Literature DB >> 23945443

The computerized adaptive diagnostic test for major depressive disorder (CAD-MDD): a screening tool for depression.

Robert D Gibbons1, Giles Hooker, Matthew D Finkelman, David J Weiss, Paul A Pilkonis, Ellen Frank, Tara Moore, David J Kupfer.   

Abstract

OBJECTIVE: To develop a computerized adaptive diagnostic screening tool for depression that decreases patient and clinician burden and increases sensitivity and specificity for clinician-based DSM-IV diagnosis of major depressive disorder (MDD).
METHOD: 656 individuals with and without minor and major depression were recruited from a psychiatric clinic and a community mental health center and through public announcements (controls without depression). The focus of the study was the development of the Computerized Adaptive Diagnostic Test for Major Depressive Disorder (CAD-MDD) diagnostic screening tool based on a decision-theoretical approach (random forests and decision trees). The item bank consisted of 88 depression scale items drawn from 73 depression measures. Sensitivity and specificity for predicting clinician-based Structured Clinical Interview for DSM-IV Axis I Disorders diagnoses of MDD were the primary outcomes. Diagnostic screening accuracy was then compared to that of the Patient Health Questionnaire-9 (PHQ-9).
RESULTS: An average of 4 items per participant was required (maximum of 6 items). Overall sensitivity and specificity were 0.95 and 0.87, respectively. For the PHQ-9, sensitivity was 0.70 and specificity was 0.91.
CONCLUSIONS: High sensitivity and reasonable specificity for a clinician-based DSM-IV diagnosis of depression can be obtained using an average of 4 adaptively administered self-report items in less than 1 minute. Relative to the currently used PHQ-9, the CAD-MDD dramatically increased sensitivity while maintaining similar specificity. As such, the CAD-MDD will identify more true positives (lower false-negative rate) than the PHQ-9 using half the number of items. Inexpensive (relative to clinical assessment), efficient, and accurate screening of depression in the settings of primary care, psychiatric epidemiology, molecular genetics, and global health are all direct applications of the current system. © Copyright 2013 Physicians Postgraduate Press, Inc.

Entities:  

Mesh:

Year:  2013        PMID: 23945443      PMCID: PMC3977175          DOI: 10.4088/JCP.12m08338

Source DB:  PubMed          Journal:  J Clin Psychiatry        ISSN: 0160-6689            Impact factor:   4.384


  4 in total

1.  Applying computerized adaptive testing to the CES-D scale: a simulation study.

Authors:  Niels Smits; Pim Cuijpers; Annemieke van Straten
Journal:  Psychiatry Res       Date:  2011-01-03       Impact factor: 3.222

2.  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

3.  Sources of unreliability in depression ratings.

Authors:  Kenneth A Kobak; Brianne Brown; Ian Sharp; Hollie Levy-Mack; Kurrie Wells; Felice Ockun; Felice Okum; Janet B W Williams
Journal:  J Clin Psychopharmacol       Date:  2009-02       Impact factor: 3.153

4.  Development of a computerized adaptive test for depression.

Authors:  Robert D Gibbons; David J Weiss; Paul A Pilkonis; Ellen Frank; Tara Moore; Jong Bae Kim; David J Kupfer
Journal:  Arch Gen Psychiatry       Date:  2012-11
  4 in total
  22 in total

1.  Prediction of remission in obsessive compulsive disorder using a novel machine learning strategy.

Authors:  Kathleen D Askland; Sarah Garnaat; Nicholas J Sibrava; Christina L Boisseau; David Strong; Maria Mancebo; Benjamin Greenberg; Steve Rasmussen; Jane Eisen
Journal:  Int J Methods Psychiatr Res       Date:  2015-05-21       Impact factor: 4.035

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.  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

5.  Developmental approach to prevent adolescent suicides: research pathways to effective upstream preventive interventions.

Authors:  Peter A Wyman
Journal:  Am J Prev Med       Date:  2014-09       Impact factor: 5.043

6.  Improving the Evaluation of Adult Mental Disorders in the Criminal Justice System With Computerized Adaptive Testing.

Authors:  Robert D Gibbons; Justin D Smith; C Hendricks Brown; Mary Sajdak; Nneka Jones Tapia; Andrew Kulik; Matthew W Epperson; John Csernansky
Journal:  Psychiatr Serv       Date:  2019-07-24       Impact factor: 3.084

Review 7.  Without Wasting a Word: Extreme Improvements in Efficiency and Accuracy Using Computerized Adaptive Testing for Mental Health Disorders (CAT-MH).

Authors:  Robert D Gibbons; Frank V deGruy
Journal:  Curr Psychiatry Rep       Date:  2019-07-01       Impact factor: 5.285

8.  Test-Retest Reliability of a Computerized Adaptive Depression Screener.

Authors:  David Beiser; Milkie Vu; Robert Gibbons
Journal:  Psychiatr Serv       Date:  2016-04-15       Impact factor: 3.084

9.  Predicting suicidality using a computer adaptive test: Two longitudinal studies of sexual and gender minority youth.

Authors:  Brian Mustanski; Sarah W Whitton; Michael E Newcomb; Antonia Clifford; Daniel T Ryan; Robert D Gibbons
Journal:  J Consult Clin Psychol       Date:  2021-03

10.  Minimal phenotyping yields genome-wide association signals of low specificity for major depression.

Authors:  Na Cai; Joana A Revez; Mark J Adams; Till F M Andlauer; Gerome Breen; Enda M Byrne; Toni-Kim Clarke; Andreas J Forstner; Hans J Grabe; Steven P Hamilton; Douglas F Levinson; Cathryn M Lewis; Glyn Lewis; Nicholas G Martin; Yuri Milaneschi; Ole Mors; Bertram Müller-Myhsok; Brenda W J H Penninx; Roy H Perlis; Giorgio Pistis; James B Potash; Martin Preisig; Jianxin Shi; Jordan W Smoller; Fabien Streit; Henning Tiemeier; Rudolf Uher; Sandra Van der Auwera; Alexander Viktorin; Myrna M Weissman; Kenneth S Kendler; Jonathan Flint
Journal:  Nat Genet       Date:  2020-03-30       Impact factor: 38.330

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