Attitudes towards AI: measurement and associations with personality.

Artificial intelligence (AI) has become an integral part of many contemporary technologies, such as social media platforms, smart devices, and global logistics systems. At the same time, research on the public acceptance of AI shows that many people feel quite apprehensive about the potential of such technologies-an observation that has been connected to both demographic and sociocultural user variables (e.g., age, previous media exposure). Yet, due to divergent and often ad-hoc measurements of AI-related attitudes, the current body of evidence remains inconclusive. Likewise, it is still unclear if attitudes towards AI are also affected by users' personality traits. In response to these research gaps, we offer a two-fold contribution. First, we present a novel, psychologically informed questionnaire (ATTARI-12) that captures attitudes towards AI as a single construct, independent of specific contexts or applications. Having observed good reliability and validity for our new measure across two studies (N1 = 490; N2 = 150), we examine several personality traits-the Big Five, the Dark Triad, and conspiracy mentality-as potential predictors of AI-related attitudes in a third study (N3 = 298). We find that agreeableness and younger age predict a more positive view towards artificially intelligent technology, whereas the susceptibility to conspiracy beliefs connects to a more negative attitude. Our findings are discussed considering potential limitations and future directions for research and practice.

Remote Testing of Reading Comprehension in 8-Year-Old Children: Mode and Setting Effects.

Proctored remote testing of cognitive abilities in the private homes of test-takers is becoming an increasingly popular alternative to standard psychological assessments in test centers or classrooms. Because these tests are administered under less standardized conditions, differences in computer devices or situational contexts might contribute to measurement biases that impede fair comparisons between test-takers. Because it is unclear whether cognitive remote testing might be a feasible assessment approach for young children, the present study (N = 1,590) evaluated a test of reading comprehension administered to children at the age of 8 years. To disentangle mode from setting effects, the children finished the test either in the classroom on paper or computer or remotely on tablets or laptops. Analyses of differential response functioning found notable differences between assessment conditions for selected items. However, biases in test scores were largely negligible. Only for children with below-average reading comprehension small setting effects between on-site and remote testing were observed. Moreover, response effort was higher in the three computerized test versions, among which, reading on tablets most strongly resembled the paper condition. Overall, these results suggest that, on average, even for young children remote testing introduces little measurement bias.

Accuracy and precision of fixed and random effects in meta-analyses of randomized control trials for continuous outcomes.

Meta-analyses of treatment effects in randomized control trials are often faced with the problem of missing information required to calculate effect sizes and their sampling variances. Particularly, correlations between pre- and posttest scores are frequently not available. As an ad-hoc solution, researchers impute a constant value for the missing correlation. As an alternative, we propose adopting a multivariate meta-regression approach that models independent group effect sizes and accounts for the dependency structure using robust variance estimation or three-level modeling. A comprehensive simulation study mimicking realistic conditions of meta-analyses in clinical and educational psychology suggested that imputing a fixed correlation 0.8 or adopting a multivariate meta-regression with robust variance estimation work well for estimating the pooled effect but lead to slightly distorted between-study heterogeneity estimates. In contrast, three-level meta-regressions resulted in largely unbiased fixed effects but more inconsistent prediction intervals. Based on these results recommendations for meta-analytic practice and future meta-analytic developments are provided.

Studying item-effect variables and their correlation patterns with multi-construct multi-state models.

Method effects on the item level can be modeled as latent difference variables in longitudinal data. These item-effect variables represent interindividual differences associated with responses to a specific item when assessing a common construct with multi-item scales. In latent variable analyses, their inclusion substantially improves model fits in comparison to classical unidimensional measurement models. More importantly, covariations between different item-effect variables and with other constructs can provide valuable insights, for example, into the structure of the studied instrument or the response process. Therefore, we introduce a multi-construct multi-state model with item-effect variables for systematic investigations of these correlation patterns within and between constructs. The implementation of this model is demonstrated using a sample of N = 2,529 Dutch respondents that provided measures of life satisfaction and positive affect at five measurement occasions. Our results confirm non-negligible item effects in two ostensibly unidimensional scales, indicating the importance of modeling interindividual differences on the item level. The correlation pattern between constructs indicated rather specific effects for individual items and no common causes, but the correlations within a construct align with the item content and support a substantive meaning. These analyses exemplify how multi-construct multi-state models allow the systematic examination of item effects to improve substantive and psychometric research.

The Predictive Validity of Item Effect Variables in the Satisfaction With Life Scale for Psychological and Physical Health.

Although the Satisfaction with Life Scale strives to capture a single dimension, describing respondents' satisfaction with life as a whole, individual items might also capture unique aspects of life satisfaction leading to some form of multidimensionality. Such systematic item-specific variance can be viewed as a content-laden secondary trait. Information on the nomological net and predictive validity can be useful to aid the interpretation of these item-specific effects. Therefore, the present study on N = 2,543 Dutch respondents adopts revised latent state-trait theory to disentangle common construct variance, random measurement error, and person-specific item effects in the Satisfaction with Life Scale across three measurement occasions. The reported analyses not only demonstrate how to examine item-specific multidimensionality in longitudinal data but also emphasize how different identification constraints for the latent variable lead to different interpretations. Moreover, the predictive validity of item effect variables for the prediction of psychological and physical health is examined. A cross-validation with the same sample at a later measurement period and robustness checks with incomplete data, support our findings on the substantive value of a multidimensional specification of the Satisfaction with Life Scale for substantive analyses. Finally, the contributions of person-specific item effects for psychological assessments are discussed.

The Dimensionality of the Brief COPE Before and During the COVID-19 Pandemic.

The Brief COPE (Coping Orientation to Problems Experienced) is a frequently used questionnaire assessing 14 theoretically derived coping mechanisms, but psychometric research has suggested inconsistent results concerning its factor structure. The aim of this study was to investigate primary and secondary order factor structures of the Brief COPE during the COVID-19 pandemic by testing 11 different models by confirmatory factor analyses and to assess differences between sex, age groups, and relationship status. Altogether, 529 respondents from Austria and Germany participated in a web-based survey. Results supported the originally hypothesized 14-factor structure but did not support previously described higher-order structures. However, bass-ackwards analyses suggested systematic overlap between different factors, which might have contributed to different factor solutions in previous research. Measurement invariance across sex, age groups, and relationship status could be confirmed. Findings suggest that cultural and situational aspects as well as the functional level should be considered in research on theoretical framing of coping behavior.

Observing many researchers using the same data and hypothesis reveals a hidden universe of uncertainty.

This study explores how researchers' analytical choices affect the reliability of scientific findings. Most discussions of reliability problems in science focus on systematic biases. We broaden the lens to emphasize the idiosyncrasy of conscious and unconscious decisions that researchers make during data analysis. We coordinated 161 researchers in 73 research teams and observed their research decisions as they used the same data to independently test the same prominent social science hypothesis: that greater immigration reduces support for social policies among the public. In this typical case of social science research, research teams reported both widely diverging numerical findings and substantive conclusions despite identical start conditions. Researchers' expertise, prior beliefs, and expectations barely predict the wide variation in research outcomes. More than 95% of the total variance in numerical results remains unexplained even after qualitative coding of all identifiable decisions in each team's workflow. This reveals a universe of uncertainty that remains hidden when considering a single study in isolation. The idiosyncratic nature of how researchers' results and conclusions varied is a previously underappreciated explanation for why many scientific hypotheses remain contested. These results call for greater epistemic humility and clarity in reporting scientific findings.

Detecting Careless Responding in Survey Data Using Stochastic Gradient Boosting.

Careless responding is a bias in survey responses that disregards the actual item content, constituting a threat to the factor structure, reliability, and validity of psychological measurements. Different approaches have been proposed to detect aberrant responses such as probing questions that directly assess test-taking behavior (e.g., bogus items), auxiliary or paradata (e.g., response times), or data-driven statistical techniques (e.g., Mahalanobis distance). In the present study, gradient boosted trees, a state-of-the-art machine learning technique, are introduced to identify careless respondents. The performance of the approach was compared with established techniques previously described in the literature (e.g., statistical outlier methods, consistency analyses, and response pattern functions) using simulated data and empirical data from a web-based study, in which diligent versus careless response behavior was experimentally induced. In the simulation study, gradient boosting machines outperformed traditional detection mechanisms in flagging aberrant responses. However, this advantage did not transfer to the empirical study. In terms of precision, the results of both traditional and the novel detection mechanisms were unsatisfactory, although the latter incorporated response times as additional information. The comparison between the results of the simulation and the online study showed that responses in real-world settings seem to be much more erratic than can be expected from the simulation studies. We critically discuss the generalizability of currently available detection methods and provide an outlook on future research on the detection of aberrant response patterns in survey research.

Exploring the myth of the chubby gamer: A meta-analysis on sedentary video gaming and body mass.

RATIONALE: High body mass and obesity are frequently linked to the use of sedentary media, like television (TV) or non-active video games. Empirical evidence regarding video gaming, however, has been mixed, and theoretical considerations explaining a relationship between general screen time and body mass may not generalize to non-active video gaming. OBJECTIVE: The current meta-analysis had two main goals. First, we wanted to provide an estimate of the average effect size of the relationship between sedentary video gaming and body mass. In doing so we acknowledged several context variables to gauge the stability of the average effect. Second, to provide additional evidence on processes, we tested the displacement effect of physical activity by video gaming time with the help of a meta-analytic structural equation model (MASEM). METHOD: Published and unpublished studies were identified through keyword searches in different databases and references in relevant reports were inspected for further studies. We present a random-effects, three-level meta-analysis based on 20 studies (total N = 38,097) with 32 effect sizes. RESULTS: The analyses revealed a small positive relationship between non-active video game use and body mass, ρˆ=.09, 95% CI [0.03, 0.14], indicating that they shared less than 1% in variance. The studies showed significant heterogeneity, Q (31) = 593.03, p < .001, I2 = 95.13. Moderator analyses revealed that the relationship was more pronounced for adults, ρˆ=.22, 95% CI [0.04, 0.40], as compared to adolescents, ρˆ=.01, 95% CI [-0.21, 0.23], or children, ρˆ=.09, 95% CI [-0.07, 0.25]. Meta-analytic structural equation modeling found little evidence for a displacement of physical activity through time spent on video gaming. CONCLUSION: These results do not corroborate the assumption of a strong link between video gaming and body mass as respective associations are small and primarily observed among adults.

The Structure of the Toronto Alexithymia Scale (TAS-20): A Meta-Analytic Confirmatory Factor Analysis.

Alexithymia is defined as the inability of persons to describe their emotional states, to identify the feelings of others, and a utilitarian type of thinking. The most popular instrument to assess alexithymia is the Toronto Alexithymia Scale (TAS-20). Despite its widespread use, an ongoing controversy pertains to its internal structure. The TAS-20 was originally constructed to capture three different factors, but several studies suggested different factor solutions, including bifactor models and models with a method factor for the reversely keyed items. The present study examined the dimensionality of the TAS-20 using summary data of 88 samples from 62 studies (total N = 69,722) with meta-analytic structural equation modeling. We found support for the originally proposed three-dimensional solution, whereas more complex models produced inconsistent factor loadings. Because a major source of misfit stems from translated versions, the results are discussed with respect to generalizations across languages and cultural contexts.

Setting a standard for low reading proficiency: A comparison of the bookmark procedure and constrained mixture Rasch model.

In order to draw pertinent conclusions about persons with low reading skills, it is essential to use validated standard-setting procedures by which they can be assigned to their appropriate level of proficiency. Since there is no standard-setting procedure without weaknesses, external validity studies are essential. Traditionally, studies have assessed validity by comparing different judgement-based standard-setting procedures. Only a few studies have used model-based approaches for validating judgement-based procedures. The present study addressed this shortcoming and compared agreement of the cut score placement between a judgement-based approach (i.e., Bookmark procedure) and a model-based one (i.e., constrained mixture Rasch model). This was performed by differentiating between individuals with low reading proficiency and those with a functional level of reading proficiency in three independent samples of the German National Educational Panel Study that included students from the ninth grade (N = 13,897) as well as adults (Ns = 5,335 and 3,145). The analyses showed quite similar mean cut scores for the two standard-setting procedures in two of the samples, whereas the third sample showed more pronounced differences. Importantly, these findings demonstrate that model-based approaches provide a valid and resource-efficient alternative for external validation, although they can be sensitive to the ability distribution within a sample.

Determinants of profiles of competence development in mathematics and reading in upper secondary education in Germany.

The registered report was targeted at identifying latent profiles of competence development in reading and mathematics among N = 15,012 German students in upper secondary education sampled in a multi-stage stratified cluster design across German schools. These students were initially assessed in grade 9 and provided competence assessments on three measurement occasions across six years using tests especially developed for the German National Educational Panel Study (NEPS). Using Latent Growth Mixture Models, Using Latent Growth Mixture Models, we aimed at identifying multiple profiles of competence development. Specifically, we expected to find at least one generalized (i.e., reading and mathematical competence develop similarly) and two specialized profiles (i.e., one of the domains develops faster) of competence development and that these profiles are explained by the specialization of interest and of vocational education of students. Contrary to our expectations, we did not find multiple latent profiles of competence development. The model describing our data best was a single-group latent growth model confirming a competence development profile, which can be described as specializing in mathematical competences, indicating a higher increase in mathematical competences as compared to reading competences in upper secondary school. Since only one latent profile was identified, potential predictors (specialization of vocational education and interest) for different profiles of competence development were not examined.

Linking of Rasch-Scaled Tests: Consequences of Limited Item Pools and Model Misfit.

In the context of item response theory (IRT), linking the scales of two measurement points is a prerequisite to examine a change in competence over time. In educational large-scale assessments, non-identical test forms sharing a number of anchor-items are frequently scaled and linked using two- or three-parametric item response models. However, if item pools are limited and/or sample sizes are small to medium, the sparser Rasch model is a suitable alternative regarding the precision of parameter estimation. As the Rasch model implies stricter assumptions about the response process, a violation of these assumptions may manifest as model misfit in form of item discrimination parameters empirically deviating from their fixed value of one. The present simulation study investigated the performance of four IRT linking methods-fixed parameter calibration, mean/mean linking, weighted mean/mean linking, and concurrent calibration-applied to Rasch-scaled data with a small item pool. Moreover, the number of anchor items required in the absence/presence of moderate model misfit was investigated in small to medium sample sizes. Effects on the link outcome were operationalized as bias, relative bias, and root mean square error of the estimated sample mean and variance of the latent variable. In the light of this limited context, concurrent calibration had substantial convergence issues, while the other methods resulted in an overall satisfying and similar parameter recovery-even in the presence of moderate model misfit. Our findings suggest that in case of model misfit, the share of anchor items should exceed 20% as is currently proposed in the literature. Future studies should further investigate the effects of anchor item composition regarding unbalanced model misfit.

Profiles of competence development in upper secondary education and their predictors.

This registered report protocol elaborates on the theory, methods, and material of a study to identify latent profiles of competence development in reading and mathematics among German students in upper secondary education. It is expected that generalized (reading and mathematical competence develop similarly) and specialized (one of the domains develops faster) competence profiles will be identified. Moreover, it is hypothesized that students' domain-specific interest and educational history will predict membership of these latent profiles as these factors influence the students' learning environments. For this study, we will use data from the German National Educational Panel Study, including students from ninth grade in secondary schools (expected N = 14,500). These students were tracked across six years and provided competence assessments on three occasions. The latent profiles based on the students' reading and mathematical competences will be identified using latent growth mixture modeling. If different types of profiles can be identified, multinomial regression will be utilized to analyze whether the likelihood of belonging to a certain competence development profile is influenced by students' domain-specific interest or educational history. As this protocol is submitted before any analyses were conducted, it will provide neither results nor conclusions.

Web-based and mixed-mode cognitive large-scale assessments in higher education: An evaluation of selection bias, measurement bias, and prediction bias.

Educational large-scale studies typically adopt highly standardized settings to collect cognitive data on large samples of respondents. Increasing costs alongside dwindling response rates in these studies necessitate exploring alternative assessment strategies such as unsupervised web-based testing. Before respective assessment modes can be implemented on a broad scale, their impact on cognitive measurements needs to be quantified. Therefore, an experimental study on N = 17,473 university students from the German National Educational Panel Study has been conducted. Respondents were randomly assigned to a supervised paper-based, a supervised computerized, and an unsupervised web-based mode to work on a test of scientific literacy. Mode-specific effects on selection bias, measurement bias, and predictive bias were examined. The results showed a higher response rate in web-based testing as compared to the supervised modes, without introducing a pronounced mode-specific selection bias. Analyses of differential test functioning showed systematically larger test scores in paper-based testing, particularly among low to medium ability respondents. Prediction bias for web-based testing was observed for one out of four criteria on study-related success factors. Overall, the results indicate that unsupervised web-based testing is not strictly equivalent to other assessment modes. However, the respective bias introduced by web-based testing was generally small. Thus, unsupervised web-based assessments seem to be a feasible option in cognitive large-scale studies in higher education.

Airborne human papillomavirus (HPV) transmission risk during ablation procedures: A systematic review and meta-analysis.

BACKGROUND: Human Papillomavirus (HPV) is associated with development of oropharyngeal cancer. Aim of this review was to assess airborne transmission risk of infectious particles from HPV lesions to airway mucosa of medical staff during established ablation procedures. METHODS: A systematic review of human and animal studies, published before 09/2020, relevant to airborne HPV transmission. Controlled studies reporting prevalence of HPV-associated upper airway (nasal/oral/pharyngeal) disease in staff performing ablation procedures (laser, loop electrosurgical excision [LEEP], cryosurgery) on HPV lesions were included in meta-analysis. Additionally, we aimed for a comprehensive systematic overview of studies regarding occupational risk of airborne HPV transmission and safety measures during ablation procedures. RESULTS: A total of n = 30 original studies report outcomes related to HPV transmission risk in medical staff conducting ablation procedures. HPV DNA detection in ablation smoke (n = 7), matching HPV genotypes on ablated HPV lesions and face/airways of medical staff after ablation (n = 2), and evidence for infectivity of papillomavirus in ablation smoke (n = 3, animal models only) were reported. Three case reports describe occupational HPV disease of upper airway mucosa. Three controlled studies assessed warts (in CO2 laser-users only); when pooling all controls (general population, non-laser users), nasal/oral/pharyngeal lesion sites were more common amongst laser-users (OR = 5.75; 95%CI[1.55, 21.38]; p < .001). DISCUSSION: Airborne HPV dispersal with matching "high-risk" HPV-genotypes in airways of medical staff after ablations (LEEP and CO2-laser) and cases of HPV-associated upper airways neoplasms based on exposure to laser and LEEP smoke are documented. Upper airway mucosa is a more common anatomical site for warts in CO2 laser users compared to controls. Simple safety measures greatly reduce HPV contamination and transmission risk.

Limited evidence for the effect of red color on cognitive performance: A meta-analysis.

Red color supposedly affects cognitive functioning in achievement situations and impairs test performance. Although this has been shown for different cognitive domains in different populations and cultural contexts, recent studies including close replications failed to corroborate this effect. Reported here is a random-effects meta-analysis of 67 effect sizes (38 samples) that compared test performance after viewing red or a control color. For anagram tests and knowledge tests no significant difference between color conditions was found (Cohen's d of -0.06 and -0.04); for reasoning tests the pooled effect of d = -0.34, 95% CI [-0.61, -0.06] indicated significantly lower scores in the red condition. The cumulative meta-analysis revealed substantially larger effects in initial studies as compared to subsequent research. After correcting for publication bias no evidential value for an effect of red color on intellectual performance was available. The review casts doubt on the existence of a robust color-priming effect in achievement situations.

Cognitive Abilities Explain Wording Effects in the Rosenberg Self-Esteem Scale.

There is consensus that the 10 items of the Rosenberg Self-Esteem Scale (RSES) reflect wording effects resulting from positively and negatively keyed items. The present study examined the effects of cognitive abilities on the factor structure of the RSES with a novel, nonparametric latent variable technique called local structural equation models. In a nationally representative German large-scale assessment including 12,437 students competing measurement models for the RSES were compared: a bifactor model with a common factor and a specific factor for all negatively worded items had an optimal fit. Local structural equation models showed that the unidimensionality of the scale increased with higher levels of reading competence and reasoning, while the proportion of variance attributed to the negatively keyed items declined. Wording effects on the factor structure of the RSES seem to represent a response style artifact associated with cognitive abilities.