CoChat
Sign Up
Cited by 174Memory Processes and InfluencesNeural and Behavioral Psychology StudiesVisual perception and processing mechanisms

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Domain-general enhancements of metacognitive ability through adaptive training.

Open access
Carpenter, Jason, Sherman, Maxine T., Kievit, Rogier A., Seth, Anil K., Lau, Hakwan, Fleming, Stephen M.·2019·Journal of Experimental Psychology: General
DOI 10.1037/xge0000505PMC PMC6390881

Published version of a preprint

Open this paper in CoChat — free account

Abstract

The metacognitive ability to introspect about self-performance varies substantially across individuals. Given that effective monitoring of performance is deemed important for effective behavioral control, intervening to improve metacognition may have widespread benefits, for example in educational and clinical settings. However, it is unknown whether and how metacognition can be systematically improved through training independently of task performance, or whether metacognitive improvements generalize across different task domains. Across 8 sessions, here we provided feedback to two groups of participants in a perceptual discrimination task: an experimental group (n = 29) received feedback on their metacognitive judgments, while an active control group (n = 32) received feedback on their decision performance only. Relative to the control group, adaptive training led to increases in metacognitive calibration (as assessed by Brier scores), which generalized both to untrained stimuli and an untrained task (recognition memory). Leveraging signal detection modeling we found that metacognitive improvements were driven both by changes in metacognitive efficiency (meta-d'/d') and confidence level, and that later increases in metacognitive efficiency were positively mediated by earlier shifts in confidence. Our results reveal a striking malleability of introspection and indicate the potential for a domain-general enhancement of metacognitive abilities. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1037/xge0000505

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Task and session structure. Panel A: Participants were tested on both a perceptual discrimination and recognition memory task, each involving two stimulus types: abstract shapes and words. The perceptual task (left) comprised a two-alternative forced-choice discrimination judgment as to the brighter of two simultaneously presented stimuli on each trial. The memory task (right) comprised an encoding phase followed by a series of two-alternative forced-choice recognition memory judgments. Panel B: Experiment timeline. Each participant completed 10 sessions in total: a pretraining session, eight training sessions, and a posttraining session. All four conditions were assessed at pre- and posttraining, but only the perceptual task with a single stimulus type (shapes or words) was trained during Sessions 2 through 9. During training sessions, the control groups received feedback on their objective perceptual discrimination performance, whereas the experimental groups received feedback on their metacognitive calibration. In both groups, feedback was delivered every 27 trials.
Figure 1 Task and session structure. Panel A: Participants were tested on both a perceptual discrimination and recognition memory task, each involving two stimulus types: abstract shapes and words. The perceptual task (left) comprised a two-alternative forced-choice discrimination judgment as to the brighter of two simultaneously presented stimuli on each trial. The memory task (right) comprised an encoding phase followed by a series of two-alternative forced-choice recognition memory judgments. Panel B: Experiment timeline. Each participant completed 10 sessions in total: a pretraining session, eight training sessions, and a posttraining session. All four conditions were assessed at pre- and posttraining, but only the perceptual task with a single stimulus type (shapes or words) was trained during Sessions 2 through 9. During training sessions, the control groups received feedback on their objective perceptual discrimination performance, whereas the experimental groups received feedback on their metacognitive calibration. In both groups, feedback was delivered every 27 trials.CC BY · PubMed Central
Figure 2 First-order discrimination performance. Effect of training on first-order performance (d′) in the control group (who received feedback on perceptual discrimination performance) and the experimental group (who received feedback on their metacognitive judgments) as a function of whether the judgment was made on a perception (red) or memory (blue) trial, and on the trained (filled) or untrained (unfilled) stimulus type. Error bars represent between-subjects SEM. P = perception; M = memory.
Figure 2 First-order discrimination performance. Effect of training on first-order performance (d′) in the control group (who received feedback on perceptual discrimination performance) and the experimental group (who received feedback on their metacognitive judgments) as a function of whether the judgment was made on a perception (red) or memory (blue) trial, and on the trained (filled) or untrained (unfilled) stimulus type. Error bars represent between-subjects SEM. P = perception; M = memory.CC BY · PubMed Central
Figure 3 Metacognitive calibration. Effect of training on confidence calibration (the average quadratic scoring rule score [QSR]). Calibration improved over training sessions in the experimental group in the absence of changes in first-order performance, and this improvement transferred both to an untrained stimulus and untrained recognition memory task. Error bars represent between-subjects SEM. P = perception, M = memory.
Figure 3 Metacognitive calibration. Effect of training on confidence calibration (the average quadratic scoring rule score [QSR]). Calibration improved over training sessions in the experimental group in the absence of changes in first-order performance, and this improvement transferred both to an untrained stimulus and untrained recognition memory task. Error bars represent between-subjects SEM. P = perception, M = memory.CC BY · PubMed Central
Figure 4 Effects of training on components of metacognition. Effects of training on metacognitive bias (confidence level; top panels) and metacognitive efficiency (log[meta-d′/d′]; bottom panels). The left-hand column shows data from the control group; the right-hand column shows data from the experimental group. Metacognitive efficiency (log[meta-d′/d′]) gradually improved over training in the experimental group (bottom panel) in the absence of changes in first-order performance. Error bars represent between-subjects SEM. One participant was excluded when plotting mean log(meta-d′/d′) for Session 6 due to a negative value of meta-d′ precluding a log-transform. P = perception, M = memory.
Figure 4 Effects of training on components of metacognition. Effects of training on metacognitive bias (confidence level; top panels) and metacognitive efficiency (log[meta-d′/d′]; bottom panels). The left-hand column shows data from the control group; the right-hand column shows data from the experimental group. Metacognitive efficiency (log[meta-d′/d′]) gradually improved over training in the experimental group (bottom panel) in the absence of changes in first-order performance. Error bars represent between-subjects SEM. One participant was excluded when plotting mean log(meta-d′/d′) for Session 6 due to a negative value of meta-d′ precluding a log-transform. P = perception, M = memory.CC BY · PubMed Central
Figure 5 Estimated parameters for the bivariate latent change score model of metacognitive calibration (quadratic scoring rule [QSR] scores). Calibration scores were modeled pretraining (T1) and posttraining (T2) across both domains, restricted to the trained stimulus type. Unstandardized parameter estimates are given separately for each group (with standard errors in parentheses). Solid lines indicate parameter significance at p < .05. Note that the T1 covariance, T1 intercepts and T1 memory variance were constrained to be equal across groups. T1 perception variance was estimated separately for each group as explained in the text. Per = perception; Mem = memory.
Figure 5 Estimated parameters for the bivariate latent change score model of metacognitive calibration (quadratic scoring rule [QSR] scores). Calibration scores were modeled pretraining (T1) and posttraining (T2) across both domains, restricted to the trained stimulus type. Unstandardized parameter estimates are given separately for each group (with standard errors in parentheses). Solid lines indicate parameter significance at p < .05. Note that the T1 covariance, T1 intercepts and T1 memory variance were constrained to be equal across groups. T1 perception variance was estimated separately for each group as explained in the text. Per = perception; Mem = memory.CC BY · PubMed Central
Figure 6 Temporal dissociation of shifts in metacognitive bias and metacognitive efficiency. Panel A: Rate of change over sessions of confidence level and meta-d′/d′ in the experimental group showing an early shift toward responding with higher confidence. This shift in confidence was dissociated in time from a more gradual improvement in metacognitive efficiency, with the largest changes occurring toward the end of training. Panel B: The session at which this peak shift occurred was significantly earlier for metacognitive bias (confidence level) compared with metacognitive efficiency (meta-d′/d′). Panel C: Early increases in confidence mediate the impact of feedback type on later increases in metacognitive efficiency. Values outside of parentheses indicate the coefficient mean and values inside parentheses indicate the SEM.
Figure 6 Temporal dissociation of shifts in metacognitive bias and metacognitive efficiency. Panel A: Rate of change over sessions of confidence level and meta-d′/d′ in the experimental group showing an early shift toward responding with higher confidence. This shift in confidence was dissociated in time from a more gradual improvement in metacognitive efficiency, with the largest changes occurring toward the end of training. Panel B: The session at which this peak shift occurred was significantly earlier for metacognitive bias (confidence level) compared with metacognitive efficiency (meta-d′/d′). Panel C: Early increases in confidence mediate the impact of feedback type on later increases in metacognitive efficiency. Values outside of parentheses indicate the coefficient mean and values inside parentheses indicate the SEM.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 54 references

Research works printed but not linked: 2

  1. Kass R. E., & Raftery A. E. (1995). Bayes factors. Journal of the American Statistical Association, 90, 773– 795.
  2. Rosseel Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5-12 (BETA). Journal of Statistical Software, 48, 1– 36.

Cited by

Sorted by citations

See all 174

Related

Metadata

Authors
Carpenter, J., Sherman, M. T., Kievit, R. A., Seth, A. K., Lau, H., & Fleming, S. M.
Affiliations
  • University of California, Los Angeles (US)
  • Wellcome Centre for Human Neuroimaging (GB)
  • University of Sussex (GB)
Corresponding author
Fleming, Stephen M.
ORCID
Venue
Journal of Experimental Psychology: General
Publisher
American Psychological Association (APA)
Published
2019-01
Volume
148
Issue
1
Pages
51-64
ISSN
  • 0096-3445 (ISSN-L)
  • 1939-2222
DOI
10.1037/xge0000505
PMC
PMC6390881
OpenAlex
W2953011441
Cited by
174
References
54
Citations by year
2026: 14 · 2025: 21 · 2024: 21 · 2023: 36 · 2022: 28 · 2021: 24 · 2020: 17 · 2019: 12
FWCI
8.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Experimental Psychology General (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Sussex Research Online (University of Sussex) (submittedVersion, cc-by)
  • UCL Discovery (University College London) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo (cc-by)
Funders
  • National Institutes of Health (R01NS088628)
  • Wellcome Trust (206648/Z/17/Z)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
metacognition, metacognitive calibration, metacognitive training, self-reflection, metacognitive efficiency, confidence, feedback, perceptual discrimination, recognition memory, signal detection theory, Brier score
MeSH terms
Metacognition, Adult, Female, Humans, Male, Middle Aged, Models, Psychological, Practice, Psychological, Task Performance and Analysis, Feedback, Psychological, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review