Application of the Person-Centered Care to Manage Responsive Behaviors in Clients with Major Neurocognitive Disorders: A Qualitative Single Case Study
Bibliographic record
Abstract
OBJECTIVES: Our study aimed to describe "how" and "why" the person-centered care (PCC) approach was applied within a long-term care (LTC) community to manage responsive behaviors (RBs) in individuals with major neurocognitive disorders. METHODS: A descriptive holistic single case study design was employed in the context of an LTC community in Quebec, using semi-structured interviews and non-participatory observations of experienced care providers working with clients with RBs, photographing the physical environment, and accessing documents available on the LTC community's public website. A thematic content analysis was used for data analysis. RESULTS: The findings generated insight into the importance of considering multiple components of the LTC community to apply the PCC approach for managing RBs, including a) creating a homelike environment, b) developing a therapeutic relationship with clients, c) engaging clients in meaningful activities, and d) empowering care providers by offering essential resources. CONCLUSIONS: Applying and implementing the PCC approach within an LTC community to manage clients' RBs is a long-term multi-dimensional process that requires a solid foundation. CLINICAL IMPLICATIONS: These findings highlight the importance of considering multiple factors relevant to persons, environments, and meaningful activities to apply the PCC approach within LTC communities to manage RBs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".