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Two different approaches to the affective profiles model: median splits (variable-oriented) and cluster analysis

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  • 1Blekinge Center of Competence, Blekinge County Council , Karlskrona , Sweden ; Department of Psychology, University of Gothenburg , Gothenburg , Sweden ; Network for Empowerment and Well-Being, University of Gothenburg , Gothenburg , Sweden ; Centre for Ethics, Law and Mental Health (CELAM), University of Gothenburg , Gothenburg , Sweden.

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Summary

This study compared two methods for classifying affective profiles. Cluster analysis, a person-oriented approach, created more distinct and homogeneous profiles than the median splits method, better reflecting gender differences.

Keywords:
Affective profiles modelCluster analysisComplex adaptive systemsMedian splitsNegative affectPerson-oriented approachPositive affectVariable-oriented approach

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Area of Science:

  • Psychology
  • Affective Science
  • Quantitative Psychology

Background:

  • The affective profiles model categorizes individuals based on positive and negative affect levels.
  • Previous research often uses median splits to assign individuals to affective profiles.
  • This median split method may lack validity due to arbitrary high/low affect distinctions.

Purpose of the Study:

  • To compare the validity of a person-oriented cluster analysis approach versus a variable-oriented median splits approach for affective profiling.
  • To investigate the homogeneity and distinctiveness of profiles generated by each method.
  • To examine the agreement between profiling methods and their relationship with gender.

Main Methods:

  • Recruited 2,225 participants via Amazon's Mechanical Turk for self-reported affect assessment using the Positive Affect Negative Affect Schedule.
  • Employed cluster analysis and median splits to create affective profiles.
  • Compared profile homogeneity, distinctiveness (Silhouette coefficients), and agreement using Rand Index and cell-wise analyses, including gender interactions.

Main Results:

  • Cluster analysis yielded more homogeneous and distinct profiles (homogeneity=0.62, Silhouette=0.68) compared to median splits (homogeneity=0.75, Silhouette=0.59).
  • 78% of participants were consistently classified, but 22% differed based on the method.
  • Cluster analysis revealed significant gender differences, assigning males more to self-fulfilling profiles and females less, aligning with theoretical expectations.

Conclusions:

  • Cluster analysis provides a more conceptually valid and empirically robust method for affective profiling than median splits.
  • The affective profiles model appears to represent a complex, dynamic adaptive system, with cluster analysis better capturing nuanced individual differences and gender patterns.
  • Further research is needed to definitively establish the superiority of one approach, but cluster analysis shows promise for nuanced affective research.