Psychological Treatment of Major Depression: An Analysis of the Sexual Desire
Bibliographic record
Abstract
Objective: Sexual dysfunction is frequently reported as a side effect of many antidepressant medications.As a result, for those depressed patients to whom sexual desire is important, psychological treatment may be a better intervention.Thus, the present study aimed to determine the possible changes in sexual desire following psychological treatments in depression, when focus of therapy is not on sexual function.Methods: This is a quasi-experimental study, which was conducted in Tehran, Iran.A total of 281 depressed patients in the remission phase underwent psychological treatments, either cognitive behavioral therapy (CBT, n=131) or mindfulness-based cognitive therapy (MBCT, n=150).The therapy did not focus on any aspect of sexual function.Using a single item measure before and after treatment, sexual desire of the patients was categorized into intact, mild, moderate, or severe decline.A total of 255 participants completed the study questionnaires and were randomly assigned to CBT (122) and MBCT groups (133).Before therapy, 128(50.2%)participants were categorized in intact sexual desire group, 73(28.6%) in mild sexual desire dysfunction group, 40(15.7%) in moderate sexual desire dysfunction group, and 14(5.5%) in severe sexual desire dysfunction group.Logistic regression was used for analyzing the data by SPSS-16.Results: Low sexual desire in depression remission was predicted by age (P<0.001,OR=0.21,CI=0.01-0.03),presence of comorbid anxiety disorder (P<0.04,OR=-0.13,CI=-0.46-0.02),and global assessment of functioning (GAF) (P<0.001,OR=-0.23,CI=-0.03-0.01).Clinical improvement in sexual desire was predicted by the type of intervention (P=0.023,OR=0.351,CI=0.142-0.869)and GAF (P=0.003,OR=0.927,CI=0.881-0.975).Conclusion: CBT might be superior to MBCT in improving sexual desire in patients with depression.Further studies using validated sexual function questionnaires are necessary.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".