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Record W4412172522 · doi:10.1080/10615806.2025.2530702

Cumulative genetic effects of HPA axis on social phobia scrutiny fear: psychoticism and social face as mediators

2025· article· en· W4412172522 on OpenAlexaff
Yuting Yang, Wenting Liang, Wenping Zhao, Qi Lan, Mingzhu Zhou, Pingyuan Gong

Bibliographic record

VenueAnxiety Stress & Coping · 2025
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsInstitute of Population and Public HealthScience North
FundersNational Social Science Fund of China
KeywordsPsychoticismScrutinyPsychologyFace (sociological concept)Social psychologySociologyPersonalityBig Five personality traitsPhilosophyTheologySocial science

Abstract

fetched live from OpenAlex

BACKGROUND: Social phobia scrutiny fear is a stress response triggered by perceptions of social evaluation. However, the role of genetic polymorphisms in the Hypothalamic Pituitary Adrenal (HPA) axis in shaping this fear is not well understood. This study investigates how the cumulative genetic score of the HPA axis influences social phobia scrutiny fear. METHOD: Two independent samples were used. The first examined the relationship between the cumulative genetic effects of the HPA axis and social phobia scrutiny fear. The second sample replicated these findings and explored the mediating roles of psychoticism and social face. RESULTS: Both samples revealed that individuals with a higher cumulative genetic score, associated with increased cortisol reactivity, experienced greater social phobia scrutiny fear. Moreover, psychoticism and social face mediated this relationship, with a stronger genetic predisposition, higher psychoticism, and more pronounced social face correlating with greater scrutiny fear. CONCLUSION: These findings highlight the significant role of the HPA axis in social phobia scrutiny fear and shed light on the psychological pathways through which genetic effects are influenced by personality traits.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.314
Teacher spread0.295 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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