British journal of psychology最新文献

The memory conformity effect occurs when people witness a given incident (e.g. a crime) then talk to each other about it, and the statement of one person affects the memory account of the other person with respect to this incident. The aim of this article is to improve the quality of witness testimony by verifying the effectiveness of three methods that aim to reduce memory conformity effect: (1) an extended warning against misinformation; (2) a method based on information about memory functioning and its fallibility and (3) a method consisting in motivating participants to resist influence and demonstrating their individual vulnerability to it. In the presented experiment, the innovative MORI technique was used to study the memory conformity effect. This technique allows a pair of participants to sit beside each other, look at the same screen and see a different version of the same criminal event. In the next stages, the subjects are asked to answer a series of questions about different details, thereby introducing mutual misinformation; then, the participants perform an individual memory test. In the experimental conditions, this test was preceded by one of the three tested methods in each group, with the aim of determining their effectiveness in reducing memory conformity. It turns out that the implementation of an extended warning against misinformation eliminated the memory conformity effect, while the application of two other methods led to a reduction (but not complete elimination) of the studied phenomenon.

The allure of aesthetic appeal in images captivates our senses, yet the underlying intricacies of aesthetic preferences remain elusive. In this study, we pioneer a novel perspective by utilizing several different machine learning (ML) models that focus on aesthetic attributes known to influence preferences. Our models process these attributes as inputs to predict the aesthetic scores of images. Moreover, to delve deeper and obtain interpretable explanations regarding the factors driving aesthetic preferences, we utilize the popular Explainable AI (XAI) technique known as SHapley Additive exPlanations (SHAP). Our methodology compares the performance of various ML models, including Random Forest, XGBoost, Support Vector Regression, and Multilayer Perceptron, in accurately predicting aesthetic scores, and consistently observing results in conjunction with SHAP. We conduct experiments on three image aesthetic benchmarks, namely Aesthetics with Attributes Database (AADB), Explainable Visual Aesthetics (EVA), and Personalized image Aesthetics database with Rich Attributes (PARA), providing insights into the roles of attributes and their interactions. Finally, our study presents ML models for aesthetics research, alongside the introduction of XAI. Our aim is to shed light on the complex nature of aesthetic preferences in images through ML and to provide a deeper understanding of the attributes that influence aesthetic judgements.

Since its release the Power Threat Meaning Framework (PTMF) has received considerable interest and uptake. However, there have not yet been any attempts to review the scope of this emergent literature. This scoping review aimed to identify and synthesize: (1) all empirical research which utilized the PTMF in their methodologies, (2) the characteristics of these studies, (3) the different ways in which these studies utilized the PTMF, and (4) the key findings of these studies. This review was conducted in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) scoping review extension (PRISMA-ScR). Following systematic searches of academic databases and grey literature, 17 studies meeting eligibility criteria were included. These papers were subject to critical appraisal, data charting, and narrative synthesis. This review identified four uses of the PTMF: (1) PTMF-informed data collection, (2) PTMF-informed data analysis, (3) Experiences of/views on the PTMF, and (4) PTMF-informed psychological practices. This evidence-base demonstrated the merits of utilizing the PTMF across a range of disciplines, settings, and populations. This heterogeneity also presents challenges for evidence synthesis. Implications for research (e.g. importance of the coherent and consistent approach to research) and practice/policy (e.g. professional training, collaboration, service-level barriers) are considered.

Open research practices seek to enhance the transparency and reproducibility of research. While there is evidence of increased uptake in these practices, such as study preregistration and open data, facilitated by new infrastructure and policies, little research has assessed general uptake of such practices across psychology university researchers. The current study estimates psychologists' level of engagement in open research practices across universities in the United Kingdom and Ireland, while also assessing possible explanatory factors that may impact their engagement. Data were collected from 602 psychology researchers in the United Kingdom and Ireland on the extent to which they have implemented various practices (e.g., use of preprints, preregistration, open data, open materials). Here we present the summarized descriptive results, as well as considering differences between various categories of researcher (e.g., career stage, subdiscipline, methodology), and examining the relationship between researcher's practices and their self-reported capability, opportunity, and motivation (COM-B) to engage in open research practices. Results show that while there is considerable variability in engagement of open research practices, differences across career stage and subdiscipline of psychology are small by comparison. We observed consistent differences according to respondent's research methodology and based on the presence of institutional support for open research. COM-B dimensions were collectively significant predictors of engagement in open research, with automatic motivation emerging as a consistently strong predictor. We discuss these findings, outline some of the challenges experienced in this study, and offer suggestions and recommendations for future research. Estimating the prevalence of responsible research practices is important to assess sustained behaviour change in research reform, tailor educational training initiatives, and to understand potential factors that might impact engagement.

The influence of socio-economic status (SES) on child temperament and psychological symptoms was examined using a nationally representative sample in Singapore. Data were available for 2169 children from 1987 families. Caregivers' reports were obtained on children aged 4–6. SES was operationalized as an aggregation of household income per capita, parental education level and housing type. Compared to their counterparts from higher SES families, children from low-SES families tended to exhibit (a) higher negative affectivity but lower effortful control, and (b) higher internalizing and externalizing symptoms. In addition, children with a ‘resilient’ temperamental profile (i.e. low negative affectivity and high effortful control) were more likely to come from families with much higher SES, relative to children with other profiles. Children with high internalizing symptoms tended to come from low-SES backgrounds, regardless of their externalizing symptoms. Among children with low internalizing symptoms, those with high externalizing symptoms came from lower SES backgrounds compared to those with low externalizing symptoms. Parental warmth and distress mediated the association between SES and child temperament and symptom profiles, with the exception of distress in the SES–temperament link. These findings supported the family stress model and highlighted the novel perspective of SES's influence on configurations of child temperament and symptom characteristics.

The study investigated how active and avoidant coping styles predicted the trajectory membership of anxiety symptoms during the transition into early adolescence. A total of 321 Chinese children aged 9 to 10 years were recruited from a primary school in mainland China. Self-reported trait anxiety, coping styles and anxiety symptoms were assessed at baseline. After 6 months, self-reported anxiety symptoms were measured at three follow-up assessments with an interval of 6 months. Latent class growth modelling revealed high (18.7%) and low (81.3%) trajectories of anxiety symptoms in children during the transition into early adolescence. After controlling for trait anxiety, depression and sex, high active coping style predicted the trajectory of high anxiety symptoms, which was not moderated by trait anxiety. Before controlling for these covariates, the relation between active coping style and anxiety symptoms was in the opposite direction. A high avoidant coping style showed a trend to predict the trajectory of high anxiety symptoms only for children with low trait anxiety. These findings add a developmental context to the relationships of active and avoidant coping styles to anxiety symptoms and suggest that trait anxiety may moderate these relationships.