Phenomenological shifts for healthcare professionals after experiencing a research‐based drama on living with dementia
Bibliographic record
Abstract
AIM: The aim of this article is to report research findings describing phenomenological shifts, that is, changes in patterns of lived experience, for healthcare professionals who attended a performance of a research-based drama, called I'm Still Here. BACKGROUND: The research drama, based on six studies, was created to help change the ways persons understand, think about and relate with persons living with dementia. METHODS: In 2006-2007, 50 healthcare professionals from various disciplines and eight nursing students participated in this study. Participants were recruited from four Canadian cities in the province of Ontario where focus groups were held before and after engaging in a live performance of I'm Still Here. FINDINGS: Analysis of focus group transcripts showed shifts in patterns of lived experience for the healthcare professional participants as evident in the participants' descriptions. The phenomenological shifts reflected a move from descriptions of 'diminishing humanness to discerning humanness', from 'disengaged care/mundane relating to reflexive relating in the now', and 'terrifying portrayals of loss to awakening to hopeful possibility'. The shifts described herein are supported with examples from the focus group transcripts. CONCLUSIONS: Findings reveal the power of drama as a vibrant and meaningful means of shifting understandings, images and intended actions of healthcare professions which have the potential to affect the lived experiences, relationships and quality of life of persons with dementia.
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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 | 0.010 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".