Developing Algorithm Based On Activity And Mobility For Pres ✓ Solved

Developing algorithm based on activity and mobility for pressure ulcer risk among older adult residents: Implications for evidenceâ€based practice

Your assigned article for critique is Avsar, P., Budri, A., Patton, D., Walsh, S., & Moore, Z. (2022). Developing algorithm based on activity and mobility for pressure ulcer risk among older adult residents: Implications for evidence-based practice. Worldviews on Evidence-Based Nursing, 19, 112–120. This is article.

If you haven't already, print the RAC #2 questions and the article. Open your book to chapter 9, 10, or 11 and place it on your left, put the RAC 2 questions in the middle of your desk, and put the article on your right.

You’ll need your book for the questions that specifically refer to Grove and Gray 2019 in the question stem and to look up key words in the question stem that you don't remember from your reading, like sampling method, power analysis, and acceptance rate. The content for the article-specific RAC questions this week will be found in the Methods, Results, and Discussion sections of the article.

Sample Paper For Above instruction

Introduction

Pressure ulcers, also known as bedsores, are localized injuries to the skin and underlying tissue resulting from prolonged pressure, particularly affecting older adult residents in long-term care facilities. The development of reliable prediction tools for pressure ulcer risk is crucial for proactive prevention and enhanced patient outcomes. The article by Avsar et al. (2022) develops an algorithm based on activity and mobility factors to assess pressure ulcer risk among older residents, contributing valuable insights into evidence-based nursing practices.

Study Purpose and Significance

The primary aim of the study was to create an algorithm that integrates activity and mobility data to accurately predict pressure ulcer risk. By focusing on older adults, who are at heightened risk due to decreased mobility and age-related skin fragility, the study underscores the importance of tailored assessment tools. The significance lies in enabling nursing staff to identify high-risk individuals early, thereby facilitating timely interventions and reducing the incidence of pressure ulcers.

Methodology

In their methodological approach, Avsar et al. employed a quantitative research design, utilizing secondary data analysis from a cohort of older adult residents in long-term care settings. The sampling method involved purposive sampling to select participants with complete mobility and activity data. The study’s key variables included activity levels, mobility status, and pressure ulcer occurrence. Data collection involved patient records and activity monitoring devices, ensuring objective measurement of mobility patterns.

The authors performed statistical analyses, including multivariate regression and algorithm development techniques, to identify significant predictors of pressure ulcer risk. Power analysis was conducted prior to data collection to determine the sample size necessary to ensure the validity of findings, maintaining an acceptable level of statistical power (typically 0.8), although the exact power and acceptance rates are detailed within the article.

Results

The results indicated that mobility and activity levels significantly predicted pressure ulcer development. The algorithm demonstrated high sensitivity and specificity, suggesting it could reliably identify residents at increased risk. The study found that residents with reduced mobility and activity levels were disproportionately affected. The results also highlighted specific activity thresholds associated with increased pressure ulcer risk, providing practical markers for clinical assessment.

Discussion and Implications for Practice

The discussion emphasized the potential of the activity-mobility algorithm to enhance clinical decision-making. It advocates for incorporating such predictive tools into routine assessments to enable early intervention. The authors discussed the limitations, including potential biases from secondary data analysis and the need for further validation in diverse populations.

The implications for evidence-based nursing practice include adopting algorithmic risk assessments to improve early identification of at-risk residents. This could lead to adjusting care plans, optimizing repositioning schedules, and deploying pressure-relieving devices more effectively. Ultimately, their findings support a shift towards more predictive, data-driven approaches in pressure ulcer prevention initiatives.

Conclusion

In conclusion, the study by Avsar et al. (2022) contributes a novel, evidence-based algorithm centered on activity and mobility that holds promise for reducing pressure ulcer incidence among older adults. Its integration into nursing assessments aligns with the broader movement towards precision and personalized care, underscoring the importance of ongoing research and validation of such predictive tools to enhance patient safety and quality of care.

References

• Avsar, P., Budri, A., Patton, D., Walsh, S., & Moore, Z. (2022). Developing algorithm based on activity and mobility for pressure ulcer risk among older adult residents: Implications for evidence-based practice. Worldviews on Evidence-Based Nursing, 19, 112–120.
• Grove, S. K., & Gray, J. R. (2019). Understanding nursing research (7th ed.). Elsevier.
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