Delivering person-centred dementia care: Perceptions of radiography practitioners within diagnostic imaging and radiotherapy departments
Bibliographic record
Abstract
INTRODUCTION: Despite abundant literature on the diagnosis of dementia, limited research has explored the lived experiences of radiography practitioners when providing care to people living with dementia in the department. OBJECTIVES: This qualitative study explored the perceptions and compatibility of current professional guidance by both diagnostic imaging and radiotherapeutic radiography practitioners as well as the key stakeholders involved with developing the Society and College of Radiographers clinical practice guidelines for caring for people with dementia. METHODS: This was a two-phase multi-method study. Fifteen diagnostic imaging and two therapeutic radiography practitioners from across the UK participated with online focus group discussions. Four key stakeholders involved with the development of the Society and College of Radiographers guidelines took part with individual semi-structured interviews. Data analysis included narrative and thematic analysis. RESULTS: Participants from both phases identified enablers and barriers to providing person-centred dementia care. Three superordinate themes were identified linked to (1) Working with care partners, (2) Departmental environmental design, and (3) Communication and interprofessional infrastructure. DISCUSSION: Many radiography practitioners still feel unprepared when caring for people living with dementia despite the clinical practice guidelines. Care partners were identified as having the potential to help alleviate some of the challenges radiographers faced. Participants were also aware of the impact of the departmental environment and recognised that poor way finding designs could lead to frustration. Radiography practitioners were not always aware that a patient was living with dementia prior to their attendance in the department making it difficult for practitioners to make appropriate accommodations such as additional time at appointments or the departmental environment. Our findings suggest there is a need for profession specific education and training for radiography practitioners to support the provision of person-centred dementia care. There is also a need to support the design of dementia friendly diagnostic imaging and radiotherapy departments.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".