Do socioeconomic inequities arise during school-based physical activity interventions? An exploratory case study of the GoActive trial.

Do socioeconomic inequities arise during school-based physical activity interventions? An exploratory case study of the GoActive trial.
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DOI:
10.1136/bmjopen-2022-065953
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发表时间:
2023-03-13
期刊:
影响因子:
2.9
通讯作者:
--
中科院分区:
医学3区
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调查GoActive校本体育活动干预的干预和评估过程中的社会经济不平等,并展示一种评估干预相关不平等的新方法。试验数据的探索性事后次要数据分析。GoActive试验于2016年9月至2018年7月在剑桥郡和埃塞克斯(英国)的中学进行。13-14岁青少年(n=2838,16所学校)。在干预和评估过程的六个阶段评估了社会经济不平等:(1)提供和获得资源;(2)干预吸收;(3)干预有效性(加速度计评估的中度至剧烈体力活动(MVPA));(4)长期依从性;(5)评价反应;(6)对健康的影响。从自我报告和客观措施的数据进行了分析,个人层面和学校层面的社会经济地位(SEP),使用经典的假设检验和多层次回归模型相结合。阶段:(1)学校体育教育机构在提供体育活动资源方面没有差异(如设施质量(0-3),低=2.6(0.5);高=2.5(0.4))。(2)低SEP的学生参与干预显著较少(例如,网站访问:低=37.2%;中=45.4%;高=47.0%; p=0.001)。(3)低SEP青少年的MVPA有积极的干预效果(3.13分钟/天,95% CI −1.27至7.54,但不是中/高SEP青少年(−1.49; 95% CI −6.54至3.57)。(4)在干预后10个月,这种差异增加(低SEP:4.90; 95% CI 0.09至9.70;中/高SEP:-2.76; 95% CI-6.78至1.26)。(5)低SEP青少年对评价指标的不依从性更高(例如,加速计依从性%(低vs高):基线:88.4 vs 92.5;干预后:61.6 vs 69.2;随访:54.5 vs 70.2)。(6)在低SEP青少年中,对体重指数(BMI)z评分的干预效果更有利(低SEP:−0.10; 95% CI −0.19至0.00;中/高:0.03; 95% CI −0.05至0.12)。这些分析表明,GoActive干预对低SEP青少年的MVPA和BMI有更有利的积极影响,尽管干预参与度较低。然而,对评价措施的不同反应可能使这些结论有偏差。我们展示了一种新的方式来评估年轻人的身体活动干预评估中的不公平现象。ISRCTN31583496。
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. Exploratory post-hoc secondary data analysis of trial data. The GoActive trial was run in secondary schools across Cambridgeshire and Essex (UK), between September 2016 and July 2018. 13–14 years old adolescents (n=2838, 16 schools). 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. 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). 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. ISRCTN31583496.
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