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Record W2099624942 · doi:10.1353/cja.2005.0065

Evaluation of the Restorative Care Education and Training Program for Nursing Homes

2005· article· en· W2099624942 on OpenAlexaff
Shanthi Johnson, Anita M. Myers, Gareth R. Jones, Clara Fitzgerald, Darien-Alexis Lazowski, Paul Stolee, J. B. Orange, Nicole Segall, Nancy A. Ecclestone

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2005
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsWestern UniversityUniversity of WaterlooAcadia University
Fundersnot available
KeywordsNursingIntervention (counseling)MedicineDependency (UML)Nursing homesPsychology

Abstract

fetched live from OpenAlex

Restorative care attempts to break the cycle of dependency and functional decline in nursing homes by addressing individual resident needs. The Restorative Care Education and Training (RCET) Program consists of a five-week workshop and resource manual for both supervisory and direct care staff. This paper describes the RCET approach and presents the implementation, process, and quasi-experimental outcome evaluation findings with 42 residents from six intervention sites and six ''wait-list'' facilities who received usual care. Baseline data supported the fact that staff primarily targeted residents with substantial functional impairments. Over four months, residents who received restorative care improved significantly on several functional outcome indicators, while the comparison sample declined in several areas of functioning. Interviews with facility directors and participating staff provided direction for modifying the RCET and insight regarding opportunities and challenges when implementing restorative care activities in nursing homes.

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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.044
GPT teacher head0.369
Teacher spread0.324 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations28
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicGeriatric Care and Nursing HomesFrench-language works237,207