Human factors in the use and efficacy of decision support technologies for type 1 diabetes: evidence from a randomized controlled trial.

AIM: Studies on decision support systems (DSS) for type 1 diabetes show low user engagement and marginal glycemic benefits. This work investigates the interplay between human factors and DSS use and efficacy.

METHODS

Adults using insulin injections or pump and continuous glucose monitoring (CGM) underwent three 2-month interventions, in randomized order: i) no DSS; ii) informative DSS (iDSS), providing summary feedback for decision-making; iii) prescriptive DSS (pDSS), recommending precise treatment actions. DSS advisory modules included tools for smart bolusing and therapy optimization. Primary outcomes were CGM-derived glycemic metrics. Exploratory analyses investigated the association between glycemic outcomes, DSS use, and psychosocial variables.

RESULTS

Fifty-three participants (26 injections, 27 pump) completed the study. Glycemic outcomes did not differ between interventions. However, using iDSS vs no DSS reduced average time >180 mg/dl for participants with lower diabetes-related knowledge (-6 %, p < 0.001) and higher hemoglobin A1c (-6 %, p < 0.01). Emotional distress (p < 0.001) and hypoglycemia worry (p < 0.01) were associated with lower DSS engagement. Participants engaged more with their preferred system (p < 0.01); 40 % of them preferred iDSS.

CONCLUSIONS

Personalized feedback (iDSS) may offer an important learning tool, especially for individuals with lower diabetes-related knowledge. Addressing diabetes-related distress and hypoglycemia worry could unlock the full potential of DSS technologies.