Negative metacognitive bias, underestimating one’s abilities, is consistently linked to psychopathology, yet prior work has often collapsed anxiety/stress and depression or examined depression alone. We tested the unique associations of depression, anxiety/stress, and posttraumatic stress disorder (PTSD) with metacognitive bias in post-9/11 veterans.

Veterans from the Translational Research Center for TBI and Stress Disorders (TRACTS, N = 601; 90% male; M age = 34.31) completed 21-item Depression, Anxiety, and Stress Scale (depression, anxiety/stress), CAPS-IV (PTSD), WHODAS-II Understanding/Communicating (self-reported cognition), and an objective cognition composite (assessment of executive function, memory, and attention). Bias was computed as self-report minus objective cognition. A subsample (n = 239) repeated testing ∼2 years later.

At time 1, more negative metacognitive bias was associated with greater anxiety/stress (r = −.41), depressive (r = −.37), and PTSD symptoms (r = −.31) (all ps < .001). In a simultaneous model, anxiety/stress (β = −.29 p < .001) and depressive symptoms (β = −.12, p = .045) explained unique variance though PTSD symptoms did not (β = −.03, p = .524). Longitudinally, changes in bias were uniquely predicted by symptom changes in anxiety/stress (β = −.33, p < .001) and PTSD (β = −.16, p = .001), but not depression (β = −.10, p = .137).

Across cross-sectional and longitudinal models, anxiety/stress emerged as the most consistent correlate of metacognitive bias, with weaker contributions from depression and PTSD. These findings highlight the importance of assessing the self-report versus objective cognition gap and the need to further understand the temporal relationship between anxiety/stress and metacognitive bias.

Confidence exhibits systematic individual differences across mental health, gender, and age. However, it remains unknown whether these distinct sources of metacognitive bias have common or distinct computational origins.

To address this question, we developed a novel dynamic computational model of metacognition to study the temporal evolution of underconfidence associated with individual differences in transdiagnostic anxiety symptoms and gender in samples of online participants (total N = 1,447).

We found that underconfidence associated with anxiety symptoms became more prominent the longer individuals took to make metacognitive judgments – suggesting that it is exacerbated by additional time for introspection. In contrast, gender-related underconfidence decreased with greater metacognitive judgment time – suggesting that additional time for introspection is able to remediate prepotent biases. Our computational model of confidence explained these effects – while both gender and anxiety symptoms involved shifts in confidence criteria, only anxiety symptoms involved a temporal accumulation of negatively biased evidence about one’s ability.

Our study reveals multiple computational pathways to the formation of underconfidence, in turn highlighting specific potential mechanisms for its remediation.