Identifying insomnia subtypes from self-reported symptoms severity: A latent class analysis

Introduction: While the high prevalence of insomnia and its association with mental health problems in young populations are well-documented, understanding and treating these co-occurring burdens requires further research into insomnia phenotypes. Data-driven statistical methods have shown promise in classifying insomnia presentations using a wide range of variables, but the potential of commonly used screening tools such as the Insomnia Severity Index (ISI) to identify meaningful clinical subtypes remains underexplored. This study aims to characterise insomnia subtypes in university students based on ISI items. Method: In an online survey, 1255 Italian university students (mean age: 23.4 ± 2.5; 87.9% female) from Sapienza University of Rome completed the ISI, the Pittsburgh Sleep Quality Index (PSQI), and the Depression Anxiety Stress Scale (DASS-21). Latent class analysis (LCA) was performed using the ISI items as indicators to evaluate one to six class solutions. Class differences in sleep quality, depression, anxiety, and stress were assessed using one-way ANOVA. Results: The four-class solution was selected based on a combination of fit indices and theoretical coherence and the classes were named as follows: “no insomnia” (NI; 31.5%), with no relevant sleep complaints; “high insomnia risk” (HI; 17.9%), showing severe nighttime and daytime insomnia symptoms; “subthreshold insomnia” (SI; 37.2%), displaying moderate nighttime symptoms and sleep dissatisfaction; “daytime symptoms only” (DS; 13.4%), featuring pronounced sleep dissatisfaction and daytime dysfunction without significant nighttime disturbance. The HI class had worse sleep quality and higher psychological distress than all other classes. NI members had the best overall condition, with SI and DS occupying intermediate positions. Notably, SI and DS did not differ significantly in sleep latency and duration, sleep disturbances, medication use, or anxiety, whereas DS had worse sleep quality and higher levels of daytime dysfunction, depression, and stress. Conclusion: LCA identified four insomnia subtypes based on ISI items scores, delineating a spectrum from no insomnia symptoms to high risk, including a profile characterised predominantly by daytime symptoms. The association of greater insomnia severity with impaired sleep and mental health, alongside the notable burden of daytime symptoms, may inform the development of tailored interventions. Future research should validate these subtypes in different clinical settings.