Reasons for not completing postvasectomy semen analysis.
Bibliographic record
Abstract
OBJECTIVE: To identify noncompliance rates for 3-month postvasectomy semen analysis (PVSA) in men who have undergone vasectomy and to explore the self-reported reasons for not completing the 3-month PVSA. DESIGN: Retrospective chart review followed by semistructured telephone interviews. SETTING: Two family medicine clinics in Saskatoon, Sask. PARTICIPANTS: Men from the clinics who had undergone vasectomy since 2009. A total of 99 patients completed telephone interviews. METHODS: After a review of electronic medical records at 2 family medicine clinics, patients who had undergone vasectomy since 2009 were identified. Upon review of their charts, the number of patients who did not have PVSA results on file was determined. Some of these men were contacted with a predetermined telephone script to discuss reasons for noncompliance. MAIN FINDINGS: The combined noncompliance rate for the 2 clinics was high (60.5%). Three main reasons for not completing the PVSA were identified among the patient responses. These included patients feeling too busy to complete PVSA, patients feeling confident in the physician or procedure immediately after vasectomy, and patients feeling the PVSA process was too inconvenient. Our high noncompliance rates are consistent with other literature. However, the findings might also have been affected by the proportion of patients who had completed their PVSA who were not included in the telephone sample. Rates differed between the 2 clinics; the clinic with the higher compliance rate acts as an academic practice, with more time for appointments and fewer patients being referred from other physicians. CONCLUSION: Noncompliance rates for PVSA in this study were high. Three main reasons for noncompliance were identified that might help guide counseling opportunities in the future.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".