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Record W2291547692 · doi:10.1080/0092623x.2015.1113579

Sexual Excitation/Sexual Inhibition Inventory (SESII-W/M): Adaptation and Validation Within a Portuguese Sample of Men and Women

2015· article· en· W2291547692 on OpenAlexaff
Cide Filipe Neves, Robin R. Milhausen, Ana Carvalheira

Bibliographic record

VenueJournal of Sex & Marital Therapy · 2015
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsPsychologyPortugueseConfirmatory factor analysisInternal consistencyConstruct validitySexual arousalConcurrent validityPsychometricsSample (material)Developmental psychologyClinical psychologySexual behaviorStatisticsStructural equation modelingMathematics

Abstract

fetched live from OpenAlex

The SESII-W/M is a self-report measure assessing factors that inhibit and enhance sexual arousal in men and women. The goal of this study was to adapt and validate it in a sample of Portuguese men and women. A total of 1,723 heterosexual men and women participated through a web survey, with ages ranging from 18 to 72 years old (M = 36.05, SD = 11.93). The levels of internal consistency were considered satisfactory in the first four factors, but not in Setting and Dyadic Elements of the Sexual Interaction. Confirmatory factor analysis partially supported the six-factor, 30-item model, as factor loadings and squared multiple correlations pointed to problems with items mainly loading on those two factors. General fit indices were lower than the ones estimated by Milhausen, Graham, Sanders, Yarber, and Maitland (2010). Psychometric sensitivity and construct validity were adequate and gender differences were consistent with the original study. The six-factor, 30-item model was retained, but changes to the factors Setting and Dyadic Elements of the Sexual Interaction, and their corresponding items, were recommended in order to strengthen the measure.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.091
GPT teacher head0.340
Teacher spread0.249 · 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 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

Citations6
Published2015
Admission routes1
Has abstractyes

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