Understanding why adolescents decide to visit family physicians: qualitative study.
Bibliographic record
Abstract
OBJECTIVE: To understand why Canadian adolescents go or do not go to see family physicians for annual checkups using the Theory of Planned Behavior as a conceptual framework. DESIGN: Qualitative analysis of small group discussions. SETTING: Edmonton, Alta, a large Canadian city. PARTICIPANTS: Seventeen adolescents (6 male, 11 female) recruited from a medical clinic and an organized youth group. METHOD: Two small group discussions and one validation focus group were held. A combination of category coding and thematic analysis was used to analyze the data transcribed. MAIN FINDINGS: Adolescents reported that regular checkups, although uncomfortable, are a good idea. They also reported that going to a family doctor for a checkup is out of their control because of numerous barriers (eg, lack of time, not knowing how to set it up, or lack of transportation). Participants thought their parents' opinions on going for routine checkups were more important than the opinions of their peers. CONCLUSION: Family physicians should recognize adolescents' attitudes toward visiting family physicians' offices and understand the potential barriers adolescents face in coming in for checkups in order to make visits to their offices more comfortable and beneficial.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".