What features of peoples childhood environments go on to shape their prosocial behavior during adulthood? Past studies linking childhood environment to adult prosocial behavior have focused primarily on adverse features, thereby neglecting the possible influence of exposure to enriched environments (e.g., access to material resources, experiences with rich cooperative relationships, and interactions with morally exemplary role models). Here, we expand the investigation of childhood environmental quality to include consideration of enriching childhood experiences and their relation to adult prosociality. In two cross-sectional studies, we found promising evidence that enriched childhood environments are associated with adult moral behavior. In study 1 (N = 1,084 MTurk workers), we adapted an existing measure of enriched childhood environmental quality for retrospective recall of childhood experiences and found that subjects recollections of their enriched childhood experiences are distinct from their recollections of adverse childhood experiences. In Study 2 (N = 2,208 MTurk workers), we found that a formative composite of subjects recollections of enriched childhood experiences is positively associated with a variety of morally relevant traits in adulthood, including agreeableness, honesty-humility, altruism, endorsement of the principle of care, empathic responding to the plights of needy others, and charitable donations in an experimental setting, and that these associations held after controlling for childhood environmental adversity, childhood socioeconomic status, sex, and age. We also found evidence suggesting that some, but not all, of the relationship between enrichment and adult prosociality can be explained by a shared genetic correlation. We include a new seven-item measure as an appendix.

Recent theorizing suggests that religious people's moral convictions are quite strategic (albeit unconsciously so), designed to make their worlds more amenable to their favored approaches to solving life's basic challenges. In a meta-analysis of 5 experiments and a preregistered replication, we find that religious identity places a sex premium on moral judgments, causing people to judge violations of conventional sexual morality as particularly objectionable. The sex premium is especially strong among highly religious people, and applies to both legal and illegal acts. Religion's influence on moral reasoning emphasizes conventional sexual norms, and may reflect the strategic projects to which religion has been applied throughout history. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Although most people present themselves as possessing prosocial traits, people differ in the extent to which they actually act prosocially in everyday life. Qualitative data that were not ostensibly collected to measure prosociality might contain information about prosocial dispositions that is not distorted by self–presentation concerns. This paper seeks to characterise charitable donors from qualitative data. We compared a manual approach of extracting predictors from participants’ self–described personal strivings to two automated approaches: A summation of words predefined as prosocial and a support vector machine classifier. Although variables extracted by the support vector machine predicted donation behaviour well in the training sample ( N = 984), virtually, no variables from any method significantly predicted donations in a holdout sample ( N = 496). Raters’ attempts to predict donations to charity based on reading participants’ personal strivings were also unsuccessful. However, raters’ predictions were associated with past charitable involvement. In sum, predictors derived from personal strivings did not robustly explain variation in charitable behaviour, but personal strivings may nevertheless contain some information about trait prosociality. The sparseness of personal strivings data, rather than the irrelevance of open–ended text or individual differences in goal pursuit, likely explains their limited value in predicting prosocial behaviour. © 2020 European Association of Personality Psychology

In the current paper, we review existing tools for solving variable selection problems in psychology. Modern regularization methods such as lasso regression have recently been introduced in the field and are incorporated into popular methodologies, such as network analysis. However, several recognized limitations of lasso regularization may limit its suitability for psychological research. In this paper, we compare the properties of lasso approaches used for variable selection to Bayesian variable selection approaches. In particular we highlight advantages of stochastic search variable selection (SSVS), that make it well suited for variable selection applications in psychology. We demonstrate these advantages and contrast SSVS with lasso type penalization in an application to predict depression symptoms in a large sample and an accompanying simulation study. We investigate the effects of sample size, effect size, and patterns of correlation among predictors on rates of correct and false inclusion and bias in the estimates. SSVS as investigated here is reasonably computationally efficient and powerful to detect moderate effects in small sample sizes (or small effects in moderate sample sizes), while protecting against false inclusion and without over-penalizing true effects. We recommend SSVS as a flexible framework that is well-suited for the field, discuss limitations, and suggest directions for future development.

Researchers commonly conceptualize forgiveness as a rich complex of psychological changes involving attitudes, emotions, and behaviors. Psychometric work with the measures developed to capture this conceptual richness, however, often points to a simpler picture of the psychological dimensions in which forgiveness takes place. In an effort to better unite forgiveness theory and measurement, we evaluate several psychometric models for common measures of forgiveness. In doing so, we study people from the United States and Japan to understand forgiveness in both nonclose and close relationships. In addition, we assess the predictive utility of these models for several behavioral outcomes that traditionally have been linked to forgiveness motives. Finally, we use the methods of item response theory, which place person abilities and item responses on the same metric and, thus, help us draw psychological inferences from the ordering of item difficulties. Our results highlight models based on correlated factors models and bifactor (S-1) models. The bifactor (S-1) model evinced particular utility: Its general factor consistently predicts variation in relevant criterion measures, including 4 different experimental economic games (when played with a transgressor), and also suffuses a second self-report measure of forgiveness. Moreover, the general factor of the bifactor (S-1) model identifies a single psychological dimension that runs from hostility to friendliness while also pointing to other sources of variance that may be conceived of as method factors. Taken together, these results suggest that forgiveness can be usefully conceptualized as prosocial change along a single attitudinal continuum that ranges from hostility to friendliness. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Particle physics has an ambitious and broad experimental programme for the coming decades. This programme requires large investments in detector hardware, either to build new facilities and experiments, or to upgrade existing ones. Similarly, it requires commensurate investment in the R&D of software to acquire, manage, process, and analyse the shear amounts of data to be recorded. In planning for the HL-LHC in particular, it is critical that all of the collaborating stakeholders agree on the software goals and priorities, and that the efforts complement each other. In this spirit, this white paper describes the R&D activities required to prepare for this software upgrade.