Literature DB >> 24548149

Establishing a common metric for depressive symptoms: linking the BDI-II, CES-D, and PHQ-9 to PROMIS depression.

Seung W Choi1, Benjamin Schalet2, Karon F Cook2, David Cella2.   

Abstract

Interest in measuring patient-reported outcomes has increased dramatically in recent decades. This has simultaneously produced numerous assessment options and confusion. In the case of depressive symptoms, there are many commonly used options for measuring the same or a very similar concept. Public and professional reporting of scores can be confused by multiple scale ranges, normative levels, and clinical thresholds. A common reporting metric would have great value and can be achieved when similar instruments are administered to a single sample and then linked to each other to produce cross-walk score tables (e.g., Dorans, 2007; Kolen & Brennan, 2004). Using multiple procedures based on item response theory and equipercentile methods, we produced cross-walk tables linking 3 popular "legacy" depression instruments-the Center for Epidemiologic Studies Depression Scale (Radloff, 1977; N = 747), the Beck Depression Inventory-II (Beck, Steer, & Brown, 1996; N = 748), and the 9-item Patient Health Questionnaire (Kroenke, Spitzer, & Williams, 2001; N = 1,120)-to the depression metric of the National Institutes of Health (NIH) Patient-Reported Outcomes Measurement Information System (PROMIS; Cella et al., 2010). The PROMIS Depression metric is centered on the U.S. general population, matching the marginal distributions of gender, age, race, and education in the 2000 U.S. census (Liu et al., 2010). The linking relationships were evaluated by resampling small subsets and estimating confidence intervals for the differences between the observed and linked PROMIS scores; in addition, PROMIS cutoff scores for depression severity were estimated to correspond with those commonly used with the legacy measures. Our results allow clinicians and researchers to retrofit existing data of 3 popular depression measures to the PROMIS Depression metric and vice versa.

Entities:  

Mesh:

Year:  2014        PMID: 24548149      PMCID: PMC5515387          DOI: 10.1037/a0035768

Source DB:  PubMed          Journal:  Psychol Assess        ISSN: 1040-3590


  41 in total

1.  How should the internal structure of personality inventories be evaluated?

Authors:  Christopher J Hopwood; M Brent Donnellan
Journal:  Pers Soc Psychol Rev       Date:  2010-04-30

2.  Equating the MOS SF36 and the LSU HSI Physical Functioning Scales.

Authors:  W P Fisher; R L Eubanks; R L Marier
Journal:  J Outcome Meas       Date:  1997

3.  Measuring fatigue in persons with multiple sclerosis: creating a crosswalk between the Modified Fatigue Impact Scale and the PROMIS Fatigue Short Form.

Authors:  Vanessa K Noonan; Karon F Cook; Alyssa M Bamer; Seung W Choi; Jiseon Kim; Dagmar Amtmann
Journal:  Qual Life Res       Date:  2011-11-03       Impact factor: 4.147

4.  The use of PROMIS and assessment center to deliver patient-reported outcome measures in clinical research.

Authors:  Richard C Gershon; Nan Rothrock; Rachel Hanrahan; Michael Bass; David Cella
Journal:  J Appl Meas       Date:  2010

5.  Describing depression: congruence between patient experiences and clinical assessments.

Authors:  Morgen A R Kelly; Jennifer Q Morse; Angela Stover; Tara Hofkens; Emily Huisman; Stuart Shulman; Susan V Eisen; Sara J Becker; Kevin Weinfurt; Elaine Boland; Paul A Pilkonis
Journal:  Br J Clin Psychol       Date:  2011-03

Review 6.  Getting what you ask for: on the selectivity of depression rating scales.

Authors:  Koen Demyttenaere; Jürgen De Fruyt
Journal:  Psychother Psychosom       Date:  2003 Mar-Apr       Impact factor: 17.659

7.  Having a fit: impact of number of items and distribution of data on traditional criteria for assessing IRT's unidimensionality assumption.

Authors:  Karon F Cook; Michael A Kallen; Dagmar Amtmann
Journal:  Qual Life Res       Date:  2009-03-18       Impact factor: 4.147

8.  Linking pain items from two studies onto a common scale using item response theory.

Authors:  Wen-Hung Chen; Dennis A Revicki; Jin-Shei Lai; Karon F Cook; Dagmar Amtmann
Journal:  J Pain Symptom Manage       Date:  2009-07-03       Impact factor: 3.612

9.  Development and psychometric analysis of the PROMIS pain behavior item bank.

Authors:  Dennis A Revicki; Wen-Hung Chen; Neesha Harnam; Karon F Cook; Dagmar Amtmann; Leigh F Callahan; Mark P Jensen; Francis J Keefe
Journal:  Pain       Date:  2009-08-15       Impact factor: 6.961

10.  Evaluation of item candidates: the PROMIS qualitative item review.

Authors:  Darren A DeWalt; Nan Rothrock; Susan Yount; Arthur A Stone
Journal:  Med Care       Date:  2007-05       Impact factor: 2.983

View more
  155 in total

1.  Effect of a Faith-Based Education Program on Self-Assessed Physical, Mental and Spiritual (Religious) Health Parameters.

Authors:  Frans J Cronjé; Levenda S Sommers; James K Faulkner; W A J Meintjes; Charles H Van Wijk; Robert P Turner
Journal:  J Relig Health       Date:  2017-02

2.  From Big Data to Knowledge in the Social Sciences.

Authors:  Bradford W Hesse; Richard P Moser; William T Riley
Journal:  Ann Am Acad Pol Soc Sci       Date:  2015-05-01

3.  Cardiovascular disease risk factors are elevated among a cohort of young sexual and gender minorities in Chicago.

Authors:  Ethan Morgan; Richard D'Aquila; Mercedes R Carnethon; Brian Mustanski
Journal:  J Behav Med       Date:  2019-04-09

4.  Integrating HIV Prevention and Relationship Education for Young Same-Sex Male Couples: A Pilot Trial of the 2GETHER Intervention.

Authors:  Michael E Newcomb; Kathryn R Macapagal; Brian A Feinstein; Emily Bettin; Gregory Swann; Sarah W Whitton
Journal:  AIDS Behav       Date:  2017-08

Review 5.  Functional Disability in Mild Cognitive Impairment: A Systematic Review and Meta-Analysis.

Authors:  Cutter A Lindbergh; Rodney K Dishman; L Stephen Miller
Journal:  Neuropsychol Rev       Date:  2016-07-08       Impact factor: 7.444

Review 6.  Measurement framework for the Environmental influences on Child Health Outcomes research program.

Authors:  Courtney K Blackwell; Lauren S Wakschlag; Richard C Gershon; David Cella
Journal:  Curr Opin Pediatr       Date:  2018-04       Impact factor: 2.856

7.  Using Patient-reported Outcomes Measurement Information System Measures to Understand the Relationship Between Improvement in Physical Function and Depressive Symptoms.

Authors:  Casey M Beleckas; Jason Guattery; Aaron M Chamberlain; Taleef Khan; Michael P Kelly; Ryan P Calfee
Journal:  J Am Acad Orthop Surg       Date:  2018-12-15       Impact factor: 3.020

8.  The sensitivity of the MOS SF-12 and PROMIS® global summary scores to adverse health events in an older cohort.

Authors:  Joanne Allen; Fiona M Alpass; Christine V Stephens
Journal:  Qual Life Res       Date:  2018-05-03       Impact factor: 4.147

9.  Linking Scores with Patient-Reported Health Outcome Instruments: A Validation Study and Comparison of Three Linking Methods.

Authors:  Benjamin D Schalet; Sangdon Lim; David Cella; Seung W Choi
Journal:  Psychometrika       Date:  2021-06-26       Impact factor: 2.500

10.  Preoperative PROMIS Scores Predict Postoperative PROMIS Score Improvement for Patients Undergoing Hand Surgery.

Authors:  David N Bernstein; Jeff R Houck; Ronald M Gonzalez; Danielle M Wilbur; Richard J Miller; David J Mitten; Warren C Hammert
Journal:  Hand (N Y)       Date:  2018-08-03
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.