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Exploring Patterns in Preferences for Daily Care and Activities Among Nursing Home Residents

机译:探索疗养院院长的偏好偏好和养老院居民的活动

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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.
机译:养老院已从任务转移到以人为本的护理(PCC)环境。了解日常护理和活动的居民偏好是PCC的基础。根据偏好检查驻地相似度可能对组或社区范围的PCC规划有用。目前研究的目的是根据偏好中的相似性对居民进行分组,并确定预测这些群体成员资格的因素。进行了使用来自最小数据集(n = 244,718)的数据的居民偏好的潜在类分析。居民函数,抑郁,认知障碍和社会主干被用作阶级成员的预测因素。四类模型显示居民集群周围的整体兴趣或无聊,在有关于日常护理和活动或治疗或活动偏好的特定兴趣方面的选择。种族和种族,认知障碍和抑郁症阶级成员资格。调查结果表明,居民可以通过偏好和知识进行分组,并对居民群体成员的知识有助于直接努力系统地满足居民偏好。

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