The Development, Standardization, and Initial Validation of the Chicago Multiscale Depression Inventory
Abstract
Current self-report depression scales may overestimate depression symptoms in medical patients by including items measuring symptoms inherent to many medical conditions. They may therefore reflect a patient's medical rather than psychological state. We present the Chicago Multiscale Depression Inventory (CMDI), a factorially derived self-report depression scale that includes Mood, Evaluative, and Vegetative subscales. The CMDI and its subscales were designed to be used separately or combined; we posit that the nonvegetative CMDI subscales are the most accurate means of examining depression in medical patients. In this study we outline the development, standardization, and initial validation of the CMDI, a multistep process that required a total sample of 1,062 adults. We show the CMDI and each of its subscales to be internally consistent, reliable, and valid. Confirmatory factor analysis supports the CMDI factor structure. Finally, we report standardization scores for each of the CMDI scales, derived from an age-, race- and gender-stratified standardization sample of 420 adults.
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High scores on the CMDI reflect reports of a high level of depression and decreases in CMDI score correspond with the reporting of a reduction in depressive symptoms.
“High scores on the CMDI reflect reports of a high level of depression and decreases in CMDI score correspond with the reporting of a reduction in depressive symptoms.”
From The Effectiveness of an Acceptance and Commitment Therapy Self-help Intervention for Chronic Pain. (2010) · cites this paper as [18]
Cites
Mood, vegetative disturbance, and dexamethasone suppression test after stroke
Finklestein, S. P., Benowitz, L. I., Baldessarini, R. J., Arana, G. W., Levine, D. N., Woo, E., Bear, D. M., Moya, K. L., & Stoll, A. L. (1982) · Annals of Neurology · doi:10.1002/ana.410120509 · Cited by 187 · see citing works
The development of depressive symptoms among women with rheumatoid arthritis the role of function
Katz, P., & Yelin, E. H. (1995) · Arthritis & Rheumatism · doi:10.1002/art.1780380108 · Cited by 126 · see citing works
Relationship of depression to medical illness
Kathol, R. G., & Petty, F. (1981) · Journal of Affective Disorders · doi:10.1016/0165-0327(81)90036-7 · Cited by 116 · see citing works
Application of modern psychometric theory in psychiatric research
Gibbons, R. D., Clark, D. C., Cavanaugh, S. V. A., & Davis, J. M. (1985) · Journal of Psychiatric Research · doi:10.1016/0022-3956(85)90067-6 · Cited by 116 · see citing works
Older People's Performance on the Profile of Mood States (POMS)
Kaye, J. M., Lawton, M. P., Gitlin, L. N., et al. (1988) · Clinical Gerontologist · doi:10.1300/j018v07n03_05 · Cited by 35 · see citing works
Depressive symptoms and the dexamethasone suppression test in parkinsonian patients
Frochtengarten, M. L., Villares, J., Maluf, E., & Carlini, E. A. (1987) · Biological Psychiatry · doi:10.1016/0006-3223(87)90156-9 · Cited by 29 · see citing works
Learned helplessness and depression among Israeli women.
Rosenbaum, M., & Shichman, S. (1979) · Journal of Clinical Psychology · doi:10.1002/1097-4679(197904)35:2 · Cited by 10 · see citing works
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Hanna, M., & Strober, L. B. (2020) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2020.102261 · Cited by 202 · see citing works
The Effectiveness of an Acceptance and Commitment Therapy Self-help Intervention for Chronic Pain.
Johnston, M., Foster, M., Shennan, J., Starkey, N. J., & Johnson, A. (2010) · The Clinical Journal of Pain · doi:10.1097/ajp.0b013e3181cf59ce · Cited by 142 · see citing works
Strober, L. B. (2018) · Disability and health journal · doi:10.1016/j.dhjo.2018.05.003 · Cited by 99 · see citing works
Schmitt, M. M., Goverover, Y., DeLuca, J., & Chiaravalloti, N. (2014) · Rehabilitation Psychology · doi:10.1037/a0035288 · Cited by 70 · see citing works
Strober, L. B., Chiaravalloti, N., & DeLuca, J. (2018) · Work · doi:10.3233/wor-172667 · Cited by 36 · see citing works
Giordano, A., Ferrari, G., Radice, D., Randi, G., Bisanti, L., Solari, A., & study, O. B. O. T. P. (2012) · European Journal of Neurology · doi:10.1111/j.1468-1331.2011.03638.x · Cited by 35 · see citing works
Genova, H. M., Genualdi, A., Goverover, Y., Chiaravalloti, N. D., Marino, C., & Lengenfelder, J. (2017) · Social Neuroscience · doi:10.1080/17470919.2016.1173584 · Cited by 13 · see citing works
- Authors
- Nyenhuis, D. L., & Luchetta, T.
- Affiliations
- Rush University Medical Center (US)
- ORCID
- Nyenhuis, David L.
- Venue
- Journal of Personality Assessment
- Publisher
- Informa UK Limited
- Published
- 1998-04
- Volume
- 70
- Issue
- 2
- Pages
- 386-401
- ISSN
- 0022-3891 (ISSN-L)
- 1532-7752
- OpenAlex
- W2062761396
- Cited by
- 155
- References
- 7
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 5 · 2022: 8 · 2021: 7 · 2020: 3 · 2019: 9 · 2018: 7 · 2017: 3 · 2016: 7 · 2015: 14 · 2014: 4 · 2013: 9 · 2012: 5
- FWCI
- 5.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Personality Assessment (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5k04ns001055-03, 5r01ns022128-07)
- Office of Naval Research
- National Institute of Neurological Disorders and Stroke (K04 NS01055, R01 NS22128)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Social Sciences › Psychology › Applied Psychology › Psychological Testing and Assessment
- Keywords
- medical patients, mood, vegetative symptoms, factor structure, scale standardization, internal consistency, psychometric validation
- MeSH terms
- Adult, Aged, Aged, 80 and over, Depressive Disorder, Factor Analysis, Statistical, Female, Humans, Male, Psychological Tests, Psychometrics, United States, Reproducibility of Results
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