Research on bystander intervention has produced a great number of studies showing that the presence of other people in a critical situation reduces the likelihood that an individual will help. As the last systematic review of bystander research was published in 1981 and was not a quantitative meta-analysis in the modern sense, the present meta-analysis updates the knowledge about the bystander effect and its potential moderators. The present work (a) integrates the bystander literature from the 1960s to 2010, (b) provides statistical tests of potential moderators, and (c) presents new theoretical and empirical perspectives on the novel finding of non-negative bystander effects in certain dangerous emergencies as well as situations where bystanders are a source of physical support for the potentially intervening individual. In a fixed effects model, data from over 7,700 participants and 105 independent effect sizes revealed an overall effect size of g = -0.35. The bystander effect was attenuated when situations were perceived as dangerous (compared with non-dangerous), perpetrators were present (compared with non-present), and the costs of intervention were physical (compared with non-physical). This pattern of findings is consistent with the arousal-cost-reward model, which proposes that dangerous emergencies are recognized faster and more clearly as real emergencies, thereby inducing higher levels of arousal and hence more helping. We also identified situations where bystanders provide welcome physical support for the potentially intervening individual and thus reduce the bystander effect, such as when the bystanders were exclusively male, when they were naive rather than passive confederates or only virtually present persons, and when the bystanders were not strangers.
This article was originally submitted for publication to the Editor of Advances in Methods and Practices in Psychological Science (AMPPS) in 2015. When the submitted manuscript was subsequently posted online (Silberzahn et al., 2015), it received some media attention, and two of the authors were invited to write a brief commentary in Nature advocating for greater crowdsourcing of data analysis by scientists. This commentary, arguing that crowdsourced research "can balance discussions, validate findings and better inform policy" (Silberzahn & Uhlmann, 2015, p. 189), included a new figure that displayed the analytic teams' effectsize estimates and cited the submitted manuscript as the source of the findings, with a link to the preprint. However, the authors forgot to add a citation of the Nature commentary to the final published version of the AMPPS article or to note that the main findings had been previously publicized via the commentary, the online preprint, research presentations at conferences and universities, and media reports by other people. The authors regret the oversight.
G-factor models such as the bifactor model and the hierarchical G-factor model are increasingly applied in psychology. Many applications of these models have produced anomalous and unexpected results that are often not in line with the theoretical assumptions on which these applications are based. Examples of such anomalous results are vanishing specific factors and irregular loading patterns. In this article, the authors show that from the perspective of stochastic measurement theory anomalous results have to be expected when G-factor models are applied to a single-level (rather than a 2-level) sampling process. The authors argue that the application of the bifactor model and related models require a 2-level sampling process that is usually not present in empirical studies. We demonstrate how alternative models with a G-factor and specific factors can be derived that are more well-defined for the actual single-level sampling design that underlies most empirical studies. It is shown in detail how 2 alternative models, the bifactor-(S - 1) model and the bifactor-(S·I - 1) model, can be defined. The properties of these models are described and illustrated with an empirical example. Finally, further alternatives for analyzing multidimensional models are discussed. (PsycINFO Database Record
Fit indices are widely used in order to test the model fit for structural equation models. In a highly influential study, Hu and Bentler (1999) showed that certain cutoff values for these indices could be derived, which, over time, has led to the reification of these suggested thresholds as "golden rules" for establishing the fit or other aspects of structural equation models. The current study shows how differences in unique variances influence the value of the global chi-square model test and the most commonly used fit indices: Root-mean-square error of approximation, standardized root-mean-square residual, and the comparative fit index. Using data simulation, the authors illustrate how the value of the chi-square test, the root-mean-square error of approximation, and the standardized root-mean-square residual are decreased when unique variances are increased although model misspecification is present. For a broader understanding of the phenomenon, the authors used different sample sizes, number of observed variables per factor, and types of misspecification. A theoretical explanation is provided, and implications for the application of structural equation modeling are discussed.
Highlights► Structural model of the inter-relations of inhibition, intelligence and creativity. ► Cognitive inhibition was measured by means of the random motor generation task. ► Inhibition generally shows a positive relation with creativity measures. ► Inhibition is specifically related to ideational fluency. ► Intelligence is specifically related to ideational originality.
Publication bias remains a controversial issue in psychological science. The tendency of psychological science to avoid publishing null results produces a situation that limits the replicability assumption of science, as replication cannot be meaningful without the potential acknowledgment of failed replications. We argue that the field often constructs arguments to block the publication and interpretation of null results and that null results may be further extinguished through questionable researcher practices. Given that science is dependent on the process of falsification, we argue that these problems reduce psychological science's capability to have a proper mechanism for theory falsification, thus resulting in the promulgation of numerous "undead" theories that are ideologically popular but have little basis in fact.
Although phonological awareness (PA) and rapid automatized naming (RAN) are confirmed as early predictors of reading in a large number of orthographies, it is as yet unclear whether the predictive patterns are universal or language specific. This was examined in a longitudinal study across Grades 1 and 2 with 1,120 children acquiring one of five alphabetic orthographies with different degrees of orthographic complexity (English, French, German, Dutch, and Greek). Path analyses revealed that a universal model could not be confirmed. When we specified the best-fitting model separately for each language, RAN was a consistent predictor of reading fluency in all orthographies, whereas the association between PA and reading was complex and mostly interactive. We conclude that RAN taps into a language-universal cognitive mechanism that is involved in reading alphabetic orthographies (independent of complexity), whereas the PA-reading relationship depends on many factors like task characteristics, developmental status, and orthographic complexity. Phonological awareness (PA) and rapid automatized naming (RAN) have consistently been found to be closely associated with children's reading development explaining unique variance in children's reading skills above and beyond general factors like age and nonverbal IQ (Araújo, Reis, Petersson, & Faísca, 2015; Melby-Lervåg, Lyster, & Hulme, 2012; Norton & Wolf, 2012). PA refers to the ability to identify and manipulate phonological segments in spoken words, and RAN denotes the ability to name serial displays of letters, digits, pictured objects, or colors as quickly as possible. PA is important as all orthographic systems represent phonological units in one way or another. Children with deficient access to the relevant phonological units will have problems to fully understand the mappings between a certain spoken language and its orthography and training of PA seems to improve reading outcomes (e.g., Suggate, 2016). An important and as yet unresolved issue is whether PA precedes reading acquisition or whether it evolves as a consequence or during the course of learning to read (
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