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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

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Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
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Statistical Analysis: Overview01:11

Statistical Analysis: Overview

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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
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What is Variation?01:14

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
The range, standard deviation, standard error, and variance are the different measures of variation.
Range: The range is the difference between its maximum and...
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Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
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Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Data Validation01:15

Data Validation

144
Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
Key parameters for method validation include:
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Related Experiment Video

Updated: Jun 6, 2025

Using Continuous Data Tracking Technology to Study Exercise Adherence in Pulmonary Rehabilitation
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Variation in adherence measures as a function of calculation methods.

Jeffrey M Rohay1, Jacqueline M Dunbar-Jacob1

  • 1University of Pittsburgh, School of Nursing, Pittsburgh, PA, United States.

Frontiers in Pharmacology
|November 29, 2024
PubMed
Summary

Medication adherence rates differ significantly based on calculation methods (PILLCOUNT, DAILY, TIMING). Variability also differs, highlighting the importance of defining adherence measures in research.

Keywords:
adherencecalculation methodelectronic monitoringoperational definitionwithin patient variability

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Area of Science:

  • Pharmacology
  • Health Services Research

Background:

  • Medication adherence is crucial for managing comorbid conditions.
  • Existing operational definitions of medication adherence vary, potentially impacting study outcomes.

Purpose of the Study:

  • To compare different operational definitions of medication adherence.
  • To examine within-patient variability across these measures in patients with comorbid conditions.

Main Methods:

  • Electronically monitored adherence data were analyzed using three methods: PILLCOUNT, DAILY, and TIMING.
  • Measures were aggregated into six 30-day periods.
  • Within-patient variability was calculated for DAILY and TIMING adherence.

Main Results:

  • Adherence rates varied: PILLCOUNT (89%-92%), DAILY (79%-85%), and TIMING (62%-68%).
  • Within-patient variability was higher for TIMING (29%-35%) than for DAILY (20%-25%).

Conclusions:

  • The choice of adherence definition significantly impacts results and interpretation.
  • Variability measures offer a more comprehensive understanding of adherence patterns.
  • Future studies should specify the adherence calculation method used.