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问卷发放方式会对数据质量产生严重影响。

Mode of questionnaire administration can have serious effects on data quality.

作者信息

Bowling Ann

机构信息

Department of Primary Care and Population Sciences, University College London, Hampstead Campus, Rowland Hill Street, London NW3 2PF, UK.

出版信息

J Public Health (Oxf). 2005 Sep;27(3):281-91. doi: 10.1093/pubmed/fdi031. Epub 2005 May 3.

Abstract

BACKGROUND

One of the main primary data collection instruments in social, health and epidemiological research is the survey questionnaire. Modes of data collection by questionnaire differ in several ways, including the method of contacting respondents, the medium of delivering the questionnaire to respondents, and the administration of the questions. These are likely to have different effects on the quality of the data collected.

METHODS

This paper is based on a narrative review of systematic and non-systematic searches of the literature on the effects of mode of questionnaire administration on data quality.

RESULTS

Within different modes of questionnaire administration, there were many documented potential, biasing influences on the responses obtained. These were greatest between different types of mode (e.g. self-administered versus interview modes), rather than within modes. It can be difficult to separate out the effects of the different influences, at different levels.

CONCLUSIONS

The biasing effects of mode of questionnaire administration has important implications for research methodology, the validity of the results of research, and for the soundness of public policy developed from evidence using questionnaire-based research. All users of questionnaires need to be aware of these potential effects on their data.

摘要

背景

调查问卷是社会、健康和流行病学研究中主要的原始数据收集工具之一。通过问卷进行数据收集的方式在多个方面存在差异,包括联系受访者的方法、向受访者发放问卷的媒介以及问题的管理方式。这些因素可能会对所收集数据的质量产生不同影响。

方法

本文基于对有关问卷发放方式对数据质量影响的文献进行系统和非系统检索的叙述性综述。

结果

在不同的问卷发放方式中,有许多文献记载的对所获回答存在潜在的、有偏差的影响。这些影响在不同类型的方式(如自填式与访谈式)之间最为显著,而非在同一方式内。在不同层面上区分不同影响的效果可能会很困难。

结论

问卷发放方式的偏差效应对于研究方法、研究结果的有效性以及基于问卷研究证据制定的公共政策的合理性具有重要意义。所有问卷使用者都需要意识到这些因素对其数据可能产生的潜在影响。

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