Cognitive theories of depression, such as Beck’s cognitive model (Beck, 1967), propose that biases and deficits in cognitive control over emotional information contribute to the development and persistence of depression.
Specifically, these theories posit that depressed individuals have difficulty exerting control over negative thoughts and feelings, leading to a preponderance of negative content in working memory (Joormann & Tanovic, 2015).
Quigley, L., Thiruchselvam, T., & Quilty, L. C. (2022). Cognitive control biases in depression: A systematic review and meta-analysis. Psychological Bulletin, 148(9-10), 662–709. https://doi.org/10.1037/bul0000372
Key Points
- This rigorous meta-analysis synthesized over 70 studies to provide robust evidence that depression vulnerability is associated with a small but consistent cognitive processing bias that favors negative over positive material.
- Depression-vulnerable individuals demonstrated significantly worse cognitive control of negative information compared to both neutral and positive information.
- Control samples exhibited worse cognitive control of positive relative to negative information.
- The difference in cognitive control biases between depression-vulnerable and control groups was statistically significant.
- There was limited and inconsistent evidence that sample characteristics (e.g., depression diagnosis status) or methodological factors (e.g., type of cognitive control task) moderated the magnitude of cognitive control biases.
Rationale
Cognitive theories of depression posit that biases in cognitive control over emotional information play a causal role in the development and persistence of depressive symptoms (Beck, 1967; Joormann & Tanovic, 2015).
These theories propose that difficulties regulating negative thoughts, feelings, and memories contribute to the negative thinking patterns and poor mood regulation characteristic of depression (De Raedt & Koster, 2010; Gotlib & Joormann, 2010).
While narrative reviews support these theories by demonstrating cognitive control biases related to depression (Joormann & Siemer, 2011; LeMoult & Gotlib, 2019), they qualitatively integrate findings across studies.
In contrast, meta-analysis provides a rigorous quantitative method to summarize effects and examine moderators (Borenstein et al., 2009).
This study employed systematic review methodology and meta-analytic techniques to evaluate the magnitude and consistency of cognitive control biases in depression, potential publication bias in the literature, and sample and methodological variables that may impact effects.
Determining the presence and size of effects has important implications for etiological models and treatment strategies targeting biased cognitive control in depression.
Method
The authors systematically searched electronic databases for research on cognitive control biases in depression published up to January 2022.
Seventy-three articles describing 77 independent studies involving 2,229 depressed adults and 1,905 controls met the inclusion criteria.
Characteristics coded from each study included sample demographics, depression diagnosis status, task details, performance indices analyzed, and more.
Random effects meta-analysis models were used to compute effect sizes (Hedges’s g) for differences in cognitive control performance between depressed and control groups (between-groups analyses) and within depressed and control groups across emotional and neutral stimuli (within-groups analyses).
Sample
The included studies involved adults aged 18-65 years with a diagnosis of major depressive disorder (MDD; k = 56 studies), remitted MDD (rMDD; k = 20), or elevated self-reported symptoms (dysphoria; k = 11).
Statistical Analysis
The main analyses involved correlational effects models with robust variance estimation, which accounts for dependencies between effect sizes extracted from the same studies.
Categorical (e.g., diagnosis status) and continuous (e.g., age) variables were evaluated as moderators using meta-regression.
Results
The depressed groups demonstrated worse cognitive control performance for negative (g = 0.52), positive (g = 0.30), and neutral (g = 0.37) stimuli compared to controls in between-groups analyses.
Within-groups analyses revealed worse cognitive control of negative versus neutral (g = 0.18) and negative versus positive stimuli (g = 0.13) among depressed groups.
Controls exhibited worse cognitive control of positive versus negative stimuli (g = -0.14).
Insight
This meta-analysis indicates depression is characterized by impaired cognitive control that favors processing and maintenance of negative material over neutral and positive material.
These biases likely contribute to negative thinking patterns that maintain depressed mood.
Strengths
- Systematic review methodology using PRISMA guidelines
- Contacted study authors for unpublished data
- Assessed publication bias
- Used robust statistical models accounting for dependency in effects extracted from the same studies
Limitations
- English-language studies only
- Majority conducted in Western countries (especially USA)
- Grouping of some moderator categories (e.g., symptom severity) resulted in loss of variability
- Insufficient studies to test interactions between moderators
Clinical Implications
The consistent finding that depression is associated with greater cognitive control difficulties for negative versus positive information has important theoretical and practical implications.
Theoretically, it supports cognitive models that biased cognitive control serves to increase negative thought content and maintain depressive schemas (Beck, 1967; Joormann & Tanovic, 2015).
Clinically, directly assessing and modifying cognitive control biases could enhance the prevention, diagnosis, and treatment of depression.
For example, cognitive control bias measures that are not influenced by self-report biases may improve the identification of at-risk individuals and the assessment of symptom severity (Harrison et al., 2016).
Training programs targeting cognitive control over emotional material could reduce risk among vulnerable groups or augment psychotherapy to improve treatment outcomes (Koster et al., 2017).
Tracking changes in cognitive control biases over treatment may also predict relapse or recurrence of depression (Siegle et al., 2007).
Overall, elucidating the role of cognitive mechanisms in depression can inform the development of more effective interventions.
References
Primary paper
Quigley, L., Thiruchselvam, T., & Quilty, L. C. (2022). Cognitive control biases in depression: A systematic review and meta-analysis. Psychological Bulletin, 148(9-10), 662–709. https://doi.org/10.1037/bul0000372
Other references
Beck, A. T. (1967). Depression: Clinical, experimental and theoretical aspects. Harper & Row.
Borenstein, M., Hedges, L. V., Higgins, J. P., & Rothstein, H. R. (2009). Introduction to meta-analysis. Wiley. https://doi.org/10.1002/9780470743386
De Raedt, R., & Koster, E. H. (2010). Understanding vulnerability for depression from a cognitive neuroscience perspective: A reappraisal of attentional factors and a new conceptual framework. Cognitive, Affective, & Behavioral Neuroscience, 10(1), 50–70. https://doi.org/10.3758/cabn.10.1.50
Gotlib, I. H., & Joormann, J. (2010). Cognition and depression: Current status and future directions. Annual Review of Clinical Psychology, 6(1), 285–312. https://doi.org/10.1146/annurev.clinpsy.121208.131305
Harrison, A. J., Gibb, B. E., & McKinnon, M. C. (2016). Cognitive mechanisms in health anxiety: Repetitive thought and catastrophic misinterpretation. Behaviour Research and Therapy, 90, 78-87. https://doi.org/10.1016/j.brat.2016.12.008
Joormann, J., & Siemer, M. (2011). Affective processing and emotion regulation in dysphoria and depression: Cognitive biases and deficits in cognitive control. Social and Personality Psychology Compass, 5(1), 13–28. https://doi.org/10.1111/j.1751-9004.2010.00335.x
Joormann, J., & Tanovic, E. (2015). Cognitive vulnerability to depression: Examining cognitive control and emotion regulation. Current Opinion in Psychology, 4, 86–92. https://doi.org/10.1016/j.copsyc.2014.12.006
Koster, E. H. W., Hoorelbeke, K., Onraedt, T., Owens, M., & Derakshan, N. (2017). Cognitive control interventions for depression: A systematic review of findings from training studies. Clinical Psychology Review, 53, 79–92. https://doi.org/10.1016/j.cpr.2017.02.002
LeMoult, J., & Gotlib, I. H. (2019). Depression: A cognitive perspective. Clinical Psychology Review, 69, 51–66. https://doi.org/10.1016/j.cpr.2018.06.008
Siegle, G. J., Carter, W., & Thase, M. E. (2007). Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. American Journal of Psychiatry, 164(4), 735-738. https://doi.org/10.1176/ajp.2007.164.4.735
Keep Learning
- How might we design experiments to further test the causal role of cognitive control biases in the development and maintenance of depression?
- What are some strategies we could use in psychotherapy or training programs to improve cognitive control over emotional information? How might we measure their effectiveness?
- How might cognitive control biases interact with other cognitive biases implicated in depression, such as attention and memory biases? What experiments could explore these relationships?
- Could cognitive control biases be a transdiagnostic risk factor linking depression to other forms of psychopathology? What evidence supports or refutes this idea?
- What neural mechanisms might underlie biased cognitive control over emotional material in depression? What neuroimaging studies are needed to elucidate this?
