Abstract

Personalizing assessments, predictions, and treatments of individuals is currently a defining trend in psychological research and applied fields, including personalized learning, personalized medicine, and personalized advertisement. For instance, the recent pandemic has reminded parents and educators of how challenging yet crucial it is to get the right learning task to the right student at the right time. Increasingly, psychologists and social scientists are realizing that the between-person methods that we have long relied upon to describe, predict, and treat individuals may fail to live up to these tasks (e.g., Molenaar, 2004). Consequently, there is a risk of a credibility loss, possibly similar to the one seen during the replicability crisis (Ioannides, 2005), because we have only started to understand how many of the conclusions that we tend to draw based on between-person methods are based on a misunderstanding of what these methods can tell us and what they cannot. An imminent methodological revolution will likely lead to a change of even well-established psychological theories (Barbot et al., 2020). Fortunately, methodological solutions for personalized descriptions and predictions, such as many within-person analyses, are available and undergo rapid development, although they are not yet embraced in all areas of psychology, and some come with their own limitations. This article first discusses the extent of the theory-method gap, consisting of theories about within-person patterns being studied with between-person methods in psychology, and the potential loss of trust that might follow from this theory-method gap. Second, this article addresses advantages and limitations of available within-person methods. Third, this article discusses how within-person methods may help improving the individual descriptions and predictions that are needed in many applied fields that aim for tailored individual solutions, including personalized learning and personalized medicine.

Highlights

  • Psychology aspires to understand what determines the behavior and mental states of, and differences between, individuals, in contrast to sociology or other social sciences, which aspire to describe and predict the behavior and functioning of groups

  • There is a risk of a credibility loss, possibly similar to the one seen during the replicability crisis (Ioannides, 2005), because we have only started to understand how many of the conclusions that we tend to draw based on between-person methods are based on a misunderstanding of what these methods can tell us and what they cannot

  • This article first discusses the extent of the theory-method gap, consisting of theories about within-person patterns being studied with between-person methods in psychology, and the potential loss of trust that might follow from this theory-method gap

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Summary

A Theory-Method Gap in Psychology

Psychology aims to describe and predict how individuals feel, think, and behave, many of the analytical and diagnostical methods used to study such questions about individuals focus mostly on group-based statistics, such as mean-score differences between groups, or group-based correlation or regression coefficients. Terns opposing the overall trend may be overlooked (see e.g., This means, for instance, that the factor structure of one Anscombe, 1973; Matejka & Fitzmaurice, 2017) This construct, the results of a factor analysis, or the relations problem has been long known and is yet often ignored (e.g., among more than two variables in structural equation mod- Asendorpf, 1993; Asendorpf, 2000; Kuhl, 1977; Lewin, els can look different in between-person analyses than in 1930; Wottawa, 1981). Many of the studies addressing either this negative correlation between X and Y, while the other half of the individuals show patterns in line with a perfectly positive correlation between X and Y

Simpson’s paradox
Definition of ergodicity
Please note
Within-person
Co-variance mixed up with co-endorsement10
Different people ‘walking’ different paths in path models11
Getting Ready for the Future by Learning from the Past
ISOA approach
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