Exploring the definition, measurement, and reporting of engagement in remote measurement studies for physical and mental health symptom tracking: A systematic review

Abstract

BackgroundRemote Measurement Technologies (RMTs) could revolutionise management of chronic health conditions by providing real-time symptom tracking. However, the promise of RMTs relies on user engagement, which at present is variably reported in the field. This review aimed to synthesise the RMT literature to identify how and to what extent engagement is defined, measured, and reported, and to present recommendations for the standardisation of future work.MethodsSeven databases (Embase, MEDLINE and PsycINFO (via Ovid), PubMed, IEEE Xplore, Web of Science, and Cochrane Central Register of Controlled Trials) were searched in July 2020 for papers using RMT apps for symptom monitoring in adults with a health condition, prompting users to track at least three times during the study period. Data were synthesised using critical interpretive synthesis.ResultsA total of 76 papers met the inclusion criteria. Sixty five percent of papers did not include a definition of engagement. Thirty five percent included both a definition and measurement of engagement. Four synthetic constructs were developed for measuring engagement: i) engagement with the research protocol, ii) objective RMT engagement, iii) subjective RMT engagement, and iv) interactions between objective and subjective RMT engagement.DiscussionThe field is currently impeded by incoherent measures and a lack of consideration for engagement definitions. A process for implementing the reporting of engagement in study design is presented, alongside a framework for definition and measurement options available. Future work should consider engagement with RMTs as distinct from the wider eHealth literature, and measure objective versus subjective RMT engagement.RegistrationThis review has been registered on PROSPERO [CRD42020192652].

Recruitment and retention of adolescents for an ecological momentary assessment measurement burst mental health study: The MHIM engagement strategy

“…These are problematic as they can constitute additional burdens and barriers to participation. [12][13][14][15][16][17][18] Participants may also have difficulty adhering to the intensive prompt schedule, for example, due to forgetting, incompatibility with their schedule or excessive burden. 19 Established engagement strategies may not adapt well to EMA.…”

“…For example, issues associated with remote measurement studies include the use of smartphones for intensive data collection, wearing or carrying additional devices, privacy concerns around location monitoring, inequalities in access to technologies when participants are expected to use their own devices and technological issues such as noncompatibility of data collection applications with participants' devices, battery drainage or other bugs. These are problematic as they can constitute additional burdens and barriers to participation 12–18 . Participants may also have difficulty adhering to the intensive prompt schedule, for example, due to forgetting, incompatibility with their schedule or excessive burden 19 …”

Engaging adolescents in contemporary longitudinal health research: strategies for promoting participation and retention

“…Some digital data collection methods such as EMA or wearable devices can be experienced as more effortful or intrusive than traditional methods. Further, unequal access to or comfort with the relevant technologies contributes to nonrandom participation [58,80] and technological issues such as difficulties with data collection applications can add barriers [80]. Therefore, technology (and internet) access and familiarity of the target participants should be taken into consideration when planning data collection [30].…”

Lessons learned from recruiting into a longitudinal remote measurement study in major depressive disorder

“…Engagement is a multi-stage construct indicating the extent to which a resource is actively used 10 . Examining engagement with the research protocol in RMT studies, for example via recruitment rates, provides a necessary first step 11 . Whilst findings suggest that people with MDD endorse the view that RMTs could be used to detect and predict relapses 12,13 , work has highlighted potential barriers to recruitment into such research.…”