PDF(Pubmed)
Abstract：
Measuring cognition in an aging populabtion is a public health priority. A move towards survey measurement via the web (as opposed to phone or in-person) is cost-effective but challenging as it may induce bias in cognitive measures. We examine this possibility using an experiment embedded in the 2018 wave of data collection for the U.S. Health and Retirement Study (HRS).
We utilize techniques from multiple group item response theory to assess the effect of survey mode on performance on the HRS cognitive measure. We also study the problem of attrition by attempting to predict dropout and via approaches meant to minimize bias in subsequent inferences due to attrition.
We find evidence of an increase in scores for HRS respondents who are randomly assigned to the web-based mode of data collection in 2018. Web-based respondents score higher in 2018 than experimentally matched phone-based respondents, and they show much larger gains relative to 2016 performance and subsequently larger declines in 2020. The differential in favor of web-based responding is observed across all items, but is most pronounced for the Serial 7 task and numeracy items. Due to the relative ease of the web-based mode, we suggest a cutscore of 12 being used to indicate CIND (cognitively impaired but not demented) status when using the web-based version rather than 11.
The difference in mode may be nonignorable for many uses of the HRS cognitive measure. In particular, it may require reconsideration of some cutscore-based approaches to identify impairment.
We utilize techniques from multiple group item response theory to assess the effect of survey mode on performance on the HRS cognitive measure. We also study the problem of attrition by attempting to predict dropout and via approaches meant to minimize bias in subsequent inferences due to attrition.
We find evidence of an increase in scores for HRS respondents who are randomly assigned to the web-based mode of data collection in 2018. Web-based respondents score higher in 2018 than experimentally matched phone-based respondents, and they show much larger gains relative to 2016 performance and subsequently larger declines in 2020. The differential in favor of web-based responding is observed across all items, but is most pronounced for the Serial 7 task and numeracy items. Due to the relative ease of the web-based mode, we suggest a cutscore of 12 being used to indicate CIND (cognitively impaired but not demented) status when using the web-based version rather than 11.
The difference in mode may be nonignorable for many uses of the HRS cognitive measure. In particular, it may require reconsideration of some cutscore-based approaches to identify impairment.
摘要：
目的：测量老龄化人口的认知是公共卫生的优先事项。通过网络（而不是电话或面对面）进行调查测量是具有成本效益的，但具有挑战性，因为它可能会引起认知测量的偏见。我们使用2018年美国健康与退休研究（HRS）数据收集浪潮中的一项实验来检验这种可能性。
方法：我们利用多组项目反应理论的技术来评估调查模式对HRS认知测量表现的影响。我们还通过尝试预测辍学并通过旨在最大程度地减少由于减员而导致的后续推论中的偏差的方法来研究减员问题。
结果：我们发现证据表明，2018年被随机分配到基于网络的数据收集模式的HRS受访者的分数有所提高。基于网络的受访者在2018年的得分高于基于电话的受访者，与2016年相比，它们表现出更大的增长，随后在2020年表现出更大的下降。在所有项目中都观察到支持基于网络的响应的偏见，但最明显的是串行7任务和算术项目。由于基于Web的模式相对容易，我们建议在使用基于网络的版本时,使用12分而不是11分来指示CIND(认知受损但未痴呆)状态.
结论：对于HRS认知测量的许多用途，模式差异可能是不可忽略的。特别是,它可能需要重新考虑一些基于cutscore的方法来识别损害。
方法：我们利用多组项目反应理论的技术来评估调查模式对HRS认知测量表现的影响。我们还通过尝试预测辍学并通过旨在最大程度地减少由于减员而导致的后续推论中的偏差的方法来研究减员问题。
结果：我们发现证据表明，2018年被随机分配到基于网络的数据收集模式的HRS受访者的分数有所提高。基于网络的受访者在2018年的得分高于基于电话的受访者，与2016年相比，它们表现出更大的增长，随后在2020年表现出更大的下降。在所有项目中都观察到支持基于网络的响应的偏见，但最明显的是串行7任务和算术项目。由于基于Web的模式相对容易，我们建议在使用基于网络的版本时,使用12分而不是11分来指示CIND(认知受损但未痴呆)状态.
结论：对于HRS认知测量的许多用途，模式差异可能是不可忽略的。特别是,它可能需要重新考虑一些基于cutscore的方法来识别损害。
