Consensus Building Using Modified Delphi Panel and Nominal Group Techniques for Social Prescribing Intervention in Patients With Type 2 Diabetes Mellitus

Background: Health interventions have been prioritised worldwide to curb the growth and life impact of Type 2 diabetes mellitus (T2DM). Social prescribing (SP), as a complex health intervention, has shown promise in producing positive outcomes. This study aims to establish an expert consensus on a model and SP intervention’s multicomponents to empower self-care and health literacy in T2DM patients.

Methods: A descriptive design using two consensus-building techniques took place between June and September 2023. The modified nominal group technique (NGT) was used to reach a consensus on the SP intervention model with 12 experts, who participated in two online meetings and voted on a scale of 1–9. In addition, a modified Delphi panel with 10 experts in two online rounds to reach a consensus on the intervention’s multicomponents, who rated the categories of the intervention on a Likert scale of 1–5. Consensus was reached when an agreement level ≥ 75% was obtained. The data were analysed via descriptive analysis, and the consensus level was calculated based on the mean, standard deviation and percentage.

Results: Using the modified NGT, the experts reached a 93.52% consensus on the final model flowchart. In the modified Delphi panel’s first round, 27 original interventions were evaluated. In the second round, one was removed because of low agreement, six were revised, and five new ones were added based on participant feedback. A consensus was achieved on 30 interventions across the six categories (cross-cutting intervention components, physical activity, nutrition, medication management, self-monitoring and well-being).

Conclusions: Both consensus techniques ensure that the SP model and these interventions meet the person’s needs and the community it serves. They allow a better understanding of self-care and health literacy strategies, contributing to future health programs and policies for more efficiently managing T2DM.