Universität zu Köln

Betz, Linda T. ORCID: 0000-0003-1741-4069, Rosen, Marlene, Salokangas, Raimo K. R. and Kambeitz, Joseph (2022). Disentangling the impact of childhood abuse and neglect on depressive affect in adulthood: A machine learning approach in a general population sample. J. Affect. Disord., 315. S. 17 - 27. AMSTERDAM: ELSEVIER. ISSN 1573-2517

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Abstract

Background: Different types of childhood maltreatment (CM) are key risk factors for psychopathology. Specifically, there is evidence for a unique role of emotional abuse in affective psychopathology in children and youth; however, its predictive power for depressive symptomatology in adulthood is still unknown. Additionally, emotional abuse encompasses several facets, but the strength of their individual contribution to depressive affect has not been examined. Method: Here, we used a machine learning (ML) approach based on Random Forests to assess the performance of domain scores and individual items from the Childhood Trauma Questionnaire (CTQ) in predicting self-reported levels of depressive affect in an adult general population sample. Models were generated in a training sample (N = 769) and validated in an independent test sample (N = 466). Using state-of-the-art methods from interpretable ML, we identified the most predictive domains and facets of CM for adult depressive affect. Results: Models based on individual CM items explained more variance in the independent test sample than models based on CM domain scores (R2 = 7.6 % vs. 6.4 %). Emotional abuse, particularly its more subjective components such as reactions to and appraisal of the abuse, emerged as the strongest predictors of adult depressive affect. Limitations: Assessment of CM was retrospective and lacked information on timing and duration. Moreover, re-ported rates of CM and depressive affect were comparatively low. Conclusions: Our findings corroborate the strong role of subjective experience in CM-related psychopathology across the lifespan that necessitates greater attention in research, policy, and clinical practice.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Betz, Linda T. UNSPECIFIED orcid.org/0000-0003-1741-4069 UNSPECIFIED Rosen, Marlene UNSPECIFIED UNSPECIFIED UNSPECIFIED Salokangas, Raimo K. R. UNSPECIFIED UNSPECIFIED UNSPECIFIED Kambeitz, Joseph UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-669915
DOI:	10.1016/j.jad.2022.07.042
Journal or Publication Title:	J. Affect. Disord.
Volume:	315
Page Range:	S. 17 - 27
Date:	2022
Publisher:	ELSEVIER
Place of Publication:	AMSTERDAM
ISSN:	1573-2517
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language MENTAL-HEALTH IMPACT; MALTREATMENT; EXPERIENCES; SYMPTOMS; ASSOCIATION; PREDICTION; TRAUMA; RISK; CARE Multiple languages Clinical Neurology; Psychiatry Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/66991