ArticleFrontiers in psychology2014
Inter-rater reliability for movement pattern analysis (MPA): measuring patterning of behaviors versus discrete behavior counts as indicators of decision-making style.
Article in Frontiers in psychology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The Positive Side of Maximization: Linking Maximization Tendency With Meaning in Life Through Time Perspectives.Frontiers in psychology · 2021Article
- How Shall I Count the Ways? A Method for Quantifying the Qualitative Aspects of Unscripted Movement With Laban Movement Analysis.Frontiers in psychology · 2019Article
- Embodied Decision-Making Style: Below and Beyond Cognition.Frontiers in psychology · 2018Review
- Beyond Self-Report: Emerging Methods for Capturing Individual Differences in Decision-Making Process.Frontiers in psychology · 2016Review
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Authors and funding
3 authors.
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Abstract
The unique yield of collecting observational data on human movement has received increasing attention in a number of domains, including the study of decision-making style. As such, interest has grown in the nuances of core methodological issues, including the best ways of assessing inter-rater reliability. In this paper we focus on one key topic - the distinction between establishing reliability for the patterning of behaviors as opposed to the computation of raw counts - and suggest that reliability for each be compared empirically rather than determined a priori. We illustrate by assessing inter-rater reliability for key outcome measures derived from movement pattern analysis (MPA), an observational methodology that records body movements as indicators of decision-making style with demonstrated predictive validity. While reliability ranged from moderate to good for raw counts of behaviors reflecting each of two Overall Factors generated within MPA (Assertion and Perspective), inter-rater reliability for patterning (proportional indicators of each factor) was significantly higher and excellent (ICC = 0.89). Furthermore, patterning, as compared to raw counts, provided better prediction of observable decision-making process assessed in the laboratory. These analyses support the utility of using an empirical approach to inform the consideration of measuring patterning versus discrete behavioral counts of behaviors when determining inter-rater reliability of observable behavior. They also speak to the substantial reliability that may be achieved via application of theoretically grounded observational systems such as MPA that reveal thinking and action motivations via visible movement patterns.
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