A research lab using mobile health technologies.
Our lab uses ecological momentary assessments (EMAs), passive sensor data, and just-in-time adaptive interventions (JITAI) to improve understanding of relationships between environment, thoughts, feelings, and health behaviors.
Oklahoma researchers develop smartphone app to help people quit smoking
We are a multidisciplinary team leveraging mobile technology.
Led by Dr. Michael Businelle, our team combines expertise in psychology, communication, and technology to develop and implement effective, real-time, mobile health interventions.
Explore Active and Completed Projects at Businelle Research Lab.
Dive into our diverse research initiatives focused on mobile health technology, smoking cessation, mental health, and health disparities in various populations.
mHealth Shared Resource: Advancing Cancer-Related Research
Explore our comprehensive services supporting researchers in utilizing technology for studying and intervening upon cancer-related health risk factors and behaviors.
Recent Publications
*Langford, J. S., *Hébert, E., Jones, D., **Tonkin, S., Barker, B., *Ulm, C., Shi, D., *Becerra, J., & Businelle, M. (in press). Effects of ecological momentary assessment prompting schedule on affect measurement variability and associations with next-day health behaviors. Assessment. https://journals.sagepub.com/doi/10.1177/10731911261444953
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*Shao, R., Neil, J. M., Chen, M., Hannafon, B., Nipp, R., *Montgomery, A., Frank-Pearce, S. G., Moxley, K., Richardson, D. L., Elliott, J., *Benson, L., Gossett, A. G., & Businelle, M. S. (in press). A mobile health app for real-time symptom monitoring in patients with cancer during COVID-19: Feasibility, acceptability, and utility. BMC Cancer. https://link.springer.com/article/10.1186/s12885-026-15772-2
Rhudy, J. L., Kell, P. A., Shadlow, J. O., Lowe, T. S., Stephens, L. D., Zvolensky, M. J., Garey, L., Kendzor, D. E., & Businelle, M. S. (in press). Assessing racial/ethnic differences in sleep-pain relationships using intensive longitudinal modeling among Native Americans. https://academic.oup.com/sleep/article/49/1/zsaf216/8212284
*Langford, J. S., *Hébert, E., Kendzor, D., Chen, M., Vidrine, D., & Businelle, M. (2025). Detecting imminent smoking lapse risk: Prospective lapse risk algorithm versus participant retrospective self-report. Drug and Alcohol Dependence, 276, 112873. https://pmc.ncbi.nlm.nih.gov/articles/PMC12666626/
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