Development and Validation of a Five-Factor Sexual Satisfaction and Distress Scale for Women: The Sexual Satisfaction Scale for Women (SSS-W)
Bibliographic record
Abstract
INTRODUCTION: This article presents data based on the responses of over 800 women who contributed to the development of the Sexual Satisfaction Scale for Women (SSS-W). AIM: The aim of this study was to develop a comprehensive, multifaceted, valid, and reliable self-report measure of women's sexual satisfaction and distress. METHODS: Phase I involved the initial selection of items based on past literature and on interviews of women diagnosed with sexual dysfunction and an exploratory factor analysis. Phase II involved an additional administration of the questionnaire, factor analyses, and refinement of the questionnaire items. Phase III involved administration of the final questionnaire to a sample of women with clinically diagnosed sexual dysfunction and controls. RESULTS: Psychometric evaluation of the SSS-W conducted in a sample of women meeting DSM-IV-TR criteria for female sexual dysfunction and in a control sample provided preliminary evidence of reliability and validity. The ability of the SSS-W to discriminate between sexually functional and dysfunctional women was demonstrated for each of the SSS-W domain scores and total score. CONCLUSION: The SSS-W is a brief, 30-item measure of sexual satisfaction and sexual distress, composed of five domains supported by factor analyses: contentment, communication, compatibility, relational concern, and personal concern. It exhibits sound psychometric properties and has a demonstrated ability to discriminate between clinical and nonclinical samples.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".