Relationships between Loneliness and Occupational Dysfunction in Community-Dwelling Older Adults: A Cross-Sectional Study.

IF 1.3 4区 医学 Q3 REHABILITATION
Daiki Nakashima, Keisuke Fujii, Yuta Kubo, Kyosuke Yorozuya
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Abstract

The study explored cross-sectional associations between loneliness and occupational dysfunction in community-dwelling older adults. Seventy-four older adults (12 men and 62 women; mean age 73.9 ± 8.3 years) completed a questionnaire survey that included the Japanese version of the UCLA Loneliness Scale Version 3 and the Classification and Assessment of Occupational Dysfunction (CAOD). Bayesian statistical modeling was used for a more stable estimation given the small sample. For model selection, we assumed a univariate analysis model of the CAOD (Model 1); a multivariate analysis model, including confounding factors in Model 1 (Model 2); and a multivariate analysis model, including random effects in Model 2 (Model 3). The best model was selected by comparing the widely applicable information criterion (WAIC) and the widely applicable Bayesian information criterion (WBIC) for each model. Bayesian statistics with the dependent variable as "loneliness" showed that the best model used "occupational dysfunction" as the independent variable and included confounding factors and random effects (WAIC = 474.5 and WBIC = 213.1). The best model identified an association between occupational dysfunction and loneliness (odds ratio [OR] = 2.363; 95% Bayesian confidence interval [CI] = 1.105-5.259). This study highlights the role of occupational dysfunction in addition to the risks and related factors reported to date when dealing with loneliness. Therapists could help older adults cope with loneliness by supporting their social participation and improving their occupational dysfunction.

Abstract Image

社区老年人孤独感与职业功能障碍的关系:一项横断面研究。
本研究探讨了社区居住老年人孤独感与职业功能障碍之间的横断面关联。74名老年人(12名男性,62名女性;平均年龄73.9±8.3岁)完成了一份问卷调查,包括日语版UCLA孤独量表第3版和职业功能障碍分类与评估(CAOD)。在样本较小的情况下,采用贝叶斯统计模型进行较为稳定的估计。对于模型选择,我们假设CAOD的单变量分析模型(模型1);多元分析模型,包括模型1中的混杂因素(模型2);多变量分析模型,包括模型2中的随机效应(模型3)。通过比较每个模型的广泛适用信息准则(WAIC)和广泛适用贝叶斯信息准则(WBIC)来选择最佳模型。因变量为“孤独”的贝叶斯统计结果表明,最佳模型以“职业功能障碍”为自变量,包含混杂因素和随机效应(WAIC = 474.5, WBIC = 213.1)。最佳模型确定了职业功能障碍与孤独感之间的关联(优势比[OR] = 2.363;95%贝叶斯置信区间[CI] = 1.105-5.259)。本研究强调了职业功能障碍在处理孤独感时的作用,以及迄今为止报道的风险和相关因素。治疗师可以通过支持老年人的社会参与和改善他们的职业功能障碍来帮助他们应对孤独。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.50
自引率
6.70%
发文量
121
审稿时长
>12 weeks
期刊介绍: Occupational Therapy International is a peer-reviewed journal, publishing manuscripts that reflect the practice of occupational therapy throughout the world. Research studies or original concept papers are considered for publication. Priority for publication will be given to research studies that provide recommendations for evidence-based practice and demonstrate the effectiveness of a specific treatment method. Single subject case studies evaluating treatment effectiveness are also encouraged. Other topics that are appropriate for the journal include reliability and validity of clinical instruments, assistive technology, community rehabilitation, cultural comparisons, health promotion and wellness.
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