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Record W7117295574 · doi:10.1002/alz70858_104091

Standardized Delirium and Dementia‐Friendly Mobile Comfort Carts to Increase Senior‐Friendly Non‐Pharmacologic Care

2025· article· en· W7117295574 on OpenAlexaff
Justin Y. Lee, Matteen Pezeskhi, Arianna R. Paolone, Christina Sanders, Susy Marrone, Shari Duxbury, Patricia Ford, Leanne Nightingale, Joye Anne St. Onge, Heather McLeod, Micheline Gagnon, Michele Patterson, Shawn Mondoux, Jane Loncke, Donna Johnson

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicIntensive Care Unit Cognitive Disorders
Canadian institutionsSt. Joseph’s Healthcare HamiltonMcMaster UniversitySt Joseph's Health CareHamilton Health SciencesSt Joseph's Health Centre
Fundersnot available
KeywordsDeliriumMEDLINEQuality of life (healthcare)mHealthHealth careTelemedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Hospital environments can be harmful to older adults and contribute to hospitalization-associated disability. To improve health outcomes, guidelines recommend more emphasis on non-pharmacological care to better address physical, emotional, cognitive, and rehabilitative needs of older adults. We sought to develop, implement and evaluate the use of standardized mobile 'Comfort Carts' containing non-pharmacological resources to enhance patient comfort, increase cognitive and physical stimulation, and help manage responsive behaviours associated with delirium and dementia. METHODS: A 'Comfort Cart' containing a standardized set of non-pharmacological resources for hospitalized older adults at risk of delirium and responsive behaviours associated with dementia was developed through multidisciplinary stakeholder consultations and a needs assessment survey of clinicians, patients, and hospital volunteers. Hospital volunteers were trained to use the 'Comfort Cart' to facilitate patient interactions and non-pharmacological care to all patients admitted to an orthopedic unit at a tertiary care academic hospital. We conducted daily program audits over a 1-year period and post-implementation surveys to evaluate its effectiveness and acceptability. RESULTS: The 'Comfort Cart' program has facilitated over 669 patient visits to date by hospital volunteers, including 50 with patients with dementia or those at high-risk for delirium and/or responsive behaviours. Over 168 hours of patient-volunteer interactions were logged with a mean visit duration per patient of 16.5 (SD 19.5) minutes. More than half of visits (58.1%) improved patients' mood or behaviour. The longer the duration of a visit, the higher the likelihood that it would improve a patient's mood or behaviour. In post-program implementation surveys, 76% of healthcare staff agreed that the 'Comfort Cart' addressed barriers for implementing non-pharmacological care and 80% of volunteers stated that the 'Comfort Cart' helped them have meaningful visits with patients. All patients and caregivers surveyed felt that the program was important to meet the needs of hospitalized older adults, and 91% reported that it positively contributed to the perceived level of compassionate and overall patient care that they received in hospital. CONCLUSIONS: Standardized mobile 'Comfort Carts' satisfy unmet non-pharmacological needs in the care of older adults and positively impact patient experience in hospital.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.300
Teacher spread0.290 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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