Effect of counseling model on sexual dysfunction among women with diabetes
Bibliographic record
Abstract
Background: Diabetes mellitus (DM) is an important cause of sexual dysfunction both in men and women. In Egypt, Ibrahim et al. reported that the prevalence of FSD in 2013 was 52.8%. Aim of the study: To evaluate the effect of sexual counseling model on sexual dysfunction among women with diabetes.Research design: Quasi experimental research design was used.Setting: The study was conducted at outpatient clinic & internal medicine department at Minia university hospital. Subjects a purposive sample of one hundred diabetic women who suffered from sexual dysfunctions.Tools of data collection: Two tools were used as following: 1- A structured interviewing questionnaire, 2- The Female Sexual Function Index scale to measures sexual function of diabetic women.Results: The frequency of sexual dysfunction was more prevalent in diabetic women in which the mean age of studied women was (39.68 ± 6.2) years. There were statistically significant differences regarding to the Female Sexual Function Index total mean scores between pre and post six months of counseling sessions.Conclusion: Implementation of counseling sessions based on PLISSIT model had a significant effect in improving the sexual function among diabetic women in pre and after six months of sexual counseling.Recommendations: Applying ongoing educational programs based on PLISSIT model for diabetic women in all available diabetic clinics with preparation of secure environment to discuss sexual problems with women freely. In service educational programs for care givers on how to deal and manage various sexual dysfunctions for diabetic women by using PLISSIT counseling model.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".