The most optimal school recruitment strategies for school-based obesity prevention and health promotion research in the United States: A systematic review with Delphi study.
Aliye B CepniReshma VilsonRachel R HelbingDavid W WalshCraig A JohnstonCynthia Y YoonSheryl O HughesTracey A LedouxPublished in: Obesity reviews : an official journal of the International Association for the Study of Obesity (2024)
This systematic review with the Delphi study aimed to identify effective and resource-efficient (optimal) strategies for recruiting schools into health promotion interventions in the United States. A literature search was conducted in PubMed, Cochrane Library, and CINAHL (EBSCO). A total of 116 interventions reported in 160 articles were included. Most school-based interventions did not report data regarding school recruitment duration (81%), target school size (63%), and school recruitment strategies (78%). Further, no details were provided regarding the reasons for declining to participate despite being eligible. For the Delphi, responses from 23 researchers in school-based clinical trials were collected. A qualitative descriptive approach was used for coding responses and collapsed into higher-order categories based on school recruitment strategies. Delphi participants reported that (1) creating new or leveraging pre-existing partnerships, (2) intervention champion, (3) minimal school disruptions, (4) working with open mind/flexibility, and (5) transparent communication are the most optimal school recruitment strategies. Staff time and travel were the most frequently reported costs for implementing those strategies. The overall trend in school-based obesity prevention intervention studies illustrates the importance of a better understanding school recruitment. Improved reporting can allow researchers to budget their time and resources better and provide greater confidence in reaching their target school size.
Keyphrases
- physical activity
- mental health
- systematic review
- health promotion
- clinical trial
- randomized controlled trial
- high school
- metabolic syndrome
- type diabetes
- insulin resistance
- minimally invasive
- machine learning
- study protocol
- electronic health record
- emergency department
- adipose tissue
- open label
- big data
- deep learning
- high fat diet induced
- phase iii