How could discourse theories of identity formation critically engage patient-centered care in older adults?
Bibliographic record
Abstract
Purpose The purpose of this paper is to explore how discourse theories can contribute to the concept of identity formation within a patient- or person-centered care (PCC) orientation, to enable more critical engagement with PCC in older people. Design/methodology/approach This is a conceptual paper. Findings This paper concludes that the discourse literature has important insights for understanding identity formation in older people as operationalized in the context of PCC in three particular ways: accounting for multiplicity in patients’ identity; exploring “the devolution of responsibility” to address shifts in performing identities in clinical encounters; and attending to a “crisis of positioning” to engage empowerment discourse within a PCC philosophy. Originality/value Whilst a notion of patient identity is at the heart of PCC, the concept remains inconsistent and underdeveloped. This is particularly problematic for the quality of care in older adults, as PCC has become increasingly synonymous with care of older people. Discourse theories of identity formation can be used to critically engage with identity within the context of PCC, so as to develop more nuanced understandings of “the person” or “the patient,” with the potential to improve research into care for aging and older adults.
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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 | 0.045 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.009 | 0.058 |
| Scholarly communication | 0.016 | 0.030 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".