“Little things matter!” Exploring the perspectives of patients with dementia about the hospital environment
Bibliographic record
Abstract
BACKGROUND: Recognising demographic changes and importance of the environment in influencing the care experience of patients with dementia, there is a need for developing the knowledge base to improve hospital environments. Involving patients in the development of the hospital environment can be a way to create more responsive services. To date, few studies have involved the direct voice of patients with dementia about their experiences of the hospital environment. DESIGN AND METHOD: Using an action research approach, we worked with patients with dementia and a team of interdisciplinary staff on a medical unit to improve dementia care. The insights provided by patients with dementia in the early phase shaped actions undertaken at the later stage to develop person-centred care within a medical ward. We used methods including go-along interviews, video recording and participant observation to enable rich data generation. AIM: This study explores the perspectives of patients with dementia about the hospital environment. RESULTS: The participants indicated that a supportive hospital environment would need to be a place of enabling independence, a place of safety, a place of supporting social interactions and a place of respect. CONCLUSIONS: Patient participants persuasively articulated the supportive and unsupportive elements in the environment that affected their well-being and care experiences. They provided useful insights and pointed out practical solutions for improvement. Action research offers patients not only opportunities to voice their opinion, but also possibilities to contribute to hospital service development. IMPLICATIONS FOR PRACTICE: This is the first study that demonstrates the possibility of using go-along interviews and videoing with patients with dementia staying in a hospital for environmental redesign. Researchers, hospital leaders and designers should further explore strategies to best support the involvement of patients with dementia in design and redesign of hospital environments.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".