Pediatricians' knowledge, perceptions, and attitudes towards providing health care for lesbian, gay, and bisexual adolescents.
Bibliographic record
Abstract
BACKGROUND: Pediatricians are often the first health-care contacts for gay, lesbian, and bisexual adolescents who are developing their sexual orientation. OBJECTIVE: This study investigated pediatricians' attitudes and practices towards gay, lesbian, and bisexual adolescents. METHOD: We sent anonymous self-administered questionnaires to 112 pediatricians in the Ottawa area. RESULTS: Of those who responded, 36 per cent reported having treated lesbian, gay, or bisexual patients, and 70 per cent reported not addressing the issue of sexual orientation. Reservations in discussing sexual orientation were due to fears of offending patients, and a lack of knowledge regarding their needs. Furthermore, 59 per cent of these pediatricians were unfamiliar with community resources for homosexual youths, and 78 per cent reported wanting more information with regards to the care of this population. CONCLUSION: Many pediatricians experience difficulties in discussing issues of sexual orientation, and generally feel inadequately prepared to address issues pertaining to the health-care needs of these adolescents. While certain issues remain controversial, the overall attitude of pediatricians towards homosexually oriented patients is positive in that they are interested in becoming more aware of issues of homosexual orientation, to better serve this population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".