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Record W2913837122 · doi:10.3928/00989134-20190111-02

Mapping Core Concepts of Person-Centered Care in Long-Term Services and Supports

2019· article· en· W2913837122 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Gerontological Nursing · 2019
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsIntrapersonal communicationWorkforceSet (abstract data type)Gerontological nursingLong-term careOntologyPsychologyCore (optical fiber)ProtégéNursingQuality (philosophy)Knowledge managementComputer scienceMedicineInterpersonal communicationSocial psychologyWorld Wide Web

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.079
GPT teacher head0.407
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it