失眠症
焦虑
子群分析
医学
危险系数
精神科
心情
心理学
置信区间
内科学
作者
Sijing Chen,Shirley Xin Li,Jihui Zhang,Siu Ping Lam,Joey Wing Yan Chan,Kate Ching Ching Chan,Albert Martin Li,Charles M. Morin,Yun Kwok Wing,Ngan Yin Chan
摘要
Background Previous study has shown that a brief cognitive‐behavioral prevention insomnia program could reduce 71% risk of developing insomnia among at‐risk adolescents. This study aimed to evaluate the differential response to insomnia prevention in subgroups of at‐risk adolescents. Methods Adolescents with a family history of insomnia and subthreshold insomnia symptoms were randomly assigned to a 4‐week insomnia prevention program or nonactive control group. Assessments were conducted at baseline, 1 week, and 6‐ and 12‐month after the intervention. Baseline sleep, daytime, and mood profiles were used to determine different subgroups by using latent class analysis (LCA). Analyses were conducted based on the intention‐to‐treat approach. Results LCA identified three subgroups: (a) insomnia symptoms only, (b) insomnia symptoms with daytime sleepiness and mild anxiety, and (c) insomnia symptoms with daytime sleepiness, mild anxiety, and depression. The incidence rate of insomnia disorder over the 12‐month follow‐up was significantly reduced for adolescents receiving intervention in subgroup 3 compared with the controls (hazard ratio [HR] = 0.37; 95% confidence interval [CI]: 0.13–0.99; p = .049) and marginally for subgroup 2 (HR = 0.14; 95% CI: 0.02–1.08; p = .059). In addition, adolescents who received intervention in subgroups 2 and 3 had a reduced risk of excessive daytime sleepiness (subgroup 2: adjusted OR [AdjOR] = 0.45, 95% CI: 0.23–0.87; subgroup 3: AdjOR = 0.32, 95% CI: 0.13–0.76) and possible anxiety (subgroup 2: AdjOR = 0.47, 95% CI: 0.27–0.82; subgroup 3: AdjOR = 0.33, 95% CI: 0.14–0.78) compared with the controls over the 12‐month follow‐up. Conclusions Adolescents at risk for insomnia can be classified into different subgroups according to their psychological profiles, which were associated with differential responses to the insomnia prevention program. These findings indicate the need for further phenotyping and subgrouping at‐risk adolescents to develop personalized insomnia prevention.
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