The Development of a Rapid Classification Scale for Sleep Quality in Community-Dwelling Older Adults – The Yilan Study, Taiwan

Abstract

Hsi-Chung Chen,1,2 Nai-Wei Hsu,3– 5 Po-Jung Pan,6 Po-Hsiu Kuo,1,7 Meng-Yueh Chien,8 Pesus Chou9 1Department of Psychiatry, National Taiwan University Hospital, Taipei, Taiwan; 2Center of Sleep Disorders, National Taiwan University Hospital, Taipei, Taiwan; 3Division of Cardiology, Department of Internal Medicine, National Yang-Ming Chiao Tung University Hospital, Yilan, Taiwan; 4Department of Medicine, School of Medicine, National Yang-Ming Chiao Tung University, Taipei, Taiwan; 5Public Health Bureau of Yilan County, Yilan, Taiwan; 6Department of Physical Medicine and Rehabilitation & Community Medicine Center, National Yang-Ming Chiao Tung University Hospital, Yilan, Taiwan; 7Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan; 8College of Medicine, National Taiwan University and the Physical Therapy Center of National Taiwan University Hospital, Taipei, Taiwan; 9Community Medicine Research Center & Institute of Public Health, National Yang-Ming Chiao Tung University, Taipei, TaiwanCorrespondence: Hsi-Chung ChenDepartment of Psychiatry, National Taiwan University Hospital, No. 7 Chung San South Road, Taipei, 10002, TaiwanTel [phone] ext. 66787Fax [phone]Email [email protected]: Poor sleep quality is prevailing, deleterious, but heterogeneous in older adults. This study aimed to develop a simplified instrument to screen and classify poor sleep quality in community-dwelling older adults, by which stepped care with needs-based interventions could be implemented.Methods: Cohorts of adults aged 65 years and older were used to develop the Rapid Classification Scale for Sleep Quality (RCSSQ). Poor sleep quality was defined with the Pittsburgh Sleep Quality Index (PSQI). Established subgroups of poor sleep quality in the development dataset (n = 2622) were used as the criterion standard. Two independent validation datasets (n = 964 and 193, respectively) were used to examine the external validity. Questions in the PSQI were examined by the stepwise multinomial logistic regressions to determine the optimal numbers of items in the RCSSQ. On the premise of item parsimony and instrument validity, the optimal combination of reduced items was determined.Results: In the development dataset, the 4-item RCSSQ (RCSSQ-4) was the optimal predictive model. In terms of internal validity, the accuracy rates to identify PSQI-defined poor sleep quality and its subgroups in the developmental dataset by the RCSSQ-4 were 89.0% and 79.9%, respectively. Meanwhile, the RCSSQ-4 also had good external validity in the validation datasets to detect PSQI-defined poor sleep quality (accuracy rates: 89.1– 90.7%). Furthermore, the profiles of PSQI component scores and comorbid conditions for the predicted subgroups in the validation dataset were comparable with the criterion standard.Conclusion: The RCSSQ-4 is a valid instrument for screening and subgrouping poor sleep quality in community-dwelling older adults. The RCSSQ-4 may help guide tailored interventions under the context of stepped care in the community.Keywords: older adults, screen, sleep quality, subgroup, scale, the Yilan study

Keywords

• older adults
• screen
• sleep quality
• subgroup
• scale
• the yilan study