Western journal of nursing research · 2024
Latent Profile Analysis of Sleep Quality in Pregnant Women With Gestational Diabetes Mellitus and Its Influencing Factors.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Chen Yanxia, Wang Hui, Yang Yiling, Li Jiale, Luo Tingyu, Wei Huixin, Wei Fengxiang, Chen Weiqiang
Аннотация
BACKGROUND: Sleep problems are prevalent among individuals diagnosed with gestational diabetes mellitus (GDM), significantly impacting their overall quality of life.
OBJECTIVE: This study sought to adopt a person-centered methodology to unveil the latent profiles of sleep quality and identify factors influencing sleep patterns in patients with GDM.
METHODS: The cross-sectional study gathered sociodemographic features, clinical information, sleep problems (Pittsburgh Sleep Quality Index), personality traits (Type D Personality Scale), social support (Perceived Social Support Scale), and self-efficacy (General Self-efficacy Scale). Latent profile analysis was conducted to identify profiles of sleep quality, while multinomial logistic regression was employed to ascertain the factors influencing these identified profiles.
RESULTS: Among the 431 participants, 423 (98.1%) completed the questionnaire, with 53.0% reporting moderate-to-poor sleep quality. This study identified 4 distinct profiles of sleep quality among patients with GDM: the "good sleep quality" group (47.0%), the "poor sleep quality-long sleep duration" group (10.0%), the "moderate sleep quality" group (25.3%), and the "poor sleep quality-short sleep duration" group (17.7%). Individuals with type D personality were associated with the "poor sleep quality-long sleep duration" [odds ratio (OR) = 3.21, P = .005], "moderate sleep quality" (OR = 2.65, P = .003), and "poor sleep quality-short sleep duration" group (OR = 2.31, P = .018). Individuals with a history of GDM were associated with "poor sleep quality-long sleep duration" group (OR = 3.46, P = .005).
CONCLUSIONS: The research revealed significant classification characteristics of sleep quality in patients with GDM, offering valuable insights for tailoring interventions to address distinct subcategories of sleep-related issues.
OBJECTIVE: This study sought to adopt a person-centered methodology to unveil the latent profiles of sleep quality and identify factors influencing sleep patterns in patients with GDM.
METHODS: The cross-sectional study gathered sociodemographic features, clinical information, sleep problems (Pittsburgh Sleep Quality Index), personality traits (Type D Personality Scale), social support (Perceived Social Support Scale), and self-efficacy (General Self-efficacy Scale). Latent profile analysis was conducted to identify profiles of sleep quality, while multinomial logistic regression was employed to ascertain the factors influencing these identified profiles.
RESULTS: Among the 431 participants, 423 (98.1%) completed the questionnaire, with 53.0% reporting moderate-to-poor sleep quality. This study identified 4 distinct profiles of sleep quality among patients with GDM: the "good sleep quality" group (47.0%), the "poor sleep quality-long sleep duration" group (10.0%), the "moderate sleep quality" group (25.3%), and the "poor sleep quality-short sleep duration" group (17.7%). Individuals with type D personality were associated with the "poor sleep quality-long sleep duration" [odds ratio (OR) = 3.21, P = .005], "moderate sleep quality" (OR = 2.65, P = .003), and "poor sleep quality-short sleep duration" group (OR = 2.31, P = .018). Individuals with a history of GDM were associated with "poor sleep quality-long sleep duration" group (OR = 3.46, P = .005).
CONCLUSIONS: The research revealed significant classification characteristics of sleep quality in patients with GDM, offering valuable insights for tailoring interventions to address distinct subcategories of sleep-related issues.