Behavior-Analytic Approaches to the Management of Diabetes Mellitus: Current Status and Future Directions
Behavior analysts belong in diabetes care teams, using phones and apps to teach adults the daily skills that keep blood sugar stable.
01Research in Context
What this study did
Raiff et al. (2021) looked at every ABA study that tried to help adults manage diabetes. They pulled the papers together and wrote a plain-language map of what works.
The review is not a new experiment. It is a guide for BCBAs who want to join primary-care teams and use phones, apps, or telehealth to teach self-care skills.
What they found
The field is small but growing. Most studies use simple behavioral tricks like goal setting, self-monitoring, and feedback to keep blood sugar in range.
Technology makes the tricks stick. Text reminders and glucose apps give instant feedback, so adults check sugar levels more often and take insulin on time.
How this fits with other research
Lerman (2024) extends this idea. Her paper hands you a ready-made blueprint for training nurses and doctors in ABA tools, exactly what Raiff says we need.
Powell et al. (2020) supply the nuts and bolts. They show how Plan-Do-Study-Act cycles and control charts can fit diabetes care into busy clinics without losing ABA heart.
Johnson et al. (1994) is the grandparent. Their Deming-style quality loop prefigures the same team-based, data-every-day model Raiff now pushes for diabetes.
Why it matters
If you work with adults or healthcare teams, this review gives you the green light to step in. Ask the clinic if you can add a daily text prompt or a shared glucose graph. Start small: one patient, one provider, one week of data. You bring the behavioral engine; they bring the medical access. Together you can keep people out of the ER and in their own lives.
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02At a glance
03Original abstract
Diabetes mellitus is the seventh leading cause of death in the United States, requiring a series of complex behavior changes that must be sustained for a lifetime (e.g., counting carbohydrates, self-monitoring blood glucose, adjusting insulin). Although complex, all of these tasks involve behavior, making them amenable targets for behavior analysts. In this article, the authors describe interventions that have focused on antecedent, consequent, multicomponent, and alternate procedures for the management of diabetes, highlighting ways in which technology has been used to overcome common barriers to the use of these intensive, evidence-based interventions. Additional variables relevant to poorly managed diabetes (e.g., delay discounting) are also discussed. Future research and practice should focus on harnessing continued advances in information technology while also considering underexplored behavioral technologies for the effective treatment of diabetes, with a focus on identifying sustainable, long-term solutions for maintaining proper diabetes management. Practical implementation of these interventions will depend on having qualified behavior analysts working in integrated primary care settings where the interventions are most likely to be used, which will require interdisciplinary training and collaboration.
Behavior Analysis in Practice, 2021 · doi:10.1007/s40617-020-00488-x