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Record W2049573881 · doi:10.1007/s10578-014-0513-z

Impaired Facial Affect Perception in Unaffected Children at Familial Risk for Panic Disorder

2014· article· en· W2049573881 on OpenAlexafffund
Cynthia Bilodeau, Jacques Bradwejn, Diana Koszycki

Bibliographic record

VenueChild Psychiatry & Human Development · 2014
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsMontfort HospitalSaint Paul UniversityUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsPsychologyAffect (linguistics)PsychopathologyPanic disorderSadnessAnxietyFacial expressionDevelopmental psychologyEndophenotypeClinical psychologyCognitionPsychiatryAnger

Abstract

fetched live from OpenAlex

Recent studies suggest that impaired processing of facial affect has a familial component and may reflect a marker of liability to psychopathology. This study investigated whether facial affect processing is impaired in offspring with parental panic disorder (PD). Psychiatrically healthy children with parental PD (n = 51) and age and sex matched control children with no parental psychopathology (n = 51) completed a standard facial recognition task. High-risk children made more errors recognizing fearful faces than controls and misattributed fear and angry facial affect as surprised. High-risk females also made more errors recognizing sad faces compared to low risk females and misattributed sadness as fear. No difference emerged for self-rated anxiety while viewing facial expressions. However, self-rated anxiety correlated moderately with misrecognition of fearful facial affect in high-risk children. Overall, our data suggest that the ability to correctly recognize negative facial emotions is impaired in children with parental PD. Further research is needed to confirm if these deficits represent a trait marker of liability for PD and elucidate the contribution of genetic and family environmental influences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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 teacher head, not a consensus.

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

Citations5
Published2014
Admission routes2
Has abstractyes

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