A Standardized Diagnostic Interview for Hypoactive Sexual Desire Disorder in Women: Standard Operating Procedure (SOP Part 2)
Bibliographic record
Abstract
INTRODUCTION: Taking into account that Hypoactive Sexual Desire Disorder (HSDD) is a patient-reported symptom and that the disorder is in general the result of the interaction of biological and psychosocial factors (see part 1), it is necessary to provide healthcare professionals with an operating procedure that is patient centered and multidimensional. AIM: Describing a patient-centered and multidimensional standard procedure to diagnose and manage HSDD on a primary care level. METHODS: Review of the literature. Semistructured interview and description of process. RESULT.: The interactive process with the patient follows several steps: initiation, narrative of the patient to understand the individual profile of the disorder, differentiating questions, descriptive diagnosis, exploration of conditioning biomedical, individual psychological, interpersonal, and sociocultural factors (including biomedical examinations), establishment of a biopsychosocial comprehensive explanatory diagnosis, which can be summarized in a nine-field matrix. This matrix will serve as orientation for therapeutic interventions adapted to the individual person. These interventions should always be based on basic counseling as a basis of treatment. Then adapted to the individual condition specific hormonal treatments (mainly estrogen and testosterone alone or combined) can be used after exclusion of contraindications. In patients with predominant psychosocial factors contributing to HSDD individual or couple psychotherapy is indicated. Psychopharmacological drugs are in development and partially investigated and will add to the therapeutic possibilities in the future. CONCLUSION: This model can serve as an ideal basis for the approach to the female patient with HSDD. It can be adapted to the individual clinical setting.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".