Research suggesting that political conservatives are happier than political liberals has relied exclusively on self-report measures of subjective well-being. We show that this finding is fully mediated by conservatives' self-enhancing style of self-report (study 1; N = 1433) and then describe three studies drawing from "big data" sources to assess liberal-conservative differences in happiness-related behavior (studies 2 to 4; N = 4936). Relative to conservatives, liberals more frequently used positive emotional language in their speech and smiled more intensely and genuinely in photographs. Our results were consistent across large samples of online survey takers, U.S. politicians, Twitter users, and LinkedIn users. Our findings illustrate the nuanced relationship between political ideology, self-enhancement, and happiness and illuminate the contradictory ways that happiness differences can manifest across behavior and self-reports.

Anxiety sensitivity, a trait characterised by fear of anxiety-related body sensations, has been linked to heightened attention to pain, appraising body sensations as threatening, and remembering threatrelated information. We assessed whether individuals with greater anxiety sensitivity overestimate in remembering pain. We also assessed whether emotion regulation strategies that direct attention away from pain (distraction), or alter appraisals of pain (reappraisal), alleviate memory bias. Participants (N = 137) were randomly assigned to one of two emotion regulation conditions or to a control condition before taking part in a cold pressor task. Greater anxiety sensitivity was associated with overestimation in remembering pain. Engaging in reappraisal mitigated this memory bias but engaging in distraction did not. This is the first study to examine the relations among anxiety sensitivity, emotion regulation and memory for pain. The findings suggest that health-care practitioners can encourage reappraisal to promote more positive memories of procedural pain, particularly in patients high in anxiety sensitivity.

Background Promoting well-being and preventing poor mental health in young people is a major global priority. Building emotional competence (EC) skills via a mobile app may be an effective, scalable and acceptable way to do this. However, few large-scale controlled trials have examined the efficacy of mobile apps in promoting mental health in young people; none have tailored the app to individual profiles. Method/design The Emotional Competence for Well-Being in Young Adults cohort multiple randomised controlled trial (cmRCT) involves a longitudinal prospective cohort to examine well-being, mental health and EC in 16–22 year olds across 12 months. Within the cohort, eligible participants are entered to either the PREVENT trial (if selected EC scores at baseline within worst-performing quartile) or to the PROMOTE trial (if selected EC scores not within worst-performing quartile). In both trials, participants are randomised (i) to continue with usual practice, repeated assessments and a self-monitoring app; (ii) to additionally receive generic cognitive-behavioural therapy self-help in app; (iii) to additionally receive personalised EC self-help in app. In total, 2142 participants aged 16 to 22 years, with no current or past history of major depression, bipolar disorder or psychosis will be recruited across UK, Germany, Spain, and Belgium. Assessments take place at baseline (pre-randomisation), 1, 3 and 12 months post-randomisation. Primary endpoint and outcome for PREVENT is level of depression symptoms on the Patient Health Questionnaire-9 at 3 months; primary endpoint and outcome for PROMOTE is emotional well-being assessed on the Warwick-Edinburgh Mental Wellbeing Scale at 3 months. Depressive symptoms, anxiety, well-being, health-related quality of life, functioning and cost-effectiveness are secondary outcomes. Compliance, adverse events and potentially mediating variables will be carefully monitored. Conclusions The trial aims to provide a better understanding of the causal role of learning EC skills using interventions delivered via mobile phone apps with respect to promoting well-being and preventing poor mental health in young people. This knowledge will be used to develop and disseminate innovative evidence-based, feasible, and effective Mobile-health public health strategies for preventing poor mental health and promoting well-being. Trial registration ClinicalTrials.gov (www.clinicaltrials.org). Number of identification: NCT04148508 November 2019.

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The internal structure of ability emotional intelligence (EI) tests at item level has been hardly studied, and if studied often the predicted structure did not show. In the present study, an a priori model for responses to EI ability items using Likert response scales with a Situational Judgement Test (SJT) format is investigated with confirmatory factor analysis. The model consists of (1) a target EI ability factor, (2) an acquiescence factor, which is a method factor induced by the Likert response scales, and (3) design-based error covariances, which are induced by the SJT format. It is investigated whether this a priori model can account for the observed associations between the raw item responses of the Components of Emotion Understanding Test-24 (CEUT-24). The CEUT-24 is a new test developed to assess emotion understanding, a key aspect of the EI ability construct, based on the componential emotion framework. The sample consisted of 1184 participants (15–22 years old) from four European countries (United Kingdom, Belgium, Germany, and Spain) speaking four different languages (English, Dutch, German and Spanish). Findings showed that the a priori model fitted the data well in all four languages. Furthermore, measurement invariance testing gave evidence for a well-fitting configural, metric, and partial scalar invariance model. The conclusion is that within a regular CFA framework using raw observed items responses, method factors (acquiescence response style and scenario induced variance) can be disentangled from the targeted EI ability factor.