Challenges of person-centred dementia care : a critical ethnography of culture change in long-term care
Bibliographic record
Abstract
To address shortcomings in traditional long-term residential care (LTRC), facilities are increasingly adopting person-centred care (PCC) approaches. Despite the proliferation of PCC models and discourses, there is limited understanding in gerontology of how such approaches are experienced on the ground. This dissertation addresses this gap through an ethnographic study of Cedar Grove, a large facility located in an urban centre in Western Canada that is undergoing culture change. During 12 months of fieldwork, I explored the range of issues this organization encountered as it endeavours to maintain the “person” at the centre of care. The purpose of this study is to contribute empirical data on how this orientation shapes daily life for residents, families, staff and administrators. This study is informed by the literatures of PCC and personhood theory, and it draws on a conceptual framework integrating critical, feminist and Foucauldian gerontology. It analyzes care across personal, interpersonal, and organizational levels, and considers the broader social-political-economic context of LTRC. Data generation employs multiple methods: participant observation, Dementia Care Mapping (DCM), group meetings, individual interviews, researcher-produced photographs, and a review of relevant organizational and policy documents. Findings reveal organizational tensions between ideals of safety and PCC, multifaceted challenges to relational care, and the importance of everyday activity toward social inclusion. Data suggest five key implications: 1) Intersectionality highlights residents’ disparate access to social inclusion and ways to support more heterogeneous populations, 2) Increased access to unstructured, everyday activity might address boredom and foster meaning in residents’ lives, 3) Job descriptions might better prioritize social care and flexibility in work roles to better address issues of time constraints, workload, and resident acuity, all of which challenge PCC, 4) Organizational support for narrative-based biography is vital to overcoming systemic barriers to its use in practice. Finally, 5) A methodological implication of this study relates to how DCM facilitated insight into residents’ non-verbal expressions of personhood and bodily, affective communications. The mobilization of this research to practice during fieldwork highlights DCM’s ability to convey positive practice skills in a way that supports uptake, positively impacting residents’ quality of life.
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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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.026 | 0.036 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| 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".