Assessing the potential for nonresponse bias and measurement concordance in the clinical preventive services self-administered questionnaire survey1

Q3 Social Sciences Journal of Economic and Social Measurement Pub Date : 2022-04-01 DOI:10.3233/jem-220483
P. Muhuri
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Abstract

Health survey statistics are essential for setting national targets, monitoring population-level trends, and tracking progress in adults’ utilization of preventive health services. However, survey estimates can be subject to nonresponse bias. This paper primarily assesses the potential for nonresponse bias in six utilization estimates from the Clinical Preventive Services Self-Administered Questionnaire (PSAQ) survey. The article highlights several findings. First, the eligible PSAQ sample person’s selective nonresponse associated with influenza vaccinations and blood pressure check-ups reported in the Medical Expenditure Panel Survey provides indirect evidence of overestimating the utilization of those services in the PSAQ survey. Second, the study found a few weighting class variables correlated with PSAQ response propensity and survey variables. Third, surprisingly, base-weighted estimates of preventive service utilization changed little despite multiple post-survey adjustments, suggesting no substantial nonresponse bias. Additionally, the study finds moderate to near-perfect concordance in responses to selected preventive service questions across interview modes.
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评估临床预防服务自我管理问卷调查中潜在的无反应偏倚和测量一致性1
健康调查统计数据对于制定国家目标、监测人口水平趋势和跟踪成年人利用预防性健康服务的进展至关重要。然而,调查估计可能存在无回应偏差。本文主要评估了临床预防服务自我管理问卷(PSAQ)调查中六项利用率估计中无反应偏倚的可能性。这篇文章强调了几个发现。首先,医疗支出小组调查中报告的合格PSAQ样本与流感疫苗接种和血压检查相关的选择性无反应提供了间接证据,证明PSAQ调查高估了这些服务的利用率。其次,研究发现一些加权类变量与PSAQ反应倾向和调查变量相关。第三,令人惊讶的是,尽管进行了多次调查后调整,但预防性服务利用率的基本加权估计值变化不大,这表明没有实质性的无应答偏差。此外,该研究发现,在不同的访谈模式中,对所选预防性服务问题的回答存在中度到近乎完美的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Economic and Social Measurement
Journal of Economic and Social Measurement Social Sciences-Social Sciences (all)
CiteScore
1.60
自引率
0.00%
发文量
4
期刊介绍: The Journal of Economic and Social Measurement (JESM) is a quarterly journal that is concerned with the investigation of all aspects of production, distribution and use of economic and other societal statistical data, and with the use of computers in that context. JESM publishes articles that consider the statistical methodology of economic and social science measurements. It is concerned with the methods and problems of data distribution, including the design and implementation of data base systems and, more generally, computer software and hardware for distributing and accessing statistical data files. Its focus on computer software also includes the valuation of algorithms and their implementation, assessing the degree to which particular algorithms may yield more or less accurate computed results. It addresses the technical and even legal problems of the collection and use of data, legislation and administrative actions affecting government produced or distributed data files, and similar topics. The journal serves as a forum for the exchange of information and views between data producers and users. In addition, it considers the various uses to which statistical data may be put, particularly to the degree that these uses illustrate or affect the properties of the data. The data considered in JESM are usually economic or social, as mentioned, but this is not a requirement; the editorial policies of JESM do not place a priori restrictions upon the data that might be considered within individual articles. Furthermore, there are no limitations concerning the source of the data.
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