Factor Mixture Modeling of the Insomnia Severity Index among Psychology Clinic Outpatients

Insomnia symptoms are common among individuals with psychiatric disorders, and associated with increased symptom severity. However, the Insomnia Severity Index (ISI) has rarely been psychometrically evaluated in a psychiatric sample. Furthermore, the latent structure of the ISI has not been evaluated using factor mixture modeling, which improves upon prior analytic techniques by integrating factor structure and including exogenous variables. Thus, the current study used factor mixture modeling to test the latent structure of the ISI among two samples of psychology clinic outpatients (Ns = 366 and 331). The ISI was best represented with a three-class structure representing “no or minimal,” “moderate,” and “severe” insomnia symptoms, with significantly escalating symptoms of depression, anxiety, and posttraumatic stress across these classes. Clinical cut-scores for the “severe” class were also derived using receiver operating curve analyses. Implications for theoretical conceptualization of insomnia among those with psychiatric disorders and clinical implications are discussed.