An even more trivial effect size was computed for the wholist-verbalisers and analytic-imagers (d = 0.02 and d = 0.01 respectively).
If we set the mean effect size of missing studies at.001 and define the threshold for a "trivial" effect size to be.01, then the Orwin Fail-Safe N for our database is 544 studies.
Yet only one pairing produced a statistically significant difference between mean values (RER at 120 W) after Holm Bonferonni adjustment; but the small APE and CV for this pair of 0.8 and 0.6 %, respectively, and a trivial effect size (0.16) all confirmed this was a physiologically insignificant difference.
Beta can also be considered as a measure of impulsivity, but no study found significant group differences, and the effect sizes were trivial.
Overall, most APE and CV values for the simultaneous comparison were very small, typically varying around 0.5 2.0 %, with all effect sizes being trivial (maximum of 0.16); indeed, 77 % of the effect sizes were <0.1.
Furthermore, evidence-based guidelines for the interpretation of the clinical relevance of changes in the different EORTC QLQ-C30 subscales were recently published [ 55], categorizing differences between scores in trivial, small, medium or large effect sizes.
Evidence-based guidelines for the interpretation of the clinical relevance of changes in the different EORTC QLQ-C30 subscales were recently published [ 48], categorizing difference between scores (on the 0-100 pointscalele) in trivial, small, medium, or large effect sizes.
Further, evidence-based guidelines for the interpretation of the clinical relevance of changes in the different EORTC QLQ-C30 subscales were recently published [ 48], categorizing differences between scores in trivial, small, medium, or large effect sizes.
However, with large sample sizes, confidence intervals with bounds close enough to zero can lead us to comfortable conclusions that population effect sizes larger than trivial ones are improbable.
