ABSTRACT
It is widely accepted that affect is associated with motivation, decision making and well-being. Studies from various domains suggest that anticipated affect is a key determinant of behavioral intention. In this research, we conducted a meta-analysis to determine the strength of the correlation between anticipated affect and behavioral intention. We searched the electronic databases PsycInfo, Scopus, Pubmed and Cochrane Library for articles published before July 2021. Studies were included based on the criteria 1) Participants are adults, 2) Participants rated their intention to engage in some behavior and the affect that they anticipate to experience if they perform or (not perform) the particular behavior, and 3) Pearson correlation coefficient(s) between behavioral intention and anticipated affect are reported. Studies whose target populations were patients with known psychiatric conditions were excluded. Correlation coefficients gathered from the selected studies were analyzed using a correlation-based meta-analysis. Meta-analytic estimate from 87 selected studies indicates a strong correlation between anticipated affect and behavioral intention (r = .61,95%CI = [.57,.64],p < .0001,k = 67,N = 25652). However, significant heterogeneity is observed across the included studies and moderator analysis shows a significant difference (p = .006) between hedonic vs. non-hedonic behaviors. While the estimated correlation between anticipated affect and behavioral intention is large, there is heterogeneity across studies. This correlation is significantly higher for hedonic behaviors than non-hedonic behaviors. We suggest that differences in the range of affect/emotions covered by each study is another potential moderator. Our results motivate further studies, covering a broader range of affect/emotions for a more accurate estimate of the correlation between anticipated affect and behavioral intention as well as experimental interventions to validate the causal direction of this relationship. Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-023-04383-w.
ABSTRACT
In the course of evolution, the genomes of grasses have maintained an observable degree of gene order conservation. The information available for already sequenced genomes can be used to predict the gene order of nonsequenced species by means of comparative colinearity studies. The "Wheat Zapper" application presented here performs on-demand colinearity analysis between wheat, rice, Sorghum, and Brachypodium in a simple, time efficient, and flexible manner. This application was specifically designed to provide plant scientists with a set of tools, comprising not only synteny inference, but also automated primer design, intron/exon boundaries prediction, visual representation using the graphic tool Circos 0.53, and the possibility of downloading FASTA sequences for downstream applications. Quality of the "Wheat Zapper" prediction was confirmed against the genome of maize, with good correlation (r > 0.83) observed between the gene order predicted on the basis of synteny and their actual position on the genome. Further, the accuracy of "Wheat Zapper" was calculated at 0.65 considering the "Genome Zipper" application as the "gold" standard. The differences between these two tools are amply discussed, making the point that "Wheat Zapper" is an accurate and reliable on-demand tool that is sure to benefit the cereal scientific community. The Wheat Zapper is available at http://wge.ndsu.nodak.edu/wheatzapper/ .
