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Record W3017877606 · doi:10.1017/s0714980820000082

Stakeholder Engagement in Practice Change: Enabling Person-Centred Mealtime Experiences in Residential Care Homes

2020· article· en· W3017877606 on OpenAlexaff
Sienna Caspar, Erin Davis, Kelsey Berg, Susan E. Slaughter, Heather Keller, Peter Kellett

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsResearch Institute for AgingUniversity of WaterlooUniversity of AlbertaUniversity of Lethbridge
Fundersnot available
KeywordsStakeholder engagementStakeholderScale (ratio)PsychologySocial careIntervention (counseling)NursingPerson-centered careDementiaApplied psychologyMedicinePublic relationsHealth carePolitical scienceGeography

Abstract

fetched live from OpenAlex

Person-centred care is recognized as best practice in dementia care. The purpose of this study was to evaluate the effectiveness of a stakeholder engagement practice change initiative aimed at increasing the provision of person-centred mealtimes in a residential care home (RCH). A single-group, time series design was used to assess the impact of the practice change initiative on mealtime environment across four time periods (pre-intervention, 1-month, 3-month, and 6-month follow-up). Statistically significant improvements were noted in all mealtime environment scales by 6 months, including the physical environment (z = -3.06, p = 0.013), social environment (z = -3.69, p = 0.001), relationship and person-centred scale (z = -3.51, p = 0.003), and overall environment scale (z = -3.60, p = 0.002). This practice change initiative, which focused on enhancing stakeholder engagement, provided a feasible method for increasing the practice of person-centred care during mealtimes in an RCH through the application of supportive leadership, collaborative decision making, and staff engagement.

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)0.022
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0030.002
Open science0.0020.007
Research integrity0.0010.002
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 head0.100
GPT teacher head0.320
Teacher spread0.220 · 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 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

Citations21
Published2020
Admission routes1
Has abstractyes

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