Roberts Tonya J, Saliba Debra
J Gerontol Nurs. 2019 Aug 1;45(8):7-13. doi: 10.3928/00989134-20190709-02.
Nursing homes have shifted from task-focused to person-centered care (PCC) environments. Understanding resident preferences for daily care and activities is fundamental to PCC. Examining resident similarities based on preferences may be useful for group or community-wide PCC planning. The aims of the current study were to group residents according to similarities in preferences and determine the factors that predict membership in these groups. A latent class analysis of resident preferences using data from the Minimum Data Set (N = 244,718) was conducted. Resident function, depression, cognitive impairment, and sociodemographics were used as predictors of class membership. The four-class model showed residents cluster around overall interest or disinterest in having choices about daily care and activities or specific interest in either care or activity preferences. Race and ethnicity, cognitive impairment, and depression predicted class membership. Findings suggest that residents can be grouped by preferences and knowledge of resident group membership could help direct efforts to systematically meet resident preferences. [Journal of Gerontological Nursing, 45(8), 7-13.].
养老院已从以任务为中心的环境转变为以居民为中心的护理（PCC）环境。了解居民对日常护理和活动的偏好是PCC的基础。根据偏好来研究居民之间的相似之处，可能有助于进行群体或社区层面的PCC规划。本研究的目的是根据偏好的相似性对居民进行分组，并确定预测这些组别的成员资格的因素。利用最低数据集（N = 244,718）的数据对居民偏好进行了潜在类别分析。居民功能、抑郁、认知障碍和社会人口统计学特征被用作类别成员资格的预测因素。四类模型显示，居民围绕着对日常护理和活动选择的总体兴趣或无兴趣，或者对护理或活动偏好的特定兴趣而聚集。种族和民族、认知障碍和抑郁可预测类别成员资格。研究结果表明，可以根据偏好对居民进行分组，而了解居民所属的组别有助于指导系统性地满足居民偏好的工作。[《老年护理杂志》，45(8)，7 - 13。]
