“Until you’re there… you don’t know how you’ll be”. a phenomenological study of the influence of lived experiences on beliefs and attitudes about being a patient.
Bibliographic record
Abstract
Canadians are worried about the future of the health care system, and provincial governments are questioning the ability of the existing system to support Canadians health care needs in the 21st Century(Industry Canada, 2011). Health care providers and system administrators are both driving and experiencing a paradigm shift; moving away from paternalism and toward an egalitarian approach. In order to practice patient centredness, health care providers must prioritize patient needs; provide information regarding treatments while taking patient preferences into account (Romanow, 2002). While there is a growing body of literature regarding patient centredness, there is scant information from the patient perspective. If the most effective and acceptable health services are those that realize the expectations of the users, this is an important area of study. Using phenomenological research methods and the theory of planned behaviour as a theoretical framework, the purpose of the study was to explore the influence of beliefs, attitudes and experiences on behaviour from the perspective of patients in primary health care or stroke rehabilitation. A second purpose was to explore the degree to which beliefs, attitudes and behaviour were similar between clinical contexts. The theory of planned behaviour was unsuitable for understanding peoples’ beliefs, attitudes and behaviour about being a patient. Being a patient was not a single, observable behaviour, but rather a set of contextually dependent strategies patients’ directed at a particular goal. The goal for each participant group was different; rehabilitation patients focused on the specific goal of recovery and discharge, while PHC patients focused on a broader goal of accessing and receiving best health care possible. These goals were reflected in their respective approaches to accessing health care services, an experience they described as socially oriented, governed and reinforced. Although patients described themselves as actively engaged, they did not approach each interaction with health care with a set of behavioural beliefs about being a patient. During the course of their participation, patients identified, developed and adopted strategies to assist in achieving the target; and evaluated those strategies more positively.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.027 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".