Questionnaires for Assessment of Female Sexual Dysfunction: A Review and Proposal for a Standardized Screener
Bibliographic record
Abstract
INTRODUCTION: There are many methods to evaluate female sexual function and dysfunction (FSD) in clinical and research settings, including questionnaires, structured interviews, and detailed case histories. Of these, questionnaires have become an easy first choice to screen individuals into different categories of FSD. AIM: The aim of this study was to review the strengths and weaknesses of different questionnaires currently available to assess different dimensions of women's sexual function and dysfunction, and to suggest a simple screener for FSD. METHODS: A literature search of relevant databases, books, and articles in journals was used to identify questionnaires that have been used in basic or epidemiological research, clinical trials, or in clinical settings. MAIN OUTCOME MEASURE: Measures were grouped in four levels based on their purposes and degree of development, and were reviewed for their psychometric properties and utility in clinical or research settings. A Sexual Complaints Screener for Women (SCS-W) was then proposed based on epidemiological methods. RESULTS: Although many questionnaires are adequate for their own purposes, our review revealed a serious lack of standardized, internationally (culturally) acceptable questionnaires that are truly epidemiologically validated in general populations and that can be used to assess FSD in women with or without a partner and independent of the partner's gender. The SCS-W is proposed as a 10-item screener to aid clinicians in making a preliminary assessment of FSD. CONCLUSIONS: The definition of FSD continues to change and basic screening tools are essential to help advance clinical diagnosis and treatment, or to slate patients adequately into the right diagnostic categories for basic and epidemiological research or clinical trials.
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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 | 0.035 | 0.038 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.014 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".