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Record W4220689291 · doi:10.3138/cjhs.2021-0063

Anxiety induction and sexual arousal in men and women

2022· article· en· W4220689291 on OpenAlexaffvenue
Andrea R. Ashbaugh, Olivia Provost-Walker, Enya Levaque, Leanne Kane, Julia Marinos, Martin L. Lalumière

Bibliographic record

VenueThe Canadian Journal of Human Sexuality · 2022
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsArousalSexual arousalAnxietyPsychologyExtinction (optical mineralogy)Clinical psychologyAudiologyDevelopmental psychologyMedicinePsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Anxiety can sometimes inhibit and sometimes potentiate sexual arousal. We examined whether an anxiety manipulation in a classical fear-conditioning paradigm impacts self-reported sexual arousal in men and women. University students (62 men, 61 women) underwent differential fear conditioning to erotic images; half the images were sometimes (60%) paired with a shock (CS+) and half were never paired with a shock (CS–). For each trial, participants rated their sexual arousal and anxiety in response to the image; skin conductance response (SCR) and zygomatic and corrugator activity were recorded. During acquisition, self-reported sexual arousal was lower to CS+ than CS− (inhibiting effect), but in men only. During extinction, self-reported sexual arousal was lower to CS+ than CS− for both genders. Some differences produced by CS+ and CS− were observed for SCR and zygomatic and corrugator activation at different points during acquisition and extinction, but the effects were unrelated to ratings of anxiety or sexual arousal. The negative impact of anxiety on sexual arousal appears to be resistant to extinction, and small gender differences were observed. Future studies should include direct measures of physiological sexual arousal. The relationship between sexual arousal and anxiety appears to be complex and should be further investigated.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.047
GPT teacher head0.325
Teacher spread0.279 · 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 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

Citations2
Published2022
Admission routes2
Has abstractyes

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