[The patient-centered interview and the way it is taught. What do family physicians who have recently received their degree think?].
Bibliographic record
Abstract
OBJECTIVE: To describe how family physicians perceive the patient-centred interview (PCI) and the way in which it is taught during residency training. DESIGN: Mailed survey. SETTING: Family physicians from a variety of practice settings in Quebec. PARTICIPANTS: Ninety-one family physicians who graduated from Laval University between 1996 and 1998. METHOD: Survey was conducted in 1999 using the modified Dillman method. The original questionnaire had mainly open-ended questions on perception of the PCI and learning activities associated with it during residency training. All qualitative data were subject to content analysis using triangulation strategies. MAIN FINDINGS: A PCI mainly involves exploring patients' experience of their illnesses; this helps physicians to better understand patients. Patients are more content with this type of interview and are, therefore, more likely to follow physicians' recommendations. Respondents reported the main drawback to be longer interview times; this was particularly true for emergency and walk-in care. The most useful learning activities during residency were reported to be supervision by direct observation and observation of supervisor-patient consultations. CONCLUSION: Patient-centred interviews enabled physicians to understand and help their patients better. Results of this study can help teachers who are developing and consolidating activities to teach residents how to conduct PCIs and how to integrate them into practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| 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".