Literature DB >> 23117634

Development of a computerized adaptive test for depression.

Robert D Gibbons1, David J Weiss, Paul A Pilkonis, Ellen Frank, Tara Moore, Jong Bae Kim, David J Kupfer.   

Abstract

CONTEXT Unlike other areas of medicine, psychiatry is almost entirely dependent on patient report to assess the presence and severity of disease; therefore, it is particularly crucial that we find both more accurate and efficient means of obtaining that report. OBJECTIVE To develop a computerized adaptive test (CAT) for depression, called the Computerized Adaptive Test-Depression Inventory (CAT-DI), that decreases patient and clinician burden and increases measurement precision. DESIGN Case-control study. SETTING A psychiatric clinic and community mental health center. PARTICIPANTS A total of 1614 individuals with and without minor and major depression were recruited for study. MAIN OUTCOME MEASURES The focus of this study was the development of the CAT-DI. The 24-item Hamilton Rating Scale for Depression, Patient Health Questionnaire 9, and the Center for Epidemiologic Studies Depression Scale were used to study the convergent validity of the new measure, and the Structured Clinical Interview for DSM-IV was used to obtain diagnostic classifications of minor and major depressive disorder. RESULTS A mean of 12 items per study participant was required to achieve a 0.3 SE in the depression severity estimate and maintain a correlation of r = 0.95 with the total 389-item test score. Using empirically derived thresholds based on a mixture of normal distributions, we found a sensitivity of 0.92 and a specificity of 0.88 for the classification of major depressive disorder in a sample consisting of depressed patients and healthy controls. Correlations on the order of r = 0.8 were found with the other clinician and self-rating scale scores. The CAT-DI provided excellent discrimination throughout the entire depressive severity continuum (minor and major depression), whereas the traditional scales did so primarily at the extremes (eg, major depression). CONCLUSIONS Traditional measurement fixes the number of items administered and allows measurement uncertainty to vary. In contrast, a CAT fixes measurement uncertainty and allows the number of items to vary. The result is a significant reduction in the number of items needed to measure depression and increased precision of measurement.

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Year:  2012        PMID: 23117634      PMCID: PMC3551289          DOI: 10.1001/archgenpsychiatry.2012.14

Source DB:  PubMed          Journal:  Arch Gen Psychiatry        ISSN: 0003-990X


  13 in total

1.  Analysis of differential item functioning in the depression item bank from the Patient Reported Outcome Measurement Information System (PROMIS): An item response theory approach.

Authors:  Jeanne A Teresi; Katja Ocepek-Welikson; Marjorie Kleinman; Joseph P Eimicke; Paul K Crane; Richard N Jones; Jin-Shei Lai; Seung W Choi; Ron D Hays; Bryce B Reeve; Steven P Reise; Paul A Pilkonis; David Cella
Journal:  Psychol Sci Q       Date:  2009

2.  Development of a computer-adaptive test for depression (D-CAT).

Authors:  Herbert Fliege; Janine Becker; Otto B Walter; Jakob B Bjorner; Burghard F Klapp; Matthias Rose
Journal:  Qual Life Res       Date:  2005-12       Impact factor: 4.147

3.  The PHQ-9: validity of a brief depression severity measure.

Authors:  K Kroenke; R L Spitzer; J B Williams
Journal:  J Gen Intern Med       Date:  2001-09       Impact factor: 5.128

Review 4.  Meta-analysis of the factor structures of four depression questionnaires: Beck, CES-D, Hamilton, and Zung.

Authors:  Alan B Shafer
Journal:  J Clin Psychol       Date:  2006-01

5.  Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): depression, anxiety, and anger.

Authors:  Paul A Pilkonis; Seung W Choi; Steven P Reise; Angela M Stover; William T Riley; David Cella
Journal:  Assessment       Date:  2011-06-21

6.  The latent symptom structure of the Beck Depression Inventory-II in outpatients with major depression.

Authors:  Lena C Quilty; K Anne Zhang; R Michael Bagby
Journal:  Psychol Assess       Date:  2010-09

7.  Parsing the general and specific components of depression and anxiety with bifactor modeling.

Authors:  Leonard J Simms; Daniel F Grös; David Watson; Michael W O'Hara
Journal:  Depress Anxiety       Date:  2008       Impact factor: 6.505

8.  Using computerized adaptive testing to reduce the burden of mental health assessment.

Authors:  Robert D Gibbons; David J Weiss; David J Kupfer; Ellen Frank; Andrea Fagiolini; Victoria J Grochocinski; Dulal K Bhaumik; Angela Stover; R Darrell Bock; Jason C Immekus
Journal:  Psychiatr Serv       Date:  2008-04       Impact factor: 3.084

9.  Mixture distributions in psychiatric research.

Authors:  R D Gibbons; E Dorus; D G Ostrow; G N Pandey; J M Davis; D L Levy
Journal:  Biol Psychiatry       Date:  1984-07       Impact factor: 13.382

10.  Computerized adaptive measurement of depression: a simulation study.

Authors:  William Gardner; Katherine Shear; Kelly J Kelleher; Kathleen A Pajer; Oommen Mammen; Daniel Buysse; Ellen Frank
Journal:  BMC Psychiatry       Date:  2004-05-06       Impact factor: 3.630

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  57 in total

Review 1.  Annual Research Review: Maternal antidepressant use during pregnancy and offspring neurodevelopmental problems - a critical review and recommendations for future research.

Authors:  Ayesha C Sujan; A Sara Öberg; Patrick D Quinn; Brian M D'Onofrio
Journal:  J Child Psychol Psychiatry       Date:  2018-12-05       Impact factor: 8.982

2.  Validation of Computerized Adaptive Testing in an Outpatient Nonacademic Setting: The VOCATIONS Trial.

Authors:  Eric D Achtyes; Scott Halstead; LeAnn Smart; Tara Moore; Ellen Frank; David J Kupfer; Robert Gibbons
Journal:  Psychiatr Serv       Date:  2015-06-01       Impact factor: 3.084

3.  Depression in Emergency Department Patients and Association With Health Care Utilization.

Authors:  David G Beiser; Charlotte E Ward; Milkie Vu; Neda Laiteerapong; Robert D Gibbons
Journal:  Acad Emerg Med       Date:  2019-04-07       Impact factor: 3.451

4.  Computerized Adaptive Tests for Rapid and Accurate Assessment of Psychopathology Dimensions in Youth.

Authors:  Robert D Gibbons; David J Kupfer; Ellen Frank; Benjamin B Lahey; Brandie A George-Milford; Candice L Biernesser; Giovanna Porta; Tara L Moore; Jong Bae Kim; David A Brent
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2019-08-26       Impact factor: 8.829

5.  Validation of the Computerized Adaptive Test for Mental Health in Primary Care.

Authors:  Andrea K Graham; Alexa Minc; Erin Staab; David G Beiser; Robert D Gibbons; Neda Laiteerapong
Journal:  Ann Fam Med       Date:  2019-01       Impact factor: 5.166

6.  Searching across diagnostic boundaries.

Authors:  Marion Leboyer; Franck Schurhoff
Journal:  Schizophr Bull       Date:  2014-08-05       Impact factor: 9.306

7.  On the structure of personality disorder traits: conjoint analyses of the CAT-PD, PID-5, and NEO-PI-3 trait models.

Authors:  Aidan G C Wright; Leonard J Simms
Journal:  Personal Disord       Date:  2014-01

8.  Addressing Methodologic Challenges and Minimizing Threats to Validity in Synthesizing Findings from Individual-Level Data Across Longitudinal Randomized Trials.

Authors:  Ahnalee Brincks; Samantha Montag; George W Howe; Shi Huang; Juned Siddique; Soyeon Ahn; Irwin N Sandler; Hilda Pantin; C Hendricks Brown
Journal:  Prev Sci       Date:  2018-02

9.  Clinical correlates of subsyndromal depression in African American individuals with psychosis: The relationship with positive symptoms and comorbid substance dependence.

Authors:  Emma E M Knowles; Samuel R Mathias; Godfrey D Pearlson; Jennifer Barrett; Josephine Mollon; Dominique Denbow; Katrina Aberzik; Molly Zatony; David C Glahn
Journal:  Schizophr Res       Date:  2018-10-26       Impact factor: 4.939

10.  Comparisons across depression assessment instruments in adolescence and young adulthood: an item response theory study using two linking methods.

Authors:  Thomas M Olino; Lan Yu; Dana L McMakin; Erika E Forbes; John R Seeley; Peter M Lewinsohn; Paul A Pilkonis
Journal:  J Abnorm Child Psychol       Date:  2013-11
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