Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Borghouts, Judith; Eikey, Elizabeth V.; Mark, Gloria; Leon, Cinthia De; Schueller, Stephen M.; Schneider, Margaret; Stadnick, Nicole A.; Zheng, Kai; Mukamel, Dana B.; Sorkin, Dara H.

doi:10.2196/24387

Cited by 552 publications

(463 citation statements)

References 244 publications

(308 reference statements)

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“…DHIs, including My Journey 3, need to be suitable and acceptable for those with higher symptom severity in order to avoid digitally excluding those who may benefit most [33]. Older age was also suggested as a factor that could also impact service user engagement and clinician adoption of the app, in line with evidence that younger adults have longer continued engagement with DHIs [28].…”

Section: Discussionmentioning

confidence: 94%

“…People with psychosis have previously been reported to have reservations about whether they have the necessary skills and experience to engage effectively with DHIs [26,27]. Means to simplify content in collaboration with service users and providing more targeted support with My Journey 3 should be considered to limit nonengagement and potential digital exclusion [28]. Such strategies are likely to be of particular importance in the early stages of new technology use in order to embed long-term engagement [29].…”

Section: Discussionmentioning

confidence: 99%

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A qualitative study of stakeholder views on the use of a digital app for supported self-management in early intervention services for psychosis

et al. 2021

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Background Digital tools such as Smartphones have the potential to increase access to mental health support including self-management interventions for individuals with psychosis, and ultimately to improve outcomes. Self-management strategies, including relapse prevention and crisis planning and setting personal recovery goals, are intended to assist people with long-term conditions to take an active role in their recovery, with evidence for a range of benefits. However, their implementation is inconsistent, and access and uptake need to be improved. The current study explores the acceptability of a Smartphone app (My Journey 3) that has been developed to facilitate supported self-management in Early Intervention in Psychosis (EIP) services. Methods Semi-structured one-to-one interviews were conducted with twenty-one EIP service users who had access to My Journey 3 as part of a feasibility trial, and with thirteen EIP service clinicians who were supporting service users with the app. Interviews focused on the acceptability and usability of My Journey 3. Data was coded to themes based on the Acceptability of Healthcare Interventions framework. Results Many service user participants found My Journey 3 to be acceptable. The symptom and medication trackers in particular were described as helpful. A smaller number of service users disliked the intervention. Individual-level factors that appeared to influence acceptability and engagement included recovery stage and symptom severity. Clinicians tended to report that My Journey 3 was a potentially positive addition to service users’ care, but they often felt unable to provide support due to competing demands in their work, which in turn may have impacted acceptability and usage of the app. Conclusions Our findings suggest that the app is perceived as having potential to improve users’ capacity to self-manage and work towards recovery goals, but barriers prevented many clinicians providing consistent and effective support as intended. Further evaluation of supported self-management apps in psychosis is warranted but needs to address implementation challenges from the start.

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Section: Discussionmentioning

confidence: 94%

Section: Discussionmentioning

confidence: 99%

A qualitative study of stakeholder views on the use of a digital app for supported self-management in early intervention services for psychosis

et al. 2021

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“…For the first time, this study evaluated the multiple dimensions of motivation at two different periods: before (conventional motivation) and during (in-app motivation) the intervention [ 31 , 32 ]. Previous studies assessed motivation at several time points but only one dimension (ie, usability or satisfaction with digital intervention) [ 33 , 34 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial

Kim¹,

Yang²,

Ahn³

et al. 2021

J Med Internet Res

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Background The digital health care community has been urged to enhance engagement and clinical outcomes by analyzing multidimensional digital phenotypes. Objective This study aims to use a machine learning approach to investigate the performance of multivariate phenotypes in predicting the engagement rate and health outcomes of digital cognitive behavioral therapy. Methods We leveraged both conventional phenotypes assessed by validated psychological questionnaires and multidimensional digital phenotypes within time-series data from a mobile app of 45 participants undergoing digital cognitive behavioral therapy for 8 weeks. We conducted a machine learning analysis to discriminate the important characteristics. Results A higher engagement rate was associated with higher weight loss at 8 weeks (r=−0.59; P<.001) and 24 weeks (r=−0.52; P=.001). Applying the machine learning approach, lower self-esteem on the conventional phenotype and higher in-app motivational measures on digital phenotypes commonly accounted for both engagement and health outcomes. In addition, 16 types of digital phenotypes (ie, lower intake of high-calorie food and evening snacks and higher interaction frequency with mentors) predicted engagement rates (mean R2 0.416, SD 0.006). The prediction of short-term weight change (mean R2 0.382, SD 0.015) was associated with 13 different digital phenotypes (ie, lower intake of high-calorie food and carbohydrate and higher intake of low-calorie food). Finally, 8 measures of digital phenotypes (ie, lower intake of carbohydrate and evening snacks and higher motivation) were associated with a long-term weight change (mean R2 0.590, SD 0.011). Conclusions Our findings successfully demonstrated how multiple psychological constructs, such as emotional, cognitive, behavioral, and motivational phenotypes, elucidate the mechanisms and clinical efficacy of a digital intervention using the machine learning method. Accordingly, our study designed an interpretable digital phenotype model, including multiple aspects of motivation before and during the intervention, predicting both engagement and clinical efficacy. This line of research may shed light on the development of advanced prevention and personalized digital therapeutics. Trial Registration ClinicalTrials.gov NCT03465306; https://clinicaltrials.gov/ct2/show/NCT03465306

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“…In addition to avatar improvements (eg, making the avatar’s body movements more natural) and customization options (eg, offering choice of avatars with varying gender expression, race, ethnicity, etc), in future iterations of the program, we also plan to implement a social feature that was suggested by users in the initial user-centered design work but was out of scope for the present work. Social connectedness has been demonstrated to increase engagement in other digital programs [ 25 ] and was associated with better engagement and abstinence outcomes in an online tobacco treatment program [ 26 , 27 ]. In addition, to prompt continued program use, we plan to include multiple session availability reminders rather than relying on a single reminder when a new session becomes available.…”

Section: Discussionmentioning

confidence: 99%

An Avatar-Led Digital Smoking Cessation Program for Sexual and Gender Minority Young Adults: Intervention Development and Results of a Single-Arm Pilot Trial

Heffner¹,

Watson²,

Serfozo³

et al. 2021

JMIR Form Res

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Background Sexual and gender minority young adults have a high prevalence of smoking and unique barriers to accessing tobacco treatment. Objective To address these challenges as well as their preferences for sexual and gender minority–targeted interventions and digital programs, we developed and evaluated the acceptability, preliminary efficacy, and impact on theory-based change processes of an acceptance and commitment therapy–based digital program called Empowered, Queer, Quitting, and Living (EQQUAL). Methods Participants (n=22) of a single-arm trial conducted to evaluate the program were young adults, age 18 to 30 years, who self-identified as sexual and gender minority individuals and smoked at least one cigarette per day. All participants received access to the EQQUAL program. Participants completed web-based surveys at baseline and at a follow-up 2 months after enrollment. We verified self-reported smoking abstinence with biochemical testing; missing data were counted as smoking or using tobacco. Results For young adults who logged in at least once (n=18), the mean number of log-ins was 5.5 (SD 3.6), mean number of sessions completed was 3.1 (SD 2.6), and 39% (7/18) completed all 6 sessions. Overall, 93% of participants (14/15) were satisfied with the EQQUAL program, 100% (15/15) found it easy to use, and 100% (15/15) said it helped them be clearer about how to quit. Abstinence from smoking or using tobacco was confirmed with biochemical testing for 23% of participants (5/22). Both quantitative and qualitative results suggested a positive overall response to the avatar guide, with areas for future improvement largely centered on the avatar’s appearance and movements. Conclusions Treatment acceptability of EQQUAL was very promising. The rate of abstinence, which was biochemically confirmed, was 3 times higher than that of the only other digital program to date that has targeted sexual and gender minority young adults and 6 to 13 times higher than those of nontargeted digital smoking interventions among sexual and gender minority young adults. Planned improvements for the next iteration of the program include making the avatar’s movements more natural; offering multiple avatar guides with different on characteristics such as race, ethnicity, and gender identity from which to choose; and providing a support forum for users to connect anonymously with peers.

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Barriers to and Facilitators of User Engagement With Digital Mental Health Interventions: Systematic Review

Cited by 552 publications

References 244 publications

A qualitative study of stakeholder views on the use of a digital app for supported self-management in early intervention services for psychosis

A qualitative study of stakeholder views on the use of a digital app for supported self-management in early intervention services for psychosis

Machine Learning Analysis to Identify Digital Behavioral Phenotypes for Engagement and Health Outcome Efficacy of an mHealth Intervention for Obesity: Randomized Controlled Trial

An Avatar-Led Digital Smoking Cessation Program for Sexual and Gender Minority Young Adults: Intervention Development and Results of a Single-Arm Pilot Trial

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