Applied nursing research : ANR · 2026
Profiles of sleep hygiene and influencing factors in patients with chronic conditions experiencing sleep disturbance: A latent class analysis.
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Seong Hohyun, Park Jongmin, Yun Jungmi
Аннотация
OBJECTIVES: This study aimed to identify distinct sleep hygiene profiles and their associated factors in a sample of Korean adults with chronic conditions experiencing sleep disturbance.
METHODS: A cross-sectional study was conducted using data from the Korean Genome and Epidemiology Study (KoGES). Participants (n = 488) with at least one chronic condition and a Pittsburgh Sleep Quality Index (PSQI) score > 5 were included. Latent class analysis was used to identify sleep hygiene profiles based on nine self-reported items. Multinomial logistic regression was used to determine factors associated with class membership.
RESULTS: Three distinct profiles were identified: 'Optimal Sleep Hygiene' (66.2%), 'Behaviorally-Driven Disrupted Sleep' (27.7%), and 'High-Risk and Dysregulated Sleep' (6.1%). The 'Behaviorally-Driven' group was significantly associated with current smoking (OR = 16.53, 95% CI: 4.75-57.43), current drinking (OR = 3.78, 95% CI: 1.95-7.32), and male gender (OR = 3.53, 95% CI: 1.42-8.73). The 'High-Risk' group was significantly associated with severe psychosocial distress (OR = 5.38, 95% CI: 1.93-14.97), current smoking (OR = 16.33, 95% CI: 2.71-98.30), and younger age (OR = 0.91, 95% CI: 0.84-0.98).
CONCLUSION: This study identified heterogeneous sleep hygiene profiles among individuals with chronic conditions, revealing that poor sleep hygiene is not a uniform construct. The findings demonstrate that these profiles are linked to distinct risk factors, primarily distinguishing between modifiable behaviors and psychosocial distress. This suggests that interventions must be tailored to the specific drivers of each profile-such as targeting lifestyle for the behaviorally-driven group or addressing psychological factors for the high-risk group-to effectively improve sleep quality in this vulnerable population.
METHODS: A cross-sectional study was conducted using data from the Korean Genome and Epidemiology Study (KoGES). Participants (n = 488) with at least one chronic condition and a Pittsburgh Sleep Quality Index (PSQI) score > 5 were included. Latent class analysis was used to identify sleep hygiene profiles based on nine self-reported items. Multinomial logistic regression was used to determine factors associated with class membership.
RESULTS: Three distinct profiles were identified: 'Optimal Sleep Hygiene' (66.2%), 'Behaviorally-Driven Disrupted Sleep' (27.7%), and 'High-Risk and Dysregulated Sleep' (6.1%). The 'Behaviorally-Driven' group was significantly associated with current smoking (OR = 16.53, 95% CI: 4.75-57.43), current drinking (OR = 3.78, 95% CI: 1.95-7.32), and male gender (OR = 3.53, 95% CI: 1.42-8.73). The 'High-Risk' group was significantly associated with severe psychosocial distress (OR = 5.38, 95% CI: 1.93-14.97), current smoking (OR = 16.33, 95% CI: 2.71-98.30), and younger age (OR = 0.91, 95% CI: 0.84-0.98).
CONCLUSION: This study identified heterogeneous sleep hygiene profiles among individuals with chronic conditions, revealing that poor sleep hygiene is not a uniform construct. The findings demonstrate that these profiles are linked to distinct risk factors, primarily distinguishing between modifiable behaviors and psychosocial distress. This suggests that interventions must be tailored to the specific drivers of each profile-such as targeting lifestyle for the behaviorally-driven group or addressing psychological factors for the high-risk group-to effectively improve sleep quality in this vulnerable population.