Mapping Core Concepts of Person-Centered Care in Long-Term Services and Supports
Bibliographic record
Abstract
Person-centered care (PCC) has a wide range of definitions, most based on expert opinion rather than empirical analysis. The current study used an empirical concept mapping approach to identify core components of PCC used in long-term services and supports (LTSS). The aim is to help providers and researchers develop a unified set of domains that can be used to assess and improve the quality of PCC in real-world settings. Results yielded six domains describing essential elements of PCC in LTSS: Enacting Humanistic Values, Direct Care Worker Values, Engagement Facilitators, Living Environment, Communication, and Supportive Systems; and two underlying dimensions: Intrapersonal Activities and Extrapersonal Services and Social and Physical Environment. Nurses can use the results to enhance clinical knowledge and skills around delivery of PCC. Researchers can use the results to build a comprehensive and unified measure to accelerate adoption of PCC practices shown to benefit older adults, families, and the LTSS workforce. [Journal of Gerontological Nursing, 45(2), 6-13.].
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".