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mHealth-Based Just-in-Time Adaptive Intervention to Improve the Physical Activity Levels of Individuals With Spinal Cord Injury: Protocol for a Randomized Controlled Trial

mHealth-Based Just-in-Time Adaptive Intervention to Improve the Physical Activity Levels of Individuals With Spinal Cord Injury: Protocol for a Randomized Controlled Trial

The framework used for this proposed study (Figure 2) is adapted from Nahum-Shani et al [26], which highlights 4 components including decision points, intervention options, tailoring variables, and decision rules. JITAIs often provide an intervention through a smartphone, wearable activity monitor, or both. The system automatically determines which intervention option, such as prompting an individual to set a goal to perform PA or prompting feedback about PA, could be helpful or especially effective.

Rachel L Carey, Ha Le, Donna L Coffman, Inbal Nahum-Shani, Mohanraj Thirumalai, Cole Hagen, Laura A Baehr, Mary Schmidt-Read, Marlyn S R Lamboy, Stephanie A Kolakowsky-Hayner, Ralph J Marino, Stephen S Intille, Shivayogi V Hiremath

JMIR Res Protoc 2024;13:e57699

Developing an Adaptive Mobile Intervention to Address Risky Substance Use Among Adolescents and Emerging Adults: Usability Study

Developing an Adaptive Mobile Intervention to Address Risky Substance Use Among Adolescents and Emerging Adults: Usability Study

Subsequently, as described in a study by Nahum-Shani et al (unpublished data, 2021), we conducted a larger MRT (N=68) of SARA with youth reporting past-month binge drinking or cannabis use to further refine the SARA app. Using data from this MRT, we assessed the proximal effect of delivering theory-based engagement strategies, including reciprocity and nonmonetary reinforcement of daily survey completion.

Lara N Coughlin, Inbal Nahum-Shani, Meredith L Philyaw-Kotov, Erin E Bonar, Mashfiqui Rabbi, Predrag Klasnja, Susan Murphy, Maureen A Walton

JMIR Mhealth Uhealth 2021;9(1):e24424