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Record W2602849795 · doi:10.1093/schbul/sbx022.040

M42. Metacognitive Deficits in Schizophrenia; Comparisons With Borderline Personality Disorder and Substance Use Disorder

2017· article· en· W2602849795 on OpenAlexaboutno aff
Kelly D. Buck, Bethany L. Leonhardt, Sunita George, Alison V. James, Jenifer L. Vohs, Paul H. Lysaker

Bibliographic record

VenueSchizophrenia Bulletin · 2017
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyAlexithymiaMetacognitionSchizophrenia (object-oriented programming)Borderline personality disorderFeelingClinical psychologyCognitionDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Background: Metacognition is a psychological function that includes a spectrum of mental activities. These activities involve thinking about thinking and range from more discrete acts, in which people recognize specific thoughts and feelings, to more synthetic acts in which an array of intentions, thoughts, feelings, and connections between events are integrated into larger complex representations. Recently, interest has arisen in the important role that metacognitive deficits may play in schizophrenia spectrum disorders. Research has found that many with schizophrenia experience compromised metacognitive capacity and the degree of impairment in metacognition has been linked to negative and disorganized symptoms, decrement in social functioning, and lower levels of subjective indicators of recovery. While metacognitive deficits have been broadly explored in schizophrenia, less is known about whether these deficits are similar or different than those found in other forms of serious mental illness. Methods: To explore this issue, we administered assessments of metacognition using the Metacognition Assessment Scale-Abbreviated, Alexithymia using the Toronto Alexithymia Scale and Social Cognition using the Bell Lysaker Emotion Recognition Scale to 65 adults with Schizophrenia, 34 adults with Borderline Personality Disorder (PD) and 32 adults with a Substance Use Disorder. We chose Borderline PD as our primary comparison because this group has also been found to have profound alterations in the ability to recognize and think about one’s own and others’ mental activities. We chose substance use disorder as a third psychiatric condition given that this is a common comorbidity of Borderline PD and Schizophrenia and because it has also been linked with deficits in the ability to reflect about mental states. Results: ANCOVA controlling for age revealed the Schizophrenia group had significant poorer overall metacognition compared to the other 2 groups while the Borderline PD group had significantly lower levels of metacognitive capacity compared to the Substance Use group. Multiple comparisons revealed that the Borderline PD group had significantly higher self-reflectivity and awareness of the other’s mind than the Schizophrenia group. In comparison with the Substance Use group, the Borderline PD condition had lower capacity to assume the perspective of others and the ability to use metacognitive knowledge than the Substance Use group. The Borderline PD and Schizophrenia group had significantly higher levels of alexithymia than the Substance Use group. Differences between the Borderline PD and Substance Use groups generally persisted after controlling for self-report of psychopathology and overall number of PD traits. No differences were among groups were found for social cognition. Conclusion: Results suggest that metacognitive functioning is differentially affected in severe mental disorders, with the deficits found in Schizophrenia being generally more severe than in Borderline PD or Substance Use disorders. Schizophrenia may involve unique deficits in the abilities needed for self-reflection and forming integrated ideas about others.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.299
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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