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Record W4387932205 · doi:10.1136/bmjopen-2023-073585

Evaluation of the Strengthening a Palliative Approach in Long Term Care (SPA-LTC) programme: a protocol of a cluster randomised control trial

2023· article· en· W4387932205 on OpenAlexafffund
Sharon Kaasalainen, Abigail Wickson‐Griffiths, Paulette V. Hunter, Genevieve Thompson, Julia Kruizinga, Lynn McCleary, Tamara Sussman, Lorraine Venturato, Sally Shaw, Sheila A. Boamah, Valérie Bourgeois-Guérin, Thomas Hadjistavropoulos, Marilyn Macdonald, Ruth Martin‐Misener, Susan McClement, Deborah Parker, Jamie Penner, Jenny Ploeg, Shane Sinclair, Kathryn Fisher

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsDalhousie UniversityUniversity of CalgaryUniversity of ReginaMcGill UniversityBrock UniversityUniversity of ManitobaUniversité du Québec à MontréalMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicineLong-term carePalliative careProtocol (science)Term (time)Cluster (spacecraft)Randomized controlled trialCluster randomised controlled trialGerontologyNursingAlternative medicineSurgeryPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Despite the high mortality rates in long-term care (LTC) homes, most do not have a formalised palliative programme. Hence, our research team has developed the Strengthening a Palliative Approach in Long Term Care (SPA-LTC) programme. The goal of the proposed study is to examine the implementation and effectiveness of the SPA-LTC programme. METHODS AND ANALYSIS: A cross-jurisdictional, effectiveness-implementation type II hybrid cluster randomised control trial design will be used to assess the SPA-LTC programme for 18 LTC homes (six homes within each of three provinces). Randomisation will occur at the level of the LTC home within each province, using a 1:1 ratio (three homes in the intervention and control groups). Baseline staff surveys will take place over a 3-month period at the beginning for both the intervention and control groups. The intervention group will then receive facilitated training and education for staff, and residents and their family members will participate in the SPA-LTC programme. Postintervention data collection will be conducted in a similar manner as in the baseline period for both groups. The overall target sample size will be 594 (297 per arm, 33 resident/family member participants per home, 18 homes). Data collection and analysis will involve organisational, staff, resident and family measures. The primary outcome will be a binary measure capturing any emergency department use in the last 6 months of life (resident); with secondary outcomes including location of death (resident), satisfaction and decisional conflict (family), knowledge and confidence implementing a palliative approach (staff), along with implementation outcomes (ie, feasibility, reach, fidelity and perceived sustainability of the SPA-LTC programme). The primary outcome will be analysed via multivariable logistic regression using generalised estimating equations. Intention-to-treat principles will be used in the analysis. ETHICS AND DISSEMINATION: The study has received ethical approval. Results will be disseminated at various presentations and feedback sessions; at provincial, national and international conferences, and in a series of manuscripts that will be submitted to peer-reviewed, open access journals. TRIAL REGISTRATION NUMBER: NCT039359.

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)0.104
metaresearch head score (Gemma)0.077
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.104
Threshold uncertainty score0.548

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1040.077
Meta-epidemiology (narrow)0.0070.004
Meta-epidemiology (broad)0.0100.007
Bibliometrics0.0040.006
Science and technology studies0.0040.005
Scholarly communication0.0060.004
Open science0.0050.003
Research integrity0.0090.010
Insufficient payload (model declined to judge)0.0520.011

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 head0.209
GPT teacher head0.532
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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2023
Admission routes2
Has abstractyes

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