Measures of Engagement With mHealth Interventions in Patients With Heart Failure: Scoping Review

Abstract

Background Despite the potential of mobile health (mHealth) interventions to facilitate the early detection of signs of heart failure (HF) decompensation and provide personalized management of symptoms, the outcomes of such interventions in patients with HF have been inconsistent. As engagement with mHealth is required for interventions to be effective, poor patient engagement with mHealth interventions may be associated with mixed evidence. It is crucial to understand how engagement with mHealth interventions is measured in patients with HF, and the effects of engagement on HF outcomes. Objective In this review, we aimed to describe measures of patient engagement with mHealth interventions and the effects of engagement on HF outcomes. Methods We conducted a systematic literature search in 7 databases for relevant studies published in the English language from 2009 to September 2021 and reported the descriptive characteristics of the studies. We used content analysis to identify themes that described patient engagement with mHealth interventions in the qualitative studies included in the review. Results We synthesized 32 studies that operationalized engagement with mHealth interventions in 4771 patients with HF (3239/4771, 67.88%, male), ranging from a sample of 7 to 1571 (median 53.3) patients, followed for a median duration of 90 (IQR 45-180) days. Patient engagement with mHealth interventions was measured only quantitatively based on system usage data in 72% (23/32) of the studies, only qualitatively based on data from semistructured interviews and focus groups in 6% (2/32) of studies, and by a combination of both quantitative and qualitative data in 22% (7/32) of studies. System usage data were evaluated using 6 metrics of engagement: number of physiological parameters transmitted (19/30, 63% studies), number of HF questionnaires completed (2/30, 7% studies), number of log-ins (4/30, 13% studies), number of SMS text message responses (1/30, 3% studies), time spent (5/30, 17% studies), and the number of features accessed and screen viewed (4/30, 13% studies). There was a lack of consistency in how the system usage metrics were reported across studies. In total, 80% of the studies reported only descriptive characteristics of system usage data. The emotional, cognitive, and behavioral domains of patient engagement were identified through qualitative studies. Patient engagement levels ranged from 45% to 100% and decreased over time. The effects of engagement on HF knowledge, self-care, exercise adherence, and HF hospitalization were inconclusive. Conclusions The measures of patient engagement with mHealth interventions in patients with HF are underreported and lack consistency. The application of inferential analytical methods to engagement data is extremely limited. There is a need for a working group on mHealth that may consolidate the previous operational definitions of patient engagement into an optimal and standardized measure.

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

“…Subjective measures of engagement, by contrast, were far less common: self-report or EMA (4/20, 20%) and qualitative methods (1/20, 5%). Unfortunately, the lack of attention to the subjective experiences of participants in engagement measurement is not unique to MRTs of mHealth interventions [ 14 , 17 ]. Surprisingly, only 8 (40%) out of the 20 studies measured engagement using >1 method (no study used >2 methods).…”

“…Perski et al [ 10 ], by contrast, reviewed how engagement was conceptualized in digital behavior change interventions (their review was not limited to mHealth interventions; it included other digital interventions). Other recent reviews evaluated the measurement of engagement in mHealth interventions designed for specific health conditions [ 17 , 18 ]. However, none of these reviews examined mHealth interventions evaluated by MRTs, perhaps owing to the relative infancy of the trial design.…”

Participant Engagement in Microrandomized Trials of mHealth Interventions: Scoping Review

“…Only one study was found to measure this form of engagement we labelled as "engagement as comprehension". Unfortunately, the lack of attention to the subjective experiences of participants in engagement measurement is not unique to MRTs of mHealth interventions [12].…”

“…Second, we did not use existing frameworks such as the Frequency, Intensity, Time, and Type principle [49] to further categorize engagement within the usage and responsiveness category. This has been done in previous scoping reviews [12] and is necessary to obtain a nuanced understanding of engagement measurement in mHealth interventions. Unfortunately, we were not able to do so as some studies and protocols did not clearly operationalize their measurement of engagement in exact terms.…”

“…Other recent reviews evaluated the measurement of engagement in mHealth interventions designed for specific health conditionsincluding but not limited to heart failure [12] and depression [13]. None of these reviews, however, examined mHealth interventions…”