JMIR Publications

ABSTRACT

Background:

The use of sensors in smartphones, smartwatches, or wearable devices has facilitated the personalization of interventions to increase users’ physical activity (PA). Recent research has focused on evaluating the effects of personalized interventions in improving PA among users. However, it is critical to deliver the intervention at an appropriate time to each user to increase the likelihood of adoption of the intervention. Earlier review studies have not focused on the personalization of intervention timing for increasing PA.

Objective:

This review aimed to (1) examine studies using information technology (IT) based PA interventions with personalized intervention timing (PIT), (2) identify inputs, techniques, content, and delivery mode used for providing PIT, and (3) identify gaps in the current literature and suggest future research directions.

Methods:

A scoping review was undertaken using PsycINFO, PubMed, Scopus, and Web of Science databases based on a structured search query. The main inclusion criteria were that the study: (1) aimed to promote PA; (2) included some form of PIT; (3) used some form of IT for delivery of the intervention to the user. If deemed relevant, papers were included in this review after removing duplicates and examining the title, abstract, and full-text of the shortlisted papers.

Results:

The literature search resulted in 18 eligible studies. In this review, 13 studies focused on increasing PA or reducing sedentary behavior (SB) as the primary objective, while it was the secondary focus in the remaining studies. The input factors used to provide PIT were categorized as user preference, activity level, schedule, location, and predicted patterns. Based on the intervention technique, studies were classified as manual, semiautomated, or automated. Of these, the automated interventions were either knowledge-based or data-driven. Only 6 studies have evaluated the effectiveness of the intervention, and all reported positive outcomes.

Conclusions:

This review assesses aspects of the intervention system providing PIT to increase PA. The studies evaluated PIT in conjunction with other personalizations, such as activity recommendation, with no study evaluating the effectiveness of PIT only. Based on the findings from this review, the following research directions for increasing the effectiveness of personalized interventions are proposed. First, the effectiveness of PIT in PA interventions is yet to be rigorously evaluated, and preliminary studies in this direction are promising. Second, the effectiveness of temporal and environmental factors as inputs and the combination of input types should be evaluated. Third, combinations of intervention content and mode of intervention delivery need to be evaluated. Fourth, standardized metrics for PA measurement and correlations between existing metrics should be established. Fifth, automated intervention systems need to be adapted to integrate clinical guidelines with sophisticated machine learning algorithms. Several important directions for future research are also highlighted in this review.