Engagement with mobile health interventions for depression: A systematic review

Abstract

Background Depressive disorders are a major public health problem, and many people face barriers to accessing evidence-based mental health treatment. Mobile health (mHealth) interventions may circumvent logistical barriers to in-person care (e.g., cost, transportation), however the symptoms of depression (low motivation, concentration difficulties) may make it difficult for people with the disorder to engage with mHealth. Objective The aim of this systematic review is to examine assessment and reporting of engagement in clinical trials of mHealth interventions for depression, including objective engagement (e.g., number of times program is used), subjective engagement (e.g., qualitative data on users' experiences), and associations between engagement and other clinically important variables (e.g., symptom improvement, participant characteristics). Methods Three electronic databases (PsycINFO, Web of Science, PubMed) were searched in February 2020 using search terms for mHealth and depression. Studies were included in the review if they tested a mHealth intervention designed for people with depressive disorders or elevated depression symptoms. Results Thirty studies met inclusion criteria and were reviewed. Most studies reported objective engagement ( N = 23, 76.7%), approximately half reported subjective engagement ( N = 16, 53.3%), and relatively few examined associations between engagement and clinical improvement, participant characteristics, or other clinically relevant variables ( N = 13, 43.3%). Conclusions Although most studies in this small but rapidly growing literature report at least one measure of engagement, there is substantial heterogeneity. Intentional, theory-driven, and consistent measurement of engagement with mHealth interventions for depression may advance the field's understanding of effective engagement to facilitate clinical improvement, identify dose-response relationships, and maximize generalizability for underserved populations.

A systematic review of engagement reporting in remote measurement studies for health symptom tracking

“…Papers reporting secondary analyses were included, given that they have the potential to report on engagement information that might not have been presented in the initial paper 29 . General wellbeing or fitness studies were excluded as users might have different motivations to engage than if the symptom tracking was linked with specific disease management.…”

“…Generic apps were excluded on the assumption that they might carry pre-defined engagement metrics. Engagement reporting was not included in the search strategy or eligibility criteria in order to evaluate the consistency of reporting across the literature 29 . No papers were excluded on the basis of quality, in order to describe the overall state of the research field 93 .…”

“…A data extraction form was developed and refined, informed by recent systematic reviews on engagement in eHealth 28 , 29 and a preliminary review of included papers. Due to the large volume of eligible studies, three team members performed data extraction; KMW independently checked the extraction data for accuracy.…”

“…These subjective and objective components were underpinned by corresponding measurements. This framework has since been used to synthesise the reporting of engagement in eHealth interventions for depression 29 . Thus, an exploration of varying definitions and measurements of engagement has been key to standardising the findings of the wider eHealth literature.…”

Changing Medical Paradigm on Inflammatory Eye Disease: Technology and Its Implications for P4 Medicine

“…Through proposed changes in Society 5.0 and adoption of mobile health (mHealth) principles, providers and researchers may be able to deduce certain ocular inflammatory dynamics at an individual level with correlating digital phenotypes [ 39 ] (i.e., ePROs, sensor data, on-screen time, blink pattern recognition) [ 5 ]. Various mHealth-driven approach to gain personalized data have gone underway with significant findings, particularly in chronic disease and mood disorder management [ 36 , 40 , 41 ]. This expansion of perspective helped elucidate new aspects of pathophysiology, disease course, biomarkers, and disease subgroups [ 26 , 30 , 31 ], laying ground for tailored therapeutic targets for highly diverse and heterogenous diseases, including various immune-mediated ocular disorders.…”