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Record W4382542101 · doi:10.1093/jsxmed/qdad068.019

(020) Post-SSRI/SNRI Sexual Dysfunction: A review

2023· review· en· W4382542101 on OpenAlexaff

Bibliographic record

VenueThe Journal of Sexual Medicine · 2023
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsSexual dysfunctionSexual functionPsychologyConceptualizationPsychotherapistPsychiatryClinical psychologyMedicinePsychoanalysisComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction Post-SSRI-SNRI Sexual Dysfunction (PSSD) is conceptualized as distressing issues with sexual function/pleasure that emerge with SSRI/SNRI initiation and persist after SSRI/SNRI termination and depression remission, and that are not due to other contributors. Although there is increasing recognition of PSSD in clinical practice and research, it is not well understood, researched, or managed. Objectives To provide an overview of SSRIs/SNRIs and their side effects (sexual and otherwise), to present and evaluate the working definition of PSSD, to describe current etiological theories and management strategies of PSSD, and to highlight future directions. Methods A review of the literature was undertaken in order to understand the current conceptualization of PSSD. Particular attention was paid to sexual and nonsexual side effects of PSSD as well as etiological theories and management strategies. Results SSRIs and SNRIs often lead to sexual side effects, which may affect treatment adherence and compliance. A small subset of individuals may develop PSSD, in which distressing sexual dysfunction persists after termination of the SSRI/SNRI and can last months to years. Nonsexual side effects (e.g., cognitive, emotional) have also been reported, and the desire for informed consent as well as collaborative health care has been reported by those affected. PSSD has been recognized as a medical condition by the European Medicines Association since 2019. Conclusions PSSD is increasingly recognized as a potential side effect of SSRI/SNRI use, and concerted collaboration and effort is needed in order to comprehensively understand this condition and its management. Disclosure No.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.197
GPT teacher head0.424
Teacher spread0.226 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes1
Has abstractyes

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