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Do socioeconomic inequities arise during school-based physical activity interventions? An exploratory case study of the GoActive trial
OBJECTIVE: To investigate socioeconomic inequities in the intervention and evaluation process of the GoActive school-based physical activity intervention and demonstrate a novel approach to evaluating intervention-related inequalities. DESIGN: Exploratory post-hoc secondary data analysis of trial da...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10016273/ https://www.ncbi.nlm.nih.gov/pubmed/36914195 http://dx.doi.org/10.1136/bmjopen-2022-065953 |
Sumario: | OBJECTIVE: To investigate socioeconomic inequities in the intervention and evaluation process of the GoActive school-based physical activity intervention and demonstrate a novel approach to evaluating intervention-related inequalities. DESIGN: Exploratory post-hoc secondary data analysis of trial data. SETTING: The GoActive trial was run in secondary schools across Cambridgeshire and Essex (UK), between September 2016 and July 2018. PARTICIPANTS: 13–14 years old adolescents (n=2838, 16 schools). METHODS: Socioeconomic inequities across six stages in the intervention and evaluation process were evaluated: (1) provision of and access to resources; (2) intervention uptake; (3) intervention effectiveness (accelerometer-assessed moderate-to-vigorous physical activity (MVPA)); (4) long-term compliance; (5) response in evaluation; and (6) impact on health. Data from self-report and objective measures were analysed by individual-level and school-level socioeconomic position (SEP) using a combination of classical hypothesis tests and multilevel regression modelling. RESULTS: Stage: (1) There was no difference in the provision of physical activity resources by school-level SEP (eg, quality of facilities (0–3), low=2.6 (0.5); high=2.5 (0.4). (2) Students of low-SEP engaged significantly less with the intervention (eg, website access: low=37.2%; middle=45.4%; high=47.0%; p=0.001). (3) There was a positive intervention effect on MVPA in adolescents of low-SEP (3.13 min/day, 95% CI −1.27 to 7.54, but not middle/high (−1.49; 95% CI −6.54 to 3.57). (4) At 10 months post-intervention, this difference increased (low SEP: 4.90; 95% CI 0.09 to 9.70; middle/high SEP: −2.76; 95% CI −6.78 to 1.26). (5) There was greater non-compliance to evaluation measures among adolescents of low-SEP (eg, % accelerometer compliance (low vs high): baseline: 88.4 vs 92.5; post-intervention: 61.6 vs 69.2; follow-up: 54.5 vs 70.2. (6) The intervention effect on body mass index (BMI) z-score was more favourable in adolescents of low-SEP (low SEP: −0.10; 95% CI −0.19 to 0.00; middle/high: 0.03; 95% CI −0.05 to 0.12). CONCLUSIONS: These analyses suggest the GoActive intervention had a more favourable positive effect on MVPA and BMI in adolescents of low-SEP, despite lower intervention engagement. However, differential response to evaluation measures may have biassed these conclusions. We demonstrate a novel way of evaluating inequities within young people’s physical activity intervention evaluations. TRIAL REGISTRATION NUMBER: ISRCTN31583496. |
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