1 Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada 2 Centre for Evaluation of Medicines, McMaster University, Hamilton, Ontario, Canada 3 Health Policy and Management, Johns Hopkins University, Bloomberg School of Public Health, Baltimore, Maryland, USA 4 Health Preference Assessment, RTI Health Solutions, Research Triangle Park, North Carolina, USA.
Patient. 2010 Dec 1;3(4):249-56. doi: 10.2165/11539650-000000000-00000.
Despite the increased popularity of conjoint analysis in health outcomes research, little is known about what specific methods are being used for the design and reporting of these studies. This variation in method type and reporting quality sometimes makes it difficult to assess substantive findings. This review identifies and describes recent applications of conjoint analysis based on a systematic review of conjoint analysis in the health literature. We focus on significant unanswered questions for which there is neither compelling empirical evidence nor agreement among researchers.We searched multiple electronic databases to identify English-language articles of conjoint analysis applications in human health studies published since 2005 through to July 2008. Two independent reviewers completed the detailed data extraction, including descriptive information, methodological details on survey type, experimental design, survey format, attributes and levels, sample size, number of conjoint scenarios per respondent, and analysis methods. Review articles and methods studies were excluded. The detailed extraction form was piloted to identify key elements to be included in the database using a standardized taxonomy.We identified 79 conjoint analysis articles that met the inclusion criteria. The number of applied studies increased substantially over time in a broad range of clinical applications, cancer being the most frequent. Most used a discrete-choice survey format (71%), with the number of attributes ranging from 3 to 16. Most surveys included 6 attributes, and 73% presented 7-15 scenarios to each respondent. Sample size varied substantially (minimum = 13, maximum = 1258), with most studies (38%) including between 100 and 300 respondents. Cost was included as an attribute to estimate willingness to pay in approximately 40% of the articles across all years.Conjoint analysis in health has expanded to include a broad range of applications and methodological approaches. Although we found substantial variation in methods, terminology, and presentation of findings, our observations on sample size, the number of attributes, and number of scenarios presented to respondents should be helpful in guiding researchers when planning a new conjoint analysis study in health.
尽管联合分析在健康结果研究中的应用越来越普及,但对于这些研究的设计和报告所使用的具体方法知之甚少。由于方法类型和报告质量的差异,有时难以评估实质性发现。本综述通过对健康文献中联合分析的系统评价,确定并描述了最近联合分析的应用。我们专注于那些没有令人信服的经验证据,也没有研究人员达成共识的重大未解决问题。我们搜索了多个电子数据库,以确定自 2005 年至 2008 年 7 月期间在人类健康研究中发表的英文联合分析应用文章。两名独立的评审员完成了详细的数据提取,包括描述性信息、关于调查类型、实验设计、调查格式、属性和水平、样本量、每个受访者的联合场景数量以及分析方法的方法学细节。排除了综述文章和方法研究。使用标准化分类法,通过预试验确定详细提取表中要包括的关键要素。我们确定了 79 篇符合纳入标准的联合分析文章。在广泛的临床应用中,应用研究的数量随着时间的推移大幅增加,其中癌症最为频繁。大多数使用离散选择调查格式(71%),属性数量从 3 到 16 不等。大多数调查包括 6 个属性,73%的调查向每个受访者展示了 7-15 个场景。样本量差异很大(最小值=13,最大值=1258),大多数研究(38%)包括 100-300 名受访者。在所有年份的文章中,约有 40%将成本作为属性纳入,以估计支付意愿。健康中的联合分析已经扩展到包括广泛的应用和方法学方法。尽管我们发现方法、术语和结果呈现存在很大差异,但我们对样本量、属性数量和向受访者呈现的场景数量的观察结果,应有助于指导研究人员在计划健康方面的新联合分析研究时。