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Record W2979071750 · doi:10.1177/0886109919878275

Not Into Sex: Women’s Experiences of Treatment-Emergent Sexual Dysfunction

2019· article· en· W2979071750 on OpenAlexaff
Erin Leveque, Heather Samarron, Jessica Shaw

Bibliographic record

VenueAffilia · 2019
Typearticle
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsThematic analysisGrounded theoryContext (archaeology)Mental healthPsychologyQualitative researchSexual dysfunctionClinical psychologyDevelopmental psychologyPsychotherapistPsychiatrySociology

Abstract

fetched live from OpenAlex

Despite recent studies suggesting that treatment-emergent sexual dysfunction (TESD) in women is much more prevalent than previously thought, it is not often discussed between physicians and female patients prior to prescribing psychotropic medication. Missing from the available quantitative research on TESD are stories from the women themselves, their experiences with disclosure or lack thereof, and the impact TESD has had on their sense of self and in their relationships. Concerned that this could have a significant influence on women’s mental, emotional, and sexual health, we conducted a study where we interviewed 10 women who self-identified as experiencing TESD after taking psychotropic medications for their mental health. Semistructured, in-depth interviews were conducted, informed by critical feminist practice, and grounded in feminist standpoint theory. Transcripts were then analyzed using thematic analysis to demonstrate the impact TESD had on the lives of these women. Six themes emerged from the interviews: (1) inadequate disclosure about TESD from physicians, (2) gender-based difference in how TESD is discussed, (3) the experience of physical side effects, (4) emotional responses to side effects, (5) concerns about how the partners of women living with TESD experience it, and (6) the importance of knowledge sharing. We conclude this article with a discussion of how these stories fit within the larger social context.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.995

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)0.0060.001

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 head0.026
GPT teacher head0.289
Teacher spread0.262 · 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 designQualitative
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
Published2019
Admission routes1
Has abstractyes

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