Integrating person-centred care and social justice: a model for practice with larger-bodied patients
Why this work is in the frame
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Bibliographic record
Abstract
Person-centred care (PCC) has been touted as a promising paradigm for improving patients' experiences and outcomes, and the overall therapeutic environment for a range of health conditions, including obesity. While this approach represents an important shift away from a paternalistic and disease-focused paradigm, we argue that PCC must be explicitly informed by a social justice lens to achieve optimal conditions for health and well-being. We suggest that existing studies on PCC for obesity only go so far in achieving social justice goals as they operate within a biomedical model that by default pathologises excess weight and predetermines patients' goals as weight loss and/or management, regardless of patients' embodied experiences and desires. There remains a dearth of empirical research on what social justice-informed PCC looks like in practice with larger patients. This interview study fills a research gap by exploring the perspectives of 1) health practitioners (n=22) who take a critical, social justice-informed approach to weight and 2) larger patients (n=20) served by such practitioners. The research question that informed this paper was: What are the characteristics of social justice-informed PCC that play out in clinical interactions between healthcare practitioners and larger-bodied patients? We identified five themes, namely: 1) Integrating evidence-based practice with compassionate, narrative-based care; 2) Adopting a curious attitude about the patient's world; 3) Centring patients' own wisdom and expertise about their conditions; 4) Working within the constraints of the system to advocate for patients to receive equitable care; 5) Collaborating across professions and with community services to address the multifaceted nature of patient health. The findings illustrate that despite participants' diverse perspectives around weight and health, they shared a commitment to PCC by upholding patient self-determination and addressing weight stigma alongside other systemic factors that affect patient health outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 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) | 0.000 | 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 it