Abstract

Negative interpretation biases have been found to characterize adults with depression and to be involved in the development and maintenance of the disorder. However, less is known about their role in youth depression. The present study investigated i) whether negative interpretation biases characterize children and adolescents with depression and ii) to what extent these biases are more pronounced in currently depressed youth compared to youth at risk for depression (as some negative interpretation biases have been found already in high-risk youth before disorder onset). After a negative mood induction interpretation biases were assessed with two experimental tasks: Ambiguous Scenarios Task (AST) and Scrambled Sentences Task (SST) in three groups of 9–14-year-olds: children and adolescents with a diagnosis of major depression (n = 32), children and adolescents with a high risk for depression (children of depressed parents; n = 48), as well as low-risk children and adolescents (n = 42). Depressed youth exhibited substantially more negative interpretation biases than both high-risk and low-risk groups (as assessed with both tasks), while the high-risk group showed more negative interpretation biases than the low-risk group only as assessed via the SST. The results indicate that the negative interpretation biases that are to some extent already present in high-risk populations before disorder onset are strongly amplified in currently depressed youth. The different findings for the two tasks suggest that more implicit interpretation biases (assessed with the SST) might represent cognitive vulnerabilities for depression whereas more explicit interpretation biases (assessed with the AST) may arise as a consequence of depressive symptomatology.

Highlights

  • Depression is one of the most common psychiatric disorders in childhood and adolescence (Costello et al 2003; Lewinsohn et al 1993) with up to 20% of young people having experienced at least one episode of major depression (MD) by the end of adolescence (Thapar et al 2012)

  • Two experimental tasks capturing different aspects of interpretation were used to assess interpretation biases in three groups of children and adolescents: currently depressed children and adolescents (MD group), children and adolescents at high risk for depression due to having a parent with a history of depression (HR group), and children and adolescents with a low risk for depression (LR group). Both tasks revealed a more negative interpretation bias in children and adolescents with MD compared to both groups of healthy youth and strong correlations between bias scores and depression and anxiety symptoms, while only one task (SST) revealed a more negative interpretation bias in youth at risk for depression compared to low-risk youth

  • Our results suggest that an implicit interpretation bias can already be found in at-risk youth before onset of a depressive disorder and might act as a cognitive vulnerability or risk factor contributing to the development of depression

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Summary

Introduction

Depression is one of the most common psychiatric disorders in childhood and adolescence (Costello et al 2003; Lewinsohn et al 1993) with up to 20% of young people having experienced at least one episode of major depression (MD) by the end of adolescence (Thapar et al 2012). Early-onset MD often follows a recurrent course (e.g., Lewinsohn et al 1999; Weissman et al 1999), which further contributes to the negative consequences of the disorder (Wilson et al 2015; Hammen et al 2008). Negative cognitive biases are tendencies to preferentially process negative compared to positive or neutral information and can be found on various levels of information processing, including attention, interpretation, and memory (Everaert et al 2012; LeMoult and Gotlib 2019). In particular, refer to tendencies to create more negative and fewer positive meanings to explain ambiguous emotional information (Everaert et al 2017). The association between negative interpretation biases and depression has received substantial empirical support (see Everaert et al 2017, for a comprehensive meta-analysis)

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