Computerized adaptive measurement of depression: A simulation study
Open accessAbstract
BACKGROUND: Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity. METHODS: Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale. RESULTS: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated r =.92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r =.74) than the BDI total score did (r =.70). CONCLUSIONS: Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity.
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Adaptive testing techniques have been shown to reduce the number of necessary items to almost a quarter of that needed in paper versions of questionnaires without any loss of accuracy.
“These “adaptive testing techniques” have been shown to reduce the number of necessary items to almost a quarter of that needed in paper versions of questionnaires [42] without any loss of accuracy.”
From Directions for the International Society for Research on Internet Interventions (ISRII) (2006) · cites this paper as [42]
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References 55 · Cited by 65
Research works printed but not linked: 1
- First MB Spitzer RL Gibbon M Williams JBW Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) 1997 Washington, DC, American Psychiatric Press
- Authors
- Gardner, W., Shear, K., Kelleher, K. J., Pajer, K. A., Mammen, O., Buysse, D., & Frank, E.
- Affiliations
- The Ohio State University (US)
- University of Pittsburgh (US)
- Corresponding author
- Gardner, William
- Venue
- BMC Psychiatry
- Published
- 2004-05-06
- Volume
- 4
- Issue
- 1
- Pages
- 13-13
- ISSN
- 1471-244X (ISSN-L)
- PMC
- PMC416483
- OpenAlex
- W2125153636
- Cited by
- 65
- References
- 55
- Citations by year
- 2024: 1 · 2023: 3 · 2022: 3 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 4 · 2017: 5 · 2016: 4 · 2015: 4 · 2014: 1 · 2013: 3 · 2012: 8
- FWCI
- 2.63
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Psychiatry (publishedVersion)
- PubMed Central (publishedVersion, other-oa)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- The Knowledge Bank (The Ohio State University) (submittedVersion)
- Funders
- National Institutes of Health (5r24mh053817-05)
- National Institute of Mental Health (MH 29618, R24MH056848, MH53817, R01MH029618, P30MH030915, MH56848, R37MH029618, MH30915)
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- computerized adaptive testing, depression measurement, Beck Depression Inventory, major depressive episode, depression severity, diagnostic accuracy, Hamilton Depression Rating Scale, severe combined immunodeficiency
- MeSH terms
- Adult, Algorithms, Computer Simulation, Depressive Disorder, Diagnosis, Computer-Assisted, Factor Analysis, Statistical, Female, Humans, Male, Mass Screening, Personality Inventory, Pilot Projects, Psychiatric Status Rating Scales, Psychometrics, Severity of Illness Index, Software, Prevalence, Patient Selection, Area Under Curve, Internet
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