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Record W4396675553 · doi:10.1093/sxmrev/qeae024

A review of published studies on virtual reality in sexuality research

2024· review· en· W4396675553 on OpenAlexaff
João Miguel Marques, Caio Petrus Monteiro Figueiredo, Marco de Tubino Scanavino

Bibliographic record

VenueSexual Medicine Reviews · 2024
Typereview
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsWestern University
Fundersnot available
KeywordsPsycINFOHuman sexualityPornographyVirtual realityPsychologyCINAHLApplied psychologySexual orientationClinical psychologyMEDLINEMedicineSocial psychologyComputer sciencePsychological interventionPsychiatryHuman–computer interaction

Abstract

fetched live from OpenAlex

INTRODUCTION: Virtual reality (VR) technology contributes to greater approach of methodological safety to make ecological validity more feasible and a growing interest in sexuality behaviors. OBJECTIVES: The aim of this study was to show VR in the sexuality area by a comprehensive review of outcomes, offer a synthesis of the studies, and make a methodological quality assessment of finding results. A secondary goal was to investigate the effect of immersion on diverse sexual responses outcomes. METHODS: We designed a review based on a systematic review strategy describing types of studies, participants, data collection and outcomes; searched in 4 electronic databases (PubMed, EMBASE, PsycINFO, and SciELO), and made a full-text screening process. RESULTS: The study found 18 articles that met research criteria synthesized within 3 outcome groups: erection measures, level of immersion, and biomarker studies. Synthesis shows a lack of methodological aspects that impair results, such as description of methods from bias protection, randomization, or concealment. The literature still needs to improve its methodology, even though it already shows relevant data for intervention in sexual dysfunction, forensic psychiatry, sexual attraction, orientation, and use of pornography. CONCLUSION: Current methodological issues need better design to highlight relevant issues in sexuality with stronger quality of design, opening boundaries to new diagnostic or interventional technologies to sexual health.

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)0.050
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.504
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0500.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0140.001
Bibliometrics0.0020.006
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0010.002

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 head0.531
GPT teacher head0.610
Teacher spread0.079 · 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; both teacher heads agree on what is shown here.

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
Published2024
Admission routes1
Has abstractyes

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