Discrepancies between the self-reporting of STI preventive care and the actual care provided by male doctors to male patients in Karnataka, India
Bibliographic record
Abstract
OBJECTIVE: To examine the discrepancies between the self-reporting of STI preventive care and the actual care provided by male doctors to male patients in several subdistricts of the state of Karnataka, south India. METHODS: Of 3376 allopathic medical practitioners (doctors) enumerated, 2846 were contacted in person. Doctors who saw at least five patients with STI a month were then interviewed (814). Further, 451 of these practitioners were visited by a 'surrogate patient.' Comparative analyses were conducted of items from the survey questionnaire and from the surrogate patient answer sheet that unambiguously tapped into the same information. RESULTS: Systematic differences in the self-report by the doctors and the report by the surrogate patients were found. For instance, 99% of practitioners reported examining the patients, whereas only 71% of surrogate patients reported being examined. 96% of practitioners reported advising condom use, whereas only 19% of surrogate patients reported receiving this advice. 97% of practitioners reported advising partner treatment, whereas only 10% of surrogate patients reported receiving this advice. Younger practitioners, doctors in rural centres and doctors with STI in-service training were more likely to be discordant in what they self-reported and what surrogate patients reported. CONCLUSIONS: The discrepancies between doctor self-reporting and surrogate patient observations bring into question the reliability of practitioner recall, suggesting that the use of self-reporting surveys should be reassessed.
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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 | 0.002 | 0.012 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".