About This Code
This example code was designed for the curation and analysis of data arising from the Substance Abuse Research Assistant (SARA) micro-randomized trial (MRT).
How can a behavioral scientist use this code?
The documentation included with this code details the rationale for the construction of variables used in the analysis. A behavioral scientist can use this code as a starting point for the curation and analysis of data in their own MRT.
Adherence to data collection (e.g., completion of ecological momentary assessments [EMAs]) is low for most mobile health apps, a critical challenge facing scientists who wish to develop theoretically- and empirically- grounded just-in-time adaptive interventions (JITAI). Motivated by the need to tackle this challenge, a micro-randomized trial (MRT) was conducted to investigate different engagement strategies to increase adherence to data collection in the mobile health setting, particularly, engagement strategies which require only minimal monetary incentives. Prior research has indicated that monetary incentives can undermine intrinsic motivation and intervention scalability. Adolecents and emerging adults with past-month substance use were enrolled into the MRT. Participants were randomized multiple times daily to receive one of several possible engagement strategies. The engagement strategies were compared based on the proximal outcome, improvement in proximal engagement in daily mHealth self-reporting. The example code provided here describes the curation and analysis of data collected from this MRT.
View YouTube video HERE.
1. Rabbi, M., Philyaw-Kotov, M., Klasnja, P., Bonar, E., Nahum-Shani, I., Walton, M., & Murphy, S. (2018, January 18). SARA – Substance Abuse Research Assistant. https://doi.org/10.17605/OSF.IO/WHGFP
This reference contains the study protocol which was pre-specified prior to the curation and analysis of data from the MRT. Four research questions were specified in the protocol, of which, three were tackled by the example code above and the reference below (Nahum-Shani et al., 2021)
2. Nahum-Shani, I., Rabbi, M., Yap, J., Philyaw-Kotov, M. L., Klasnja, P., Bonar, E. E., … & Walton, M. A. (2021). Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial. Health Psychology, 40(12), 974.
This reference contains the results of the investigation of three of the four research questions which were pre-specified in the protocol above.
3. Rabbi, M., Kotov, M. P., Cunningham, R., Bonar, E. E., Nahum-Shani, I., Klasnja, P., … & Murphy, S. (2018). Toward increasing engagement in substance use data collection: development of the Substance Abuse Research Assistant app and protocol for a microrandomized trial using adolescents and emerging adults. JMIR research protocols, 7(7), e9850.
This reference describes the scientific motivation for the development of the Substance Abuse Research Assistant (SARA) app. Further, this reference contains sample screenshots of the SARA app and describes in detail the various data collection strategies integrated into the app.
1. Update on 2020-09-14: Winner, Michigan Institute of Data Science (MIDAS) Reproducibility Challenge, 2020
Nahum-Shani, I., Yap, J., Walton, M. (2020, September 14). Developing Workflows and Templates for Reproducing Results from Mobile Health (mHealth) Trials. [Conference presentation]. MIDAS 2020 Reproducibility Day, Ann Arbor, MI, United States. https://www.youtube.com/watch?v=T-cMb-_Xl38 (timestamp begins at 1:11:29)
2. Update on 2017-08-21: The study was registered on clinicaltrials.gov
Record on classic clinicaltrials.gov site: https://clinicaltrials.gov/ct2/show/NCT03255317
Record on new (beta version) clinicaltrials.gov site: https://beta.clinicaltrials.gov/study/NCT03255317?patient=SARA%20-%20Substance%20Abuse%20Research%20Assistant%20(SARA)&locStr=&distance=0