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SCOPE: safer care for older persons (in residential) environments—a pilot study to enhance care aide-led quality improvement in nursing homes

2022· other· en· W6921478046 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFigshare · 2022
Typeother
Languageen
FieldEngineering
TopicPhysics and Engineering Research Articles
Canadian institutionsUniversity of TorontoYork UniversityAthabasca UniversityUniversity of CalgaryUniversity of AlbertaUniversity of Manitoba
Fundersnot available
KeywordsCoachingPsychological interventionSAFERQuality managementRubricIntervention (counseling)Minimum Data SetQuality (philosophy)Nursing homesLong-term care

Abstract

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Abstract Background Nursing home residents require daily support. While care aides provide most of this support they are rarely empowered to lead quality improvement (QI) initiatives. Researchers have shown that care aide-led teams can successfully participate in a QI intervention called Safer Care for Older Persons in Residential Care Environments (SCOPE). In preparation for a large-scale study, we conducted a 1-year pilot to evaluate how well coaching strategies helped teams to enact this intervention. Secondarily, we measured if improvements in team cohesion and communication, and resident quality of care, occurred. Methods This study was conducted using a prospective single-arm study design, on 7 nursing homes in Winnipeg Manitoba belonging to the Translating Research in Elder Care research program. One QI team was selected per site, led by care aides who partnered with other front-line staff. Each team received facilitated coaching to enact SCOPE during three learning sessions, and additional support from quality advisors between these sessions. Researchers developed a rubric to evaluate how well teams enacted their interventions (i.e., created actionable aim statements, implemented interventions using plan-do-study-act cycles, and used measurement to guide decision-making). Team cohesion and communication were measured using surveys, and changes in unit-level quality indicators were measured using Resident Assessment Instrument-Minimum Data Set data. Results Most teams successfully enacted their interventions. Five of 7 teams created adequate-to-excellent aim statements. While 6 of 7 teams successfully implemented plan-do-study-act cycles, only 2 reported spreading their change ideas to other residents and staff on their unit. Three of 7 teams explicitly stated how measurement was used to guide intervention decisions. Teams scored high in cohesion and communication at baseline, and hence improved minimally. Indicators of resident quality care improved in 4 nursing home units; teams at 3 of these sites were scored as ‘excellent’ in two or more enactment areas, versus 1 of the 3 remaining teams. Conclusions Our coaching strategies helped most care aide-led teams to enact SCOPE. Coaching modifications are needed to help teams more effectively use measurement. Refinements to our evaluation rubric are also recommended.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.791
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0250.000

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 head0.023
GPT teacher head0.309
Teacher spread0.286 · 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