Latent profile of the insomnia severity index: A longitudinal study

To identify the distinct classification of insomnia symptoms and to explore their association with sleep problems and depression.

Latent profile analysis was used to examine patterns of insomnia symptoms in two samples. Discovery and replication samples comprised 1043 (Mean age at baseline = 18.95 ± 0.93 years, 62.2% females) and 729 (Mean age at baseline = 18.71 ± 1.02 years, 66.4% females) college students, respectively. Participants completed measures of sleep problems (insomnia symptoms, sleep quality, susceptibility to insomnia, perceived consequences of insomnia, dream recall frequency, and percentage of recurring nightmares) and other psychological variables (rumination and depression). Binary logistic regression was used to analyze the effects of different types of insomnia symptoms at baseline on sleep problems and depression two years later.

Four classes of insomnia symptoms were identified, and classified as "non-insomnia" (class 1, 45.7%), "mild subjective symptoms but severe subjective feelings" (class 2, 23.9%), "severe subjective symptoms but mild subjective feelings" (class 3, 22.0%), and "high insomnia risk" (class 4, 8.4%), respectively. Compared with the group classified as non-insomnia group, other classifications significantly predicted insomnia two years later, only class 4 significantly predicted depression, and class 3 significantly predicted susceptibility to insomnia, after adjusting gender, insomnia, depression, and susceptibility to insomnia at baseline.

The findings highlighted the importance of identifying the patterns of insomnia symptoms, and the need for tailored intervention to improve sleep problems. Additionally, when screening for insomnia symptoms, simplified screening using Insomnia Severity Index (ISI) dimensions or items should be considered.