Canonical text (the exact bytes fingerprinted)

TRUVACE RECORD VERSION
record: TRV-2026-1342
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-10-14T18:13:11.842033Z
status: published
lens: g_space
sector: health
headline: Assessing AI Feasibility for Pain Evaluation in Hospitalized Cognitively Impaired Older Adults
dek: Purpose The objectives for this study were to examine the acceptability and feasibility of using the artificial intelligence-driven application PainChek Ⓡ to identify pain within older adults with cognitive impairment in the inpatient setting within Ontario. Design A prospective cohort design was used. Methods Six nurses were recruited and completed standardized training. Following the recruitment and onboarding of nurse participants, 25 patient participants were enrolled and assessed using the application. Once…
gain_title: In a small Ontario inpatient study, nurses found an AI-driven pain assessment app acceptable and feasible for identifying pain in older adults with delirium, cognitive impairment, or dementia.
problem_title: (none)
trace_subject: (none)
gain_reading: In a small Ontario inpatient study, nurses found an AI-driven pain assessment app acceptable and feasible for identifying pain in older adults with delirium, cognitive impairment, or dementia.
gain_evidence: it is acceptable and feasible to use PainChek Ⓡ within the older adult hospital setting
problem_reading: (none)
problem_evidence: (none)
quick_read: Researchers in Ontario tested PainChek, an artificial intelligence-driven application, as a way to detect pain in hospitalized older adults who have cognitive impairment. Six nurses completed standardized training and then used the app to assess 25 patients, after which they were interviewed about their experiences.

This matters because pain is hard to evaluate when patients cannot reliably describe it, and the study offers early evidence that a digital tool can fit into nursing practice. However, the sample was small and the authors say feasibility and scalability still need testing in real-world environments, and the study does not report how accurate the app's pain scores were.
limitation: The authors state that more research is needed to evaluate feasibility and scalability in real-world environments, and the study involved only six nurses and 25 patients.
tag: Evidence-backed gain
key_points: The study used a prospective cohort design in an inpatient setting in Ontario. | Six nurses were trained and 25 patients were enrolled and assessed with the app. | Among participants, 64% had dementia, 20% had cognitive impairment, and 16% had delirium. | Average length of stay in the study was 7.8 days, and average pain scores were in the mild range. | Nurse interviews were analyzed with descriptive content analysis and validated through member checking.
rundown: The research team recruited six nurses, gave them standardized training, and then enrolled 25 patients who were assessed using the PainChek application. Qualitative interviews with the nurses followed once patient data collection was finished.

Descriptive statistics were used for patient and nurse data. The cohort comprised mostly patients with dementia, with smaller groups with cognitive impairment and delirium, and pain scores averaged in the mild range during assessment.

Nurses' accounts were coded thematically using the nursing metaparadigm as the conceptual framework, and results were checked through member checking. The authors conclude the tool is acceptable and feasible in this hospital setting.
sources:
- peer_reviewed | Pain Management Nursing | https://doi.org/10.1016/j.pmn.2026.09.013 | 2026-10-03
prev: 0000000000000000000000000000000000000000000000000000000000000000

sha256

cbb218f182192ae383fdb339aca8720d6c38c93acebe78a58a0f695a79d6aa01

previous

0000000000000000000000000000000000000000000000000000000000000000