The person in the room: How relating holistically contributes to an effective patient-care provider alliance
Bibliographic record
Abstract
The purpose of this paper is to explore how relating to the 'whole' person--both the physical body and the invisible aspects of the 'self'--is essential in the establishment of a strong therapeutic alliance between patients and health care providers. Our work is based on interviews conducted with individuals affected by neurological illnesses (patients and family care providers). Hsieh and Shannon's (2005) conventional content analysis was used to analyze the data. Under the broad theme of 'maintaining a coherent sense of self' we identified four distinct sub-themes related to interactions with health care providers. The results elucidate the more complex and deep needs of patients who must access care on an ongoing basis, and highlight the important role that care providers play in supporting individuals who are experiencing physical, spiritual and social losses. Care must attend to the deep needs of these individuals by communicating in a style that addresses both emotional and cognitive needs of patients, by thorough and holistic assessment and by appropriate referrals.
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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 | 0.026 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.022 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.022 |
| Research integrity | 0.004 | 0.006 |
| 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".