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Record W1980062255 · doi:10.1080/01621424.2013.757177

Engaging Home Health Care Providers in a Fall Prevention Best Practice Initiative

2012· article· en· W1980062255 on OpenAlexaff
Jay Shaw, Katharina Sidhu, Colleen Kearney, Mary Keeber, Sandra McKay

Bibliographic record

VenueHome Health Care Services Quarterly · 2012
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsToronto Rehabilitation Institute
Fundersnot available
KeywordsNursingBest practiceMedicineFocus groupHealth careFamily medicineSociology

Abstract

fetched live from OpenAlex

This article reports key findings regarding the engagement of home health care providers in the implementation of a fall prevention best practice initiative. Participants were 29 home health care providers from physiotherapy, occupational therapy, and nursing. Each participant completed a self-efficacy for evidence-based practice survey, and a smaller subgroup of volunteers participated in focus groups for each discipline individually. Findings suggest home health care providers value the implementation of best practice in everyday care, but may need to be highly involved in the development of best practice initiatives and implementation strategies to foster engagement with the initiative in everyday practice.

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 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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.159
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.001

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 head0.069
GPT teacher head0.484
Teacher spread0.415 · 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 teacher head, not a consensus.

Study designQualitative
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

Citations18
Published2012
Admission routes1
Has abstractyes

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