The Sexual Interest and Desire Inventory—Female (SIDI-F): Item Response Analyses of Data from Women Diagnosed with Hypoactive Sexual Desire Disorder
Bibliographic record
Abstract
INTRODUCTION: Hypoactive sexual desire disorder (HSDD) is the most common sexual complaint in women. Currently there are no validated instruments for specifically assessing HSDD severity, or change in HSDD severity in response to treatment, in premenopausal women. The Sexual Interest and Desire Inventory-Female (SIDI-F) is a clinician-administered instrument that was developed to measure severity and change in response to treatment of HSDD. Seventeen items were included in a preliminary version of the SIDI-F, including 10 items related to desire, and seven items related to possible comorbid factors (e.g., other kinds of sexual dysfunction, general relationship satisfaction, mood, and fatigue). AIM: The aim of the study was to use the outcome of item response analyses of blinded data from two randomized, placebo-controlled trials, to assist in the revision of the scale. METHODS: A nonparametric item response (IRT) model was used to assess the relation between item functioning and HSDD severity on this preliminary version of the SIDI-F. RESULTS: Results show that the majority of SIDI-F items demonstrated good sensitivity to differences in overall HSDD severity. That is, there was an orderly relation between differences in option selection for an item and differences in overall HSDD severity. The IRT analyses further indicated that revisions were warranted for a number of these items. Five items were not sensitive to differences in HSDD severity and were removed from the scale. CONCLUSION: The SIDI-F is a brief, clinician-administered rating scale designed to assess severity of HSDD symptoms in women. IRT analyses show that majority of the items of the SIDI-F function well in discriminating individual differences in HSDD severity. A revised 13-item version of the SIDI-F is currently undergoing further validation.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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".