Paschal Sheeran, Caroline Frisch, Olivia Listrom, Yifei Pei, Andrea Bermudez, Alexander J Rothman, Jennifer S Smith
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We conducted a systematic review of the effectiveness of interventions to promote colorectal cancer screening (CCS) and generated benchmarks via the percentile distribution of <i>OR</i>s, screening rates for intervention and control arms, and differential screening rates (intervention minus control rate) in respective trials.</p><p><strong>Method: </strong>Literature searches identified 187 eligible tests (<i>N</i> = 371,018).</p><p><strong>Results: </strong>Random effects meta-analysis computed a sample-weighted <i>OR</i> = 1.69 (95% CI [1.55, 1.84]) and meta-regression showed that there was no improvement in the effectiveness of CCS interventions between 1996 and 2022. Benchmarking indicated that the median effect size was <i>OR</i> = 1.32, equivalent to a 35.7% screening rate in the intervention arm, and a 5.9% differential screening rate. Benchmarks were also generated for different types of screening (e.g., fecal immunochemical test, colonoscopy), sample characteristics (e.g., race, socioeconomic status), and methodological features (e.g., control conditions).</p><p><strong>Conclusions: </strong>Interventions to promote CCS have a small effect and effectiveness has not increased over time. The percentile values for effect sizes and screening rates reported here can be used to benchmark the effectiveness of future trials. Benchmarking offers a way to evaluate interventions that are grounded in accumulated evidence and can inform judgments about tradeoffs among effectiveness, reach, and cost. (PsycInfo Database Record (c) 2024 APA, all rights reserved).</p>","PeriodicalId":55066,"journal":{"name":"Health Psychology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Systematic review of interventions to promote colorectal cancer screening: Benchmarking effect sizes and screening rates.\",\"authors\":\"Paschal Sheeran, Caroline Frisch, Olivia Listrom, Yifei Pei, Andrea Bermudez, Alexander J Rothman, Jennifer S Smith\",\"doi\":\"10.1037/hea0001444\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>The effectiveness of behavioral interventions is typically evaluated relative to control conditions using null hypothesis significance testing (i.e., <i>p</i> < .05) or effect sizes. These criteria overlook comparisons with previous interventions and do little to promote a cumulative science of behavior change. We conducted a systematic review of the effectiveness of interventions to promote colorectal cancer screening (CCS) and generated benchmarks via the percentile distribution of <i>OR</i>s, screening rates for intervention and control arms, and differential screening rates (intervention minus control rate) in respective trials.</p><p><strong>Method: </strong>Literature searches identified 187 eligible tests (<i>N</i> = 371,018).</p><p><strong>Results: </strong>Random effects meta-analysis computed a sample-weighted <i>OR</i> = 1.69 (95% CI [1.55, 1.84]) and meta-regression showed that there was no improvement in the effectiveness of CCS interventions between 1996 and 2022. Benchmarking indicated that the median effect size was <i>OR</i> = 1.32, equivalent to a 35.7% screening rate in the intervention arm, and a 5.9% differential screening rate. Benchmarks were also generated for different types of screening (e.g., fecal immunochemical test, colonoscopy), sample characteristics (e.g., race, socioeconomic status), and methodological features (e.g., control conditions).</p><p><strong>Conclusions: </strong>Interventions to promote CCS have a small effect and effectiveness has not increased over time. The percentile values for effect sizes and screening rates reported here can be used to benchmark the effectiveness of future trials. Benchmarking offers a way to evaluate interventions that are grounded in accumulated evidence and can inform judgments about tradeoffs among effectiveness, reach, and cost. 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引用次数: 0
摘要
目的:行为干预的有效性通常是相对于对照条件而言的,使用的是无效假设显著性检验(即 p < .05)或效应大小。这些标准忽视了与以往干预措施的比较,也不利于促进行为改变的累积科学。我们对促进结直肠癌筛查(CCS)的干预措施的有效性进行了系统性回顾,并通过各试验中的ORs百分位数分布、干预组和对照组的筛查率以及差异筛查率(干预率减去对照率)生成了基准:方法:文献检索确定了 187 项符合条件的试验(N=371,018):随机效应荟萃分析计算出的样本加权OR=1.69(95% CI [1.55,1.84]),荟萃回归显示,1996年至2022年期间,CCS干预措施的效果没有改善。基准分析表明,效果大小的中位数为 OR = 1.32,相当于干预组 35.7% 的筛查率和 5.9% 的差异筛查率。此外,还针对不同筛查类型(如粪便免疫化学检验、结肠镜检查)、样本特征(如种族、社会经济地位)和方法特征(如对照条件)制定了基准:结论:促进 CCS 的干预措施效果较小,其有效性并未随着时间的推移而提高。此处报告的效应大小和筛查率的百分位值可用于为未来试验的有效性设定基准。标杆法提供了一种评估干预措施的方法,这种方法以积累的证据为基础,可以为判断有效性、覆盖面和成本之间的权衡提供信息。(PsycInfo Database Record (c) 2024 APA,保留所有权利)。
Systematic review of interventions to promote colorectal cancer screening: Benchmarking effect sizes and screening rates.
Objective: The effectiveness of behavioral interventions is typically evaluated relative to control conditions using null hypothesis significance testing (i.e., p < .05) or effect sizes. These criteria overlook comparisons with previous interventions and do little to promote a cumulative science of behavior change. We conducted a systematic review of the effectiveness of interventions to promote colorectal cancer screening (CCS) and generated benchmarks via the percentile distribution of ORs, screening rates for intervention and control arms, and differential screening rates (intervention minus control rate) in respective trials.
Method: Literature searches identified 187 eligible tests (N = 371,018).
Results: Random effects meta-analysis computed a sample-weighted OR = 1.69 (95% CI [1.55, 1.84]) and meta-regression showed that there was no improvement in the effectiveness of CCS interventions between 1996 and 2022. Benchmarking indicated that the median effect size was OR = 1.32, equivalent to a 35.7% screening rate in the intervention arm, and a 5.9% differential screening rate. Benchmarks were also generated for different types of screening (e.g., fecal immunochemical test, colonoscopy), sample characteristics (e.g., race, socioeconomic status), and methodological features (e.g., control conditions).
Conclusions: Interventions to promote CCS have a small effect and effectiveness has not increased over time. The percentile values for effect sizes and screening rates reported here can be used to benchmark the effectiveness of future trials. Benchmarking offers a way to evaluate interventions that are grounded in accumulated evidence and can inform judgments about tradeoffs among effectiveness, reach, and cost. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
期刊介绍:
Health Psychology publishes articles on psychological, biobehavioral, social, and environmental factors in physical health and medical illness, and other issues in health psychology.