Building health behavior models to guide the development of just-in-time adaptive interventions: a pragmatic framework
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Advances in wireless devices and mobile technology offer many opportunities for delivering just-in-time adaptive interventions (JITAIs)-suites of interventions that adapt over time to an individual's changing status and circumstances with the goal to address the individual's need for support, whenever this need arises. A major challenge confronting behavioral scientists aiming to develop a JITAI concerns the selection and integration of existing empirical, theoretical and practical evidence into a scientific model that can inform the construction of a JITAI and help identify scientific gaps. The purpose of this paper is to establish a pragmatic framework that can be used to organize existing evidence into a useful model for JITAI construction. This framework involves clarifying the conceptual purpose of a JITAI, namely, the provision of just-in-time support via adaptation, as well as describing the components of a JITAI and articulating a list of concrete questions to guide the establishment of a useful model for JITAI construction. The proposed framework includes an organizing scheme for translating the relatively static scientific models underlying many health behavior interventions into a more dynamic model that better incorporates the element of time. This framework will help to guide the next generation of empirical work to support the creation of effective JITAIs.
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Recent developments in mobile health (mHealth) technology allow for greater options in delivering personalized JITAI content, which reduces participant burden by integrating intervention practices into their daily lives, thereby expanding access to intervention content beyond in-person delivery.
“Recent developments in mobile health (mHealth) technology allow for greater options in delivering personalized JITAI content, which reduces participant burden by integrating intervention practices into their daily lives, thereby expanding access to intervention content beyond in-person delivery (Nahum-Shani et al. 2015).”
From Effects of a Personalized Stress Management Intervention on Maternal Mental Health: A Randomized Clinical Trial. (2025) · cites this paper as Nahum-Shani et al. 2015
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Self-citationDionne-Odom, J. N., Taylor, R., Rocque, G., Chambless, C., Ramsey, T., Azuero, A., Ivankova, N., Martin, M. Y., & Bakitas, M. A. (2018) · Journal of Pain and Symptom Management · doi:10.1016/j.jpainsymman.2018.02.009 · Cited by 66 · see citing works
Smith, K. E., Mason, T. B., Juarascio, A., Weinbach, N., Dvorak, R., Crosby, R. D., & Wonderlich, S. A. (2020) · International Journal of Eating Disorders · doi:10.1002/eat.23235 · Cited by 53 · see citing works
Toward Usable Evidence: Optimizing Knowledge Accumulation in HCI Research on Health Behavior Change
Klasnja, P., Hekler, E. B., Korinek, E. V., Harlow, J., & Mishra, S. R. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3026013 · Cited by 44 · see citing works
Self-citationSpadaro, B., Martin-Key, N. A., & Bahn, S. (2021) · Journal of Medical Internet Research · doi:10.2196/27507 · Cited by 45 · see citing works
Nahum-Shani, I., Rabbi, M., Yap, J., Philyaw-Kotov, M. L., Klasnja, P., Bonar, E. E., Cunningham, R. M., Murphy, S. A., & Walton, M. A. (2021) · Health Psychology · doi:10.1037/hea0001101 · Cited by 41 · see citing works
Self-citationSmith, K. E., Mason, T. B., Juarascio, A., Schaefer, L. M., Crosby, R. D., Engel, S. G., & Wonderlich, S. A. (2019) · International Journal of Eating Disorders · doi:10.1002/eat.23124 · Cited by 34 · see citing works
Garland, E. L., Gullapalli, B. T., Prince, K. C., Hanley, A. W., Sanyer, M., Tuomenoksa, M., & Rahman, T. (2023) · Mindfulness · doi:10.1007/s12671-023-02137-0 · Cited by 34 · see citing works
Spruijt-Metz, D., Marlin, B. M., Pavel, M., Rivera, D. E., Hekler, E., De La Torre, S., El Mistiri, M., Golaszweski, N. M., Li, C., Braga De Braganca, R., et al. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19042267 · Cited by 30 · see citing works
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The mobile assistance for regulating smoking (MARS) micro-randomized trial design protocol
Nahum-Shani, I., Potter, L. N., Lam, C. Y., Yap, J., Moreno, A., Stoffel, R., Wu, Z., Wan, N., Dempsey, W., Kumar, S., et al. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106513 · Cited by 23 · see citing works
Self-citationOptimizing Expectations via Mobile Apps: A New Approach for Examining and Enhancing Placebo Effects
Gruszka, P., Burger, C., & Jensen, M. P. (2019) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2019.00365 · Cited by 15 · see citing works
A Roadmap to an Equitable Digital Diabetes Ecosystem
Kerr, D., Klonoff, D. C., Bergenstal, R. M., Choudhary, P., & Ji, L. (2023) · Endocrine Practice · doi:10.1016/j.eprac.2022.12.016 · Cited by 10 · see citing works
Developing personalized algorithms for sensing mental health symptoms in daily life
Timmons, A. C., Tutul, A. A., Avramidis, K., Duong, J. B., Carta, K. E., Walters, S. N., Jumonville, G. A., Carrasco, A. S., Freitag, G. F., Romero, D. N., et al. (2025) · npj Mental Health Research · doi:10.1038/s44184-025-00147-5 · Cited by 7 · see citing works
Brill, E., Vinay, R., Nißen, M., Joshi, P., Klöppel, S., & Kowatsch, T. (2025) · JMIR Formative Research · doi:10.2196/66885 · Cited by 5 · see citing works
Tandon, S. D., Moskowitz, J. T., Edwards, R. C., Zhang, Y., Giase, G., Sinche, B., Blum, A. L., Krislov, S., Reynolds, H. M., Rangarajan, A., et al. (2025) · Archives of Women's Mental Health · doi:10.1007/s00737-025-01619-5 · Cited by 3 · see citing works
“…health (mHealth) technology allow for greater options in delivering personalized JITAI content, which reduces participant burden by integrating intervention practices into their daily lives, thereby expanding access to intervention content beyond in-person delivery (Nahum-Shani et al. 2015 ).”
- Authors
- Nahum-Shani, I., Hekler, E. B., & Spruijt-Metz, D.
- Affiliations
- University of Michigan (US)
- Arizona State University (US)
- Venue
- Health Psychology
- Published
- 2015-12
- Volume
- 34
- Issue
- Suppl
- Pages
- 1209-1219
- ISSN
- 0278-6133 (ISSN-L)
- 1930-7810
- PMC
- PMC4732268
- OpenAlex
- W2427775456
- Semantic Scholar
- aa16cd7a68fac2b304e481f41de27745f61f0649
- Cited by
- 568
- References
- 70
- Citations by year
- 2026: 60 · 2025: 54 · 2024: 50 · 2023: 54 · 2022: 55 · 2021: 61 · 2020: 86 · 2019: 52 · 2018: 35 · 2017: 37 · 2016: 19 · 2015: 4
- FWCI
- 57.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Health Psychology (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (NIH/NIDA R01DA039901, NIH/NIDA P50DA039838, NIH/NIAAA R01AA023187, NIH/SEPA R25RR032159, NSF IIS-1449751)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- just-in-time adaptive interventions, health behavior models, mobile health, adaptive interventions, evidence integration
- MeSH terms
- Biobehavioral Sciences, Adaptation, Psychological, Communication, Humans, Models, Theoretical, Time Factors, Health Behavior, Early Medical Intervention
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