Patient-centredness in a context of increasing diversity: Location, location, location
Bibliographic record
Abstract
The concept of ‘patient-centredness’ is increasingly central inmedical education curriculum (Richards & Inglehart 2006;Tsimtsiou et al. 2007); yet, it is also well-recognised that thepatients whom we serve are becoming increasingly diverse. Inthis edition, Gustafson and Reitmanova (2010) call ourattention to the fact that the Canadian population is becomingincreasingly diverse, and the make-up of that diversity hasshifted over the past decades. This shift has significantinfluence in terms of how medical education is conceptualised,planned and delivered. Therefore, our commentary beginswith a question for consideration: What does it mean to bepatient-centred in a context of increasing diversity?Patient-centred care (PCC) (Stewart et al. 1995; Tsimtsiouet al. 2007) is an approach that privileges the social aspects byacknowledging that a patient is more than her or his biology,symptoms, and/or body. It is often defined by what it is not:‘technology centred, doctor centred, hospital centred, diseasecentred’ (Stewart 2001, p 444) and occurs ‘when medicalmanagement comprises more than a single pill’ (Bauman et al.2003, p 253).Despite institutional attempts to apply a patient-centredapproach, these remain frequently uncritically, or superficially,realised in medical education (Tsimtsiou et al. 2007).A dualistic sorting of knowledge into two main categories:objective (disease, evidence-based, competence) and subjec-tive (illness, social, caring) (Good & Good 1993; Morris 2000)is common in medical education. Despite calls for patient-centredness, patients’ accounts of the illness experiencefrequently fall under the subjective, thus untrustworthy,domain. In contrast, medical tests and laboratory reports areconsidered ‘factual’ because of their presumed objectivity. Thisreinscribes traditional relations of power in the physician–patient relationship.One knows, the other feels; one prescribes, the othercomplies; one is paid, the other pays. Although thissharp division has begun to blur under the pressureof postmodern innovations such as the ubiquitousmalpractice suit, the old conceptual infrastructurethat sustained it is still, confusingly, in place. (Morris2000, pp 37–38)Traditionally, medical education has been constitutedthrough the study of disease, understanding sickness as abreakdown of the machine that is the body. Toombs (1993,1995) encouraged a shift calling for an approach that considersillness an interruption of participation in the social world. Ifengaged in educational settings, such an understanding hasthe potential to transform medical practice, making the patient,not the disease, the focus of diagnosis and treatment.However, such a shift would require thoughtfulness aboutthe patients, and their multiple complexities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".