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Related Experiment Video

Updated: Nov 25, 2025

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Eavesdropping on Missing Data: What Are University Students Doing When They Miss Experience Sampling Reports?

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  • 1University of Pennsylvania, Philadelphia, USA.

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|December 21, 2020
PubMed
Summary

Missing data in experience sampling method (ESM) studies is a concern. This study found little evidence that missing reports from university students was linked to specific behaviors, supporting ESM research validity.

Keywords:
complianceecological momentary assessmentexperience sampling methodmissing datavalidity

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Area of Science:

  • Psychological Science
  • Methodology

Background:

  • Experience sampling method (ESM) studies rely on participant self-reports.
  • Non-response to ESM prompts can introduce missing data, potentially biasing results.
  • Understanding predictors of missing data is crucial for assessing the validity of ESM findings.

Purpose of the Study:

  • To investigate systematic predictors of missed reports in experience sampling method (ESM) studies.
  • To assess the impact of participant behavior on data completeness in ESM research.
  • To provide evidence regarding the validity of ESM data in student populations.

Main Methods:

  • Utilized the Electronically Activated Recorder (EAR) to unobtrusively record participant audio for one week.
  • Collected 3,678 audio observations to determine participant activities during missed and completed ESM reports.
  • Coded 46 variables from audio recordings to predict missing ESM reports from 228 university students.

Main Results:

  • Found minimal correlation between missing ESM reports and 46 coded behavioral variables.
  • Observed little evidence that specific participant activities predicted non-response to ESM prompts.
  • Data suggest that missing ESM reports in this sample were largely random.

Conclusions:

  • The findings provide reassurance for the validity of experience sampling method (ESM) research.
  • Missing data in ESM studies with similar student populations may not systematically threaten research inferences.
  • Further research can explore potential biases in diverse populations or with different ESM protocols.