Cited by 376Psychological Testing and AssessmentAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesMental Health Treatment and Access

A Self-Report Scale to Help Make Psychiatric Diagnoses: The Psychiatric Diagnostic Screening Questionnaire

Open access
Zimmerman, Mark, Mattia, Jill I.·2001·Archives of General Psychiatry

Abstract

BACKGROUND: The Psychiatric Diagnostic Screening Questionnaire (PDSQ) is a brief, psychometrically strong, self-report scale designed to screen for the most common DSM-IV Axis I disorders encountered in outpatient mental health settings. In the present report, we describe the diagnostic performance (sensitivity, specificity, and positive and negative predictive values) of the PDSQ in an outpatient setting. METHODS: Six hundred thirty psychiatric outpatients presenting for treatment were evaluated with the Structured Clinical Interview for DSM-IV after completing the PDSQ. Patients arrived approximately 20 minutes before the scheduled time of the appointment to complete the scale. Diagnostic raters were blind to responses on the scale. RESULTS: The PDSQ's subscales' diagnostic performance varied in a predictable manner according to the cutoff score-as the threshold for case identification increased, subscale sensitivity decreased and specificity increased. Mean subscale sensitivities of 80%, 85%, and 90% resulted in mean subscale specificities of 78%, 73%, and 66%, respectively, and negative predictive values of 95%, 96%, and 97%. Receiver operating curves were determined for each subscale and all areas under the curve were significant. CONCLUSIONS: The PDSQ is a diagnostic aid designed to be used in clinical practice to facilitate the efficiency of conducting initial diagnostic evaluations. From a clinical perspective, it is most important that a diagnostic aid have good sensitivity, so that most cases are detected, and high negative predictive value, so that most noncases on the measure are indeed noncases. Our results indicate that most of the PDSQ subscales were able to achieve this goal.

Integrity signals

Registry

Crossref · 10.1001/archpsyc.58.8.787

Cites

102 of 102 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cites

Flagged first, then by citations

2 of the 104 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Zimmerman, M., & Mattia, J. I.
Affiliations
Brown University (US)
Venue
Archives of General Psychiatry
Published
2001-08-01
Volume
58
Issue
8
Pages
787
ISSN
0003-990X (ISSN-L)
OpenAlex
W2082866684
Cited by
375
References
104
Citations by year
2026: 5 · 2025: 14 · 2024: 13 · 2023: 11 · 2022: 17 · 2021: 18 · 2020: 11 · 2019: 14 · 2018: 12 · 2017: 20 · 2016: 22 · 2015: 14 · 2014: 19 · 2013: 17 · 2012: 18
FWCI
12.45
Type
journal article
Language
en
Open access
Locations
  • Archives of General Psychiatry (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute of Mental Health (MH-56404)
Topics
  • Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
  • Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
Keywords
psychiatric diagnosis, sensitivity and specificity, negative predictive value, cut-off values, receiver operating characteristic, outpatient mental health
MeSH terms
Adult, Ambulatory Care, Mental Disorders, Female, Humans, Male, Personality Inventory, Predictive Value of Tests, Psychiatric Status Rating Scales, Psychometrics, Surveys and Questionnaires, ROC Curve, Sensitivity and Specificity

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review