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Record W4205757671 · doi:10.1016/j.jsxm.2021.12.002

Psychometric Properties of Common Measures of Hypersexuality in an Online Canadian Sample

2022· article· en· W4205757671 on OpenAlexaffabout
Mark E. Olver, Drew A. Kingston, Erin Laverty, Michael C. Seto

Bibliographic record

VenueThe Journal of Sexual Medicine · 2022
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsCanadian Public Health AssociationRoyal Ottawa Mental Health CentreUniversity of Saskatchewan
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisConstruct validityHypersexualityCriterion validityClinical psychologyConcurrent validityMeasurement invarianceExploratory factor analysisValidityPsychometricsTest validityDevelopmental psychologyStructural equation modelingInternal consistencySexual behaviorStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: Hypersexuality has been posited as the central defining feature of Compulsive Sexual Behavior Disorder, and although the acceptance and inclusion of this construct in psychiatric nosologies provides some legitimacy, concerns surrounding terminology, assessment, and diagnosis remain. AIM: The present study was an independent psychometric examination of 2 of the most commonly used measures of Compulsive Sexual Behavior Disorder; specifically, the gender invariance of the latent structure, reliability (test retest, internal consistency), and external correlates (concurrent validity) of these measures. METHODS: The Sexual Compulsivity Scale and the Hypersexual Behavior Inventory were completed by 2 nonclinical online community samples of cisgender women (ns = 525 and 359), cisgender men (ns = 419 and 364), and transgender or non-binary individuals (ns = 38 and 11). OUTCOMES: Criterion based measures of sexual history and total sexual outlet (number of orgasms per week) were gathered to validate Sexual Compulsivity Scale and Hypersexual Behavior Inventory total and factor scores. RESULTS: Results supported the factorial validity of both assessment measures: correlated 3 factor solutions were established through exploratory factor analysis of 1 sample, and confirmatory factor analysis in the second sample. Multiple group confirmatory factor analysis, conducted on the 2 combined samples, also supported the gender invariance of the 3-factor solutions. Additional basic psychometric indices of test-retest and internal consistency reliability and criterion-related (concurrent) validity conducted across the 2 online samples were supported. CLINICAL IMPLICATIONS: Common measures of hypersexuality have potential for use in its assessment, treatment, and management. STRENGTHS & LIMITATIONS: Study strengths include: the inclusion of 2 fairly large and diverse online samples, thorough checks for insufficient effort/validity of responding, validity and reliability methodology (ie, measurement at multiple time points, obtaining behavioral indicators of sexual health), and a comprehensive set of psychometric analyses to inform conclusions regarding the external validity, reliability, and latent structure of hypersexuality measures across gender groups. Study limitations include: potential concerns related to validity and accuracy of responding owing to a reliance on self-report, the potential for selection bias, and limiting the examination of the latent structure of hypersexuality to cisgender men and women such that the results may not generalize to gender diverse populations. CONCLUSION: Hypersexuality is a multidimensional construct, with a common latent structure among cisgender men and women, consistency in measurement over time, and meaningful concurrent associations with behavioral criteria that have relevance for sexual health. Olver ME, Kingston DA, Laverty EK, et al. Psychometric Properties of Common Measures of Hypersexuality in an Online Canadian Sample. J Sex Med 2022;19:331-346.

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)0.004
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 score0.240
Threshold uncertainty score0.869

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.258
GPT teacher head0.387
Teacher spread0.129 · 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

Citations4
Published2022
Admission routes2
Has abstractyes

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