How many patients should ideally be scanned during a short-term in-vivo study?

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Multiple Choice

How many patients should ideally be scanned during a short-term in-vivo study?

Explanation:
In a short-term in-vivo study, the aim is to gather sufficient data to assess the reliability and repeatability of bone densitometry measurements under controlled conditions. Scanning a larger number of patients tends to yield more statistically significant results, especially when evaluating the effects of certain variables or interventions over time. Selecting 15 patients and performing three scans on each is beneficial because it allows for a robust analysis of the measurements. This setup provides multiple data points from each patient, helping to account for intra-patient variability. A total of 45 scans (15 patients × 3 times) enhances the statistical reliability of the findings, making it easier to identify consistent patterns or changes in bone density measurements. This number of patients and repetitions strikes a balance between logistical feasibility and ensuring that the study is adequately powered to detect meaningful differences or trends in the data, which is essential in clinical research.

In a short-term in-vivo study, the aim is to gather sufficient data to assess the reliability and repeatability of bone densitometry measurements under controlled conditions. Scanning a larger number of patients tends to yield more statistically significant results, especially when evaluating the effects of certain variables or interventions over time.

Selecting 15 patients and performing three scans on each is beneficial because it allows for a robust analysis of the measurements. This setup provides multiple data points from each patient, helping to account for intra-patient variability. A total of 45 scans (15 patients × 3 times) enhances the statistical reliability of the findings, making it easier to identify consistent patterns or changes in bone density measurements.

This number of patients and repetitions strikes a balance between logistical feasibility and ensuring that the study is adequately powered to detect meaningful differences or trends in the data, which is essential in clinical research.

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