Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW, Australia; Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia.
Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, NSW, Australia.
Value Health. 2020 Mar;23(3):289-293. doi: 10.1016/j.jval.2019.10.001. Epub 2019 Nov 27.
Debriefing questions can assess if respondents understand discrete choice experiments (DCEs) and are answering in a way consistent with theories of decision making and utility maximization. Nevertheless, there is limited literature about how often debriefing questions are included or how the results are used in health economics. The aim of this study was to conduct a survey of the frequency, type, and analysis of debriefing questions in health DCEs.
We conducted an online survey of authors of published health DCEs, asking about their use of debriefing questions, including frequency, type, and analysis. We descriptively analyzed the sample characteristics and responses. Free-text questions were analyzed with qualitative thematic analysis.
We received 70 responses (43% response rate), of which 50% reported using debriefing questions. They were most commonly designed to assess difficulty (91%), understanding (49%), and attribute nonattendance (31%) rather than learning effects (3%) or monotonicity (11%). On average, 37% of debriefing questions were analyzed (range, 0% to 69%), and the results were used <50% of the time, usually to exclude respondents or interpret overall results. Researcher experience or confidence with DCEs did not affect their use of debriefing questions.
These results suggest that although half of researchers conducting health DCEs use debriefing questions, many do not analyze, use, or report the responses. Given the additional respondent burden, there is a need for reliable and valid debriefing questions. In the meantime, the inclusion, analysis, and reporting of debriefing questions should be carefully considered before DCE implementation.
解释性问题可评估被调查者是否理解离散选择实验（DCE），以及他们的回答是否符合决策和效用最大化理论。然而，关于解释性问题的使用频率或在健康经济学中如何使用的文献有限。本研究旨在对健康 DCE 中解释性问题的频率、类型和分析进行调查。
我们对已发表的健康 DCE 作者进行了在线调查，询问他们使用解释性问题的情况，包括频率、类型和分析。我们对样本特征和回复进行了描述性分析。对自由文本问题进行了定性主题分析。
我们收到了 70 份回复（43%的回复率），其中 50%的人报告使用了解释性问题。它们最常用于评估难度（91%）、理解（49%）和属性非参与（31%），而不是学习效果（3%）或单调性（11%）。平均而言，37%的解释性问题得到了分析（范围为 0%至 69%），且结果的使用频率不到 50%，通常用于排除被调查者或解释总体结果。研究人员在 DCE 方面的经验或信心并不影响他们使用解释性问题。
这些结果表明，尽管一半的健康 DCE 研究者使用了解释性问题，但许多人并未分析、使用或报告回复。考虑到被调查者的额外负担，需要可靠和有效的解释性问题。同时，在实施 DCE 之前，应仔细考虑解释性问题的纳入、分析和报告。
