Probability, cost, and interpretation biases’ relationships with depressive and anxious symptom severity: differential mediation by worry and repetitive negative thinking

ABSTRACT

People high in depressive or anxious symptom severity show repetitive negative thinking, including worry and rumination. They also show various cognitive phenomena, including probability, cost, and interpretation biases. Since there is conceptual overlap between these cognitive biases and repetitive negative thinking – all involve thinking about potential threats and misfortunes – we wondered whether repetitive negative thinking could account for (mediate) these cognitive biases’ associations with depressive and anxious symptom severity. In three studies, conducted in two languages and cultures, cost bias and (in two studies) interpretation bias only predicted symptom severity via worry and repetitive negative thinking; this suggests these biases are actually associated with repetitive negative thinking, rather than with symptoms. In contrast, probability bias showed direct relationships with depressive (all studies) and anxious (two studies) symptom severity, suggesting its relationships with symptoms are partly independent of repetitive negative thinking. These results show the value of studying relationships among the various cognitive features of psychopathology. Furthermore, new interventions which target cognitive biases in depression or anxiety must show that they can improve upon cognitive behavioural therapy, which is already widely available, targets both repetitive negative thinking and probability bias, and is highly effective.

KEYWORDS:

• Depression
• anxiety
• probability bias
• repetitive negative thinking
• worry

Acknowledgements

Author contributions: Robert W. Booth: Conceptualisation, methodology, project administration, data curation, data analysis and writing. Bundy Mackintosh: Conceptualisation, methodology and writing – review and editing. Servet Hasşerbetçi: Methodology, data curation and writing – review and editing. Anonymised datasets and example analysis code are available on the Open Science Framework, at https://doi.org/10.17605/OSF.IO/SFA2N. We are grateful to Colette Hirsch for her comments on our study design.

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Funding

The author(s) reported there is no funding associated with the work featured in this article.