applications of MI for DMHI, the potential drawbacks of financial incentives in this context, and open questions for future research.

Establishing a Working Definition of User Experience for eHealth Interventions of Self-reported User Experience Measures With eHealth Researchers and Adolescents: Scoping Review

BACKGROUND

Across eHealth intervention studies involving children, adolescents, and their parents, researchers have measured user experience to assist with intervention development, refinement, and evaluation. To date, no widely accepted definitions or measures of user experience exist to support a standardized approach for evaluation and comparison within or across interventions.

OBJECTIVE

We conduct a scoping review with subsequent Delphi consultation to identify how user experience is defined and measured in eHealth research studies, characterize the measurement tools used, and establish working definitions for domains of user experience that could be used in future eHealth evaluations.

METHODS

We systematically searched electronic databases for published and gray literature available from January 1, 2005, to April 11, 2019. We included studies assessing an eHealth intervention that targeted any health condition and was designed for use by children, adolescents, and their parents. eHealth interventions needed to be web-, computer-, or mobile-based, mediated by the internet with some degree of interactivity. We required studies to report the measurement of user experience as first-person experiences, involving cognitive and behavioral factors reported by intervention users. We appraised the quality of user experience measures in included studies using published criteria: well-established, approaching well-established, promising, or not yet established. We conducted a descriptive analysis of how user experience was defined and measured in each study. Review findings subsequently informed the survey questions used in the Delphi consultations with eHealth researchers and adolescent users for how user experience should be defined and measured.

RESULTS

Of the 8634 articles screened for eligibility, 129 articles and 1 erratum were included in the review. A total of 30 eHealth researchers and 27 adolescents participated in the Delphi consultations. On the basis of the literature and consultations, we proposed working definitions for 6 main user experience domains: acceptability, satisfaction, credibility, usability, user-reported adherence, and perceived impact. Although most studies incorporated a study-specific measure, we identified 10 well-established measures to quantify 5 of the 6 domains of user experience (all except for self-reported adherence). Our adolescent and researcher participants ranked perceived impact as one of the most important domains of user experience and usability as one of the least important domains. Rankings between adolescents and researchers diverged for other domains.

CONCLUSIONS

Findings highlight the various ways in which user experience has been defined and measured across studies and what aspects are most valued by researchers and adolescent users. We propose incorporating the working definitions and available measures of user experience to support consistent evaluation and reporting of outcomes across studies. Future studies can refine the definitions and measurement of user experience, explore how user experience relates to other eHealth outcomes, and inform the design and use of human-centered eHealth interventions.

Assessing the Implementation and Effectiveness of the Electronic Patient-Reported Outcome Tool for Older Adults With Complex Care Needs: Mixed Methods Study

Background

Goal-oriented care is being adopted to deliver person-centered primary care to older adults with multimorbidity and complex care needs. Although this model holds promise, its implementation remains a challenge. Digital health solutions may enable processes to improve adoption; however, they require evaluation to determine feasibility and impact.

Objective

This study aims to evaluate the implementation and effectiveness of the electronic Patient-Reported Outcome (ePRO) mobile app and portal system, designed to enable goal-oriented care delivery in interprofessional primary care practices. The research questions driving this study are as follows: Does ePRO improve quality of life and self-management in older adults with complex needs? What mechanisms are likely driving observed outcomes?

Methods

A multimethod, pragmatic randomized controlled trial using a stepped-wedge design and ethnographic case studies was conducted over a 15-month period in 6 comprehensive primary care practices across Ontario with a target enrollment of 176 patients. The 6 practices were randomized into either early (3-month control period; 12-month intervention) or late (6-month control period; 9-month intervention) groups. The primary outcome measure of interest was the Assessment of Quality of Life-4D (AQoL-4D). Data were collected at baseline and at 3 monthly intervals for the duration of the trial. Ethnographic data included observations and interviews with patients and providers at the midpoint and end of the intervention. Outcome data were analyzed using linear models conducted at the individual level, accounting for cluster effects at the practice level, and ethnographic data were analyzed using qualitative description and framework analysis methods.

Results

Recruitment challenges resulted in fewer sites and participants than expected; of the 176 target, only 142 (80.6%) patients were identified as eligible to participate because of lower-than-expected provider participation and fewer-than-expected patients willing to participate or perceived as ready to engage in goal-setting. Of the 142 patients approached, 45 (32%) participated. Patients set a variety of goals related to self-management, mental health, social health, and overall well-being. Owing to underpowering, the impact of ePRO on quality of life could not be definitively assessed; however, the intervention group, ePRO plus usual care (mean 15.28, SD 18.60) demonstrated a nonsignificant decrease in quality of life (t₂₄=−1.20; P=.24) when compared with usual care only (mean 21.76, SD 2.17). The ethnographic data reveal a complex implementation process in which the meaningfulness (or coherence) of the technology to individuals’ lives and work acted as a key driver of adoption and tool appraisal.

Conclusions

This trial experienced many unexpected and significant implementation challenges related to recruitment and engagement. Future studies could be improved through better alignment of the research methods and intervention to the complex and diverse clinical settings, dynamic goal-oriented care process, and readiness of provider and patient participants.

Trial Registration

ClinicalTrials.gov NCT02917954; https://clinicaltrials.gov/ct2/show/NCT02917954

A randomized pilot study of Rhythms And You (RAY): An internet-based program for bipolar disorder administered with and without clinical helper support in primary care

BACKGROUND

Rhythms And You (RAY) is an online intervention for bipolar disorders (BD) based on Interpersonal and Social Rhythm Therapy. We examined RAY's feasibility and acceptability for individuals with BD recruited from primary care. Because online interventions may be more effective when paired with human support, we evaluated RAY with and without weekly brief (∼5 min) calls from clinical helpers (CH).

METHODS

Participants (n = 47) meeting criteria for BD I, II or other specified BD, presenting for primary care, were randomly assigned to RAY, RAY-CH, or Adjunctive Reading Material (ARM) control. RAY consisted of 12 weekly online modules. ARM consisted of 12 weekly emails. Participants were assessed at baseline, 4, 8, and 12 weeks.

RESULTS

RAY showed high completion rates and Client Satisfaction Questionnaire scores (36/47, 77% and 25.1 ± 5.5, respectively; no group differences). Effect sizes for RAY- CH ranged from small [Internal State Scale-Activation Subscale (ISS-ACT); d = 0.3] to large [SF-12 Mental Health Composite Score (SF-12 MHC); d = 1.3]. ARM also showed moderate effects (ISS-ACT d = 0.7; Quick Inventory of Depressive Symptoms, d = 0.8). SF-12 MHC scores showed a time*group interaction (F = 2.38, df = 6,32, p = 0.05) favoring RAY-CH. Number of logins trended toward significant association with improved social rhythm regularity (F = 4.09, df = 1, 17, p = 0.06).

LIMITATIONS

Sample size is small, limiting conclusions that can be drawn.

CONCLUSIONS

Remote delivery of RAY for individuals with BD is feasible and acceptable. More time spent engaged in RAY was associated with greater improvement in social rhythm regularity. Preliminary evidence suggests adding brief human support to RAY may yield better outcomes.

A look at engagement profiles and behavior change: A profile analysis examining engagement with the Aim2Be lifestyle behavior modification app for teens and their families

Mobile-Health is increasingly used to deliver lifestyle modification interventions; however, little is known about how users engage with these apps. This study aims to profile how teens engage with Aim2Be- a lifestyles behavior modification app), characterize engagement profiles, and examine which engagement profiles support changes in behaviors (diet, physical activity, screen time and sleep) and changes in the mediators targeted by the app. Data were collected from 301 teens (14.8 years, 49% boys, 68% Caucasian) living in Canada, from March to October 2018, who utilized the Aim2Be app for 4.5 months. App-analytics tracked teen engagement with the app features (selecting aims, completing tasks and quick wins, using the knowledge center and social wall, and accessing the virtual coach). Factor mixture modeling identified the following engagement profiles: Uninvolved (32%) did not use most app features; Dabblers (25%) minimally used the app features; Engaged (24%) had moderate-to-high use of app features; and Keeners (19%) had the highest use of all app features. Regression models showed that teens were more engaged with Aim2Be if their parents were involved and if they participated with their mothers and/or an educated parent. Finally, Keeners significantly improved on most mediators of behavior change and increased their fruit and vegetable intake. The findings suggest that parental engagement supported teen engagement of the Aim2Be app and high engagement was needed to support behavior change among teens. Gaining a greater understanding of the features that appeal to teens is necessary to support behavior change.

Effect of Engagement With Digital Interventions on Mental Health Outcomes: A Systematic Review and Meta-Analysis

Digital mental health interventions (DMHIs) present a promising way to address gaps in mental health service provision. However, the relationship between user engagement and outcomes in the context of these interventions has not been established. This study addressed the current state of evidence on the relationship between engagement with DMHIs and mental health outcomes. MEDLINE, PsycINFO, and EmBASE databases were searched from inception to August 1, 2021. Original or secondary analyses of randomized controlled trials (RCTs) were included if they examined the relationship between DMHI engagement and post-intervention outcome(s). Thirty-five studies were eligible for inclusion in the narrative review and 25 studies had sufficient data for meta-analysis. Random-effects meta-analyses indicated that greater engagement was significantly associated with post-intervention mental health improvements, regardless of whether this relationship was explored using correlational [r = 0.24, 95% CI (0.17, 0.32), Z = 6.29, p < 0.001] or between-groups designs [Hedges' g = 0.40, 95% CI (0.097, 0.705), p = 0.010]. This association was also consistent regardless of intervention type (unguided/guided), diagnostic status, or mental health condition targeted. This is the first review providing empirical evidence that engagement with DMHIs is associated with therapeutic gains. Implications and future directions are discussed.

Systematic Review Registration: PROSPERO, identifier: CRD 42020184706.

The effects of self-management interventions on depressive symptoms in adults with chronic physical disease(s) experiencing depressive symptomatology: a systematic review and meta-analysis

BACKGROUND

Chronic diseases are the leading cause of death worldwide. It is estimated that 20% of adults with chronic physical diseases experience concomitant depression, increasing their risk of morbidity and mortality. Low intensity psychosocial interventions, such as self-management, are part of recommended treatment; however, no systematic review has evaluated the effects of depression self-management interventions for this population. The primary objective was to examine the effect of self-management interventions on reducing depressive symptomatology in adults with chronic disease(s) and co-occurring depressive symptoms. Secondary objectives were to evaluate the effect of these interventions on improving other psychosocial and physiological outcomes (e.g., anxiety, glycemic control) and to assess potential differential effect based on key participant and intervention characteristics (e.g., chronic disease, provider).

METHODS

Studies comparing depression self-management interventions to a control group were identified through a) systematic searches of databases to June 2018 [MEDLINE (1946 -), EMBASE (1996 -), PsycINFO (1967 -), CINAHL (1984 -)] and b) secondary 'snowball' search strategies. The methodological quality of included studies was critically reviewed. Screening of all titles, abstracts, and full texts for eligibility was assessed independently by two authors. Data were extracted by one author and verified by a second.

RESULTS

Fifteen studies were retained: 12 for meta-analysis and three for descriptive review. In total, these trials included 2064 participants and most commonly evaluated interventions for people with cancer (n = 7) or diabetes (n = 4). From baseline to < 6-months (T1), the pooled mean effect size was - 0.47 [95% CI -0.73, - 0.21] as compared to control groups for the primary outcome of depression and - 0.53 [95% CI -0.91, - 0.15] at ≥ 6-months (T2). Results were also significant for anxiety (T1) and glycemic control (T2). Self-management skills of decision-making and taking action were significant moderators of depression at T1.

CONCLUSION

Self-management interventions show promise in improving depression and anxiety in those with concomitant chronic physical disease. The findings may contribute to the development of future Self-management interventions and delivering evidence-based care to this population. Further high-quality RCTs are needed to identify sources of heterogeneity and investigate key intervention components.

Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review

Background

Low back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change.

Objective

This systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates.

Methods

We searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates.

Results

We retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials.

Conclusions

This systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants’ ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.

Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis

BACKGROUND

SMS text messages as a form of mobile health are increasingly being used to support individuals with chronic diseases in novel ways that leverage the mobility and capabilities of mobile phones. However, there are knowledge gaps in mobile health, including how to maximize engagement.

OBJECTIVE

This study aims to categorize program SMS text messages and participant replies using machine learning (ML) and to examine whether message characteristics are associated with premature program stopping and engagement.

METHODS

We assessed communication logs from SMS text message-based chronic disease prevention studies that encouraged 1-way (SupportMe/ITM) and 2-way (TEXTMEDS [Text Messages to Improve Medication Adherence and Secondary Prevention]) communication. Outgoing messages were manually categorized into 5 message intents (informative, instructional, motivational, supportive, and notification) and replies into 7 groups (stop, thanks, questions, reporting healthy, reporting struggle, general comment, and other). Grid search with 10-fold cross-validation was implemented to identify the best-performing ML models and evaluated using nested cross-validation. Regression models with interaction terms were used to compare the association of message intent with premature program stopping and engagement (replied at least 3 times and did not prematurely stop) in SupportMe/ITM and TEXTMEDS.

RESULTS

We analyzed 1550 messages and 4071 participant replies. Approximately 5.49% (145/2642) of participants responded with stop, and 11.7% (309/2642) of participants were engaged. Our optimal ML model correctly classified program message intent with 76.6% (95% CI 63.5%-89.8%) and replies with 77.8% (95% CI 74.1%-81.4%) balanced accuracy (average area under the curve was 0.95 and 0.96, respectively). Overall, supportive (odds ratio [OR] 0.53, 95% CI 0.35-0.81) messages were associated with reduced chance of stopping, as were informative messages in SupportMe/ITM (OR 0.35, 95% CI 0.20-0.60) but not in TEXTMEDS (for interaction, P<.001). Notification messages were associated with a higher chance of stopping in SupportMe/ITM (OR 5.76, 95% CI 3.66-9.06) but not TEXTMEDS (for interaction, P=.01). Overall, informative (OR 1.76, 95% CI 1.46-2.12) and instructional (OR 1.47, 95% CI 1.21-1.80) messages were associated with higher engagement but not motivational messages (OR 1.18, 95% CI 0.82-1.70; P=.37). For supportive messages, the association with engagement was opposite with SupportMe/ITM (OR 1.77, 95% CI 1.21-2.58) compared with TEXTMEDS (OR 0.77, 95% CI 0.60-0.98; for interaction, P<.001). Notification messages were associated with reduced engagement in SupportMe/ITM (OR 0.07, 95% CI 0.05-0.10) and TEXTMEDS (OR 0.28, 95% CI 0.20-0.39); however, the strength of the association was greater in SupportMe/ITM (for interaction P<.001).

CONCLUSIONS

ML models enable monitoring and detailed characterization of program messages and participant replies. Outgoing message intent may influence premature program stopping and engagement, although the strength and direction of association appear to vary by program type. Future studies will need to examine whether modifying message characteristics can optimize engagement and whether this leads to behavior change.

Optimizing cognitive-behavioral therapy for social anxiety disorder and understanding the mechanisms of change: Study protocol for a randomized factorial trial

BACKGROUND

Social anxiety disorder (SAD) is characterized by a marked fear of negative evaluation in social situations and significant impairments. Even with the most effective treatments, remission rates are around 50%. An important reason for the limited effectiveness of treatments is the lack of evidence-based explanation of how treatments work and what their active ingredients might be. An approach to unpack the active ingredients and mechanisms of treatment is the factorial design.

OBJECTIVES

The study is a factorial trial aiming (1) to examine the main effects and interactions for the four main treatment components of internet-based cognitive-behavioral therapy (ICBT) for SAD (i.e., psychoeducation, cognitive restructuring, attentional training, and exposure) and (2) to examine whether and which change mechanisms mediate the relationship between treatment components and symptom reduction.

METHODS

A total of 464 adults diagnosed with SAD will be randomized to one of 16 conditions containing combinations of the treatment components. The primary endpoint is SAD symptomatology at eight weeks. Secondary endpoints include symptoms of depression and anxiety, quality of life, and negative effects. Hypothesized change mechanisms are the increase of knowledge about SAD, the decrease of dysfunctional cognitions, the decrease of self-focused attention, and the decrease of avoidance and safety behaviors.

DISCUSSION

A better understanding of the differential efficacy of treatment components and mechanisms of treatment underlying ICBT for SAD might inform clinicians and researchers to plan more potent and scalable treatments.

TRIAL REGISTRATION

clinicaltrials.gov (NCT04879641) on June, 11th 2021. https://clinicaltrials.gov/ct2/show/NCT04879641.

Mobile Apps That Promote Emotion Regulation, Positive Mental Health, and Well-being in the General Population: Systematic Review and Meta-analysis

BACKGROUND

Among the general public, there appears to be a growing need and interest in receiving digital mental health and well-being support. In response to this, mental health apps (MHapps) are becoming available for monitoring, managing, and promoting positive mental health and well-being. Thus far, evidence supports favorable outcomes when users engage with MHapps, yet there is a relative paucity of reviews on apps that support positive mental health and well-being.

OBJECTIVE

We aimed to systematically review the available research on MHapps that promote emotion regulation, positive mental health, and well-being in the general population aged 18-45 years. More specifically, the review aimed at providing a systematic description of the theoretical background and features of MHapps while evaluating any potential effectiveness.

METHODS

A comprehensive literature search of key databases, including MEDLINE (via Ovid), EMBASE (via Ovid), PsycINFO (via Ovid), Web of Science, and the Cochrane Register of Controlled Trials (CENTRAL), was performed until January 2021. Studies were included if they described standalone mental health and well-being apps for adults without a formal mental health diagnosis. The quality of all studies was assessed against the Mixed Methods Appraisal Tool. In addition, the Cochrane Risk-of-Bias tool (RoB-2) was used to assess randomized control trials (RCTs). Data were extracted using a modified extraction form from the Cochrane Handbook of Systematic Reviews. A narrative synthesis and meta-analysis were then undertaken to address the review aims.

RESULTS

In total, 3156 abstracts were identified. Of these, 52 publications describing 48 MHapps met the inclusion criteria. Together, the studies evaluated interventions across 15 countries. Thirty-nine RCTs were identified suggesting some support for the role of individual MHapps in improving and promoting mental health and well-being. Regarding the pooled effect, MHapps, when compared to controls, showed a small effect for reducing mental health symptoms (k=19, Hedges g=-0.24, 95% CI -0.34 to -0.14; P<.001) and improving well-being (k=13, g=0.17, 95% CI 0.05-0.29, P=.004), and a medium effect for emotion regulation (k=6, g=0.49, 95% CI 0.23-0.74, P<.001). There is also a wide knowledge base of creative and innovative ways to engage users in techniques such as mood monitoring and guided exercises. Studies were generally assessed to contribute unclear or a high risk of bias, or to be of medium to low methodological quality.

CONCLUSIONS

The emerging evidence for MHapps that promote positive mental health and well-being suggests promising outcomes. Despite a wide range of MHapps, few apps specifically promote emotion regulation. However, our findings may position emotion regulation as an important mechanism for inclusion in future MHapps. A fair proportion of the included studies were pilot or feasibility trials (k=17, 33%), and full-scale RCTs reported high attrition rates and nondiverse samples. Given the number and pace at which MHapps are being released, further robust research is warranted to inform the development and testing of evidence-based programs.

How are guide profession and routine care setting related to adherence and symptom change in iCBT for depression? - an explorative log-data analysis

BACKGROUND

While the antidepressant efficacy of guided digital interventions has been proven in randomized controlled trials, findings from routine care are less clear. Low adherence rates are common and limit the potential effectiveness. Adherence has been linked to sociodemographic variables and the amount of guidance, but the role of the guide's profession and their work setting has not yet been studied for routine care.

METHODS

Routinely collected log data from a digital intervention for depressed patients (iFightDepression tool) were analyzed in an exploratory manner. The sample is a convenience sample from routine care, where guidance is provided by general practitioners (GP), certified psychotherapists (PT) or medical doctors specialized in mental health. Log data from 2184 patients were analyzed and five usage parameters were extracted to measure adherence (first-to-last login, time on tool, number of sessions, workshops completed and minimal dose). Multiple logistic regression was used to analyze relations between the guide's profession and clinical context as well as other covariates and adherence and symptom change on a brief depression questionnaire (PHQ-9).

RESULTS

The analyses showed a significant relation of guide profession and adherence. Guidance by PT was associated to the highest adherence scores (reference category). The odds ratios (ORs) of scoring above the median in each usage parameter for patients guided by GPs were 0.50-0.63 (all ps < 0.002) and 0.61-0.80 (p = .002-0.197) for MH. Higher age, initial PHQ-9 score and self-reported diagnosis of depression were also significantly associated with higher adherence scores. In a subsample providing enough data on the PHQ-9 (n = 347), no association of guide profession with symptom reduction was found. Instead, a greater reduction was observed for patients with a higher baseline PHQ-9 (β = -0. 39, t(341.75) = -8.814, p < .001) and for those who had achieved minimal dose (β = -2.42, t(340.34) = -4.174, P < .001) and those who had achieved minimal dose and scored high on time on tool (β = 0.22, t(341.75) = 1.965, P = .050).

CONCLUSION

Being guided by PT was associated with the highest adherence. The lowest adherence was observed in patients who were guided by GP. While no association of guide profession and symptom reduction was found in a subsample, greater adherence was associated with symptom reduction.

A pilot feasibility study of an unguided, internet-delivered cognitive behavioral therapy program for irritable bowel syndrome

BACKGROUND

Irritable bowel syndrome (IBS) is linked with lower health-related quality of life. Cognitive behavioral therapy (CBT) designed for IBS management can improve outcomes but further research of more accessible implementations of this treatment approach for IBS is needed. This study assessed the feasibility of a web-delivered CBT program among adults with IBS to apply to a future clinical trial.

METHODS

Twenty-five participants were randomized to receive an unguided web-based, CBT program for IBS. The primary outcome was changes in IBS symptom severity (IBS Symptom Severity Scale [IBS-SSS]). Secondary outcomes included IBS-specific CBT therapeutic mechanisms of change (GI-specific anxiety, unhelpful IBS behaviors, and GI-focused cognitions) and changes in depressive (Patient Health Questionnaire-9 [PHQ-9]) and anxiety (Generalized Anxiety Disorder-7 scale [GAD-7]) symptom severity.

KEY RESULTS

Among participants randomized to receive web-based CBT, the average baseline IBS-SSS score was 296.3 (SD=100.9). IBS symptom severity significantly improved at 2-month (p < 0.001) and 3-month follow-up (p < 0.0001); the within-group effect size between baseline and 3-month follow-up IBS-SSS scores was large (d = 1.14) and 63.6% experienced a clinically meaningful improvement (ie, ≥50-point IBS-SSS score reduction). GI-specific anxiety symptoms and cognitions significantly improved at 2-month follow-up, as did unhelpful IBS safety behaviors. Additionally, clinically meaningful improvement was observed in depressive and anxiety symptoms at 3-month follow-up among participants with symptoms above the clinical threshold (ie, PHQ-9 ≥ 10 and GAD-7 ≥ 10, respectively) at baseline.

CONCLUSIONS & INFERENCES

These preliminary findings warrant a larger trial to investigate an unguided, web-based CBT for IBS symptom management that is powered to detect between-group treatment effects.

Efficacy of internet-delivered acceptance and commitment therapy for severe health anxiety: results from a randomized, controlled trial

BACKGROUND

Health anxiety is common, disabling and costly due to patients' extensive use of health care services. Internet-delivered treatment may overcome barriers of accessibility to specialized treatment. We aimed to evaluate the efficacy of internet-delivered acceptance and commitment therapy (iACT).

METHODS

A randomized, controlled trial of iACT versus an internet-delivered discussion forum (iFORUM), performed in a Danish university hospital setting. Patients self-referred and underwent video-diagnostic assessment. Eligible patients (≥18 years) with health anxiety were randomized to 12 weeks of intervention. The randomization was blinded for the assessor. The primary outcome was between-group unadjusted mean differences in health anxiety symptoms measured by the Whiteley-7 Index (WI-7, range 0-100) from baseline to 6-month follow-up (6-MFU) using intention to treat and a linear mixed model. The study is registered at clinicaltrials.gov, number NCT02735434.

RESULTS

A total of 151 patients self-referred, and 101 patients were randomized to iACT (n = 53) or iFORUM (n = 48). A mean difference in change over time of 19.0 points [95% confidence interval (CI) 10.8-27.2, p < 0.001] was shown on the WI-7, and a large standardized effect size of d = 0.80 (95% CI 0.38-1.23) at 6-MFU. The number needed to treat was 2.8 (95% CI 1.8-6.1, p < 0.001), and twice as many patients in iACT were no longer clinical cases (35% v. 16%; risk ratio 2.17, 95% CI 1.00-4.70, p = 0.050). Adverse events were few and insignificant.

CONCLUSIONS

iACT for health anxiety led to sustained effects at 6-MFU. The study contributes to the development of easily accessible treatment options and deserves wider application.

Non-use of telemedicine: A scoping review

Many telemedicine interventions fail to be implemented in medical care with non-use and discontinued use by patients being among the major reasons. The aim of this scoping review was to provide an overview of barriers associated with non-use and discontinued use of telemedicine. An electronic search was conducted in Pubmed in October 2019 and updated in November 2020, followed by a hand search in the beginning of 2021. All potential articles were screened by two independent reviewers based on predefined inclusion and exclusion criteria. A qualitative content analysis according to Mayring was carried out. The topics 'intervention', 'context of use' and 'user' were chosen as overarching themes. Out of 1377 potentially relevant articles, 73 were included. User-related barriers were mentioned in most of the analysed studies, followed by barriers related to the intervention. The analysis provides the basis for overcoming non-use issues in telemedicine.

Predictors of Booster Engagement Following a Web-Based Brief Intervention for Alcohol Misuse Among National Guard Members: Secondary Analysis of a Randomized Controlled Trial

BACKGROUND

Alcohol misuse is a major health concern among military members. Reserve component members face unique barriers as they live off base with limited access to behavioral health services. Web and app-based brief interventions are a promising means to improve access to treatment for those who misuse alcohol, with the use of booster sessions to enhance effectiveness, solidify gains, and reinforce changes. However, little is known about who will engage in booster sessions.

OBJECTIVE

This study aims to evaluate booster engagement across booster delivery modalities (Web and Peer) and identify participant-specific factors associated with booster session engagement.

METHODS

Following a brief web-based alcohol misuse intervention in National Guard members (N=739), we examined engagement in a series of three booster sessions. Using unadjusted and adjusted models, demographic and clinical characteristics that may serve as predictors of booster session engagement were examined across the 2 arms of the trial with different types of booster sessions: peer-delivered (N=245) and web-delivered (N=246).

RESULTS

Booster session completion was greater for Peer than Web Booster sessions, with 142 (58%) service members in the Peer Booster arm completing all three boosters compared with only 108 (44%) of participants in the Web Booster arm (χ²₃=10.3; P=.006). In a model in which the 2 groups were combined, socioeconomic factors predicted booster engagement. In separate models, the demographic and clinical predictors of booster engagement varied between the 2 delivery modalities.

CONCLUSIONS

The use of peer-delivered boosters, especially among subsets of reserve members at risk of lack of engagement, may foster greater uptake and improve treatment outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02181283; https://clinicaltrials.gov/ct2/show/NCT02181283.

How the COVID-19 Pandemic Can and Must Expand Social Worker e-Interventions for Mental Health, Family Wellness, and Beyond

Both media and academic reports have highlighted COVID-19's negative impacts on mental health and safety in the United States, yet care and service gaps persist. Evidence suggests that a default to in-person service delivery did not meet clients' needs before the pandemic, and that unmet needs have ballooned since COVID-19 spread throughout the United States due to a combination of increased stress, social isolation, and fewer available services during lockdowns. This article reviews literature on online interventions' utility and effectiveness in preventing and treating problems likely exacerbated under pandemic conditions, including mental health conditions, anger, couple dynamics, parenting, and alcohol misuse. The article also describes barriers to evidence-based e-interventions' wider and more consistent use, highlights some vulnerable populations' unique service needs, outlines service gaps that online programs might effectively mitigate, and offers a path by which social workers can lead an interdisciplinary charge in researching, developing, and implementing e-interventions during the current pandemic and beyond.

Predicting Treatment Outcomes in Guided Internet-Delivered Therapy for Anxiety Disorders-The Role of Treatment Self-Efficacy

Aim: Guided Internet-delivered therapy has shown to be an effective treatment format for anxiety disorders. However, not all patients experience improvement, and although predictors of treatment outcome have been identified, few are consistent over time and across studies. The current study aimed to examine whether treatment self-efficacy (self-efficacy regarding the mastery of obstacles during treatment) in guided Internet-delivered therapy for anxiety disorders in adults could be a predictor of lower dropout rates and greater symptom reduction. Method: The analyzed data comes from an open effectiveness study including 575 patients receiving guided Internet-delivered therapy for panic disorder or social anxiety disorder. Treatment self-efficacy was measured at pre-treatment. Symptom reduction was measured at 10 measurement points, including a 6-month follow-up. A mixed linear model was applied in the analysis. Results: The results showed that high treatment self-efficacy was a predictor of both lower dropout rates and greater symptom reduction. Significant interaction effects between time and treatment self-efficacy were found for several of the nine modules that constitutes the treatment program, suggesting that treatment self-efficacy could be a moderator of symptom reduction. Three of nine modules in the panic disorder treatment and six of nine in the social anxiety disorder treatment showed significant interaction effects. Conclusion: The results suggest that measuring treatment self-efficacy may be a valuable tool to identify patients at risk of dropping out, and that treatment self-efficacy could be a predictor and moderator of symptom reduction in guided Internet-delivered therapy. The implications of the results are discussed.

The Use of Task Shifting to Improve Treatment Engagement in an Internet-Based Mindfulness Intervention Among Chinese University Students: Randomized Controlled Trial

BACKGROUND

Traditional in-person psychotherapies are incapable of addressing global mental health needs. Use of computer-based interventions is one promising solution for closing the gap between the amount of global mental health treatment needed and received.

OBJECTIVE

Although many meta-analyses have provided evidence supporting the efficacy of self-guided, computer-based interventions, most report low rates of treatment engagement (eg, high attrition and low adherence). The aim of this study is to investigate the efficacy of an adjunctive treatment component that uses task shifting, wherein mental health care is provided by nonspecialist peer counselors to enhance engagement in an internet-based, self-directed, evidence-based mindfulness intervention among Chinese university students.

METHODS

From 3 universities across China, 54 students who reported at least mild stress, anxiety, or depression were randomly assigned to a 4-week internet-based mindfulness intervention (MIND) or to the intervention plus peer counselor support (MIND+), respectively. Be Mindful delivers all the elements of mindfulness-based cognitive therapy in an internet-based, 4-week course. Participants completed daily monitoring of mindfulness practice and mood, as well as baseline and posttreatment self-reported levels of depression, anxiety, stress, and trait mindfulness. We screened 56 volunteer peer counselor candidates who had no former training in the delivery of mental health services. Of these, 10 were invited to participate in a day-long training, and 4 were selected. Peer counselors were instructed to provide 6 brief (15-20 minute) sessions each week, to help encouraging participants to complete the internet-based intervention. Peer counselors received weekly web-based group supervision.

RESULTS

For both conditions, participation in the internet-based intervention was associated with significant improvements in mindfulness and mental health outcomes. The pre-post effect sizes (Cohen d) for mindfulness, depression, anxiety, and stress were 0.55, 0.95, 0.89, and 1.13, respectively. Participants assigned to the MIND+ (vs MIND) condition demonstrated significantly less attrition and more adherence, as indicated by a greater likelihood of completing posttreatment assessments (16/27, 59% vs 7/27, 26%; χ²₁=6.1; P=.01) and a higher percentage of course completion (72.6/100, 72.6% vs 50.7/100, 50.7%; t₅₂=2.10; P=.04), respectively. No significant between-group differences in daily frequency and duration of mindfulness practice were observed. Multilevel logistic growth models showed that MIND+ participants reported significantly greater pre-post improvements in daily stress ratings (interaction estimate 0.39, SE 0.18; t₃₁₇=2.29; P=.02) and depression (interaction estimate 0.38, SE 0.16; t₃₃₀=2.37; P=.02) than those in the MIND condition.

CONCLUSIONS

This study provides new insights into effective ways of leveraging technology and task shifting to implement large-scale mental health initiatives that are financially feasible, easily transportable, and quickly scalable in low-resource settings. The findings suggest that volunteer peer counselors receiving low-cost, low-intensity training and supervision may significantly improve participants' indices of treatment engagement and mental health outcomes in an internet-based mindfulness intervention among Chinese university students.

Predictors of adherence to an internet-based cognitive behavioral therapy program for individuals with chronic pain and comorbid psychological distress

BACKGROUND

The burden caused by chronic pain is significant, affecting at least 10 percent of the world´s population. While internet-based treatments based on cognitive behavioral therapy (CBT) have been shown to be promising in this area, attrition levels vary significantly. The purpose of this study was to investigate predictor variables for participants' adherence to an internet-based CBT treatment for individuals with chronic pain as well as to investigate associations between adherence and treatment outcome.

METHODS

Data for this study was retrieved from a randomized controlled trial including 95 individuals with chronic pain who received internet-based CBT. Treatment adherence was studied through three outcome variables: treatment progress, treatment completion and exercise completion. The predictor variables were grouped into four clusters: background variables (age, gender, marital status, level of education, and typical computer usage); the second cluster included health status variables (sick leave, current psychiatric diagnosis, previous psychotherapy for pain, current pharmacological treatment, previous depression, current depression, and current depressive symptoms); the third cluster included pain-related variables (opioid medication, history of pain, and pain symptoms) and the fourth cluster included motivation variables (measured with treatment preference, treatment credibility, compliance to the treatment schedule and contact with the therapists).

RESULTS

Findings showed that treatment progress was predicted by higher treatment credibility at baseline, whereas participants who were behind schedule in the second week of the program finished fewer treatment modules. When analyzing each cluster of predictor variables separately, current depressive symptoms also predicted fewer completed treatment modules. Among the pain-related variables, higher pain acceptance was the only predictor for completing more treatment modules. Treatment completion (which in this study was defined as having completed at least 75% of treatment modules) was predicted by higher treatment credibility and fewer depressive symptoms at baseline, and was thus similar to the results regarding treatment progress. Finally, all adherence variables predicted the treatment outcome pain interference.

CONCLUSIONS

Low treatment credibility, depressive symptoms and falling behind the treatment schedule early on were the most important predictor variables for low treatment adherence, while a number of demographical and pain-related variables were not related to adherence. The results from this study may help clinicians identify patients who are less likely to complete, and thus benefit from, their pain treatment. Trial registration ClinicalTrials.gov NTC03316846.

Online Acceptance and Commitment Therapy (ACT) interventions for chronic pain: A systematic literature review

BACKGROUND

We systematically reviewed all literature concerning online Acceptance and Commitment Therapy (ACT) interventions for chronic pain to evaluate their (1) ACT content, (2) design characteristics, (3) design rationales, and (4) adherence.

MATERIAL AND METHODS

A systematic search was performed on July 9th, 2020 in; PubMed, PsycINFO, CINAHL, and Web of Science. Search terms related to: Acceptance and Commitment Therapy, chronic pain, and eHealth. Extracted data concerned ACT content, design characteristics, adherence, and design rationales.

RESULTS

20 articles, in which 14 interventions were described, met all inclusion criteria. Adherence and design rationales were described to a limited extent in the included studies. In total, the majority provided an overview of the included ACT processes. In 10 articles it was described that the intervention was delivered via a dedicated website (n = 10), which was sometimes combined with an app (n = 3). Guidance was included in most studies (n = 19). Studies including RCT's (n = 8) reported online ACT interventions to be effective.

CONCLUSION

Online ACT interventions for chronic pain have been shown to be effective and have generally been constructed in line with ACT theory. However, the majority of studies does not provide information about the choices to optimize the fit between task, technology, and user. Considerations behind the choices for intervention features as well as design rationales could help to optimize future online ACT interventions. Additionally, consistent attention should be paid to measurement and operationalization of adherence, since this is a crucial link between content, design and effectiveness.

Effectiveness of an Internet-Based Machine-Guided Stress Management Program Based on Cognitive Behavioral Therapy for Improving Depression Among Workers: Protocol for a Randomized Controlled Trial

Background

The effect of an unguided internet-based cognitive behavioral therapy (iCBT) stress management program on depression may be enhanced by applying artificial intelligence (AI) technologies to guide participants adopting the program.

Objective

The aim of this study is to describe a research protocol to investigate the effect of a newly developed iCBT stress management program adopting AI technologies on improving depression among healthy workers during the COVID-19 pandemic.

Methods

This study is a two-arm, parallel, randomized controlled trial. Participants (N=1400) will be recruited, and those who meet the inclusion criteria will be randomly allocated to the intervention or control (treatment as usual) group. A 6-week, six-module, internet-based stress management program, SMART-CBT, has been developed that includes machine-guided exercises to help participants acquire CBT skills, and it applies machine learning and deep learning technologies. The intervention group will participate in the program for 10 weeks. The primary outcome, depression, will be measured using the Beck Depression Inventory II at baseline and 3- and 6-month follow-ups. A mixed model repeated measures analysis will be used to test the intervention effect (group × time interactions) in the total sample (universal prevention) on an intention-to-treat basis.

Results

The study was at the stage of recruitment of participants at the time of submission. The data analysis related to the primary outcome will start in January 2022, and the results might be published in 2022 or 2023.

Conclusions

This is the first study to investigate the effectiveness of a fully automated machine-guided iCBT program for improving subthreshold depression among workers using a randomized controlled trial design. The study will explore the potential of a machine-guided stress management program that can be disseminated online to a large number of workers with minimal cost in the post–COVID-19 era.

Trial Registration

UMIN Clinical Trials Registry（UMIN-CTR) UMIN000043897; https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000050125

International Registered Report Identifier (IRRID)

PRR1-10.2196/30305

Evaluating the use of a recommender system for selecting optimal messages for smoking cessation: patterns and effects of user-system engagement

Background

Motivational messaging is a frequently used digital intervention to promote positive health behavior changes, including smoking cessation. Typically, motivational messaging systems have not actively sought feedback on each message, preventing a closer examination of the user-system engagement. This study assessed the granular user-system engagement around a recommender system (a new system that actively sought user feedback on each message to improve message selection) for promoting smoking cessation and the impact of engagement on cessation outcome.

Methods

We prospectively followed a cohort of current smokers enrolled to use the recommender system for 6 months. The system sent participants motivational messages to support smoking cessation every 3 days and used machine learning to incorporate user feedback (i.e., user’s rating on the perceived influence of each message, collected on a 5-point Likert scale with 1 indicating strong disagreement and 5 indicating strong agreement on perceiving the influence on quitting smoking) to improve the selection of the following message. We assessed user-system engagement by various metrics, including user response rate (i.e., the percent of times a user rated the messages) and the perceived influence of messages. We compared retention rates across different levels of user-system engagement and assessed the association between engagement and the 7-day point prevalence abstinence (missing outcome = smoking) by using multiple logistic regression.

Results

We analyzed data from 731 participants (13% Black; 73% women). The user response rate was 0.24 (SD = 0.34) and user-perceived influence was 3.76 (SD = 0.84). The retention rate positively increased with the user response rate (trend test P < 0.001). Compared with non-response, six-month cessation increased with the levels of response rates: low response rate (odds ratio [OR] = 1.86, 95% confidence interval [CI]: 1.07–3.23), moderate response rate (OR = 2.30, 95% CI: 1.36–3.88), high response rate (OR = 2.69, 95% CI: 1.58–4.58). The association between perceived message influence and the outcome showed a similar pattern.

Conclusions

High user-system engagement was positively associated with both high retention rate and smoking cessation, suggesting that investigation of methods to increase engagement may be crucial to increase the impact of the recommender system for smoking cessation.

Trial registration

Registration Identifier: NCT03224520. Registration date: July 21, 2017.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11803-8.

[Adherence to digital health interventions: definitions, methods, and open questions]

Many digital interventions rely on the participation of their users to have a positive impact. In various areas it can be observed that the use of digital interventions is often reduced or fully discontinued by the users after a short period of time. This is seen as one of the main factors that can limit the effectiveness of digital interventions. In this context, the concept of adherence to digital interventions is becoming increasingly important. Adherence to digital interventions is roughly defined as "the degree to which the user followed the program as it was designed," which can also be paraphrased as "intended use" or "use as it is designed." However, both the theoretical-conceptual and practical discussions regarding adherence to digital interventions still receive too little attention.The aim of this narrative review article is to shed more light on the concept of adherence to digital interventions and to distinguish it from related concepts. It also discusses the methods and metrics that can be used to operationalize adherence and the predictors that positively influence adherence. Finally, needs for action to better address adherence are considered critically.

A Cognitive Behavioral Therapy-, Biofeedback-, and Game-Based eHealth Intervention to Treat Anxiety in Children and Young People With Long-Term Physical Conditions (Starship Rescue): Co-design and Open Trial

Background

Approximately 10%-12% of New Zealand children and young people have long-term physical conditions (chronic illnesses) and are more likely to develop psychological problems, particularly anxiety and depression. Delayed treatment leads to worse health care and poorer long-term outcomes. Recently, eHealth interventions, especially those based on principles of cognitive behavioral therapy and biofeedback, have been shown to be moderately effective in reducing anxiety. However, these modalities have rarely been combined. Young people have expressed a preference for well-designed and technology-based support to deal with psychological issues.

Objective

This study aims to co-design and evaluate the acceptability and usability of a cognitive behavioral therapy and biofeedback-based, 5-module eHealth game called Starship Rescue and to provide preliminary evidence regarding its effectiveness in addressing anxiety and quality of life in young people with long-term physical conditions.

Methods

Starship Rescue was co-designed with 15 children and young people from a tertiary hospital in New Zealand. Following this, 24 others aged 10-17 years participated in an open trial of the game, accessing it over an 8-week period. The acceptability of the game to all participants was assessed using a brief, open-ended questionnaire. More detailed feedback was obtained from a subset of 10 participants via semistructured interviews. Usability was evaluated via device-recorded frequency and duration of access on completion of the game and the System Usability Scale. Anxiety levels were measured at baseline, completion, and 3 months after completion of the game using the Generalized Anxiety Disorder 7-item scale and Spence Child Anxiety Scale, and at the start of each module and on completion using an embedded Likert visual analog scale. Quality of life was measured at baseline, completion, and 3 months after completion using the Pediatric Quality of Life Inventory scale.

Results

Users gave Starship Rescue an overall rating of 5.9 out of 10 (range 3-10) and a mean score of 71 out of 100 (SD 11.7; minimum 47.5; maximum 90) on the System Usability Scale. The mean period for the use of the game was just over 11 weeks (78.8 days, 13.5 hours, 40 minutes). Significant reductions in anxiety were noted between the start and end of the game on the Generalized Anxiety Disorder 7-item scale (−4.6; P<.001), Spence Child Anxiety Scale (−9.6; P=.005), and the Likert visual analog scales (−2.4; P=.001). Quality of life also improved on the Pediatric Quality of Life Inventory scale (+4.3; P=.04). All changes were sustained at the 3-month follow-up.

Conclusions

This study provides preliminary evidence for Starship Rescue as an acceptable, usable, and effective eHealth intervention for treating anxiety in young people with long-term physical conditions. Further evaluation is planned via a randomized controlled trial.

Trial Registration

Australian New Zealand Clinical Trials Network Registry (ANZCTR) ACTRN12616001253493; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=371443

Données d’utilisation d’un autotraitement guidé en ligne pour promouvoir la résilience après une catastrophe naturelle

Objectifs Malgré l’existence de plusieurs traitements en ligne pour les personnes avec un trouble de stress posttraumatique (TSPT), peu d’études se sont penchées sur les données d’utilisation d’une telle intervention. Étant donné le potentiel de la modalité en ligne à pallier les obstacles limitant l’accès à l’aide psychologique, il importe de documenter les interactions des usagers avec ces outils en lien avec l’amélioration des symptômes ciblés. L’objectif de cette étude est de documenter les données d’utilisation de la plateforme de traitement en ligne RESILIENT par les personnes évacuées des feux de Fort McMurray, Alberta (Canada), et d’examiner leur association avec l’efficacité du traitement sur les symptômes de trouble de stress posttraumatique (TSPT), d’insomnie et de dépression, et l’adhésion au traitement, mesurée par le nombre de modules consultés par les participants.

Méthode Quatre-vingt-dix-sept personnes évacuées des feux de Fort McMurray présentant des symptômes de TSPT, d’insomnie et de dépression sont incluses dans la présente étude. Les participants étaient invités à utiliser la plateforme RESILIENT, un autotraitement en ligne guidé par un thérapeute qui cible les symptômes de TSPT, le sommeil et l’humeur, et comprend 12 modules offrant des stratégies de thérapies cognitives et comportementales (TCC) basées sur les données probantes. Des données d’utilisation objectives (p. ex. nombre de modules consultés) et subjectives (p. ex. niveau d’efforts investis) ont été recueillies.

Résultats Afin de prédire la réduction des symptômes de TSPT, de dépression et d’insomnie, ainsi que le nombre de modules consultés par les participants, des modèles de régressions séquentielles ont été effectués, avec un contrôle statistique pour les symptômes prétraitement, l’âge et le genre. Les modèles finaux ont révélé qu’une réduction des symptômes de TSPT, de dépression et d’insomnie était prédite significativement par le nombre de modules consultés (β = - 0,41 ; - 0,53 ; - 0,49 respectivement, tous p < 0,001) ainsi que par le niveau d’efforts moyen autorapporté au module 7 (mi-parcours) (β = - 0,43 ; p < 0,001 ; β = - 0,38 ; p = 0,005 et β = - 0,36 ; p = 0,007 respectivement). Le nombre de modules consultés, par ailleurs, était prédit significativement par le nombre de mots dans le 4e module (β = 0,34 ; p < 0,001) et dans le 7e module (β = 0,44 ; p < 0,001), ainsi que par le nombre d’entrées dans le journal du sommeil (β = 0,28 ; p < 0,001).

Conclusion Les résultats ont confirmé qu’une plus grande interaction avec la plateforme influence positivement l’efficacité du traitement et qu’une utilisation accrue en début de traitement semble être un bon prédicteur de l’achèvement de celui-ci. Cette étude confirme l’importance de soutenir l’engagement des participants envers le traitement en ligne afin d’optimiser son efficacité.

Associations between Digital Health Intervention Engagement and Dietary Intake: A Systematic Review

There has been a proliferation of digital health interventions (DHIs) targeting dietary intake. Despite their potential, the effectiveness of DHIs are thought to be dependent, in part, on user engagement. However, the relationship between engagement and the effectiveness of dietary DHIs is not well understood. The aim of this review is to describe the association between DHI engagement and dietary intake. A systematic search of four electronic databases and grey literature for records published before December 2019 was conducted. Studies were eligible if they examined a quantitative association between objective measures of engagement with a DHI (subjective experience or usage) and measures of dietary intake in adults (aged ≥18 years). From 10,653 citations, seven studies were included. Five studies included usage measures of engagement and two examined subjective experiences. Narrative synthesis, using vote counting, found mixed evidence of an association with usage measures (5 of 12 associations indicated a positive relationship, 7 were inconclusive) and no evidence regarding an association with subjective experience (both studies were inconclusive). The findings provide early evidence supporting an association between measures of usage and dietary intake; however, this was inconsistent. Further research examining the association between DHI engagement and dietary intake is warranted.

The effect of an online individualized program to prevent nurse burnout – a mixed method study

Purpose

Preventing burnout and promoting psychological well-being in nurses are of great importance. In this study the effect of an online, stand-alone individualized preventive program for nurse burnout based on cognitive behavioral therapy (CBT) is described and explained.

Design/methodology/approach

A mixed method study with an explanatory sequential design was applied. Quantitative data were collected from September 2015 to March 2016 during an intervention study with a pretest-posttest wait-list control group design within a population of hospital nurses in the Dutch speaking part of Belgium. Consecutively, 13 nurses from the intervention group who fully completed the program were interviewed.

Findings

All interviewed participants experienced some sort of effect due to working with the program. Emotional exhaustion remained stable in the intervention group and increased in the control group. However, this difference was not significant. Personal accomplishment decreased significantly within the intervention group when compared to the control group. This might be explained by the self-awareness that was created through the program, which confronted participants with their weaknesses and problems.

Originality/value

This study adds to the understanding of online individual burnout prevention. The results suggest the feasibility of an online program to prevent nurse burnout. This could be optimized by complementing it with organizational interventions, introducing refresher courses, reminders and follow-up. Furthermore, additional attention should be devoted to preparing the implementation in order to minimize attrition rates.

Targeting subjective engagement in experimental therapeutics for digital mental health interventions

Engagement is a multifaceted construct and a likely mechanism by which digital interventions achieve clinical improvements. To date, clinical research on digital mental health interventions (DMHIs) has overwhelmingly defined engagement and assessed its association with clinical outcomes through the objective/behavioral metrics of use of or interactions with a DMHI, such as number of log-ins or time spent using the technology. However, engagement also entails users' subjective experience. Research is largely lacking that tests the relationship between subjective metrics of engagement and clinical outcomes. The purpose of this study is to present a proof-of-concept exploratory evaluation of the association between subjective engagement measures of a mobile DMHI with changes in depression and anxiety. Adult primary care patients (N = 146) who screened positive for depression or anxiety were randomized to receive a DMHI, IntelliCare, immediately or following an 8-week waitlist. Subjective engagement was measured via the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire. Across both conditions, results showed that individuals who perceived a mobile intervention as more useful, easy to use and learn, and satisfying had greater improvements in depression and anxiety over eight weeks. Findings support our proposed experimental therapeutics framework that hypothesizes objective/behavioral and subjective engagement metrics as mechanisms that lead to changes in clinical outcomes, as well as support directing intervention design efforts for DMHIs to target the user experience.

Preferences for Digital Smartphone Mental Health Apps Among Adolescents: Qualitative Interview Study

Background

Mental health digital apps hold promise for providing scalable solutions to individual self-care, education, and illness prevention. However, a problem with these apps is that they lack engaging user interfaces and experiences and thus potentially result in high attrition. Although guidelines for new digital interventions for adults have begun to examine engagement, there is a paucity of evidence on how to best address digital interventions for adolescents. As adolescence is a period of transition, during which the onset of many potentially lifelong mental health conditions frequently occurs, understanding how best to engage this population is crucial.

Objective

The study aims to detect potential barriers to engagement and to gather feedback on the current elements of app design regarding user experience, user interface, and content.

Methods

This study used a qualitative design. A sample of 14 adolescents was asked to use the app for 1 week and was interviewed using a semistructured interview schedule. The interviews were transcribed and analyzed using thematic analysis.

Results

Overall, 13 participants completed the interviews. The authors developed 6 main themes and 20 subthemes based on the data that influenced engagement with and the perceived usefulness of the app. Our main themes were timing, stigma, perception, congruity, usefulness, and user experience.

Conclusions

In line with previous research, we suggest how these aspects of app development should be considered for future apps that aim to prevent and manage mental health conditions.

Developing an explanatory theoretical model for engagement with a web-based mental health platform: results of a mixed methods study

BACKGROUND

With the growing need for accessible, high-quality mental health services, especially during the COVID-19 pandemic, there has been increasing development and uptake of web-based interventions in the form of self-directed mental health platforms. The Big White Wall (BWW) is a web-based platform for people experiencing mental illness and addiction that offers a range of evidence-based self-directed treatment strategies. Drawing on existing data from a large-scale evaluation of the implementation of BWW in Ontario, Canada (which involved a pragmatic randomized controlled trail with an embedded qualitative process evaluation), we sought to investigate the influences on the extent to which people engage with BWW.

METHODS

In this paper we drew on BWW trial participants' usage data (number of logins) and the qualitative data from the process evaluation that explored participants' experiences, engagement with and reactions to BWW.

RESULTS

Our results showed that there were highly complex relationships between the influences that contributed to the level of engagement with BWW intervention. We found that a) how people expected to benefit from using a platform like BWW was an important indicator of their future usage, b) moderate perceived symptoms were linked with higher engagement; whereas fewer actual depressive symptoms predicted use and anxiety had a positive linear relationship with usage, and that c) usage depended on positive early experiences with the platform.

CONCLUSIONS

Our findings suggest that the nature of engagement with platforms such as BWW is not easily predicted. We propose a theoretical framework for explaining the level of user engagement with BWW that might also be generalizable to other similar platforms.

Examination of the relationship between lapses and weight loss in a smartphone-based just-in time adaptive intervention

We developed a smartphone-based just-in-time adaptive intervention (JITAI), called OnTrack, that provides personalized intervention to prevent dietary lapses (i.e., nonadherence from the behavioral weight loss intervention diet). OnTrack utilizes ecological momentary assessment (EMA; repeated electronic surveys) for self-reporting lapse triggers, predicts lapses using machine learning, and provides brief intervention to prevent lapse. We have established preliminary feasibility, acceptability, and efficacy of OnTrack, but no study has examined our hypothesized mechanism of action: reduced lapse frequency will be associated with greater weight loss while using OnTrack. This secondary analysis investigated the association between lapse frequency and the weekly percentage of weight loss. Post hoc analyses evaluated the moderating effect of OnTrack engagement on this association. Participants (N = 121) with overweight/obesity (MBMI = 34.51; 84.3% female; 69.4% White) used OnTrack with a digital weight loss program for 10 weeks. Engagement with OnTrack (i.e., EMA completed and interventions accessed) was recorded automatically, participants self-reported dietary lapses via EMA, and weighed weekly using Bluetooth scales. Linear mixed models with a random effect of subject and fixed effect of time revealed a nonsignificant association between weekly lapses and the percentage of weight loss. Post hoc analyses revealed a statistically significant moderation effect of OnTrack engagement such that fewer EMA and interventions completed conferred the expected associations between lapses and weight loss. Lapses were not associated with weight loss in this study and one explanation may be the influence of engagement levels on this relationship. Future research should investigate the role of engagement in evaluating JITAIs.

Acceptability of digital health interventions: embracing the complexity

Acceptability is a core concept in digital health. Available frameworks have not clearly articulated why and how researchers, practitioners and policy makers may wish to study the concept of acceptability. Here, we aim to discuss (i) the ways in which acceptability might differ from closely related concepts, including user engagement; (ii) the utility of the concept of acceptability in digital health research and practice; (iii) social and cultural norms that influence acceptability; and (iv) pragmatic means of measuring acceptability, within and beyond the research process. Our intention is not to offer solutions to these open questions but to initiate a debate within the digital health community. We conducted a narrative review of theoretical and empirical examples from the literature. First, we argue that acceptability may usefully be considered an emergent property of a complex, adaptive system of interacting components (e.g., affective attitude, beliefs), which in turn influences (and is influenced by) user engagement. Second, acceptability is important due to its ability to predict and explain key outcomes of interest, including user engagement and intervention effectiveness. Third, precisely what people find acceptable is deeply contextualized and interlinked with prevailing social and cultural norms. Understanding and designing for such norms (e.g., through drawing on principles of user centered design) is therefore key. Finally, there is a lack of standard acceptability measures and thresholds. Star ratings coupled with free-text responses may provide a pragmatic means of capturing acceptability. Acceptability is a multifaceted concept, which may usefully be studied with a complexity science lens.

Pilot testing an app-based stress management intervention for cancer survivors

Psychosocial eHealth intervention programs for cancer survivors are still in their infancy, with inconsistent findings so far in the scientific literature. The aim of this study was to explore system use, usefulness, ease of use, and preliminary effects of Stress Proffen, an app-based cognitive-behavioral stress management intervention for patients with cancer. A feasibility pilot project tested the intervention with cancer survivors (N = 25). The intervention contained (a) one face-to-face introduction session, (b) 10 app-based modules with stress management educational material and exercises, and (c) one follow-up phone call. Post-intervention interviews were conducted and user log-data were extracted. Outcome measures-Perceived Stress Scale (PSS), Anxiety and Depression (Hospital Anxiety and Depression Scale [HADS]), Health-Related Quality of Life (HRQoL; SF-36), and Self-Regulatory Fatigue (SRF-18)-were completed at baseline and post-intervention. Participants were primarily women (84%), age 34-71 (mean 48) and represented a variety of cancer diagnoses (majority breast cancer: 40%). Twenty-two participants completed all (pre-post) questionnaires. Sixteen participants (67%) completed at least 7 of 10 modules within the 8-week study period. Post-intervention interviews described StressProffen as providing a new, appreciated, and easily accessible stress management tool for the cancer survivors. Dependent/paired t-tests showed significant pre-post intervention effects with significant decrease in stress (p = .008), anxiety (p = .019), and self-regulatory fatigue (p = .025), and improved HRQoL (Role Physical, General Health, Vitality, and Role Emotional, all p's <.01). App-based stress management interventions such as StressProffen can provide appreciated support for cancer survivors, should be easy to use, can provide significant stress reduction, and improve emotional well-being. Further testing in a randomized controlled trial is warranted and is in progress. Clinicaltrials.gov: NCT0293961.

Engagement patterns with a digital therapeutic for substance use disorders: Correlations with abstinence outcomes

INTRODUCTION

Patient engagement may play a key role in the success or failure of treatments for substance use disorder (SUD). This exploratory analysis of data from a large, multisite effectiveness trial (NCT01104805) sought to determine how patient engagement with a digital therapeutic for SUD delivered at clinics was associated with abstinence outcomes.

METHODS

The study evaluated engagement for 206 participants enrolled in a treatment program for SUDs related to cocaine, alcohol, cannabis, or other stimulants who were randomized to receive treatment as usual (TAU) or reduced TAU plus the digital Therapeutic Education System (TES) for 12 weeks. Participants were eligible for contingency management incentives for module completion (modules cover Community Reinforcement Approach topic areas) and negative urine drug screens. Analyses examined the association of module completion with end-of-treatment abstinence.

RESULTS

Participants completed a mean of 38.8 (range 0-72) TES modules over 12 weeks of treatment. Study completers (n = 157) completed a mean of 45.5 (range 9-72) TES modules, whereas study noncompleters (n = 49) completed a mean of 17.4 (range 0-45) TES modules. The study observed a strong positive correlation between TES engagement (i.e., total number of modules completed) and the probability of abstinence during weeks 9-12 of treatment among 157 study completers (OR = 1.11; 95% CI 1.08-1.14). Each module completed increased the odds of abstinence during weeks 9-12 by approximately 11% for study completers and 9% for the full sample. The study observed a similar, but weaker, association between engagement and abstinence among 49 patients who did not complete the study (OR = 1.02; 95% CI 0.98-1.07).

CONCLUSIONS

Greater engagement with a digital therapeutic for patients with SUD (i.e., number of modules completed over time) was strongly associated with the probability of abstinence in the last four weeks of treatment among those who completed the recommended 12-week treatment.

TRIALS REGISTRATION

ClinicalTrials.gov Identifier: NCT01104805.

A three-armed randomised controlled trial investigating the comparative impact of guidance on the efficacy of a web-based stress management intervention and health impairing and promoting mechanisms of prevention

Background

Web-based stress management interventions (SMI) fit increasingly digital lifestyles, reduce barriers of uptake and are easily scalable. SMIs might lower levels of stress in employees and thereby contribute to the prevention of depressive symptomatology. Different guidance formats can impact the efficacy of SMIs, with higher intensity assumed to result in larger effects. However, head-to-head comparisons of guidance formats are rare. This is the first trial to examine the impact of adherence-focused guidance compared to self-help on the efficacy of an occupational SMI compared to a wait list control condition. Additionally, it will be investigated if the SMI enfolds its impact on preventing depressive symptomatology by different pathways through reducing health impairing and increasing promoting factors.

Methods

A three-armed randomised controlled trial (RCT) on an occupational SMI was conducted. 404 employees with elevated levels of perceived stress (PSS-10 ≥ 22) were randomly assigned to: adherence-focused guidance (AFG), self-help (SH) or a wait list control group (WLC). The primary outcome was perceived stress (PSS-10). Secondary outcomes included health- and work-related measures. A parallel mediation analysis with stress and resilience as mediators for the effect on depression (CES-D) was carried out. Data collection took place at baseline (T1), after 7 weeks (T2) and 6 months (T3).

Results

The SMI was effective for all groups on the primary and secondary outcomes. For stress, analyses of covariance (ANCOVA) revealed significant group effects at T2 (F_2,400 = 36.08, P < .001) and T3 (F_2,400 = 37.04, P < .001) with large effect sizes for AFG (T2: d = 0.83; T3: d = 0.85) and SH (T2: d = 0.88; T3: d = 0.91) compared to WLC. No significant group differences were found for the efficacy between AFG and SH on the outcomes. Adherence in terms of completed modules was significantly higher for AFG compared to SH. The SMI’s impact on depression was mediated by perceived stress: a₁b₁ = − 0.77, 95% CI [− 1.26, − 0.34] and resilience: a₂b₂ = − 0.62, 95% CI [− 1.05, − 0.26].

Conclusions

The SMI was effective for reducing stress and improving other health- and work-related outcomes, irrespective of the guidance format. Results did not demonstrate superiority of adherence-focused guidance for the efficacy but for adherence in terms of completed modules. Among other reasons, better communication strategies about offered guidance and awareness-raising measures are discussed. Results from mediation analysis suggest that preventive SMIs should be designed to reach two goals: reducing the risk factor of stress and simultaneously increasing health promoting factors such as resilience.

Trial registration

German Clinical Trial Registration (DRKS) DRKS00005687, 6/6/2014.

A Brief Intervention to Increase Uptake and Adherence of an Internet-Based Program for Depression and Anxiety (Enhancing Engagement With Psychosocial Interventions): Randomized Controlled Trial

BACKGROUND

Psychosocial, self-guided, internet-based programs are effective in treating depression and anxiety. However, the community uptake of these programs is poor. Recent approaches to increasing engagement (defined as both uptake and adherence) in internet-based programs include brief engagement facilitation interventions (EFIs). However, these programs require evaluation to assess their efficacy.

OBJECTIVE

The aims of this hybrid implementation effectiveness trial are to examine the effects of a brief internet-based EFI presented before an internet-based cognitive behavioral therapy self-help program (myCompass 2) in improving engagement (uptake and adherence) with that program (primary aim), assess the relative efficacy of the myCompass 2 program, and determine whether greater engagement was associated with improved efficacy (greater reduction in depression or anxiety symptoms) relative to the control (secondary aim).

METHODS

A 3-arm randomized controlled trial (N=849; recruited via social media) assessed the independent efficacy of the EFI and myCompass 2. The myCompass 2 program was delivered with or without the EFI; both conditions were compared with an attention control condition. The EFI comprised brief (5 minutes), tailored audio-visual content on a series of click-through linear webpages.

RESULTS

Uptake was high in all groups; 82.8% (703/849) of participants clicked through the intervention following the pretest survey. However, the difference in uptake between the EFI + myCompass 2 condition (234/280, 83.6%) and the myCompass 2 alone condition (222/285, 77.9%) was not significant (n=565; χ²₁=29.2; P=.09). In addition, there was no significant difference in the proportion of participants who started any number of modules (1-14 modules) versus those who started none between the EFI + myCompass 2 (214/565, 37.9%) and the myCompass 2 alone (210/565, 37.2%) conditions (n=565; χ²₁<0.1; P=.87). Finally, there was no significant difference between the EFI + myCompass 2 and the myCompass 2 alone conditions in the number of modules started (U=39366.50; z=-0.32; P=.75) or completed (U=39494.0; z=-0.29; P=.77). The myCompass 2 program was not found to be efficacious over time for symptoms of depression (F_4,349.97=1.16; P=.33) or anxiety (F_4,445.99=0.12; P=.98). However, planned contrasts suggested that myCompass 2 may have been effective for participants with elevated generalized anxiety disorder symptoms (F_4,332.80=3.50; P=.01).

CONCLUSIONS

This brief internet-based EFI did not increase the uptake of or adherence to an existing internet-based program for depression and anxiety. Individuals' motivation to initiate and complete internet-based self-guided interventions is complex and remains a significant challenge for self-guided interventions.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry ACTRN12618001565235; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=375839.

Uptake of and Engagement With an Online Sexual Health Intervention (HOPE eIntervention) Among African American Young Adults: Mixed Methods Study

Background

Regarding health technologies, African American young adults have low rates of uptake, ongoing usage, and engagement, which may widen sexual health inequalities.

Objective

We aimed to examine rates of uptake and ongoing usage, and factors influencing uptake, ongoing usage, and engagement for a consumer health informatics (CHI) intervention for HIV/sexually transmitted infection (STI) prevention among African American young adults, using the diffusion of innovation theory, trust-centered design framework, and O’Brien and Toms’ model of engagement.

Methods

This community-based participatory mixed methods study included surveys at four time points (n=315; 280 African American participants) among young adults aged 18 to 24 years involved in a blended offline/online HIV/STI prevention intervention (HIV Outreach, Prevention, and Education [HOPE] eIntervention), which was described as a “HOPE party.” Qualitative interviews were conducted with a subset of participants (n=19) after initial surveys and website server logs indicated low uptake and ongoing usage. A generalized linear mixed-effects model identified predictors of eIntervention uptake, server logs were summarized to describe use over time, and interview transcripts were coded and thematically analyzed to identify factors affecting uptake and engagement.

Results

Participants’ initial self-reported eIntervention uptake was low, but increased significantly over time, although uptake never reached expectations. The most frequent activity was visiting the website. Demographic factors and HOPE party social network characteristics were not significantly correlated with uptake, although participant education and party network gender homophily approached significance. According to interviews, one factor driving uptake was the desire to share HIV/STI prevention information with others. Survey and interview results showed that technology access, perceived time, and institutional and technological trust were necessary conditions for uptake. Interviews revealed that factors undermining uptake were insufficient promotion and awareness building, and the platform of the intervention, with social media being less appealing due to previous negative experiences concerning discussion of sexuality on social media. During the interaction with the eIntervention, interview data showed that factors driving initial engagement were audience-targeted website esthetics and appealing visuals. Ongoing usage was impeded by insufficiently frequent updates. Similarly, lack of novelty drove disengagement, although a social media contest for sharing intervention content resulted in some re-engagement.

Conclusions

To encourage uptake, CHI interventions for African American young adults can better leverage users’ desires to share information about HIV/STI prevention with others. Ensuring implementation through trusted organizations is also important, though vigorous promotion is needed. Visual appeal and targeted content foster engagement at first, but ongoing usage may require continual content changes. A thorough analysis of CHI intervention use can inform the development of future interventions to promote uptake and engagement. To guide future analyses, we present an expanded uptake and engagement model for CHI interventions targeting African American young adults based on our empirical results.

Intervention Use and Symptom Change With Unguided Internet-Based Cognitive Behavioral Therapy for Depression During the COVID-19 Pandemic: Log Data Analysis of a Convenience Sample

BACKGROUND

Internet- and mobile-based interventions are most efficacious in the treatment of depression when they involve some form of guidance, but providing guidance requires resources such as trained personnel, who might not always be available (eg, during lockdowns to contain the COVID-19 pandemic).

OBJECTIVE

The current analysis focuses on changes in symptoms of depression in a guided sample of patients with depression who registered for an internet-based intervention, the iFightDepression tool, as well as the extent of intervention use, compared to an unguided sample. The objective is to further understand the effects of guidance and adherence on the intervention's potential to induce symptom change.

METHODS

Log data from two convenience samples in German routine care were used to assess symptom change after 6-9 weeks of intervention as well as minimal dose (finishing at least two workshops). A linear regression model with changes in Patient Health Questionnaire (PHQ-9) score as a dependent variable and guidance and minimal dose as well as their interaction as independent variables was specified.

RESULTS

Data from 1423 people with symptoms of depression (n=940 unguided, 66.1%) were included in the current analysis. In the linear regression model predicting symptom change, a significant interaction of guidance and minimal dose revealed a specifically greater improvement for patients who received guidance and also worked with the intervention content (β=-1.75, t=-2.37, P=.02), while there was little difference in symptom change due to guidance in the group that did not use the intervention. In this model, the main effect of guidance was only marginally significant (β=-.53, t=-1.78, P=.08).

CONCLUSIONS

Guidance in internet-based interventions for depression is not only an important factor to facilitate adherence, but also seems to further improve results for patients adhering to the intervention compared to those who do the same but without guidance.

Usage activity, perceived usefulness, and satisfaction in a web-based acceptance and commitment therapy program among Finnish ninth-grade adolescents

Understanding adolescent usage activity and experiences in web-based psychological intervention programs helps in developing universal programs that can be adopted for promotion of adolescent well-being and prevention of mental health problems. This study examined the usage activity, perceived usefulness (i.e., learning of mindfulness, acceptance and value-related skills), and program satisfaction of 157 Finnish ninth-grade adolescents, who participated in a school-based five-week universal acceptance and commitment therapy web intervention called Youth Compass. Individual and growth environment-related antecedents were measured before the five-week intervention, adolescents' usage activity during the intervention, and perceived usefulness and satisfaction after the intervention. The results showed that female adolescents and adolescents with high self-regulation were more active program users and had more positive experiences of the program. Most of the adolescents used the program on at least a moderate level and perceived it to be moderately or highly useful and satisfactory. Four subgroups of adolescents were identified based on their usage activity, perceived usefulness, and satisfaction: adolescents in the satisfied group (41%) had average activity and high perceived usefulness and intervention satisfaction, the dissatisfied group (18%) had low activity and very low perceived usefulness and intervention satisfaction, the active group (8%) had very high activity and average perceived usefulness and intervention satisfaction, and the moderate group (33%) had average activity, perceived usefulness and intervention satisfaction. Gender, academic achievement, closeness to mother and teacher, and conflict with teacher were significantly related to subgroup membership. The results suggested that adolescent usage activity, perceived usefulness, and satisfaction with the Youth Compass program may to some extent be predicted based on different factors.

Predicting response to transdiagnostic iCBT for emotional disorders from patient and therapist involvement

BACKGROUND

Transdiagnostic iCBT has been shown to be effective for the treatment of emotional disorders. Less is known about the optimal level of therapist and patient involvement in these interventions. Specific characteristics of Internet-delivered interventions include treatment adherence (e.g., amount of review of the materials) and guidance (e.g., amount of therapist support). Exploring the importance of these elements in treatment outcome may help to maximize the efficiency of Internet-delivered psychological interventions.

AIM

In this study, we aimed to analyze the relationship between patient and therapist involvement (i.e., platform usage and amount of therapist guidance) in a sample of patients with emotional disorders who received transdiagnostic iCBT in Spanish public specialized mental healthcare services.

METHOD

This is a secondary analysis of a randomized controlled trial. The sample included 63 patients who completed transdiagnostic iCBT for emotional disorders. Platform usage metrics included number of logins into the platform and number of times the participants reviewed the modules. Therapist guidance was measured as the number of support phone calls with a therapist and their total duration (minutes). Logistic regressions and ROC analyses were performed to explore the predictive value of platform usage and therapist guidance in symptom reduction. Clinical outcomes included depressive and anxiety symptoms assessed at baseline and post-intervention. The bivariate relationship between the platform usage and therapist guidance variables was also explored.

RESULTS

Overall, platform usage and therapist guidance were not associated with symptom improvement. However, the patient and therapist involvement parameters were intercorrelated. Specifically, the number of calls and their duration were associated with a greater number of logins (r = 0.61; p < .001) and more frequent reviews of the modules (0.46 ≤ r ≤ 0.60; p < .001). Higher baseline depression and anxiety were, respectively, associated with greater improvements in depression (r = -0.37, p = .003) and anxiety after treatment completion (r = -0.48, p < .001).

DISCUSSION

The results suggest that there is no reliable cut-off point for platform usage and therapist guidance in predicting optimal symptom reduction. However, significant associations were found between platform usage and guidance variables that warrant additional research. More research on this topic is necessary to further clarify the role of these and other platform usage and guidance variables in Internet-delivered iCBT outcomes.