Facial first impressions across culture : data-driven modelling of Chinese and British perceivers’ unconstrained facial impressions

People form first impressions from facial appearance rapidly, and these impressions can have considerable social and economic consequences. Three dimensions can explain Western perceivers’ impressions of Caucasian faces: approachability, youthful-attractiveness, and dominance. Impressions along these dimensions are theorized to be based on adaptive cues to threat detection or sexual selection, making it likely that they are universal. We tested whether the same dimensions of facial impressions emerge across culture by building data-driven models of first impressions of Asian and Caucasian faces derived from Chinese and British perceivers’ unconstrained judgments. We then cross-validated the dimensions with computer-generated average images. We found strong evidence for common approachability and youthful-attractiveness dimensions across perceiver and face race, with some evidence of a third dimension akin to capability. The models explained ~75% of the variance in facial impressions. In general, the findings demonstrate substantial cross-cultural agreement in facial impressions, especially on the most salient dimensions

Identification of cancer risk and associated behaviour: implications for social marketing campaigns for cancer prevention

Background Community misconception of what causes cancer is an important consideration when devising communication strategies around cancer prevention, while those initiating social marketing campaigns must decide whether to target the general population or to tailor messages for different audiences. This paper investigates the relationships between demographic characteristics, identification of selected cancer risk factors, and associated protective behaviours, to inform audience segmentation for cancer prevention social marketing. Methods Data for this cross-sectional study (n = 3301) are derived from Cancer Council New South Wales’ 2013 Cancer Prevention Survey. Descriptive statistics and logistic regression models were used to investigate the relationship between respondent demographic characteristics and identification of each of seven cancer risk factors; demographic characteristics and practice of the seven ‘protective’ behaviours associated with the seven cancer risk factors; and identification of cancer risk factors and practising the associated protective behaviours, controlling for demographic characteristics. Results More than 90% of respondents across demographic groups identified sun exposure and smoking cigarettes as moderate or large cancer risk factors. Around 80% identified passive smoking as a moderate/large risk factor, and 40–60% identified being overweight or obese, drinking alcohol, not eating enough vegetables and not eating enough fruit. Women and older respondents were more likely to identify most cancer risk factors as moderate/large, and to practise associated protective behaviours. Education was correlated with identification of smoking as a moderate/large cancer risk factor, and with four of the seven protective behaviours. Location (metropolitan/regional) and country of birth (Australia/other) were weak predictors of identification and of protective behaviours. Identification of a cancer risk factor as moderate/large was a significant predictor for five out of seven associated cancer-protective behaviours, controlling for demographic characteristics. Conclusions These findings suggest a role for both audience segmentation and whole-of-population approaches in cancer-prevention social marketing campaigns. Targeted campaigns can address beliefs of younger people and men about cancer risk factors. Traditional population campaigns can enhance awareness of being overweight, alcohol consumption, and poor vegetable and fruit intake as cancer risk factors

A Comparison of Different Approaches to Unravel the Latent Structure within Metabolic Syndrome

Background: Exploratory factor analysis is a commonly used statistical technique in metabolic syndrome research to uncover latent structure amongst metabolic variables. The application of factor analysis requires methodological decisions that reflect the hypothesis of the metabolic syndrome construct. These decisions often raise the complexity of the interpretation from the output. We propose two alternative techniques developed from cluster analysis which can achieve a clinically relevant structure, whilst maintaining intuitive advantages of clustering methodology. Methods: Two advanced techniques of clustering in the VARCLUS and matroid methods are discussed and implemented on a metabolic syndrome data set to analyze the structure of ten metabolic risk factors. The subjects were selected from the normative aging study based in Boston, Massachusetts. The sample included a total of 847 men aged between 21 and 81 years who provided complete data on selected risk factors during the period 1987 to 1991. Results: Four core components were identified by the clustering methods. These are labelled obesity, lipids, insulin resistance and blood pressure. The exploratory factor analysis with oblique rotation suggested an overlap of the loadings identified on the insulin resistance and obesity factors. The VARCLUS and matroid analyses separated these components and were able to demonstrate associations between individual risk factors. Conclusions: An oblique rotation can be selected to reflect the clinical concept of a single underlying syndrome, howeve

Cognitive-Affective Inconsistency and Ambivalence: Impact on the Overall Attitude–Behavior Relationship

This research explored whether overall attitude is a stronger predictor of behavior when underlying cognitive-affective inconsistency or ambivalence is low versus high. Across three prospective studies in different behaviors and populations (Study 1: eating a low-fat diet, N = 136 adults, eating five fruit and vegetables per day, N = 135 adults; Study 2: smoking initiation, N = 4,933 adolescents; and Study 3: physical activity, N = 909 adults) we tested cognitive-affective inconsistency and ambivalence individually and simultaneously as moderators of the overall attitude–behavior relationship. Across studies, more similar effects were observed for inconsistency compared with ambivalence (in both individual and simultaneous analyses). Meta-analysis across studies supported this conclusion with both cognitive-affective inconsistency and ambivalence being significant moderators when considered on their own, but only inconsistency being significant when tested simultaneously. The reported studies highlight the importance of cognitive-affective inconsistency as a determinant of the strength of overall attitude

Validation and psychometric analysis of the Internet Addiction Test in Spanish among college students

BACKGROUND: The wide use of the Internet in the workplace, academic or social field, can have an impact on daily life. One of the most used questionnaires worldwide to analyse these problems is the Internet Addiction Test (IAT). Our aim was to validate a Spanish version of the IAT and analyse its psychometric properties. METHODS: Population of study were college students participating in the uniHcos project (Universities of Granada, Huelva, Jaén, León, Salamanca, and Vigo). The questionnaire was translated and back-translated by two native English speakers. Reliability of scores was analysed using Pearson's correlation coefficient and agreement was analysed using the Bland-Altman and Kappa techniques. Test dimensions were analysed by exploratory and confirmatory factor analysis. RESULTS: The reliability of scores was good (r = 0.899, Kappa = 0.650 and mean difference using Bland-Altman = -3.5). The psychometric assessment identified two factors (Emotional Investment; Performance and Time Management) which explained 55 % of the variance (total internal consistency of 0.91) and only 19 items. The confirmatory analysis showed an acceptable goodness of fit, especially when items 6 and 8 were related (RMSEA = 0.07 90%IC = 0.06 - 0.08; WRMR = 1.01, CFI = 0.96; TLI = 0.95). The two dimensions were negatively correlated with age and positively correlated with time spent online, especially for the purposes of leisure and entertainment. DISCUSSION: The results show good reliability and psychometric properties of the Spanish version of IAT with a two-dimensional solution. This result is partially in concordance with previous validations of the IAT in other languages that have found uni- and multi-dimensional solutions using different methodologies. Moreover, we want to highlight the possibility that some item of this questionnaire is outdated due to the technological and lifestyles changes and should be not taken into account. CONCLUSION: The reliability and psychometric properties obtained in this study support the conclusion that this Spanish short version of the IAT represents a useful tool for the analysis of problems arising from misuse of the Internet

Assessing the organizational context for EBP implementation: the development and validity testing of the Implementation Climate Scale (ICS)

BACKGROUND: Although the importance of the organizational environment for implementing evidence-based practices (EBP) has been widely recognized, there are limited options for measuring implementation climate in public sector health settings. The goal of this research was to develop and test a measure of EBP implementation climate that would both capture a broad range of issues important for effective EBP implementation and be of practical use to researchers and managers seeking to understand and improve the implementation of EBPs. METHODS: Participants were 630 clinicians working in 128 work groups in 32 US-based mental health agencies. Items to measure climate for EBP implementation were developed based on past literature on implementation climate and other strategic climates and in consultation with experts on the implementation of EBPs in mental health settings. The sample was randomly split at the work group level of analysis; half of the sample was used for exploratory factor analysis (EFA), and the other half was used for confirmatory factor analysis (CFA). The entire sample was utilized for additional analyses assessing the reliability, support for level of aggregation, and construct-based evidence of validity. RESULTS: The EFA resulted in a final factor structure of six dimensions for the Implementation Climate Scale (ICS): 1) focus on EBP, 2) educational support for EBP, 3) recognition for EBP, 4) rewards for EBP, 5) selection for EBP, and 6) selection for openness. This structure was supported in the other half of the sample using CFA. Additional analyses supported the reliability and construct-based evidence of validity for the ICS, as well as the aggregation of the measure to the work group level. CONCLUSIONS: The ICS is a very brief (18 item) and pragmatic measure of a strategic climate for EBP implementation. It captures six dimensions of the organizational context that indicate to employees the extent to which their organization prioritizes and values the successful implementation of EBPs. The ICS can be used by researchers to better understand the role of the organizational context on implementation outcomes and by organizations to evaluate their current climate as they consider how to improve the likelihood of implementation success. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13012-014-0157-1) contains supplementary material, which is available to authorized users

Exploratory factor analysis of self-reported symptoms in a large, population-based military cohort

<p>Abstract</p> <p>Background</p> <p>US military engagements have consistently raised concern over the array of health outcomes experienced by service members postdeployment. Exploratory factor analysis has been used in studies of 1991 Gulf War-related illnesses, and may increase understanding of symptoms and health outcomes associated with current military conflicts in Iraq and Afghanistan. The objective of this study was to use exploratory factor analysis to describe the correlations among numerous physical and psychological symptoms in terms of a smaller number of unobserved variables or factors.</p> <p>Methods</p> <p>The Millennium Cohort Study collects extensive self-reported health data from a large, population-based military cohort, providing a unique opportunity to investigate the interrelationships of numerous physical and psychological symptoms among US military personnel. This study used data from the Millennium Cohort Study, a large, population-based military cohort. Exploratory factor analysis was used to examine the covariance structure of symptoms reported by approximately 50,000 cohort members during 2004-2006. Analyses incorporated 89 symptoms, including responses to several validated instruments embedded in the questionnaire. Techniques accommodated the categorical and sometimes incomplete nature of the survey data.</p> <p>Results</p> <p>A 14-factor model accounted for 60 percent of the total variance in symptoms data and included factors related to several physical, psychological, and behavioral constructs. A notable finding was that many factors appeared to load in accordance with symptom co-location within the survey instrument, highlighting the difficulty in disassociating the effects of question content, location, and response format on factor structure.</p> <p>Conclusions</p> <p>This study demonstrates the potential strengths and weaknesses of exploratory factor analysis to heighten understanding of the complex associations among symptoms. Further research is needed to investigate the relationship between factor analytic results and survey structure, as well as to assess the relationship between factor scores and key exposure variables.</p

Refining trait resilience: identifying engineering, ecological, and adaptive facets from extant measures of resilience

The current paper presents a new measure of trait resilience derived from three common mechanisms identified in ecological theory: Engineering, Ecological and Adaptive (EEA) resilience. Exploratory and confirmatory factor analyses of five existing resilience scales suggest that the three trait resilience facets emerge, and can be reduced to a 12-item scale. The conceptualization and value of EEA resilience within the wider trait and well-being psychology is illustrated in terms of differing relationships with adaptive expressions of the traits of the five-factor personality model and the contribution to well-being after controlling for personality and coping, or over time. The current findings suggest that EEA resilience is a useful and parsimonious model and measure of trait resilience that can readily be placed within wider trait psychology and that is found to contribute to individual well-bein

A statistical approach to quantitative data validation focused on the assessment of students' perceptions about biotechnology

Student awareness levels are frequently used to evaluate the effectiveness of educational policies to promote scientific literacy. Over the last years several studies have been developed to assess students' perceptions towards science and technology, which usually rely on quantitative methods to achieve broad characterizations, and obtain quantifiable and comparable data. Although the usefulness of this information depends on its validity and reliability, validation is frequently neglected by researchers with limited background in statistics. In this context, we propose a guideline to implement a statistical approach to questionnaire validation, combining exploratory factor analysis and reliability analysis. The work focuses on the psychometric analysis of data provided by a questionnaire assessing 1196 elementary and high school students' perceptions about biotechnology. Procedural guidelines to enhance the efficiency of quantitative inquiry surveys are given, by discussing essential methodological aspects and relevant criteria to integrate theory into practice.The authors are grateful to all the participant teachers and students that contributed to gather the data presented and to Catarina L. Santos for useful comments and suggestions on the manuscript. Maria Joao Fonseca was supported by the FCT fellowship SFRH/BD/37389/2007 and this work was sponsored by a research grant (PTDC/AGR-PRO/111857/2009) from Fundacao para a Ciencia e Tecnologia (FCT, Portugal)