Interpersonal supports for basic psychological needs and their relations with motivation, well-being, and performance: A meta-analysis.

People's motivational processes, well-being, and performance are likely to be facilitated through the support of others. Self-determination theory argues that interpersonal supports for autonomy, competence, and relatedness are crucial to achieve these outcomes. In the present study, we provide a comprehensive examination of this formulation based on a meta-analytic database consisting of 4,561 effect sizes from 881 independent samples (N = 443,556). Our results indicate that supports for autonomy, competence, and relatedness were strongly positively related with the satisfaction of these basic needs and strongly negatively related to their frustration. Interpersonal supports for basic needs were strongly positively related with subjective well-being and exhibited small to moderate positive associations with performance. Moderation analyses showed general stability of effects across cultures, although correlations of autonomy support to autonomous motivation weakened as a function of individualism. The opposite pattern was observed for the correlation between relatedness support and intrinsic motivation. Some effects also declined as a function of sample age and lag in measurements. We also find that competence- and relatedness-supportive behaviors explained incremental variance in basic need satisfaction even after controlling for the more established effects of autonomy support. In addition, lateral need supports explained incremental variance in basic need satisfaction after controlling for vertical sources of support. In sum, our results are consistent with the premise that to support optimal motivation, well-being, and performance, a broad set of behaviors that nurture all three basic needs, together with different sources of interpersonal support, should be considered to yield the most benefit. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Correlational effect size benchmarks.

Effect size information is essential for the scientific enterprise and plays an increasingly central role in the scientific process. We extracted 147,328 correlations and developed a hierarchical taxonomy of variables reported in Journal of Applied Psychology and Personnel Psychology from 1980 to 2010 to produce empirical effect size benchmarks at the omnibus level, for 20 common research domains, and for an even finer grained level of generality. Results indicate that the usual interpretation and classification of effect sizes as small, medium, and large bear almost no resemblance to findings in the field, because distributions of effect sizes exhibit tertile partitions at values approximately one-half to one-third those intuited by Cohen (1988). Our results offer information that can be used for research planning and design purposes, such as producing better informed non-nil hypotheses and estimating statistical power and planning sample size accordingly. We also offer information useful for understanding the relative importance of the effect sizes found in a particular study in relationship to others and which research domains have advanced more or less, given that larger effect sizes indicate a better understanding of a phenomenon. Also, our study offers information about research domains for which the investigation of moderating effects may be more fruitful and provide information that is likely to facilitate the implementation of Bayesian analysis. Finally, our study offers information that practitioners can use to evaluate the relative effectiveness of various types of interventions.