We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure [email protected]
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
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.
Recommend this
Email your librarian or administrator to recommend adding this to your organisation's collection.