Age of onset in obsessive-compulsive disorder: Admixture analysis with a large sample

G. E. Anholt; I. M. Aderka; A. J.L.M. Van Balkom; J. H. Smit; K. Schruers; N. J.A. Van Der Wee; M. Eikelenboom; V. De Luca; P. Van Oppen

doi:https://doi.org/10.1017/S0033291713000470

Age of onset in obsessive-compulsive disorder: Admixture analysis with a large sample

G. E. Anholt, I. M. Aderka, A. J.L.M. Van Balkom, J. H. Smit, K. Schruers, N. J.A. Van Der Wee, M. Eikelenboom, V. De Luca, P. Van Oppen

Ben-Gurion University of the Negev, University of Haifa

Research output: Contribution to journal › Article › peer-review

Abstract

Background Research into age of onset in obsessive-compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early-and late-onset OCD, rendering inconsistent results that are difficult to interpret. Method In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered. Results A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset â

Original language	American English
Pages (from-to)	185-194
Number of pages	10
Journal	Psychological Medicine
Volume	44
Issue number	1
DOIs	https://doi.org/10.1017/S0033291713000470
State	Published - 1 Jan 2014

Keywords

Admixture analysis
age of onset
obsessive-compulsive disorder

All Science Journal Classification (ASJC) codes

Psychiatry and Mental health
Applied Psychology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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https://doi.org/10.1017/S0033291713000470

Cite this

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title = "Age of onset in obsessive-compulsive disorder: Admixture analysis with a large sample",

abstract = "Background Research into age of onset in obsessive-compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early-and late-onset OCD, rendering inconsistent results that are difficult to interpret. Method In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered. Results A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset {\^a}",

keywords = "Admixture analysis, age of onset, obsessive-compulsive disorder",

author = "Anholt, {G. E.} and Aderka, {I. M.} and {Van Balkom}, {A. J.L.M.} and Smit, {J. H.} and K. Schruers and {Van Der Wee}, {N. J.A.} and M. Eikelenboom and {De Luca}, V. and {Van Oppen}, P.",

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T1 - Age of onset in obsessive-compulsive disorder

T2 - Admixture analysis with a large sample

AU - Anholt, G. E.

AU - Aderka, I. M.

AU - Van Balkom, A. J.L.M.

AU - Smit, J. H.

AU - Schruers, K.

AU - Van Der Wee, N. J.A.

AU - Eikelenboom, M.

AU - De Luca, V.

AU - Van Oppen, P.

PY - 2014/1/1

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N2 - Background Research into age of onset in obsessive-compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early-and late-onset OCD, rendering inconsistent results that are difficult to interpret. Method In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered. Results A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset â

AB - Background Research into age of onset in obsessive-compulsive disorder (OCD) has indicated significant differences between patients with early and late onset of the disorder. However, multiple criteria have been used arbitrarily for differentiating between early-and late-onset OCD, rendering inconsistent results that are difficult to interpret. Method In the current study, admixture analysis was conducted in a sample of 377 OC patients to determine the number of underlying populations of age of onset and associated demographic and clinical characteristics. Various measures of anxiety, depression, co-morbidity, autism, OCD, tics and attention deficit hyperactivity disorder (ADHD) symptoms were administered. Results A bimodal age of onset was established and the best-fitting cut-off score between early and late age of onset was 20 years (early age of onset â

KW - Admixture analysis

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Age of onset in obsessive-compulsive disorder: Admixture analysis with a large sample

Abstract

Keywords

All Science Journal Classification (ASJC) codes

UN SDGs

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