OP-8 What support do care home staff need when supporting residents at the end of life?
Bibliographic record
Abstract
Introduction Providing care towards the end of life is a core aspect of care home work, although one that often goes under recognised. Existing research focusses on needs of residents and families during this difficult time. Research addressing care home staff tends to focus on technical training needs, with emotional impact only considered in the context of the negative implications of poor training and support for staff burnout, turnover and ill-health, (Schultz, 2017; Vandrevala 2017; Barrie 2020). Whilst implementing a model of excellence in end-of-life care for Hallmark Care Homes, the emotional weight for staff of providing such care became apparent, prompting a search for evidence-based solutions. In the absence of established practical solutions, we undertook a Home Action Research Project, in which Hallmark’s researcher-in-residence supported a team of co-researchers within a single care home to design and carry out their own research into this area. Aims This research aimed to identify the support required by care home staff when providing end of life care for residents. Methods Co-producing the research design with care home staff, a variety of data collection methods maximised the engagement of staff with different work experiences, confidence and cultural backgrounds. These included traditional methods such as a survey and interviews alongside more creative methods including collaging, photo-voice and journalling. More than 30 team members shared their experiences and preferences for support. Results Findings established a need to raise organisational awareness of staff narratives of end-of life-care and identified actions that enhance or diminish staff’s receipt of necessary support. Conclusion and Impact This presentation will share the key findings, including the Staff Support Intervention designed as a result of the findings: a set of practical steps care home organisations can implement to ensure a supportive environment for staff who provide end of life care for residents. References Barrué P, Sánchez-Gómez M. La experiencia emocional de enfermeras de la unidad de hospitalización adomicilio en cuidados paliativos: un estudio cualitativo exploratorio. Enfermeria Clínica 2020;31:211–221 https://doi.org/10.1016/j.enfcli.2020.11.006 Schultz M. Taking the lead: supporting staff in coping with grief and loss in dementia care. Healthcare Management Forum 2017;30(1):16–19 Vandrevala T. et al. Perceived needs for support among care home staff providing end of life care for people with dementia: a qualitative study. International Journal of Geriatric Psychiatry 2017;32:155–163
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.003 |
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".