Objective: Research indicates that the rate of insomnia increases with age. Therefore, this study was conducted to determine the factors related to sleep quality and to identify the predictors of sleep quality in the older adult, based on the strategies of self-regulation theory.
Methods and Materials: This cross-sectional study was conducted on 335 older adults from Neishabur city, who were randomly selected in 2024. To collect data, a demographic information checklist, the standard Pittsburgh Sleep Quality Index (PSQI) questionnaire, and a custom-designed questionnaire to measure the strategies of self-regulation theory were used.
Results: The majority of the research participants were women (51%) and married individuals (73%). In terms of education, 70% of the research participants had less than a high school diploma. Additionally, the majority of them (82%) had an underlying medical condition. Sixty-five percent of the research participants had private rooms, while 16% had no bedrooms. The results showed that 70.4% of the older adults did not have good sleep quality. The mean of self-regulation was 81.96 ± 17.26, and the mean score for sleep quality among the older adults was 8.54 ± 4.65. Based on the results, the use of sleeping pills (R=-10.883, P<0.001), age (P<0.001, R= 9.830), presence of underlying diseases (P<0.001, R=5.549), gender (P<0.001, R=5.485), and performance evaluation and judgment (P<0.001, R= 3.249) were identified as predictors of sleep quality. Based on the results, evaluation and judgment of performance were the most effective predictors of sleep quality in older adults (β = -0.274, R² = 0.37, p = 0.001).
Conclusions: Among the strategies of self-regulation theory, evaluation and judgment of performance, goal setting, and self-monitoring were the most effective predictors of sleep quality in older adults. Therefore, it is recommended to design appropriate interventions aimed at empowering older adults to promote their health and improve their sleep quality, focusing on these factors and emphasizing the predictive strategies of self-regulation theory.
Type of Study:
Research |
Subject:
gerontology Received: 2024/09/05 | Accepted: 2024/11/04