Resident Reactions to Person-Centered Communication by Long-Term Care Staff
Bibliographic record
Abstract
Long-term care staff caregivers who are person centered incorporate the life history, preferences, and feelings of residents with dementia during care interactions. Communication is essential for person-centered care. However, little is known about residents' verbal reactions when staff use person-centered communication. Accordingly, this study investigated the impact of person-centered communication and missed opportunities for such communication by staff on resident reactions. Conversations (N = 46) between staff-resident dyads were audio-recorded during routine care tasks over 12 weeks. Staff utterances were coded for person-centered communication and missed opportunities. Resident utterances were coded for positive reactions, such as cooperation, and negative reactions, such as distress. Linear regression analyses revealed that the more staff used person-centered communication, the more likely that residents reacted positively. Additionally, the more missed opportunities in a conversation, the more likely that the residents reacted negatively. Conversation illustrations elaborate on the quantitative findings and implications for staff training are discussed.
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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 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".