Acceptability and adoption of the Face-it health promotion intervention targeting women with prior gestational diabetes and their partners: A qualitative study of the perspectives of healthcare professionals

Abstract

Aim: In this study, we investigated healthcare professionals' (HCPs) experiences with delivering home visits and digital coaching in the Face-it health promotion intervention targeting women with recent GDM and their families. Understanding the acceptability and adoption of a health promotion intervention can provide insights into intervention fidelity and future scalability. Methods: In total, 13 HCPs were interviewed. Data were analysed thematically through an abductive approach using Sekhon et al.'s theoretical framework of acceptability and Greenhalgh et al.'s framework for non-adoption, abandonment, scale-up, spread, and sustainability. Results: Acceptability and adoption of the intervention among HCPs were influenced by (1) skills and technology, (2) values, and (3) organisation. The intervention was experienced as acceptable to HCPs because the dialogue tool, visualising different topics, used in the home visits and digital coaching through the LIVA app were flexible and enabled them to address psychosocial health and personalise goal setting in families. However, delivering asynchronous and non-verbal communication was experienced as straining HCPs' relationship with families, which misaligned with HCPs' values. Establishing a non-judgemental environment was needed to increase intervention acceptability among HCPs towards addressing type 2 diabetes risk after GDM. Increased collaboration between HCPs may have aligned advice and support to families and could have benefitted delivery. Conclusions: When delivering health promotion to women with prior GDM, flexible intervention components that support psychosocial- and mental health topics may increase acceptability and adoption of the intervention among HCPs. HCPs' skills, values, and organisational factors should be considered prior and during implementation.