Social cohesion predicts COVID-19 vaccination intentions and uptake

COVID-19 vaccination is widely regarded as an individual decision, resting upon individual characteristics and demographic factors. In this research, we provide evidence that psychological group membership, and more precisely, social cohesion—a multidimensional concept that encompasses one's sense of connectedness to, and interrelations within, a group—can help us understand COVID-19 vaccination intentions (Study 1) and uptake (Study 2). Study 1 is a repeated-measures study with a representative sample of 3026 Australians. We found evidence that social cohesion can be conceptualised as a multidimensional structure; moreover, social cohesion at Wave 1 (early in the COVID-19) predicted greater vaccination intention and lower perceived risk of vaccination at Wave 2 (4 months later). In Study 2 (a cross-sectional study, N = 499), the multidimensional structure of social cohesion was associated with greater uptake of vaccine doses (in addition to willingness to receive further doses and perceived risk of the vaccine). These relations were found after controlling for a series of demographic (i.e., sex, age, income), health-related factors (i.e., subjective health; perceived risk; having been diagnosed with COVID-19), and individual differences (political orientation, social dominance orientation, individualism). These results demonstrate the need to go beyond individual factors when it comes to behaviours that protect groups, and particularly when examining COVID-19 vaccination—one of the most important ways of slowing the spread of the virus.     

Pain in the eye of the beholder: Variations in pain visual representations as a function of face ethnicity and culture

Pain experienced by Black individuals is systematically underestimated, and recent studies have shown that part of this bias is rooted in perceptual factors. We used Reverse Correlation to estimate visual representations of the pain expression in Black and White faces, in participants originating from both Western and African countries. Groups of raters were then asked to evaluate the presence of pain and other emotions in these representations. A second group of White raters then evaluated those same representations placed over a neutral background face (50% White; 50% Black). Image-based analyses show significant effects of culture and face ethnicity, but no interaction between the two factors. Western representations were more likely to be judged as expressing pain than African representations. For both cultural groups, raters also perceived more pain in White face representations than in Black face representations. However, when changing the background stimulus to the neutral background face, this effect of face ethnic profile disappeared. Overall, these results suggest that individuals have different expectations of how pain is expressed by Black and White individuals, and that cultural factors may explain a part of this phenomenon     

Status faking on the SVIB-M

A study and replication of students faking interest in high status occupations on the Strong Vocational Interest Blank for Men. In general, the faking was successful in shifting the specific target occupational scales and especially the occupational level scale. Other scales are affected, many with decisive upward or downward shifts. Demonstration is made of the extent to which the faking condition led to differences in the overall test results. Various aspects of the general problem of test faking are reviewed.     

Factor analysis by generalized least squares

Aitken's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are seale free and asymptotically efficient. The estimates are computed by a rapidly converging Newton-Raphson procedure. A new technique is used to deal with Heywood cases effectively.The work on this project was done when the first author was Research Statistician at Educational Testing Service, Princeton, N. J. The second author was in part supported by a grant from the Research Committee of the University of Wisconsin Graduate School. The authors wish to thank Michael Browne for many helpful comments and Marielle van Thillo for valuable assistance in the numerical computations.     

An individual difference model for the multidimensional analysis of preference data

A model for the analysis of paired comparison data is presented which combines features of the BTL-model with features of the Unfolding model. The model is metric, mathematically tractable, and has an exact algebraic solution. Since it is multidimensional and allows for individual differences, it is thought to be more realistic for some choice situations than either the Thurstone model or the BTL-model. No claim is made that the present model will be appropriate for all conceivable choice situations. Rather, it is argued that the fact that it is explicitly falsifiable is a point in its favor.This work was supported by a grant of the United States Public Health Service (1 R03 MH19139 01 MSM) and a David Ross (XR) grant of the Purdue Research Foundation (PRF 2132), both of which are gratefully acknowledged. We also owe thanks to Dr. Terry Cooper, whose careful scrutiny of an earlier draft of this paper allowed us to reduce the number of errors from n to n-1.