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Percentile ranks and benchmark estimates of change for the Health Education Impact Questionnaire: Normative data from an Australian sample

机译:健康教育影响问卷调查的百分等级和变化的基准估计:来自澳大利亚样本的规范性数据

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摘要

Objective:Participant self-report data play an essential role in the evaluation of health education activities, programmes and policies. When questionnaire items do not have a clear mapping to a performance-based continuum, percentile norms are useful for communicating individual test results to users. Similarly, when assessing programme impact, the comparison of effect sizes for group differences or baseline to follow-up change with effect sizes observed in relevant normative data provides more directly useful information compared with statistical tests of mean differences and the evaluation of effect sizes for substantive significance using universal rule-of-thumb such as those for Cohen’s ‘d’. This article aims to assist managers, programme staff and clinicians of healthcare organisations who use the Health Education Impact Questionnaire interpret their results using percentile norms for individual baseline and follow-up scores together with group effect sizes for change across the duration of typical chronic disease self-management and support programme.
机译:目的:参与者的自我报告数据在健康教育活动,计划和政策的评估中起着至关重要的作用。如果调查表项目没有明确映射到基于性能的连续体,则百分位数规范对于将单个测试结果传达给用户很有用。同样,在评估计划影响时,与均值差异的统计检验和实质性影响大小的评估相比,将群体差异或基线与后续变化的影响大小与相关规范数据中观察到的影响大小进行比较,可以提供更直接有用的信息。使用通用的经验法则(例如Cohen的d)的重要性。本文旨在帮助使用“健康教育影响调查表”的医疗组织的经理,项目人员和临床医生使用百分位数准则(针对各个基线和随访分数)以及在典型的慢性疾病自我持续期间变化的群体效应大小来解释其结果管理和支持计划。

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