Hiring on vocational interests to simultaneously improve validity and organizational diversity

We discuss how using vocational interests in the selection process can help address the diversity-validity dilemma. First, we point out how incorporating vocational interests as predictors in selection could help to reduce adverse impact. We further suggest that by using optimal predictor weights, one could simultaneously improve validity while enhancing organisational diversity. Finally, the predictive validity of vocational interests arises from their ability to capture the congruence between individuals and occupations, which is a cross-level phenomenon. Thus, when gathering validity evidence for vocational interests, multi-occupation samples should be incorporated into validation efforts.     

A systematic review of relationship sacrifices from 2002 to 2021: Moving toward inclusivity

We conducted a systematic review of research on relational sacrifices in romantic relationships from 2002 to 2021 [N = 115 studies] to answer three questions: Q1: Whose voices and vantage points are represented in the research?; Q2: What types of questions are valued?; Q3: What are the reflections and connections about relational sacrifices that were learned during the review? To address Q1, we coded sample demographics of study participants on geographical location, race/ethnicity, education/income/SES, gender (i.e., gender differences explored and beyond gender binaries), sexual orientation, age, and disability, using a coding system of 1 (exclusion/absence) to 5 (focus on context-relevant experiences for underrepresented samples). Results for Q1 showed that the most frequent codes were 1 (exclusion/absence) for information about the samples' disability status, education/income/SES, and both codes for gender (i.e., gender differences explored and beyond gender binaries); when demographic information was reported, the most frequent codes were 2 (compensatory addition) for age, sexual orientation, geographical location, and race/ethnicity. To address Q2, we coded for aspects of the study designs and conceptual dimensions of sacrifice. Results for Q2 showed that a majority of the studies in our review used quantitative and close-ended measures emphasizing behavioral frequency of sacrifice. For Q3, we include our own reflections and connections about relational sacrifices, questioning research methods, and challenging assumptions drawn from existing research to move toward a more inclusive science.     

Anticipation across modalities in children and adults: Relating anticipatory alpha rhythm lateralization,reaction time,and executive function

The development of the ability to anticipate—as manifested by preparatory actions and neural activation related to the expectation of an upcoming stimulus—may play a key role in the ontogeny of cognitive skills more broadly. This preregistered study examined anticipatory brain potentials and behavioral responses (reaction time; RT) to anticipated target stimuli in relation to individual differences in the ability to use goals to direct action (as indexed by measures of executive function; EF). A cross-sectional investigation was conducted in 40 adults (aged 18–25 years) and 40 children (aged 6–8 years) to examine the association of changes in the amplitude of modality-specific alpha-range rhythms in the electroencephalogram (EEG) during anticipation of lateralized visual, tactile, or auditory stimuli with inter- and intraindividual variation in RT and EF. Children and adults exhibited contralateral anticipatory reductions in the mu rhythm and the visual alpha rhythm for tactile and visual anticipation, respectively, indicating modality and spatially specific attention allocation. Variability in within-subject anticipatory alpha lateralization (the difference between contralateral and ipsilateral alpha power) was related to single-trial RT. This relation was more prominent in adults than in children, and was not apparent for auditory stimuli. Multilevel models indicated that interindividual differences in anticipatory mu rhythm lateralization contributed to the significant association with variability in EF, but this was not the case for visual or auditory alpha rhythms. Exploratory microstate analyses were undertaken to cluster global field power (GFP) into a distribution-free temporal analysis examining developmental differences across samples and in relation to RT and EF. Anticipation is suggested as a developmental bridge construct connecting neuroscience, behavior, and cognition, with anticipatory EEG oscillations being discussed as quantifiable and potentially malleable indicators of stimulus prediction.     

Capuchin monkeys learn to use information equally well from individual exploration and social demonstration

Animal Cognition - The limited evidence of complex culture in non-human primates contrasts strikingly with human behaviour. This may be because non-human primates fail to use information acquired...     

A rich palette of Bible use: A theoretical and empirical contribution from the context of Protestant Christian primary schools in the Netherlands

The aim of this study is to gain empirical knowledge about how the Bible functions in the context of Protestant Christian primary schools in the Netherlands. It presents the results of an empirical explorative and qualitative study on the perceptions of teachers and school administrators (directors and internal supervisors) on the goals of Bible use in Protestant primary education, as well as the roles of teachers and pupils, and how these can be understood in terms of religious pedagogical models and theories. Five small focus group interviews with teachers and six interviews with school administrators revealed a variety of goals teachers hold regarding Bible use in education and a variety of divisions of teacher–learner roles in this regard. The findings also show some particular characteristics when compared with secondary schools.     

#sustainablefashion on Instagram: A content and network analysis of user-generated posts

The social and environmental impacts of the global fashion industry face increasing scrutiny. As such, consumers and brands look towards ‘sustainable fashion’ for low-impact alternatives. Simultaneously, visual social media platforms such as Instagram have become prevalent places for fashion advertising and discourse. To investigate this under-researched area, the current study utilises visual content and social network analysis to explore how sustainable fashion is presented on Instagram, specifically: (a) what visual characteristics are present within sustainable fashion content, and (b) in what broader contexts and communities is discussion of sustainable fashion taking place? Posts included under the hashtag #sustainablefashion (N = 650) were inspected for visual characteristics, including type of clothing, presence of person, post setting, presence of nature, and post format. Most posts were photographs located indoors with no person and no nature-based elements. The hashtags used alongside #sustainablefashion were analysed with Gephi software to establish a social network and community groups of related topics. Network analysis revealed four key community groups: online-promotional, artisan-traditional, eco-ethical, and Malay-online-selling. Secondhand fashion also appeared to be the most prominent sustainable fashion alternative on Instagram. This study is one of the first to investigate the characteristics of user-generated #sustainablefashion content on Instagram. Whilst social media is a burgeoning avenue for research, existing studies primarily investigate how these platforms can be harnessed for advertising, rather than what users themselves are already posting. Implications for brands who use this platform and opportunities for future research are discussed.     

Mental health symptoms,well-being and experiences of the COVID-19 pandemic: A mixed-methods practice-based study

The COVID-19 pandemic necessitated abrupt and substantial changes in daily life, and public health strategies intended to protect physical health can negatively affect mental health and well-being, especially for individuals with pre-existing mental health challenges. For this study, we surveyed a sample of clients (N = 94) in the summer of 2020 from a community mental health clinic in the northeast United States. A mixed-methods, concurrent triangulation design was used to (a) identify client subgroups on indicators of mental health (i.e. anxious and depressive symptoms) and emotional, psychological, and social well-being using latent profile analysis (LPA), and (b) within these subgroups, examine qualitative, thematic patterns in self-described challenges, benefits and learning related to the pandemic. The LPA revealed five distinct subgroups with various levels of symptoms and well-being, including Stagnant (moderate symptoms/moderate well-being), Languishing (high symptoms/low well-being), Flourishing (low symptoms, high well-being), Fortitudinous (high symptoms, moderate well-being) and Mobilized (moderate symptoms, high well-being). These divergent subgroups support the need to conceptualise mental health symptoms apart from well-being and assess for heterogeneous constellations of such constructs among psychotherapy clients. Thematic analysis offered additional insight into pandemic experiences within each subgroup, including attention to psychological, emotional, behavioural/lifestyle, relational, physical and ecological/contextual dimensions of self-experience, as well as the ways clients had adjusted to the pandemic's circumstances. Findings support nuanced conceptualisations of positive mental health and offer insight into coping and adaptation during this public health crisis.     

Penalized optimal scaling for ordinal variables with an application to international classification of functioning core sets

Ordinal data occur frequently in the social sciences. When applying principal component analysis (PCA), however, those data are often treated as numeric, implying linear relationships between the variables at hand; alternatively, non-linear PCA is applied where the obtained quantifications are sometimes hard to interpret. Non-linear PCA for categorical data, also called optimal scoring/scaling, constructs new variables by assigning numerical values to categories such that the proportion of variance in those new variables that is explained by a predefined number of principal components (PCs) is maximized. We propose a penalized version of non-linear PCA for ordinal variables that is a smoothed intermediate between standard PCA on category labels and non-linear PCA as used so far. The new approach is by no means limited to monotonic effects and offers both better interpretability of the non-linear transformation of the category labels and better performance on validation data than unpenalized non-linear PCA and/or standard linear PCA. In particular, an application of penalized optimal scaling to ordinal data as given with the International Classification of Functioning, Disability and Health (ICF) is provided.