A Systematic Review of Sexual Distress Measures
Bibliographic record
Abstract
BACKGROUND: Sexual distress is an important component of sexual dysfunction and quality of life and many different measures have been developed for its assessment. AIM: To conduct a literature review of measures for assessing sexual distress and to list, compare, and highlight their characteristics and psychometric properties. METHODS: A systematic review was conducted using Scopus and PubMed databases to identify studies that developed and validated measures of sexual distress. The main characteristics and psychometric properties of each measure were extracted and examined. OUTCOMES: Psychometrically validated measures of sexual distress and a summary of relative strengths and limitations. RESULTS: We found 17 different measures for the assessment of sexual distress. 4 were standalone questionnaires and 13 were subscales included in questionnaires that assessed broader constructs. Although 5 measures were developed to assess sexual distress in the general population, most were developed and validated in very specific clinical groups. Most followed adequate steps in the development and validation process and have strong psychometric properties; however, several limitations were identified. CLINICAL TRANSLATION: This literature review offers researchers and clinicians a list of sexual distress measures and relevant characteristics that can be used to select the best assessment tool for their objectives. STRENGTHS AND LIMITATIONS: A thorough search procedure was used; however, there is still a chance that relevant articles might have been missed owing to our search methodology and inclusion criteria. CONCLUSION: This is a novel and state-of-the-art review of assessment tools for sexual distress that includes valuable information measure selection in the study of sexual distress and sexual dysfunction. Santos-Iglesias P, Mohamed B, Walker LM. A Systematic Review of Sexual Distress Measures. J Sex Med 2018;15:625-644.
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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 | 0.028 | 0.126 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.024 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".