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Record W4395077222 · doi:10.1007/s12062-024-09448-7

Contextual Action Theory in Nursing Home Settings: A Conceptual Framework for Considering the Active Role of Residents

2024· article· en· W4395077222 on OpenAlexafffund
Charlotte Jensen, Stephanie Chamberlain, Sheila K. Marshall, Richard A. Young, Matthias Hoben, Andrea Gruneir

Bibliographic record

VenueJournal of Population Ageing · 2024
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsYork UniversityUniversity of British ColumbiaUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsPersonhoodConceptual frameworkPerspective (graphical)RationalityAction (physics)CitizenshipNursing homesPsychologyAction researchCognitionNursingSociologyGerontologySocial psychologyMedicineEpistemologyPolitical scienceSocial sciencePedagogy

Abstract

fetched live from OpenAlex

Nursing home (NH) residents are often considered passive recipients of care with a limited role in shaping their experience. This perspective is often reproduced in NH research, which restricts resident participation, thereby upholding ageist views that cause discrimination of older adults living in NH settings. In this article, we propose using Contextual Action Theory (CAT) as a conceptual framework for exploring NH experiences in a way that incorporates the active role of residents. CAT supports the active role of NH residents by emphasizing the capabilities of human beings to form preferences and act on those preferences, without assumptions of rationality. The emphasis on human action allows researchers to consider NH experiences as co-constructed between residents, care providers, and family members, which means placing an emphasis on the actions and goals of NH residents, no matter their cognitive or physical impairments. CAT also supports personhood and social citizenship concerns in NH research, by acknowledging the differing preferences and thereby differing experiences of NH care by individual residents. We argue that CAT should be considered a useful framework for putting residents in the center of NH research.

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 imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0050.038
Scholarly communication0.0080.008
Open science0.0030.007
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.431
Teacher spread0.384 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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