Publication

Data-driven atypical profiles of depressive symptoms: Identification and validation in a large cohort

Wanders, R. B. K., Wardenaar, K. J., Penninx, B. W. J. H., Meijer, R. R. & de Jonge, P., 15-Jul-2015, In : Journal of Affective Disorders. 180, p. 36-43 8 p.

Research output: Contribution to journalArticleAcademicpeer-review

APA

Wanders, R. B. K., Wardenaar, K. J., Penninx, B. W. J. H., Meijer, R. R., & de Jonge, P. (2015). Data-driven atypical profiles of depressive symptoms: Identification and validation in a large cohort. Journal of Affective Disorders, 180, 36-43. https://doi.org/10.1016/j.jad.2015.03.043

Author

Wanders, Rob B. K. ; Wardenaar, Klaas J. ; Penninx, Brenda W. J. H. ; Meijer, Rob R. ; de Jonge, Peter. / Data-driven atypical profiles of depressive symptoms : Identification and validation in a large cohort. In: Journal of Affective Disorders. 2015 ; Vol. 180. pp. 36-43.

Harvard

Wanders, RBK, Wardenaar, KJ, Penninx, BWJH, Meijer, RR & de Jonge, P 2015, 'Data-driven atypical profiles of depressive symptoms: Identification and validation in a large cohort', Journal of Affective Disorders, vol. 180, pp. 36-43. https://doi.org/10.1016/j.jad.2015.03.043

Standard

Data-driven atypical profiles of depressive symptoms : Identification and validation in a large cohort. / Wanders, Rob B. K.; Wardenaar, Klaas J.; Penninx, Brenda W. J. H.; Meijer, Rob R.; de Jonge, Peter.

In: Journal of Affective Disorders, Vol. 180, 15.07.2015, p. 36-43.

Research output: Contribution to journalArticleAcademicpeer-review

Vancouver

Wanders RBK, Wardenaar KJ, Penninx BWJH, Meijer RR, de Jonge P. Data-driven atypical profiles of depressive symptoms: Identification and validation in a large cohort. Journal of Affective Disorders. 2015 Jul 15;180:36-43. https://doi.org/10.1016/j.jad.2015.03.043


BibTeX

@article{ac5af86c84cf41f6a62282c7879588af,
title = "Data-driven atypical profiles of depressive symptoms: Identification and validation in a large cohort",
abstract = "BACKGROUND: Atypical response behavior on depression questionnaires may invalidate depression severity measurements. This study aimed to identify and investigate atypical profiles of depressive symptoms using a data-driven approach based on the item response theory (IRT).METHODS: A large cohort of participants completed the Inventory of Depressive Symptomatology self-report (IDS-SR) at baseline (n=2329) and two-year follow-up (n=1971). Person-fit statistics were used to quantify how strongly each patient׳s observed symptom profile deviated from the expected profile given the group-based IRT model. Identified atypical profiles were investigated in terms of reported symptoms, external correlates and temporal consistency.RESULTS: Compared to others, atypical responders (6.8{\%}) showed different symptom profiles, with higher 'mood reactivity' and 'suicidal ideation' and lower levels of mild symptoms like 'sad mood'. Atypical responding was associated with more medication use (especially tricyclic antidepressants: OR=1.5), less somatization (OR=0.8), anxiety severity (OR=0.8) and anxiety diagnoses (OR=0.8-0.9), and was shown relatively stable (29.0{\%}) over time.LIMITATIONS: This is a methodological proof-of-principal based on the IDS-SR in outpatients. Implementation studies are needed.CONCLUSION: Person-fit statistics can be used to identify patients who report atypical patterns of depressive symptoms. In research and clinical practice, the extra diagnostic information provided by person-fit statistics could help determine if respondents׳ depression severity scores are interpretable or should be augmented with additional information.",
keywords = "Depression, Measurement, Item response theory, Person-fit, IDS-SR, Atypical, PERSON-FIT STATISTICS, PSYCHOMETRIC PROPERTIES, ANXIETY NESDA, DISORDER, INVENTORY, MODELS, ANTIDEPRESSANTS, PSYCHOPATHOLOGY, QUESTIONNAIRE, HETEROGENEITY",
author = "Wanders, {Rob B. K.} and Wardenaar, {Klaas J.} and Penninx, {Brenda W. J. H.} and Meijer, {Rob R.} and {de Jonge}, Peter",
note = "Copyright {\circledC} 2015 Elsevier B.V. All rights reserved.",
year = "2015",
month = "7",
day = "15",
doi = "10.1016/j.jad.2015.03.043",
language = "English",
volume = "180",
pages = "36--43",
journal = "Journal of Affective Disorders",
issn = "0165-0327",
publisher = "ELSEVIER SCIENCE BV",

}

RIS

TY - JOUR

T1 - Data-driven atypical profiles of depressive symptoms

T2 - Identification and validation in a large cohort

AU - Wanders, Rob B. K.

AU - Wardenaar, Klaas J.

AU - Penninx, Brenda W. J. H.

AU - Meijer, Rob R.

AU - de Jonge, Peter

N1 - Copyright © 2015 Elsevier B.V. All rights reserved.

PY - 2015/7/15

Y1 - 2015/7/15

N2 - BACKGROUND: Atypical response behavior on depression questionnaires may invalidate depression severity measurements. This study aimed to identify and investigate atypical profiles of depressive symptoms using a data-driven approach based on the item response theory (IRT).METHODS: A large cohort of participants completed the Inventory of Depressive Symptomatology self-report (IDS-SR) at baseline (n=2329) and two-year follow-up (n=1971). Person-fit statistics were used to quantify how strongly each patient׳s observed symptom profile deviated from the expected profile given the group-based IRT model. Identified atypical profiles were investigated in terms of reported symptoms, external correlates and temporal consistency.RESULTS: Compared to others, atypical responders (6.8%) showed different symptom profiles, with higher 'mood reactivity' and 'suicidal ideation' and lower levels of mild symptoms like 'sad mood'. Atypical responding was associated with more medication use (especially tricyclic antidepressants: OR=1.5), less somatization (OR=0.8), anxiety severity (OR=0.8) and anxiety diagnoses (OR=0.8-0.9), and was shown relatively stable (29.0%) over time.LIMITATIONS: This is a methodological proof-of-principal based on the IDS-SR in outpatients. Implementation studies are needed.CONCLUSION: Person-fit statistics can be used to identify patients who report atypical patterns of depressive symptoms. In research and clinical practice, the extra diagnostic information provided by person-fit statistics could help determine if respondents׳ depression severity scores are interpretable or should be augmented with additional information.

AB - BACKGROUND: Atypical response behavior on depression questionnaires may invalidate depression severity measurements. This study aimed to identify and investigate atypical profiles of depressive symptoms using a data-driven approach based on the item response theory (IRT).METHODS: A large cohort of participants completed the Inventory of Depressive Symptomatology self-report (IDS-SR) at baseline (n=2329) and two-year follow-up (n=1971). Person-fit statistics were used to quantify how strongly each patient׳s observed symptom profile deviated from the expected profile given the group-based IRT model. Identified atypical profiles were investigated in terms of reported symptoms, external correlates and temporal consistency.RESULTS: Compared to others, atypical responders (6.8%) showed different symptom profiles, with higher 'mood reactivity' and 'suicidal ideation' and lower levels of mild symptoms like 'sad mood'. Atypical responding was associated with more medication use (especially tricyclic antidepressants: OR=1.5), less somatization (OR=0.8), anxiety severity (OR=0.8) and anxiety diagnoses (OR=0.8-0.9), and was shown relatively stable (29.0%) over time.LIMITATIONS: This is a methodological proof-of-principal based on the IDS-SR in outpatients. Implementation studies are needed.CONCLUSION: Person-fit statistics can be used to identify patients who report atypical patterns of depressive symptoms. In research and clinical practice, the extra diagnostic information provided by person-fit statistics could help determine if respondents׳ depression severity scores are interpretable or should be augmented with additional information.

KW - Depression

KW - Measurement

KW - Item response theory

KW - Person-fit

KW - IDS-SR

KW - Atypical

KW - PERSON-FIT STATISTICS

KW - PSYCHOMETRIC PROPERTIES

KW - ANXIETY NESDA

KW - DISORDER

KW - INVENTORY

KW - MODELS

KW - ANTIDEPRESSANTS

KW - PSYCHOPATHOLOGY

KW - QUESTIONNAIRE

KW - HETEROGENEITY

U2 - 10.1016/j.jad.2015.03.043

DO - 10.1016/j.jad.2015.03.043

M3 - Article

C2 - 25881279

VL - 180

SP - 36

EP - 43

JO - Journal of Affective Disorders

JF - Journal of Affective Disorders

SN - 0165-0327

ER -

ID: 19293635