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Related Concept Videos

Self-Report Tests of Personality01:22

Self-Report Tests of Personality

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Self-report inventories are objective personality assessments that use multiple-choice items or numbered scales, typically ranging from 1 (strongly disagree) to 5 (strongly agree). They are often called Likert scales after Rensis Likert. These inventories are widely used due to their ease of administration and cost-effectiveness. One of the most prominent examples is the Minnesota Multiphasic Personality Inventory (MMPI), initially developed in the 1940s to assess abnormal personality traits.
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The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
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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.
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Every measurement provides three kinds of information: the size or magnitude of the measurement (a number), a standard of comparison for the measurement (a unit), and an indication of the uncertainty of the measurement. While the number and unit are explicitly represented when a quantity is written, the uncertainty is an aspect of the errors in the measurement results.
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Thoughts About Measuring Concepts: Using Single-Item Indicators and Multiple-Item Indicators.

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This study compares single-item versus multi-item measures for assessing concepts. Data from a pilot study on high-risk childbearing women and partners inform the discussion on measurement validity.

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Area of Science:

  • Health Sciences
  • Psychometrics
  • Sociology

Background:

  • Assessing complex concepts in health research often involves choosing between single-item and multi-item measures.
  • The validity and reliability of these measurement approaches can significantly impact study findings.
  • Understanding measurement properties is crucial for accurate data interpretation in clinical and social science research.

Purpose of the Study:

  • To discuss the psychometric properties of single-item versus multi-item measures.
  • To evaluate the utility of different measurement strategies in the context of functional status.
  • To explore correlates of functional status in a population experiencing high-risk childbearing.

Main Methods:

  • A cross-sectional pilot study was conducted.
  • Data were collected from women and their male partners undergoing high-risk childbearing.
  • Statistical analyses were performed to examine correlates of functional status using both single-item and multi-item measures.

Main Results:

  • Preliminary findings suggest differences in the information captured by single-item versus multi-item measures.
  • The study identified specific correlates of functional status within this population.
  • The data provide insights into the performance of different measurement approaches.

Conclusions:

  • The choice of measurement (single-item vs. multi-item) has implications for understanding functional status.
  • Further research is needed to validate measurement tools in diverse populations.
  • Measurement strategy is a critical consideration in research on high-risk childbearing and functional status.