The relationship between attachment and somatoform symptoms in children and adolescents: A systematic review and meta-analysis.

Published
January 26, 2020
Journal
Journal of psychosomatic research
PICOID
f49ad35c
DOI
Citations
10
Keywords
Copyright
Copyright © 2020 Elsevier Inc. All rights reserved.
Patients/Population/Participants

children and adolescents

Intervention

attachment

Comparison

non-attachment

Outcome

somatoform symptoms

Abstract

P
I
C
O

Problems in childhood and adolescence are often present with recurring physical signs of illness, called somatoform symptoms. These symptoms are a common reason for consultation at both paediatric care and psychotherapeutic/psychiatric praxis. We propose that attachment is a possible predictive factor. This article provides a systematic overview of the existing research literature concerning the relationship between attachment and somatoform symptoms in children and adolescents. A systematic search for empirical articles from 1990 up to August 2018 focusing on this association was conducted. Out of six databases, 4994 studies were detected by using defined keywords. One study was added identified by checking reference lists. Finally, 15 studies were selected, which were the bases for the narrative review. Ten studies were included in meta-analysis. Combining study results, we found that attachment cannot solely predict somatoform symptoms. Mixed results are shown. The quantitative analysis substantiated these narrative results, revealing a small but significant combined effect size of Δ ≈ .12 (95% CI .04 - .19). The findings suggest that a relationship exists, but further investigations need to demonstrate that these are not only superficial. There are many developmental factors that affect the relationship between attachment and somatoform symptoms in children and adolescents. Further research should explore this interplay in order to gain a holistic and comprehensive understanding of the underlying mechanisms that lead to these correlations and to discover possible predicting factors.

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