Conectar
Older age is one of the greatest risk factors of dementia, and the rural demographic is ageing in Canada. Compared with their urban counterparts, rural older adults often face unique challenges in accessing cognitive healthcare, which is exacerbated by a shortage of healthcare specialists, public transportation, finances, education, services and dispersed geography. This scoping review protocol outlines the methodology that will be used to examine the literature about the care priorities, service needs and lived experiences from the perspectives of rural older adults living with cognitive impairment and dementia in Canada.
Our scoping review protocol will follow the guidance of Arksey and O’Malley and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extensions for Scoping Reviews checklist. Our search strategy will identify relevant peer-reviewed literature in databases including Cumulated Index in Nursing and Allied Health Literature (CINAHL), EMBASE, PsycINFO, PubMed, Web of Science and Scopus. The database search dates for this scoping review will be from 1 January 2015 to 1 January 2025. The data will be charted by two reviewers using a standardised data extraction table. Inductive content analysis will be performed using a three-step process.
Given this scoping review will be an examination of the published literature, human subjects will not be included in this research. Therefore, ethics approval is not required. Knowledge mobilisation and dissemination strategies will include peer-reviewed journal articles, conference presentations, community workshops, newsletter articles and webinars. This study may provide valuable information for healthcare practitioners, community leaders and policymakers working to support people living with cognitive impairment and dementia in rural communities.
Our study aimed to (1) validate the accuracy of nursing mobility documentation and (2) identify the most effective timings for behavioural mapping.
We monitored the mobility of 55 inpatients using behavioural mapping throughout a nursing day shift, comparing the observed mobility levels with the nursing charting in the electronic health record during the same period.
Our results showed a high level of agreement between nursing records and observed mobility, with improved accuracy observed particularly when documentation was at 12 PM or later. Behavioural mapping observations revealed that the most effective timeframe to observe the highest levels of patient mobility was between 10 AM AND 2 PM.
To truly understand patient mobility, comparing nursing charting with methods like behavioural mapping is beneficial. This comparison helps evaluate how well nursing records reflect actual patient mobility and offers insights into the best times for charting to capture peak mobility. While behavioural mapping is a valuable tool for auditing patient mobility, its high resource demands limit its regular use. Thus, determining the most effective times and durations for observations is key for practical implementation in hospital mobility audits.
Nurses are pivotal in ensuring patient mobility in hospitals, an essential element of quality care. Their role involves safely mobilizing patients and accurately charting their mobility levels during each shift. For nursing practice, this research underscores that nurse charting can accurately reflect patient mobility, and highlights that recording the patient's highest level of mobility later in the shift offers a more precise representation of their actual mobility.
Strobe.
No Patient or Public Contribution.
Nurses routinely perform multiple risk assessments related to patient mobility in the hospital. Use of a single mobility assessment for multiple risk assessment tools could improve clinical documentation efficiency, accuracy and lay the groundwork for automated risk evaluation tools.
We tested how accurately Activity Measure for Post-Acute Care (AM-PAC) mobility scores predicted the mobility components of various fall and pressure injury risk assessment tools.
AM-PAC scores along with mobility and physical activity components on risk assessments (Braden Scale, Get Up and Go used within the Hendrich II Fall Risk Model®, Johns Hopkins Fall Risk Assessment Tool (JHFRAT) and Morse Fall Scale) were collected on a cohort of hospitalised patients. We predicted scores of risk assessments based on AM-PAC scores by fitting of ordinal logistic regressions between AM-PAC scores and risk assessments. STROBE checklist was used to report the present study.
AM-PAC scores predicted the observed mobility components of Braden, Get Up and Go and JHFRAT with high accuracy (≥85%), but with lower accuracy for the Morse Fall Scale (40%).
These findings suggest that a single mobility assessment has the potential to be a good solution for the mobility components of several fall and pressure injury risk assessments.
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