Figuring it Out in the Moment: A Theory of Unregulated Care Providers' Knowledge Utilization in Dementia Care Settings
Bibliographic record
Abstract
BACKGROUND: Within the context of knowledge translation, the disconnect between the results of research and the practice patterns of nursing care providers has not been reported in the context of institutional dementia care practice. Therefore, little is known about how knowledge about best dementia care practice, defined broadly as the person-centered approach, gets used by institutional nursing care providers. AIM: Unregulated care providers provide the majority of nursing care for older people with Alzheimer's disease and related disorders living in long-term care facilities. The purpose of this grounded theory study was to explore the process whereby these workers use knowledge about person-centered care in their dementia care practice. METHODS: Transcribed data from tape-recorded interviews with 20 unregulated care providers among eight long-term care facilities in Ontario, Canada, were coded and categorized at progressively more abstract levels until concepts and the relationships among them were integrated in a middle-range theory of knowledge utilization. RESULTS: The theory of Figuring it Out in the Moment illustrates how unregulated care providers in dementia care settings practice in the context of unpredictability, variability, and personal threat. Their use of knowledge about person-centered care is dependent on the existence of certain individual and relational conditions that interrelate with four separate, but interconnected, phases of clinical decision-making and action. CONCLUSIONS: As a middle-range theory, Figuring it Out in the Moment is concrete and pragmatic information for promoting evidence-based dementia care not included in existing overarching knowledge utilization frameworks. Areas for further investigation include how knowledge utilization is conceptualized, as well as the influences of practitioners' clinical decision-making, the nature of caregiving with particular client populations, and the characteristics of individuals alone and in relationship on the utilization of best practice knowledge.
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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 | 0.017 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.009 | 0.069 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| 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".