Attribute Development in Health-Related Discrete Choice Experiments: A Systematic Review of Qualitative Methods and Techniques to Inform Quantitative Instruments

IF 4.9 2区 医学 Q1 ECONOMICS
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Abstract

Objectives

This review sought to identify the qualitative methods and techniques that researchers have used in the past decade to develop attributes and inform health-related discrete choice experiments (DCEs) surveys from a patient perspective.

Methods

The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for reporting systematic reviews. An adapted appraisal tool following guidelines for reporting qualitative research for quantitative instruments and criteria for attribute development in DCEs was applied for quality assessment and data extraction. A narrative approach was used to synthesize data. This examination included consideration of issues pertaining to sampling, data collection, data analysis, attribute list reduction, wording, methodological adaptations to capture patient preferences, and testing the pre-experimental design decisions of the DCE survey.

Results

Of 8505 articles identified for abstract screening, 680 were included for full-text screening, 36 of which met the inclusion criteria. Practices to improve methodological robustness included pre-data collection materials to inform instruments, data collection methods specific for decision-making scenarios, purposeful selection of data analysis methods to address the research question, and participants’ involvement in reducing the list of attributes. Examples of methodological adaptations for patients were noted.

Conclusions

DCEs have the potential to become a mixed-method approach in which the qualitative phase informs a reduced list of attributes for a survey, serves the predesign decisions of the experiment by testing trade-offs, overlapping, understandability, face, and content validity and provides explanations of the quantitative results. Establishing guidelines for using qualitative methods for DCE attribute development may help to broadly enhance the methodological robustness of DCEs.
健康相关离散选择实验中的属性开发:定性方法和技术的系统回顾,为定量工具提供参考。
目的:本综述旨在确定研究人员在过去十年中采用的定性方法和技术:本综述旨在确定研究人员在过去十年中采用的定性方法和技术,以便从患者的角度开发与健康相关的离散选择实验 (DCE) 调查的属性和信息:综述遵循 PRISMA 系统综述报告指南。根据定量工具定性研究报告指南和 DCEs 属性开发标准改编的评估工具被用于质量评估和数据提取。采用叙事方法对数据进行综合。审查包括考虑与抽样、数据收集、数据分析、属性列表缩减、措辞、捕捉患者偏好的方法调整以及测试 DCE 调查的前期实验设计决策有关的问题:在经过摘要筛选的 8,505 篇文章中,有 680 篇被纳入全文筛选,其中 36 篇符合纳入标准。提高方法稳健性的做法包括:为工具提供信息的前期数据收集材料、针对决策情景的特定数据收集方法、有目的地选择数据分析方法以解决研究问题,以及让参与者参与减少属性列表。此外,还提到了为患者调整方法的例子:DCE有可能成为一种混合方法,在这种方法中,定性阶段为减少调查的属性清单提供信息,通过测试权衡、重叠、可理解性、面效和内容效度为实验的前期设计决策服务,并为定量结果提供解释。为使用定性方法开发 DCE 属性制定指导原则可能有助于广泛提高 DCE 方法的稳健性。
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来源期刊
Value in Health
Value in Health 医学-卫生保健
CiteScore
6.90
自引率
6.70%
发文量
3064
审稿时长
3-8 weeks
期刊介绍: Value in Health contains original research articles for pharmacoeconomics, health economics, and outcomes research (clinical, economic, and patient-reported outcomes/preference-based research), as well as conceptual and health policy articles that provide valuable information for health care decision-makers as well as the research community. As the official journal of ISPOR, Value in Health provides a forum for researchers, as well as health care decision-makers to translate outcomes research into health care decisions.
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