Previous research has shown that long surveys negatively impact response rate and can negatively impact the quality of the data collected through respondent fatigue. Several solutions have been tried including survey design, incentivizing respondents, esthetically enhancing surveys, infusing secondary data and shortening the scales; however, these actions create their own problems that further impact the quality of data. The purpose of this paper is to illustrate the use of a modified version of a commonly used method in medical research, Randomized, Multicenter, Parallel-Arm Research Design. This methodology is proposed as a solution to lengthy surveys in social science research for specific types of applications. Using a typology research example, a survey with 1020+ items was divided (into three parallel arms) using this methodology, given to different respondents (randomly across multiple centers), later recombined and analyzed. Exploratory results demonstrate the potential of the methodology for use in social science research. The most critical element to ensure successful use of this methodology is the creation of relevant inclusion criteria for the samples of interest.

先前的研究表明，长时间的调查会对响应率产生负面影响，并可能对通过受访者疲劳收集的数据质量产生负面影响。已经尝试了几种解决方案，包括调查设计、激励受访者、美化调查、注入二手数据和缩短规模；然而，这些行动会产生自身的问题，进一步影响数据质量。本文的目的是说明在医学研究、随机、多中心、平行臂研究设计中使用一种常用方法的修改版本。这种方法被提议作为针对特定类型应用程序的社会科学研究中冗长调查的解决方案。使用类型学研究示例，使用此方法将包含 1020 多个项目的调查分为（分为三个平行臂），给不同的受访者（随机跨多个中心），然后重新组合和分析。探索性结果证明了该方法在社会科学研究中的应用潜力。确保成功使用此方法的最关键因素是为感兴趣的样本创建相关的包含标准。