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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Experience sampling methods require more than numbers.

Laura F Bringmann1, Guðrún R Guðmundsdóttir2, Leonie Schorrlepp3,4

  • 1Department of Psychometrics and Statistics, University of Groningen, Groningen, The Netherlands. l.f.bringmann@rug.nl.

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Summary
This summary is machine-generated.

Researchers should reintroduce open-ended questions in the experience sampling method (ESM) to gain deeper insights. Analyzing these text responses provides crucial context and understanding beyond numerical data alone.

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Area of Science:

  • Psychological research methods
  • Digital phenotyping
  • Qualitative data analysis

Background:

  • The experience sampling method (ESM) traditionally collects real-time data on feelings, actions, and surroundings.
  • Current ESM studies predominantly focus on numerical data, neglecting valuable qualitative insights.
  • Open-ended responses were historically part of ESM but are now underutilized.

Purpose of the Study:

  • To advocate for the renewed collection and analysis of open-ended responses in ESM research.
  • To emphasize the importance of qualitative data for interpreting quantitative ESM findings.
  • To highlight the limitations of purely numerical data in capturing experiential richness.

Main Methods:

  • Review of current practices in experience sampling methodology.
  • Argument for the integration of qualitative text analysis within ESM frameworks.
  • Identification of the unique contributions of open-ended data to psychological research.

Main Results:

  • Open-ended responses provide essential context, explaining the 'why' behind participants' experiences.
  • Qualitative data captures nuances like the temporal order of events that numbers alone cannot convey.
  • Integrating open-ended items enriches ESM data by grounding it in lived, real-world experiences.

Conclusions:

  • ESM research would benefit significantly from systematically collecting and analyzing open-ended text items.
  • Future research and methodological guidelines should prioritize the integration of qualitative data in ESM.
  • Reinstating open-ended questions is crucial for a more comprehensive understanding of human experience through ESM.