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Record W4225016656 · doi:10.1080/00224499.2022.2066616

Anxiety and Compulsive Sexual Behavior Disorder: A Systematic Review

2022· review· en· W4225016656 on OpenAlexaff
Jennifer T. Grant Weinandy, Brinna N. Lee, K. Camille Hoagland, Joshua B. Grubbs, Beáta Bőthe

Bibliographic record

VenueThe Journal of Sex Research · 2022
Typereview
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPsycINFOAnxietyClinical psychologyPsychologyAnxiety disorderGeneralized anxiety disorderPsychiatryComorbidityMEDLINE

Abstract

fetched live from OpenAlex

edition of the International Classification of Diseases has spurred increasing interest in the clinical profile of the disorder. Such attention has included a focus on potential comorbidities, risk factors, or symptoms resulting from such behaviors, including anxiety. Anxiety disorders have long been noted as comorbid with many other diagnoses, such as posttraumatic stress disorder, obsessive compulsive disorder, and substance use disorders. This review aims to understand the relationship between anxiety and compulsive sexual behavior in adults and adolescents, based on available quantitative studies. A search of PsycInfo and PubMed revealed 40 studies which quantitatively assessed a relationship between an anxiety measure and a Compulsive Sexual Behavior Disorder measure, including dissertations and published articles using clinical and community samples. A qualitative synthesis and risk of bias analysis of the studies was conducted, rather than a meta-analysis, due to the variety of methods. Overall, studies were primarily cross-sectional and the relationship between these two constructs was unclear, likely due to several factors, including inconsistent measurement of Compulsive Sexual Behavior Disorder, lack of gender diversity, and very little longitudinal data. Directions for future research are discussed.

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)0.016
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.895
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.213
GPT teacher head0.505
Teacher spread0.292 · 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 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

Citations30
Published2022
Admission routes1
Has abstractyes

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