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Assessing distress in the community: psychometric properties and crosswalk comparison of eight measures of psychological distress

Published online by Cambridge University Press:  02 October 2017

P. J. Batterham*
Affiliation:
Centre for Mental Health Research, The Australian National University, Canberra, Australia
M. Sunderland
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use, University of New South Wales, Sydney, Australia
T. Slade
Affiliation:
NHMRC Centre of Research Excellence in Mental Health and Substance Use, University of New South Wales, Sydney, Australia
A. L. Calear
Affiliation:
Centre for Mental Health Research, The Australian National University, Canberra, Australia
N. Carragher
Affiliation:
Office of Medical Education, University of New South Wales, Sydney, NSW, Australia
*
Author for correspondence: P. J. Batterham, E-mail: [email protected]

Abstract

Background

Many measures are available for measuring psychological distress in the community. Limited research has compared these scales to identify the best performing tools. A common metric for distress measures would enable researchers and clinicians to equate scores across different measures. The current study evaluated eight psychological distress scales and developed crosswalks (tables/figures presenting multiple scales on a common metric) to enable scores on these scales to be equated.

Methods

An Australian online adult sample (N = 3620, 80% female) was administered eight psychological distress measures: Patient Health Questionnaire-4, Kessler-10/Kessler-6, Distress Questionnaire-5 (DQ5), Mental Health Inventory-5, Hopkins Symptom Checklist-25 (HSCL-25), Self-Report Questionnaire-20 (SRQ-20) and Distress Thermometer. The performance of each measure in identifying DSM-5 criteria for a range of mental disorders was tested. Scale fit to a unidimensional latent construct was assessed using Confirmatory Factor Analysis (CFA). Finally, crosswalks were developed using Item Response Theory.

Results

The DQ5 had optimal performance in identifying individuals meeting DSM-5 criteria, with adequate fit to a unidimensional construct. The HSCL-25 and SRQ-20 also had adequate fit but poorer specificity and/or sensitivity than the DQ5 in identifying caseness. The unidimensional CFA of the combined item bank for the eight scales showed acceptable fit, enabling the creation of crosswalk tables.

Conclusions

The DQ5 had optimal performance in identifying risk of mental health problems. The crosswalk tables developed in this study will enable rapid conversion between distress measures, providing more efficient means of data aggregation and a resource to facilitate interpretation of scores from multiple distress scales.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2017 

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