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Related Concept Videos

Data Collection I01:30

Data Collection I

Data collection gathers information needed to make accurate judgments about a patient's present condition. During a health history interview, subjective data is collected from the patient, their caregivers, or family members, and objective data is collected through observations and physical assessment. Patients are the primary source of subjective data. Thus information gathered from patients through interviews, observations, and physical examination is primary data. Secondary sources of data...
Data Reporting and Recording01:24

Data Reporting and Recording

Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
Measures of Central Tendency02:16

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The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians, "average" is commonly accepted for "arithmetic mean."
Archival Research01:40

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
Central Tendency: Analysis01:10

Central Tendency: Analysis

Measures of central tendency are tools used in biostatistics to identify the average or center of a dataset. They offer a single representative value for understanding and summarizing data distribution.
The mean is one such measure, calculated by totaling all values in a dataset and dividing by the number of values. For instance, the mean blood pressure reading (120, 130, 140, 150) would be 135. However, the mean can be affected by extreme values or outliers.
The median, another measure,...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

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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The Participant-Reported Implementation Update and Score (PRIUS): A Novel Method for Capturing Implementation-Related Data Over Time
06:05

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Published on: February 19, 2021

Paradata: a new data source from web-administered measures.

Azizeh K Sowan1, Louise S Jenkins

  • 1School of Nursing, Hashemite University, Zarqa, Jordan.

Computers, Informatics, Nursing : CIN
|October 28, 2010
PubMed
Summary
This summary is machine-generated.

Web-administered measures generate valuable paradata, offering insights into respondent behavior and improving data collection. This data aids in refining online surveys and enhancing user experience in health research.

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Area of Science:

  • Health Informatics
  • Survey Methodology
  • Human-Computer Interaction

Background:

  • Web administration of surveys offers efficient data collection but generates unique by-products called paradata.
  • Paradata provide insights into how respondents access and navigate online surveys, crucial for understanding the measurement process.

Purpose of the Study:

  • To define, generate, and explore the uses of paradata in Web-administered measures.
  • To highlight the significance of paradata for nursing and health researchers.
  • To address ethical considerations and challenges associated with paradata collection and utilization.

Main Methods:

  • Focuses on paradata generated from Web-administered measures, including server-side and client-side data.
  • Discusses the application of paradata in refining survey design, response formats, and navigation.
  • Examines the use of paradata for testing the usability of health information systems.

Main Results:

  • Paradata are essential for informing response format choices and examining adherence to prescribed sequences.
  • Paradata assist in designing effective Web-administered measures, optimizing layout, and determining appropriate login procedures.
  • The study underscores the critical role of paradata in improving the overall measurement process and system usability.

Conclusions:

  • Paradata offer a valuable resource for enhancing the quality and efficiency of Web-administered measures in health research.
  • Understanding and utilizing paradata can lead to more robust data collection and improved user experiences.
  • Ethical considerations must be carefully managed when collecting and using paradata to ensure respondent privacy and data integrity.