Personalized interventions for behaviour change: A scoping review of just-in-time adaptive interventions

Abstract

Purpose: Examine the development, implementation and evaluation of just-in-time adaptive interventions (JITAIs) in behaviour change and evaluate the quality of intervention reporting.

Methods: A scoping review of JITAIs incorporating mobile health (mHealth) technologies to improve health-related behaviours in adults. We searched MEDLINE, Embase and PsycINFO using terms related to JITAIs, mHealth, behaviour change and intervention methodology. Narrative analysis assessed theoretical foundations, real-time data capturing and processing methods, outcome evaluation and summarized JITAI efficacy. Quality of intervention reporting was assessed using the template for intervention description and replication (TIDieR) checklist.

Results: Sixty-two JITAIs across physical activity, sedentary behaviour, dietary behaviour, substance use, sexual behaviour, fluid intake, treatment adherence, social skills, gambling behaviour and self-management skills were included. The majority (71%) aimed to evaluate feasibility, acceptability and/or usability. Supporting evidence for JITAI development was identified in 46 studies, with 67% applying this to develop tailored intervention content. Over half (55%) relied solely on self-reported data for tailoring, and 13 studies used only passive monitoring data. While data processing methods were commonly reported, 44% did not specify their techniques. 89% of JITAI designs achieved full marks on the TIDieR checklist and provided sufficient details on JITAI components. Overall, JITAIs proved to be feasible, acceptable and user-friendly across behaviours and settings. Randomized trials showed tailored interventions were efficacious, though outcomes varied by behaviour.

Conclusions: JITAIs offer a promising approach to developing personalized interventions, with their potential effects continuously growing. The recommended checklist emphasizes the importance of reporting transparency in establishing robust intervention designs.

Keywords: behaviour change; digital health; just‐in‐time adaptive intervention; mobile health; personalized intervention.

FIGURE 1

Example of a JITAI to improve heart health. It shows an example of using JITAIs to improve heart health (distal outcome) by increasing physical activity (proximal outcome). An intervention decision is made based on the user's sedentary levels, time of the day, location and calendar availability (tailoring variables), which are collected via wearable and smartphone. During waking hours (decision points), the user receives prompts (intervention options) when they have been sedentary for 50 minutes, are not in a moving vehicle and not busy (decision rules).

FIGURE 2

Flow diagram of study selection. It illustrates the process of study selection using two criteria: the intervention should be (i) delivered as and when a need was identified in real‐time and (ii) tailored to a person's changing needs. These needs included their behaviours, internal states and/or external contexts.