Publications

Shaheed Azaad (2026) · Preprint

It is common and recommended practice in psychology to report standardised effect sizes alongside significance tests. As Cohen (1988) notes, the interpretation of these effect sizes as either small, medium, or large should depend on the field of research. The present study analysed 13,194 effects from 3,302 articles to empirically derive thresholds for social psychology (SP), individual differences psychology (IDP) and cognitive psychology (CP). Thresholds (in Pearson’s r) were smallest for SP (small: .17, medium: .24, large: .34), followed by IDP (small: .19, medium: .27, large: .41), while CP produced the largest effects (small: .24, medium: .34, large: .51). Thresholds for within-subjects designs (based on bias-corrected dz, or g) followed a different pattern: effects were smallest for IDP (small: 0.27, medium: 0.44, large: 0.78), slightly larger for SP (small: 0.33, medium: 0.49, la...

Shaheed Azaad, Yoshihisa Kashima, Nick Haslam (2026) · Preprint

Research has revealed considerable seasonal variation in human behaviour and emotion. However, whether cognitive performance is similarly seasonal remains an open question. While some studies have found a performance advantage in summer compared to winter, others have found either the reverse effect or no effect at all. Because demographics, locations, and cognitive domains of interest vary between studies, it is difficult to determine whether such heterogeneity reflects systematic variation due to study characteristics or whether significant findings are better explained by sampling variance and publication bias. In the present study, we tested for seasonality in 100,113 chess games played by 27,335 players. Not only did we not find a seasonal effect, but we also found no interactions with age, gender, the absolute latitude of the tournament location, and the human development index of...

Shaheed Azaad (2026) · Behavior Research Methods

Theoretically driven meta-analyses often involve testing whether study characteristics moderate an effect in a pattern that supports one of multiple competing theoretical accounts. To conduct such analyses, researchers must manually extract, i.e., code, these characteristics from sometimes hundreds of studies. Ideally, studies should be coded by two researchers independently to prevent errors and biases from compromising the dataset’s integrity. The laborious nature of this task, however, means that meta-analysts usually settle for double-coding just a portion of the studies included in their study. Some researchers have proposed using large language models (LLMs) as a double-coder, showing that they can reliably extract explicitly stated information (e.g., publication year) from articles. However, meta-analyses in psychology generally require studies to be coded in terms of higher-leve...

John Michael, Shaheed Azaad, Pernille Hemmer, Robrecht van der Wel (2026) · Preprint

A commentary on Zapparoli et al. (2022; Cortex)