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Validity and reliability of the Brief Insomnia Questionnaire in the general population in Hong Kong

  • Ka Fai Chung
  • , Wing Fai Yeung
  • , Fiona Yan Yee Ho
  • , Lai Ming Ho
  • , Kam Ping Yung
  • , Yee Man Yu
  • , Chi Wa Kwok

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

Objectives: The Brief Insomnia Questionnaire (BIQ) was first validated in the U.S. for insomnia disorders according to the Diagnostic and Statistical Manual, Fourth Edition, Text Revision (DSM-IV-TR), International Classification of Diseases, Tenth Edition (ICD-10) and research diagnostic criteria/International Classification of Sleep Disorders, Second Edition (RDC/ICSD-2). We aimed to determine the validity and reliability of a Hong Kong Chinese version of the BIQ to derive the DSM-5 in addition to other insomnia diagnoses in a general population sample. Methods: Probability subsamples of population-based epidemiological survey respondents (n. = 2011) completed test-retest (n. = 120) and clinical reappraisal (n. = 176) interviews. Results: Short-term test-retest reliability was moderate for most BIQ items (Pearson r. >. 0.40), except for the number of nights with problems staying asleep, amount of time awake, duration of sleep problems and sleep onset latency. The areas under the receiver operating characteristic curve for the DSM-IV-TR, DSM-5, ICD-10 and RDC/ICSD-2 insomnia disorder ranged from 0.76 to 0.86, indicating high individual-level concordance between BIQ and clinical-interview diagnoses. The use of super-normal control and BIQ symptom-level data further improves the diagnostic concordance. Prevalence estimates based on the BIQ dichotomous classification were comparable with estimates based on clinical interviews for the DSM-5, RDC/ICSD-2 and any of the DSM-IV-TR, ICD-10 and RDC/ICSD-2 insomnia disorders. Conclusion: The Hong Kong Chinese version of the BIQ generates accurate prevalence estimates for insomnia disorders in the general population. Modification of the BIQ scoring algorithms and use of trained interviewers may further improve its diagnostic performance.
Original languageEnglish
Pages (from-to)374-379
Number of pages6
JournalJournal of Psychosomatic Research
Volume76
Issue number5
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Diagnosis
  • DSM-5
  • DSM-IV-TR
  • ICD-10
  • ICSD-2
  • Insomnia

ASJC Scopus subject areas

  • Clinical Psychology
  • Psychiatry and Mental health

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