scholarly journals QUALITATIVE STUDY TO EXPLORE UPTAKE AND ACCEPTABILITY OF STEPPING ON FALL PREVENTION PROGRAM AMONG OLDER PEOPLE FROM CALD BACKGROUNDS

2015 ◽  
Vol 55 (Suppl_2) ◽  
pp. 641-642
Keyword(s):  
Qualitative Study ◽  
Older People ◽  
Fall Prevention ◽  
Prevention Program ◽  
Fall Prevention Program

scholarly journals Adoption of a Patient-Tailored Fall Prevention Program in Academic Health Systems: A Qualitative Study of Barriers and Facilitators

2020 ◽  
Vol 4 (2) ◽  
pp. 1-15
Author(s):  
Eileen J. Carter ◽  
◽  
Srijesa Khasnabish ◽  
Jason S. Adelman ◽  
Michael Bogaisky ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Health Systems ◽  
Fall Prevention ◽  
Prevention Program ◽  
Barriers And Facilitators ◽  
Academic Health ◽  
Fall Prevention Program

scholarly journals Can a multifactorial geriatric assessment predict older adult´s adherence to a fall prevention program?

2020 ◽  
Author(s):  
Renata dos Ramos Varanda ◽  
Erika Yukie Ishigaki ◽  
Maria Aquimara Zambone Magalhães ◽  
Adson da Silva Passos ◽  
Luiz Eugenio Leme ◽  
...  
Keyword(s):  
Older People ◽  
Fall Prevention ◽  
Prevention Program ◽  
Perceived Risk ◽  
Multivariate Regression ◽  
Risk Of Falling ◽  
Psychological Measures ◽  
Fall Prevention Program ◽  
High Adherence ◽  
Optimal Adherence

Abstract BackgroundThere is evidence in the literature of the effectiveness of multifactorial interventions in reducing the occurrence of falls in elderly residents in the community. However, low adherence to prevention programs is cited in the literature as a recurring problem, questioning the effectiveness and sustainability of these programs. The aim of this study is to compare subgroups of fallers with different levels of adherence to a multifactorial fall prevention program in terms of a broad range of sociodemographic, medical, disability, physical functioning, and psychological measures in a multifactorial geriatric assessment, and identify which of these measures explain optimal adherence.MethodsA prospective study conducted with two hundred and fifty-seven community-dwelling people aged ≥ 60 years who participated in a multifactorial fall prevention program. All participants underwent assessments on sociodemographic, medical, disability, physical functioning, and psychological measures. The presence on weekly sessions over 12 weeks was used to ascertain adherence. Subgroups of participants with low, moderate and high adherence were determined by k-means cluster analysis, and were compared regarding variables of interest. A multivariate regression analysis was conducted to identify participants with an optimal adherence (median; ≥ 10 sessions). ResultsParticipants with low (1 up to 4), moderate (5 up to 8) and high adherence (≥ 9 sessions) corresponded to 13.2%, 19.5% and 67.3%, respectively. Of all measures, only the low perceived risk of falling was able to discriminate subgroups of adherence. Multivariate regression analyses adjusted for covariates identified that older people with optimal adherence were less likely to be depressed and were more likely to present a higher score in a global cognition measure. Conclusions Implementation strategies should be undertaken to understand the views and beliefs of older people with low perceived risk of falling and offer person-centered rationale to increase engagement. Treating and closely monitoring older adults with depression early in the pathway of care for falls prevention so as to optimize enablers may promote adherence to programs.

Best Practices for Data Visualization: Creating and Evaluating a Report for an Evidence-Based Fall Prevention Program (Preprint)

2018 ◽  
Author(s):  
Srijesa Khasnabish ◽  
Zoe Burns ◽  
Madeline Couch ◽  
Mary Mullin ◽  
Randall Newmark ◽  
...  
Keyword(s):  
Literature Review ◽  
Best Practices ◽  
Implementation Science ◽  
Data Visualization ◽  
Systematic Literature Review ◽  
Fall Prevention ◽  
Prevention Program ◽  
Evidence Based ◽  
Data Display ◽  
Fall Prevention Program

BACKGROUND Data visualization experts have identified core principles to follow when creating visual displays of data that facilitate comprehension. Such principles can be applied to creating effective reports for clinicians that display compliance with quality improvement protocols. A basic tenet of implementation science is continuous monitoring and feedback. Applying best practices for data visualization to reports for clinicians can catalyze implementation and sustainment of new protocols. OBJECTIVE To apply best practices for data visualization to create reports that clinicians find clear and useful. METHODS First, we conducted a systematic literature review to identify best practices for data visualization. We applied these findings and feedback collected via a questionnaire to improve the Fall TIPS Monthly Report (FTMR), which shows compliance with an evidence-based fall prevention program, Fall TIPS (Tailoring Interventions for Patient Safety). This questionnaire was based on the requirements for effective data display suggested by expert Stephen Few. We then evaluated usability of the FTMR using a 15-item Health Information Technology Usability Evaluation Scale (Health-ITUES). Items were rated on a 5-point Likert scale from strongly disagree (1) to strongly agree (5). RESULTS The results of the systematic literature review emphasized that the ideal data display maximizes the information communicated while minimizing the cognitive efforts involved with data interpretation. Factors to consider include selecting the correct type of display (e.g. line vs bar graph) and creating simplistic reports. The qualitative and quantitative evaluations of the original and final FTMR revealed improved perceptions of the visual display of the reports and their usability. Themes that emerged from the staff interviews emphasized the value of simplified reports, meaningful data, and usefulness to clinicians. The mean (SD) rating on the Health-ITUES scale when evaluating the original FTMR was 3.86 (0.19) and increased to 4.29 (0.11) when evaluating the revised FTMR (Mann Whitney U Test, z=-12.25, P<0.001). CONCLUSIONS Best practices identified through a systematic review can be applied to create effective reports for clinician use. The lessons learned from evaluating FTMR perceptions and measuring usability can be applied to creating effective reports for clinician use in the context of other implementation science projects.

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