But what about the Empress of Racnoss? The allocation of attention to spiders and Doctor Who in a visual search task is predicted by fear and expertise

If there is a spider in the room, then the spider phobic in your group is most likely to point it out to you. This phenomenon is believed to arise because our attentional systems are hardwired to attend to threat in our environment, and, to a spider phobic, spiders are threatening. However, an alternative explanation is simply that attention is quickly drawn to the stimulus of most personal relevance in the environment. Our research examined whether positive stimuli with no biological or evolutionary relevance could be allocated preferential attention. We compared attention to pictures of spiders with pictures from the TV program Doctor Who, for people who varied in both their love of Doctor Who and their fear of spiders. We found a double dissociation: interference from spider and Doctor-Who-related images in a visual search task was predicted by spider fear and Doctor Who expertise, respectively. As such, allocation of attention reflected the personal relevance of the images rather than their threat content. The attentional system believed to have a causal role in anxiety disorders is therefore likely to be a general system that responds not to threat but to stimulus relevance; hence, nonevolutionary images, such as those from Doctor Who, captured attention as quickly as fear-relevant spider images. Where this leaves the Empress of Racnoss, we are unsure.     

The Relation Between Chosen Role Models and the Self-Esteem of Men and Women

This study was designed to investigate choice of role models and levels of self-esteem within a sample of college students (N = 120). Participants rated themselves and their chosen role models on 29 character traits, which allowed determination of the self-perceived likeness of the participant to their role models (difference score). The difference score was then correlated with four subtypes of self-esteem. As predicted, participants chose more same-sex than other-sex role models; women were more likely than men to choose other-sex role models. The results indicated that choice of same-sex, as opposed to other-sex role models, is not indicative of higher levels of self-esteem in general. However, self-perceived likeness of role model to participant is significantly related to self-esteem, particularly for women.     

Adverse caregiving in early life: The trauma and deprivation distinction in young children

Knowledge and understanding about the impact of cumulative adverse experiences on the health and wellbeing of children, adolescents, and adults has rapidly expanded over the past 30 years. Despite the invaluable attention and support this proliferation has drawn to the importance of early childhood experiences, we believe that it is time to move beyond broad indices of risk and toward more specific and individualized understanding of how risk exposures are linked to clinical outcomes in young children. Within infant and early childhood mental health, there is a need for greater specificity in linking adverse caregiving experiences in early life to psychopathology in children. We highlight a framework distinguishing experiences of trauma from experiences of deprivation and use the examples of posttraumatic stress disorder and reactive attachment disorder to demonstrate how greater specificity in our understanding of early adverse caregiving can lead to more accurate and targeted diagnosis and treatment for young children. Both researchers and clinicians benefit from an approach to gain a greater appreciation of the links between specific types of experiences and outcomes in the children that we serve.     

Novel metaphor comprehension: Semantic neighbourhood density interacts with concreteness

Previous research suggests that metaphor comprehension is affected both by the concreteness of the topic and vehicle and their semantic neighbours (Kintsch, 2000; Xu, 2010). However, studies have yet to manipulate these 2 variables simultaneously. To that end, we composed novel metaphors manipulated on topic concreteness and semantic neighbourhood density (SND) of topic and vehicle. In Experiment 1, participants rated the metaphors on the suitability (e.g. sensibility) of their topic-vehicle pairings. Topic concreteness interacted with SND such that participants rated metaphors from sparse semantic spaces to be more sensible than those from dense semantic spaces and preferred abstract topics over concrete topics only for metaphors from dense semantic spaces. In Experiments 2 and 3, we used presentation deadlines and found that topic concreteness and SND affect the online processing stages associated with metaphor comprehension. We discuss how the results are aligned with established psycholinguistic models of metaphor comprehension.     

Stereotypical attitudes amongst black students at a rural historically black South African university

This study investigated stereotypical attitudes towards race amongst Black students (N=274) attending a historically Black South African university (females=62%; mean age of 22.15 years; SD=3.00 years). Data on group stereotyping by race were collected using a semi-structured questionnaire. The data were analysed for themes using discourse analysis. The findings indicated that Black students from a rural background stereotyped those from urban centres as lacking in African culture and being overly westernised. Conversely, rural Blacks from urban settings stereotyped those from rural areas as respectful, cultured and materially poor. Regardless of geographical origin, the Black students perceived English-speaking Whites as competent and friendly, while Afrikaans-speaking Whites were stereotyped as racist, aggressive and hardworking. The Black students perceived Indian South Africans as unethical and deceitful whilst Coloureds were noted to lack culture and to be aggressive. Findings suggest stereotypical racist language or discourse to be persistent among a student population with historical disadvantage.     

Fostering Diversity in the Creative Arts by Addressing Students' Capacity to Aspire

Research on young people's aspirations and their capacity to aspire to higher education has proliferated in recent decades, however, very little attention has been paid to the creative arts. Diversity in the arts remains a persistent issue in many nations, and repeated attempts to promote diversity in the Australian arts community have had limited impact, suggesting the need for new approaches. Drawing on data from a 4‐year longitudinal study of students from ages 8 to 18 (n = 6,492) in government schools, we examine school students' aspirations for careers in the arts. Arts‐related careers were popular among students, yet we found a distinct lack of diversity among those aspiring to such careers. Using logistic regression analysis we found that being female, high achieving, from an English‐speaking background, possessing high cultural capital, and attending advantaged schools were significant predictors of interest in the arts, suggesting the likely reproduction of existing patterns of participation. We argue that initiatives within schools are essential to disrupting these patterns and building the capacity of a more diverse range of students to aspire to careers in the arts.     

The Impact of Item Misspecification and Dichotomization on Class and Parameter Recovery in LCA of Count Data

Mixture analysis of count data has become increasingly popular among researchers of substance use, behavioral analysis, and program evaluation. However, this increase in popularity seems to have occurred along with adoption of some conventions in model specification based on arbitrary heuristics that may impact the validity of results. Findings from a systematic review of recent drug and alcohol publications suggested count variables are often dichotomized or misspecified as continuous normal indicators in mixture analysis. Prior research suggests that misspecifying skewed distributions of continuous indicators in mixture analysis introduces bias, though the consequences of this practice when applied to count indicators has not been studied. The present work describes results from a simulation study examining bias in mixture recovery when count indicators are dichotomized (median split; presence vs. absence), ordinalized, or the distribution is misspecified (continuous normal; incorrect count distribution). All distributional misspecifications and methods of categorizing resulted in greater bias in parameter estimates and recovery of class membership relative to specifying the true distribution, though dichotomization appeared to improve class enumeration accuracy relative to all other specifications. Overall, results demonstrate the importance of accurately modeling count indicators in mixture analysis, as misspecification and categorizing data can distort study outcomes.     

Bystander Response to Sexual Assault Disclosures in the U.S. Military: Encouraging Survivors to use Formal Resources

Experiencing military sexual assault (MSA) results in serious mental health consequences. Sexual assault survivors often disclose to informal sources of support, and how these individuals respond can have a significant effect on survivors’ wellbeing. Bystander intervention is one mechanism through which institutions, such as the U.S. Military, aim to teach informal support providers to respond positively and effectively to sexual assaults. One bystander response that survivors may find helpful is the discussion of formal resources (e.g., counseling options, reporting options). The current study examined factors associated with U.S. Service members’ intentions to encourage sexual assault survivors to report and seek mental health counseling, including individual characteristics (rank, gender, personal experience of MSA) and perceptions of military sexual assault response efforts (exposure to sexual assault training, leader response to sexual assault, service barriers). The study also examined contextual factors (branch) and interactions between individual and contextual predictors. We analyzed survey data from 27,505 active duty Service members collected by the U.S. Department of Defense. As expected, rank, gender, experience of MSA, training exposure, leader response, and service barriers were associated with Service members’ intentions to encourage MSA survivors to report and seek‐help. Bystander responses to disclosures can have a significant effect on survivors’ response to the assault, and these findings can help in identifying why bystanders may or may not encourage the use of formal resources after receiving a sexual assault disclosure.     

Influence of in utero exposure to maternal depression and natural disaster-related stress on infant temperament at 6 months: The children of Superstorm Sandy

This study examined the effects of in utero exposure to maternal depression and Superstorm Sandy, a hurricane that hit metropolitan New York in 2012, on infant temperament at 6 months. Temperament was assessed using the Infant Behavior Questionnaire-Revised. Maternal depression was measured by the Edinburgh Postnatal Depression Scale. The main effects and the interaction of maternal depression and Sandy exposure on infant temperament were examined using a multivariable generalized linear model. Results show that prenatal maternal depression was associated with lower emotion regulation and greater distress. Stratification and interaction analyses suggested that the adverse effects of prenatal maternal depression on problematic temperament were amplified by in utero Sandy exposure. This study underscores the importance of providing prenatal screening and treatment for maternal depression during pregnancy while also identifying high-risk families who may have suffered from disaster-related traumas to provide necessary services. As the frequency of natural disasters may increase due to climate change, it is important to understand the consequences of in utero stress on child development and to formulate plans for early identification.     

Machine learning in suicide science: Applications and ethics

For decades, our ability to predict suicide has remained at near‐chance levels. Machine learning has recently emerged as a promising tool for advancing suicide science, particularly in the domain of suicide prediction. The present review provides an introduction to machine learning and its potential application to open questions in suicide research. Although only a few studies have implemented machine learning for suicide prediction, results to date indicate considerable improvement in accuracy and positive predictive value. Potential barriers to algorithm integration into clinical practice are discussed, as well as attendant ethical issues. Overall, machine learning approaches hold promise for accurate, scalable, and effective suicide risk detection; however, many critical questions and issues remain unexplored.