The empirical identification of insomnia subtypes: A cluster analytic approach

Jack D. Edinger, Ana I. Fins, John M. Goeke, Donna K. McMillan, Tracey L. Gersh, Andrew D. Krystal, William Vaughn McCall

Research output: Contribution to journalArticle

34 Citations (Scopus)

Abstract

Over the past 15 years, there has been considerable debate concerning the extent to which insomnia patients can be classified into diagnostic subtypes. Despite this debate, relatively little research has been conducted to empirically determine whether naturally occurring insomnia subtypes might be identified within populations of sleep clinic patients. In the current study we used a hierarchical cluster analysis to empirically identify subtypes among a mixed group of normal sleepers and the insomnia outpatients who presented to our sleep center over the past decade. Using factor- analytically derived composite variables that summarized data obtained from sleep history questionnaires and polysomnographic monitoring, this clustering procedure resulted in the identification of 14 subgroups that varied between four and 34 patients/subjects in size. Subsequently, subgroup mean scores for the composite variables used in the clustering procedure were used to construct profiles for each of the 14 clusters. A multivariate profile analysis, employed to elucidate subgroup differences, showed that these cluster profiles differed in terms of their configural shapes, average elevations, and degrees of interscale differences. Furthermore, both DSM- III-R (American Psychiatric Association) and International Classification of Sleep Disorders (ICSD) insomnia diagnoses, assigned independent of cluster findings, suggested that these subtypes differed significantly in regard to their diagnostic compositions. Nevertheless, a far-from-perfect concordance was observed between such clinically assigned diagnoses and cluster group membership. In fact, many of the empirically identified groups were composed of various DSM-III-R and/or ICSD diagnostic subtypes. These results provided only partial support for current DSM and ICSD insomnia categories. However, our results support the existence of multiple, clinically discrete insomnia subtypes and provide information that may be useful in future revisions of current insomnia nosologies.

Original languageEnglish (US)
Pages (from-to)398-411
Number of pages14
JournalSleep
Volume19
Issue number5
StatePublished - Aug 16 1996
Externally publishedYes

Fingerprint

Sleep Initiation and Maintenance Disorders
Cluster Analysis
Sleep
Diagnostic and Statistical Manual of Mental Disorders
Outpatients
Multivariate Analysis
Research
Population
Sleep Wake Disorders

Keywords

  • Cluster analysis
  • Diagnosis
  • Insomnia

ASJC Scopus subject areas

  • Clinical Neurology
  • Physiology (medical)

Cite this

Edinger, J. D., Fins, A. I., Goeke, J. M., McMillan, D. K., Gersh, T. L., Krystal, A. D., & McCall, W. V. (1996). The empirical identification of insomnia subtypes: A cluster analytic approach. Sleep, 19(5), 398-411.

The empirical identification of insomnia subtypes : A cluster analytic approach. / Edinger, Jack D.; Fins, Ana I.; Goeke, John M.; McMillan, Donna K.; Gersh, Tracey L.; Krystal, Andrew D.; McCall, William Vaughn.

In: Sleep, Vol. 19, No. 5, 16.08.1996, p. 398-411.

Research output: Contribution to journalArticle

Edinger, JD, Fins, AI, Goeke, JM, McMillan, DK, Gersh, TL, Krystal, AD & McCall, WV 1996, 'The empirical identification of insomnia subtypes: A cluster analytic approach', Sleep, vol. 19, no. 5, pp. 398-411.
Edinger JD, Fins AI, Goeke JM, McMillan DK, Gersh TL, Krystal AD et al. The empirical identification of insomnia subtypes: A cluster analytic approach. Sleep. 1996 Aug 16;19(5):398-411.
Edinger, Jack D. ; Fins, Ana I. ; Goeke, John M. ; McMillan, Donna K. ; Gersh, Tracey L. ; Krystal, Andrew D. ; McCall, William Vaughn. / The empirical identification of insomnia subtypes : A cluster analytic approach. In: Sleep. 1996 ; Vol. 19, No. 5. pp. 398-411.
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