Two studies were conducted investigating the relationship between the Zimbardo Time Perspective Inventory (ZTPI) scales and well-being measures in British (N = 179) and Russian (N = 289) student samples. On the basis of person-oriented approach, a cluster-analysis operationalization of Balanced Time Perspective (BTP) using ZTPI was proposed and validated, demonstrating more evidence for its validity than the previously suggested cut-off-point approach. Four distinct time perspective patterns were discovered in both samples: future-oriented, present-oriented, balanced and negative. The clusters revealed significant differences in well-being, with members of the BTP cluster demonstrating the highest scores in both samples. The relationship between ZTPI and Temporal Life Satisfaction Scale in the British sample was found to be non-uniform for past, present and future. Based on these findings, a distinction between three aspects of time perspective is theoretically proposed, and its implications for the future development of the ZTPI are discussed.

We conducted a theoretical and psychometric evaluation of self-determination theory’s “relative autonomy continuum” (RAC), an important aspect of the theory whose validity has recently been questioned. We first derived a Comprehensive Relative Autonomy Index (C-RAI) containing six subscales and 24 items, by conducting a paired paraphrase content analysis of existing RAI measures. We administered the C-RAI to multiple U.S. and Russian samples, assessing motivation to attend class, study a major, and take responsibility. Item-level and scale-level multidimensional scaling analyses, confirmatory factor analyses, and simplex/circumplex modeling analyses reaffirmed the validity of the RAC, across multiple samples, stems, and studies. Validation analyses predicting subjective well-being and trait autonomy from the six separate subscales, in combination with various higher order composites (weighted and unweighted), showed that an aggregate unweighted RAI score provides the most unbiased and efficient indicator of the overall quality of motivation within the behavioral domain being assessed.

Guided by the early findings of social scientists, practitioners have long advocated for greater contact between groups to reduce prejudice and increase social cohesion. Recent work, however, suggests that intergroup contact can undermine support for social change towards greater equality, especially among disadvantaged group members. Using a large and heterogeneous dataset (12,997 individuals from 69 countries), we demonstrate that intergroup contact and support for social change towards greater equality are positively associated among members of advantaged groups (ethnic majorities and cis-heterosexuals) but negatively associated among disadvantaged groups (ethnic minorities and sexual and gender minorities). Specification-curve analysis revealed important variation in the size-and at times, direction-of correlations, depending on how contact and support for social change were measured. This allowed us to identify one type of support for change-willingness to work in solidarity- that is positively associated with intergroup contact among both advantaged and disadvantaged group members.

In this article, we assess the structural equivalence of the Zimbardo Time Perspective Inventory (ZTPI) across 26 samples from 24 countries ( N = 12,200). The ZTPI is proven to be a valid and reliable index of individual differences in time perspective across five temporal categories: Past Negative, Past Positive, Present Fatalistic, Present Hedonistic, and Future. We obtained evidence for invariance of 36 items (out of 56) and also the five-factor structure of ZTPI across 23 countries. The short ZTPI scales are reliable for country-level analysis, whereas we recommend the use of the full scales for individual-level analysis. The short version of ZTPI will further promote integration of research in the time perspective domain in relation to many different psycho-social processes.

There is ample evidence that morphological and social cues in a human face provide signals of human personality and behaviour. Previous studies have discovered associations between the features of artificial composite facial images and attributions of personality traits by human experts. We present new findings demonstrating the statistically significant prediction of a wider set of personality features (all the Big Five personality traits) for both men and women using real-life static facial images. Volunteer participants (N = 12,447) provided their face photographs (31,367 images) and completed a self-report measure of the Big Five traits. We trained a cascade of artificial neural networks (ANNs) on a large labelled dataset to predict self-reported Big Five scores. The highest correlations between observed and predicted personality scores were found for conscientiousness (0.360 for men and 0.335 for women) and the mean effect size was 0.243, exceeding the results obtained in prior studies using ‘selfies’. The findings strongly support the possibility of predicting multidimensional personality profiles from static facial images using ANNs trained on large labelled datasets. Future research could investigate the relative contribution of morphological features of the face and other characteristics of facial images to predicting personality.