Is Accurate, Positive, or Inflated Self-perception Most Advantageous for Psychological Adjustment? A Competitive Test of Key Hypotheses

Humberg, Sarah, Michael Dufner, Felix D Schönbrodt, Katharina Geukes, Roos Hutteman, Albrecht Kuefner, Maarten van Zalk, Jaap J A Denissen, Steffen Nestler, and Mitja Back. 2018. “Preprint of "is Accurate, Positive, or Inflated Self-perception Most Advantageous for Psychological Adjustment? A Competitive Test of Key Hypotheses"”. Open Science Framework. January 21. osf.io/9w3bh

Abstract: Empirical research on the (mal-)adaptiveness of favorable self-perceptions, self-enhancement, and self-knowledge has typically applied a classical null-hypothesis testing approach and provided mixed and even contradictory findings. Using data from five studies (laboratory and field, total N = 2,823), we employed an information-theoretic approach combined with Response Surface Analysis to provide the first competitive test of six popular hypotheses: that more favorable self-perceptions are adaptive versus maladaptive (Hypotheses 1 and 2: Positivity of self-view hypotheses), that higher levels of self-enhancement (i.e., a higher discrepancy of self-viewed and objectively assessed ability) are adaptive versus maladaptive (Hypotheses 3 and 4: Self-enhancement hypotheses), that accurate self-perceptions are adaptive (Hypothesis 5: Self-knowledge hypothesis), and that a slight degree of self-enhancement is adaptive (Hypothesis 6: Optimal margin hypothesis). We considered self-perceptions and objective ability measures in two content domains (reasoning ability, vocabulary knowledge) and investigated six indicators of intra- and interpersonal psychological adjustment. Results showed that most adjustment indicators were best predicted by the positivity of self-perceptions, there were some specific self-enhancement effects, and evidence generally spoke against the self-knowledge and optimal margin hypotheses. Our results highlight the need for comprehensive simultaneous tests of competing hypotheses. Implications for the understanding of underlying processes are discussed.