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<p>Despite the ubiquity of thin-slice coding for behavioral measurement, there exists relatively little systematic research into the convergent validity of thin-slice coding metrics for nonverbal behaviors when using human coders. This study utilized five previous datasets to measure four commonly-measured nonverbal behaviors (gaze, gestures, nods, smiles) using three different coding metrics (duration, frequency, rating) coded in 2 or 3 min slices. Convergent validity was measured by comparing a given behavior coded with at least two different metrics. Meta-analytic assessments across studies, behaviors, and metrics indicated strong convergent validity for various metrics for each behavior. Results provide confidence to researchers on the validity of using these thin-slice coding metrics for nonverbal behaviors.</p>

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How Long? How Many? How Much? Evidence of Convergent Validity Among Thin-Slice Behavioral Coding Metrics

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月26日

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  • Nora A. Murphy,
  • Mollie A. Ruben,
  • Morgan Stosic,
  • Laetitia A. Renier,
  • Katja Schlegel,
  • Judith A. Hall,
  • Marianne Schmid Mast,
  • Brett Marroquín

摘要

Despite the ubiquity of thin-slice coding for behavioral measurement, there exists relatively little systematic research into the convergent validity of thin-slice coding metrics for nonverbal behaviors when using human coders. This study utilized five previous datasets to measure four commonly-measured nonverbal behaviors (gaze, gestures, nods, smiles) using three different coding metrics (duration, frequency, rating) coded in 2 or 3 min slices. Convergent validity was measured by comparing a given behavior coded with at least two different metrics. Meta-analytic assessments across studies, behaviors, and metrics indicated strong convergent validity for various metrics for each behavior. Results provide confidence to researchers on the validity of using these thin-slice coding metrics for nonverbal behaviors.