Barriers and enablers to maintaining self-management behaviours after attending a self-management support intervention for type 2 diabetes: A systematic review and qualitative evidence synthesis.
Márcia CarvalhoPauline DunneDominika KwasnickaMolly Byrnenull nullJennifer Mc SharryPublished in: Health psychology review (2023)
Abstract Attendance at type 2 diabetes self-management interventions is associated with improved outcomes. However, difficulties maintaining self-management behaviours attenuate long-term impact. This review aimed to identify and synthesise qualitative research on barriers and enablers to maintaining type 2 diabetes self-management behaviours after attending a self-management intervention. Eight electronic databases were searched to identify relevant peer-reviewed and grey literature studies. Data were synthesised using the best-fit framework synthesis approach, guided by the five theoretical themes and fourteen constructs for behaviour change maintenance identified by Kwasnicka et al. (2016). Study methodological limitations and confidence in findings were assessed using an adapted version of the Critical Appraisal Skills Programme (CASP) tool and the GRADE-CERQual approach respectively. Eleven articles reporting on 10 studies were included. Twenty-eight barriers and enablers were coded to the five a priori themes. Barriers were most commonly coded to the themes self-regulation, resources, and environmental and social influences. Enablers were most commonly coded to the themes habits and maintenance motives. Methodological limitations of included studies varied, leading to moderate or low confidence in most of the review findings. Interventions may improve behavioural maintenance by providing post-intervention support, promoting positive behaviour change motives, self-regulation, habit formation, and facilitating access to resources and support.
Keyphrases
- type diabetes
- randomized controlled trial
- glycemic control
- systematic review
- case control
- insulin resistance
- healthcare
- physical activity
- big data
- mental health
- study protocol
- metabolic syndrome
- tertiary care
- clinical trial
- adipose tissue
- multiple sclerosis
- white matter
- machine learning
- artificial intelligence
- deep learning
- medical students
- double blind