Adaptive interventions guide how best to sequence intervention options (e.g., intervention type, intensity, delivery modality) over time based on time-varying information about the individual.

For example, an adaptive intervention for managing obesity will provide clinicians a guide for how to begin treatment (e.g., start with a behavioral weight loss intervention), monitor treatment progress (e.g., based on weight changes) and use this information to decide whether, when, and/or how to modify treatment (e.g., augment with a meal replacement plan if weight loss by week 4 < 2lb).

Adaptive interventions are also known as ‘medication algorithms’, ‘multistage treatment regimens’, ‘adaptive treatment strategies’, ‘dynamic treatment regimens’, ‘stepped care models,’ and ‘treatment plans’, among other terms.

Technically speaking, an adaptive intervention is a sequence of decision rules that specify for each of several decision points (i.e., points in time in which an intervention decision should be made) whether and how to modify the intervention depending on a person’s needs.

Adaptive interventions play a critical role in many fields. This includes precision healthcare, which calls for matching interventions to fundamental and actionable determinants of health, and educational/academic frameworks that call for providing increasingly intensive evidence-based support (academic and/or behavioral) to students using data-driven decision-making.

References

Almirall, D., Nahum-Shani, I., Sherwood, N. E., & Murphy, S. A. (2014). Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research. Translational behavioral medicine, 4(3), 260-274.

Collins, L. M., Murphy, S. A., & Bierman, K. L. (2004). A conceptual framework for adaptive preventive interventions. Prevention science, 5(3), 185-196.

Nahum-Shani, I., & Almirall, D. (2019). An Introduction to Adaptive Interventions and SMART Designs in Education. NCSER 2020-001. National Center for Special Education Research.

Nahum-Shani, I. & Militello, L.K. (2018). Promoting Military Family Well-Being with DigitallySupported Adaptive and Just-In-Time Adaptive Interventions: Opportunities and Challenges. The National Academies of Sciences, Engineering, and Medicine consensus study: The Well-Being of Military Families; Commissioned paper: https://www.nationalacademies.org/our-work/the-well-being-of-military-families

Pfammatter, A. F., Nahum-Shani, I., DeZelar, M., Scanlan, L., McFadden, H. G., Siddique, J., … & Spring, B. (2019). SMART: study protocol for a sequential multiple assignment randomized controlled trial to optimize weight loss management. Contemporary clinical trials, 82, 36-45.

d3lab specializes in developing new methods for optimizing Adaptive Interventions, including new approaches for the design and analysis of sequential, multiple-assignment, randomized trials (SMARTs).

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