Understanding what drives schools to adopt effective school-based nutrition programs: a cross-sectional study of barriers and facilitators

TL;DR

This study explores what stops or helps schools adopt a nutrition program, finding that barriers vary by school characteristics like socioeconomic status.

Contribution

The study identifies how barriers and facilitators to adopting a nutrition program differ based on school characteristics.

Findings

Higher SES schools reported more staff workload as a barrier, while lower SES schools reported parent perception issues.

Keeping the program free and showing evidence of health benefits were the most common facilitators.

No significant associations were found between school characteristics and reported facilitators.

Abstract

Effective school-based nutrition programs can improve children’s diet and achieve population-level health outcomes if implemented at scale.

This study aimed to (i) examine the determinants (i.e. the barriers and facilitators) to the adoption of SWAP IT, an effective school-based nutrition program, and (ii) examine associations between these determinants and school characteristics, including school size, socioeconomic status (SES), and geolocation.

A cross-sectional study was conducted with one key decision maker (e.g. principals, assistant principals, and health and wellbeing officers) from primary schools across New South Wales (NSW), Australia. Descriptive statistics and logistic regression were used to identify determinants of SWAP IT adoption and examine associations with school characteristics.

Key decision makers who responded (n = 160; 47% participation rate) most frequently reported barriers included “expected workload for staff” (n = 52, 33%), and the “perception that parents and carers do not think it is the school’s place to provide this information” (n = 31, 19%). The most frequently identified facilitators were to “keep the program free” (n = 60, 38%), and “show evidence that SWAP IT supports the development of healthy habits in children” (n = 18, 11%). Significant associations were found between barriers and the following school characteristics: schools in higher SES areas were more likely to report the “expected workload for staff” (OR: 2.6; 95% CI: 1.3–5.2; P = .006), while schools in lower SES areas more often reported the “perception that parents and carers do not think it is the school’s place to provide this information” (OR 2.4; 95% CI: 1.0–5.6; P = .04). No significant associations were found between school characteristics and reported facilitators.

Barriers to the adoption of school-based nutrition programs can differ by school characteristics, highlighting the importance of considering these factors when scaling up such programs to ensure equitable adoption.

The Clinical Trials Registration #ACTRN12623000145606