Research Question:
How effective are different swallowing assessment tools (clinical versus instrumental) in predicting aspiration risk in stroke patients?
Provide an overview of swallowing assessment in stroke patients, highlighting the importance of predicting aspiration risk to prevent complications such as pneumonia or malnutrition. Discuss the distinction between clinical and instrumental assessment tools and their relevance in clinical practice.
The aim of this study is to compare the effectiveness of clinical versus instrumental swallowing assessment tools in predicting aspiration risk among stroke patients.
How effective are different swallowing assessment tools (clinical versus instrumental) in predicting aspiration risk in stroke patients?
Summarize key studies comparing clinical and instrumental tools, focusing on their predictive accuracy, reliability, and feasibility. Discuss the theoretical models underpinning swallowing assessment and risk prediction in stroke patients.
Design
Specify the research design (e.g., comparative observational study, randomized controlled trial) and justify its selection for addressing the research question.
Setting
Describe the healthcare setting where the study will be conducted, such as hospitals, rehabilitation centers, or outpatient clinics.
Sample
Define the target population, including inclusion and exclusion criteria (e.g., adults diagnosed with stroke). Specify the sampling method and sample size estimation.
Data Collection Instrument
Identify the clinical and instrumental tools to be used, such as bedside swallowing evaluations and videofluoroscopic swallowing studies.
Data Collection Procedure
Outline the step-by-step procedure for data collection, including participant recruitment, assessment administration, and any follow-up measures.
Proposed Analysis
Describe the statistical methods to compare the effectiveness of clinical versus instrumental tools, such as sensitivity, specificity, predictive values, and ROC curve analysis. Include plans for handling missing data and potential confounders.
