A comprehensive meta-analysis of interpretation biases in depression

Jonas Everaert*, Ioana R. Podina, Ernst H.W. Koster

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

179 Citations (Scopus)


Interpretation biases have long been theorized to play a central role in depression. Yet, the strength of the empirical evidence for this bias remains a topic of debate. This meta-analysis aimed to estimate the overall effect size and to identify moderators relevant to theory and methodology. PsycINFO, Embase, Web of Science, Scopus, PubMed, and dissertation databases were searched. A random-effects meta-analysis was performed on 87 studies (N = 9443). Results revealed a medium overall effect size (g = 0.72, 95%-CI:[0.62;0.82]). Equivalent effect sizes were observed for patients diagnosed with clinical depression (g = 0.60, 95%-CI:[0.37;0.75]), patients remitted from depression (g = 0.59, 95%-CI:[0.33;0.86]), and undiagnosed individuals reporting elevated depressive symptoms (g = 0.66, 95%-CI:[0.47;0.84]). The effect size was larger for self-referential stimuli (g = 0.90, 95%-CI[0.78;1.01]), but was not modified by the presence (g = 0.74, 95%-CI[0.59;0.90]) or absence (g = 0.72, 95%-CI[0.58;0.85]) of mental imagery instructions. Similar effect sizes were observed for a negative interpretation bias (g = 0.58, 95%-CI:[0.40;0.75]) and lack of a positive interpretation bias (g = 0.60, 95%-CI:[0.36;0.85]). The effect size was only significant when interpretation bias was measured directly (g = 0.88, 95%-CI[0.77;0.99]), but not when measured indirectly (g = 0.04, 95%-CI[− 0.14;0.22]). It is concluded that depression is associated with interpretation biases, but caution is necessary because methodological factors shape conclusions. Implications and recommendations for future research are outlined.

Original languageEnglish
Pages (from-to)33-48
JournalClinical Psychology Review
Publication statusPublished - Dec 2017
Externally publishedYes


  • Cognitive bias
  • Depression
  • Interpretation bias
  • Meta-analysis
  • Review


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