Family Physicians’ Experiences of Physical Examination
Bibliographic record
Abstract
PURPOSE: The increased availability of reliable diagnostic technologies has stimulated debate about the utility of physical examination in contemporary clinical practice. To reappraise its utility, we explored family physicians' experiences. METHODS: Guided by principles of phenomenology, we conducted in-depth qualitative interviews exploring 16 family physicians' experiences of conducting physical examination: 7 (44%) men and 9 women (56%) whose clinical experience varied widely, from 11 (69%) urban and 5 (31%) rural locations. We recorded the interviews, transcribed them verbatim, and identified initial themes using template analysis. We worked reflexively, critiquing our own and other team members' interpretations, in order to synthesize and write a final interpretation. RESULTS: Participants described 2 facets of physical examination: making diagnoses and estimating prognoses rationally and objectively; and responding subjectively and intuitively to patients' illnesses, which formed relationships between doctor and patient that enacted medical care in the moment. Physical examination allowed physicians to use their own bodies to experience patients' illnesses. Performing physical examination was integral to being a family doctor because it promoted rapport and developed trust. CONCLUSIONS: Physical examination is part of the identity of family physicians. It not only contributes diagnostic information but is a therapeutic intervention in and of itself. Physical examination contributes to relationship-centered care in family practice.
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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 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".