JMIR Publications

ABSTRACT

Background:

Ecological momentary assessments (EMAs) and digital wearables (DW) are commonly used remote monitoring technologies that capture real-time data in people’s natural environments. Real-time data are core to personalized medical care and intensively adaptive health interventions. The utility of such personalized care is contingent on user uptake and continued use of EMA and DW. Consequently, it is critical to understand user preferences that may increase the uptake of EMA and DW.

Objective:

The study aims to quantify users’ preferences of EMA and DW, examine variations in users’ preferences across demographic and behavioral subgroups, and assess the association between users’ preferences and intentions to use EMA and DW.

Methods:

Two discrete choice experiments (DCE) paired with self-report surveys will be administered online to a total of 3,260 US adults via Qualtrics. The first DCE will assess participants’ EMA preferences using a choice-based conjoint design that will ask participants to compare the relative importance of prompt frequency, number of questions per prompt, prompt type, health topic, and assessment duration. The second DCE will measure participants’ DW preferences using a maximum difference scaling design that will quantify the relative importance of device characteristics, effort expectancy, social influence, and facilitating technical, healthcare, and market factors. Hierarchical Bayesian multinomial logistic regression models will be employed to generate subject-specific preference utilities. Preference utilities will be compared across demographic (i.e., sex, age, race/ethnicity) and behavioral (i.e., substance use, physical activity, dietary behavior, sleep duration) subgroups. Regression models will determine whether specific utilities are associated with attitudes toward or intentions to use EMA and DW. Mixture models will determine the associations of attitudes toward and intentions to use EMA and DW with latent profiles of user preferences.

Results:

Institutional review board approved the study on 12/19/2022. Data collection started on 1/20/2023 and is currently underway.

Conclusions:

The study will provide evidence on users’ preferences of EMA and DW features that can improve initial uptake and potentially continued use of these remote monitoring tools. The sample size and composition allow for subgroup analysis by demographics and health behaviors and will provide evidence on associations between users’ preferences and intentions to uptake EMA and DW. Limitations include the cross-sectional nature of the study, which limits our ability to measure direct behavior. Rather, we capture behavioral intentions for EMA and DW uptake. The non-probability sample limits the generalizability of the results and introduces self-selection bias related to the demographic and behavioral characteristics of participants who belong to online survey panels. Clinical Trial: Not applicable.