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Social networks are fundamental for social interactions, with the social brain hypothesis positing that the size of the neocortex evolved to meet social demands. However, the role of fractional anisotropy (FA) in white matter (WM) tracts relevant to mentalizing, empathy, and social networks remains unclear. In this study, we investigated the relationships between FA in brain regions associated with social cognition (superior longitudinal fasciculus (SLF), cingulum (CING), uncinate fasciculus, inferior fronto-occipital fasciculus), social network characteristics (diversity, size, complexity), and empathy (cognitive, affective). We employed diffusion tensor imaging, tract-based spatial statistics, and mediation analyses to examine these associations. Our findings revealed that increased social network size was positively correlated with FA in the left SLF. Further, our mediation analysis showed that lower FA in left CING was associated with increased social network size, mediated by cognitive empathy. In summary, our findings suggest that WM tracts involved in social cognition play distinct roles in social network size and empathy, potentially implicating affective brain regions. In conclusion, our findings offer new perspectives on the cognitive mechanisms involved in understanding others' mental states and experiencing empathy within supportive social networks, with potential implications for understanding individual differences in social behavior and mental health., (© 2024. The Psychonomic Society, Inc.)

Responding to rating scale items is a multidimensional process, since not only the substantive trait being measured but also additional personal characteristics can affect the respondents' category choices. A flexible model class for analyzing such multidimensional responses are IRTree models, in which rating responses are decomposed into a sequence of sub-decisions. Different response processes can be involved in item responding both sequentially across those sub-decisions and as co-occurring processes within sub-decisions. In the previous literature, modeling co-occurring processes has been exclusively limited to dominance models, where higher trait levels are associated with higher expected scores. However, some response processes may rather follow an ideal point rationale, where the expected score depends on the proximity of a person's trait level to the item's location. Therefore, we propose a new multidimensional IRT model of co-occurring dominance and ideal point processes (DI-MIRT model) as a flexible framework for parameterizing IRTree sub-decisions with multiple dominance processes, multiple ideal point processes, and combinations of both. The DI-MIRT parameterization opens up new application areas for the IRTree model class and allows the specification of a wide range of theoretical assumptions regarding the cognitive processing of item responding. A simulation study shows that IRTree models with DI-MIRT parameterization provide excellent parameter recovery and accurately reflect co-occurring dominance and ideal point processes. In addition, a clear advantage over traditional IRTree models with purely sequential processes is demonstrated. Two application examples from the field of response style analysis highlight the benefits of the general IRTree framework under real-world conditions., (© 2024. The Author(s).)

Multinomial processing tree (MPT) models are a broad class of statistical models used to test sophisticated psychological theories. The research questions derived from these theories often go beyond simple condition effects on parameters and involve ordinal expectations (e.g., the same-direction effect on the memory parameter is stronger in one experimental condition than another) or disordinal expectations (e.g., the effect reverses in one experimental condition). Here, we argue that by refining common modeling practices, Bayesian hierarchical models are well suited to estimate and test these expectations. Concretely, we show that the default priors proposed in the literature lead to nonsensical predictions for individuals and the population distribution, leading to problems not only in model comparison but also in parameter estimation. Rather than relying on these priors, we argue that MPT modelers should determine priors that are consistent with their theoretical knowledge. In addition, we demonstrate how Bayesian model comparison may be used to test ordinal and disordinal interactions by means of Bayes factors. We apply the techniques discussed to empirical data from Bell et al. Journal of Experimental Psychology: Learning, Memory, and Cognition, 41, 456-472 (2015)., (© 2024. The Author(s).)

Multinomial processing tree (MPT) models are prominent and frequently used tools to model and measure cognitive processes underlying responses in many experimental paradigms. Although MPT models typically refer to cognitive processes within single individuals, they have often been applied to group data aggregated across individuals. We investigate the conditions under which MPT analyses of aggregate data make sense. After introducing the notions of structural and empirical aggregation invariance of MPT models, we show that any MPT model that holds at the level of single individuals must also hold at the aggregate level when it is both structurally and empirically aggregation invariant. Moreover, group-level parameters of aggregation-invariant MPT models are equivalent to the expected values (i.e., means) of the corresponding individual parameters. To investigate the robustness of MPT results for aggregate data when one or both invariance conditions are violated, we additionally performed a series of simulation studies, systematically manipulating (1) the sample sizes in different trees of the model, (2) model parameterization, (3) means and variances of crucial model parameters, and (4) their correlations with other parameters of the respective MPT model. Overall, our results show that MPT parameter estimates based on aggregate data are trustworthy under rather general conditions, provided that a few preconditions are met., (© 2024. The Author(s).)

Faking in self-report personality questionnaires describes a deliberate response distortion aimed at presenting oneself in an overly favorable manner. Unless the influence of faking on item responses is taken into account, faking can harm multiple psychometric properties of a test. In the present article, we account for faking using an extension of the multidimensional nominal response model (MNRM), which is an item response theory (IRT) model that offers a flexible framework for modeling different kinds of response biases. Particularly, we investigated under which circumstances the MNRM can adequately adjust substantive trait scores and latent correlations for the influence of faking and examined the role of variation in the way item content is related to social desirability (i.e., item desirability characteristics) in facilitating the modeling of faking and counteracting its detrimental effects. Using a simulation, we found that the inclusion of a faking dimension in the model can overall improve the recovery of substantive trait person parameters and latent correlations between substantive traits, especially when the impact of faking in the data is high. Item desirability characteristics moderated the effect of modeling faking and were themselves associated with different levels of parameter recovery. In an empirical demonstration with N = 1070 test-takers, we also showed that the faking modeling approach in combination with different item desirability characteristics can prove successful in empirical questionnaire data. We end the article with a discussion of implications for psychological assessment., (© 2024. The Author(s).)

To evaluate model fit in confirmatory factor analysis, researchers compare goodness-of-fit indices (GOFs) against fixed cutoff values (e.g., CFI > .950) derived from simulation studies. Methodologists have cautioned that cutoffs for GOFs are only valid for settings similar to the simulation scenarios from which cutoffs originated. Despite these warnings, fixed cutoffs for popular GOFs (i.e., χ 2 , χ 2 /df, CFI, RMSEA, SRMR) continue to be widely used in applied research. We (1) argue that the practice of using fixed cutoffs needs to be abandoned and (2) review time-honored and emerging alternatives to fixed cutoffs. We first present the most in-depth simulation study to date on the sensitivity of GOFs to model misspecification (i.e., misspecified factor dimensionality and unmodeled cross-loadings) and their susceptibility to further data and analysis characteristics (i.e., estimator, number of indicators, number and distribution of response options, loading magnitude, sample size, and factor correlation). We included all characteristics identified as influential in previous studies. Our simulation enabled us to replicate well-known influences on GOFs and establish hitherto unknown or underappreciated ones. In particular, the magnitude of the factor correlation turned out to moderate the effects of several characteristics on GOFs. Second, to address these problems, we discuss several strategies for assessing model fit that take the dependency of GOFs on the modeling context into account. We highlight tailored (or "dynamic") cutoffs as a way forward. We provide convenient tables with scenario-specific cutoffs as well as regression formulae to predict cutoffs tailored to the empirical setting of interest., (© 2023. The Author(s).)

Researchers assessing psychological constructs have to understand and choose between several competing measures. Item Pool Visualization (IPV, Dantlgraber et al., 2019) was developed to offer a systematic and detailed portrayal of the actual content and internal balance of competing measures. To enable the use of IPV, we developed and present here the IPV R package. Its aim is to allow researchers to add IPV to their repertoire with minimal effort. Creating IPV charts from raw data requires two simple function calls, because the package streamlines model specification, model estimation, and chart creation. It improves IPV conceptually by introducing the aggregate center distance and the item overview chart. It provides many customization options and generates high-quality, vector-based PDF output. The workflow of the package is explained using a reproducible open data example from a personality assessment., (© 2023. The Author(s).)

Migration forecasts are crucial for proactive immigration and integration management. While the demand for accurate migration forecasts continues to grow, the current state of migration forecasting is still unsatisfactory, because they tend to lack precision. We introduce an alternative method to forecast migration movements: prediction markets. While prediction markets are mainly unknown in migration studies, they are established in the political economy of forecasting election outcomes. For its application to a complex phenomenon in a more constrained information environment such as migration movements, we argue that prediction markets allow to balance complementarities of current qualitative and quantitative approaches if they provide solutions to avoid thin trading and integrate expert knowledge into the market. We apply the prediction market to forecast immigration in four West European countries in 2020 and find encouraging results. We discuss the strengths and limitations of prediction markets to migration forecasting, including ethical considerations, and guide its future application., Supplementary Information: The online version contains supplementary material available at 10.1186/s40878-024-00404-0., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2024.)

Robot-assisted minimally invasive surgery is the gold standard for the surgical treatment of many pathological conditions since it guarantees to the patient shorter hospital stay and quicker recovery. Several manuals and academic papers describe how to perform these interventions and thus contain important domain-specific knowledge. This information, if automatically extracted and processed, can be used to extract or summarize surgical practices or develop decision making systems that can help the surgeon or nurses to optimize the patient's management before, during, and after the surgery by providing theoretical-based suggestions. However, general English natural language understanding algorithms have lower efficacy and coverage issues when applied to domain others than those they are typically trained on, and a domain specific textual annotated corpus is missing. To overcome this problem, we annotated the first robotic-surgery procedural corpus, with PropBank-style semantic labels. Starting from the original PropBank framebank, we enriched it by adding new lemmas, frames and semantic arguments required to cover missing information in general English but needed in procedural surgical language, releasing the Robotic-Surgery Procedural Framebank (RSPF). We then collected from robotic-surgery textbooks as-is sentences for a total of 32,448 tokens, and we annotated them with RSPF labels. We so obtained and publicly released the first annotated corpus of the robotic-surgical domain that can be used to foster further research on language understanding and procedural entities and relations extraction from clinical and surgical scientific literature., Competing Interests: Conflict of interestMarco Bombieri, Marco Rospocher, Simone Paolo Ponzetto and Paolo Fiorini declare that they have not conflicts of interest., (© The Author(s) 2023.)

We examine changes in the well-being of family caregivers during the early phase of the COVID-19 pandemic in Germany, using data from the German Socio-Economic Panel (SOEP) and the SOEP-CoV study. The COVID-19 pandemic posed an extraordinary challenge for family caregivers, as care recipients are a high-risk group requiring special protection, and professional care services were severely cut back. The specific situation of the COVID-19 pandemic allows us to re-examine the caregiver stress process model. Using first difference regression models, we analyse changes in general life satisfaction and depressive symptoms (PHQ-4 score) among family caregivers between 2019 and spring 2020, differentiating by care intensity and duration of the care episode. Caregivers show similar changes in well-being as non-caregivers: a simultaneous increase in depressive symptoms and life satisfaction between 2019 and 2020. However, our results reveal heterogeneity within the group of family caregivers as we find differences according to caregiving dynamics and intensity. Among the group of continuing caregivers, high-intensity caregivers experience a larger increase in life satisfaction, and low-intensity caregivers a smaller increase in life satisfaction, compared to non-caregivers. Our results therefore provide some support for the role enhancement hypothesis for continuing caregivers with high time commitment., (© 2023. The Author(s).)

Remembering an experienced event in a coherent manner requires the binding of the event's constituent elements. Such binding effects manifest as a stochastic dependency of the retrieval of event elements. Several approaches for modeling these dependencies have been proposed. We compare the contingency-based approach by Horner & Burgess (Journal of Experimental Psychology: General, 142(4), 1370-1383, 2013), related approaches using Yule's Q (Yule, Journal of the Royal Statistical Society, 75(6), 579-652, 1912) or an adjusted Yule's Q (c.f. Horner & Burgess, Current Biology, 24(9), 988-992, 2014), an approach based on item response theory (IRT, Schreiner et al., in press), and a nonparametric variant of the IRT-based approach. We present evidence from a simulation study comparing the five approaches regarding their empirical detection rates and susceptibility to different levels of memory performance, and from an empirical application. We found the IRT-based approach and its nonparametric variant to yield the highest power for detecting dependencies or differences in dependency between conditions. However, the nonparametric variant yielded increasing Type I error rates with increasing dependency in the data when testing for differences in dependency. We found the approaches based on Yule's Q to yield biased estimates and to be strongly affected by memory performance. The other measures were unbiased given no dependency or differences in dependency but were also affected by memory performance if there was dependency in the data or if there were differences in dependency, but to a smaller extent. The results suggest that the IRT-based approach is best suited for measuring binding effects. Further considerations when deciding for a modeling approach are discussed., (© 2022. The Author(s).)

Inspired by the Conservation of Resource theory (Hobfoll, 1989), this study investigated the role of a broad set of personal vulnerabilities, social, and work-related stressors and resources as predictors of workers' well-being during the COVID-19 outbreak. Participants were 594 workers in Italy. Results showed that personality predispostions, such as positivity, neuroticism and conscientiousness as well as key aspects of the individuals' relationship with their work (such as job insecurity, type of employment contract or trust in the organization) emerged as factors promoting (or hampering) workers' adjustment during the COVID -19 outbreak. Interactions between stressors and resources were also found and discussed., Supplementary Information: The online version contains supplementary material available at 10.1007/s12144-021-02408-w., Competing Interests: Conflict of InterestAll authors declare that they have no conflict of interest., (© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.)

Purpose: In the randomized phase III trial CeTeG/NOA-09, temozolomide (TMZ)/lomustine (CCNU) combination therapy was superior to TMZ in newly diagnosed MGMT methylated glioblastoma, albeit reporting more frequent hematotoxicity. Here, we analyze high grade hematotoxicity and its prognostic relevance in the trial population., Methods: Descriptive and comparative analysis of hematotoxicity adverse events ≥ grade 3 (HAE) according to the Common Terminology of Clinical Adverse Events, version 4.0 was performed. The association of HAE with survival was assessed in a landmark analysis. Logistic regression analysis was performed to predict HAE during the concomitant phase of chemotherapy., Results: HAE occurred in 36.4% and 28.6% of patients under CCNU/TMZ and TMZ treatment, respectively. The median onset of the first HAE was during concomitant chemotherapy (i.e. first CCNU/TMZ course or daily TMZ therapy), and 42.9% of patients with HAE receiving further courses experienced repeat HAE. Median HAE duration was similar between treatment arms (CCNU/TMZ 11.5; TMZ 13 days). Chemotherapy was more often discontinued due to HAE in CCNU/TMZ than in TMZ (19.7 vs. 6.3%, p = 0.036). The occurrence of HAE was not associated with survival differences (p = 0.76). Regression analysis confirmed older age (OR 1.08) and female sex (OR 2.47), but not treatment arm, as predictors of HAE., Conclusion: Older age and female sex are associated with higher incidence of HAE. Although occurrence of HAE was not associated with shorter survival, reliable prediction of patients at risk might be beneficial to allow optimal management of therapy and allocation of supportive measures., Trial Registration: NCT01149109., (© 2023. The Author(s).)

The present study examines the effects of social interactions' situational characteristics, emotions, and personality on self-perceived learning from social interactions at work based on diary and survey data. The sample comprises 43 German vocational education and training (VET) trainees in various apprenticeship programs. During the diary period of ten working days, the participants were instructed to record five typical social interactions at work every day. Quantitative data of 1,328 social interactions were analyzed by means of multilevel analysis. Regarding social interactions' characteristics, the analysis revealed the baseline level of instrumentality, an interruption of the social interaction, its instrumentality and questions asked by the trainee during the interaction as positive predictors of self-perceived learning. A trainee's higher speech proportion, however, was a negative predictor. Regarding state emotions, the emotional experiences of bored and motivated were identified as significant positive predictors of learning from social interactions at work. Emotions' baseline level as well as personality traits had no significant influence. The results indicate that social interactions' situational characteristics have the biggest influence on self-perceived learning from social interactions., Competing Interests: The authors have no relevant financial or non-financial interests to disclose. Furthermore, they have no competing interests to declare that are relevant to the content of this article. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript., (© The Author(s) 2022.)

The COVID-19 pandemic (and its aftermath) highlights a critical need to communicate health information effectively to the global public. Given that subtle differences in information framing can have meaningful effects on behavior, behavioral science research highlights a pressing question: Is it more effective to frame COVID-19 health messages in terms of potential losses (e.g., "If you do not practice these steps, you can endanger yourself and others") or potential gains (e.g., "If you practice these steps, you can protect yourself and others")? Collecting data in 48 languages from 15,929 participants in 84 countries, we experimentally tested the effects of message framing on COVID-19-related judgments, intentions, and feelings. Loss- (vs. gain-) framed messages increased self-reported anxiety among participants cross-nationally with little-to-no impact on policy attitudes, behavioral intentions, or information seeking relevant to pandemic risks. These results were consistent across 84 countries, three variations of the message framing wording, and 560 data processing and analytic choices. Thus, results provide an empirical answer to a global communication question and highlight the emotional toll of loss-framed messages. Critically, this work demonstrates the importance of considering unintended affective consequences when evaluating nudge-style interventions., Competing Interests: Conflict of InterestThe authors declare no conflict of interest., (© The Society for Affective Science 2022.)

Web-based data collection is increasingly popular in both experimental and survey-based research because it is flexible, efficient, and location-independent. While dedicated software for laboratory-based experimentation and online surveys is commonplace, researchers looking to implement experiments in the browser have, heretofore, often had to manually construct their studies' content and logic using code. We introduce lab.js, a free, open-source experiment builder that makes it easy to build studies for both online and in-laboratory data collection. Through its visual interface, stimuli can be designed and combined into a study without programming, though studies' appearance and behavior can be fully customized using HTML, CSS, and JavaScript code if required. Presentation and response times are kept and measured with high accuracy and precision heretofore unmatched in browser-based studies. Experiments constructed with lab.js can be run directly on a local computer and published online with ease, with direct deployment to cloud hosting, export to web servers, and integration with popular data collection platforms. Studies can also be shared in an editable format, archived, re-used and adapted, enabling effortless, transparent replications, and thus facilitating open, cumulative science. The software is provided free of charge under an open-source license; further information, code, and extensive documentation are available from https://lab.js.org/ ., (© 2021. The Author(s).)

The major aim of the present megastudy of picture-naming norms was to address the shortcomings of the available picture data sets used in psychological and linguistic research by creating a new database of normed colour images that researchers from around the world can rely upon in their investigations. In order to do this, we employed a new form of normative study, namely a megastudy, whereby 1620 colour photographs of items spanning across 42 semantic categories were named and rated by a group of German speakers. This was done to establish the following linguistic norms: speech onset times (SOT), name agreement, accuracy, familiarity, visual complexity, valence, and arousal. The data, including over 64,000 audio files, were used to create the LinguaPix database of pictures, audio recordings, and linguistic norms, which to our knowledge, is the largest available research tool of its kind ( http://linguapix.uni-mannheim.de ). In this paper, we present the tool and the analysis of the major variables., (© 2021. The Author(s).)

Second-party punishment (SPP) and third-party punishment (TPP) are two basic forms of costly punishment that play an essential role in maintaining social orders. Despite scientific breakthroughs in understanding that costly punishment is driven by an integration of the wrongdoers' intention and the outcome of their actions, so far, few studies have compared the neurocognitive processes associated with the intention-outcome integration between SPP and TPP. Here, we combined economic exchange games measuring SPP and TPP with functional magnetic resonance imaging (fMRI) to compare the neuropsychological architectures underlying the intention-outcome integration during one-shot interactions with anonymous partners across four types of norm violations (no norm, accidental, attempted, and intentional violations). Our behavioral findings showed that third-parties punished only attempted norm violations less frequently than second-parties. Our neuroimaging findings revealed higher activities in the right temporoparietal junction (TPJ) and dorsolateral prefrontal cortex (dlPFC) for attempted norm violations during TPP relative to SPP; more activities in these regions with less punishment frequency; and enhancement of functional connectivity of the right TPJ with the right dlPFC and dorsomedial PFC. Our findings demonstrated specific psychological and neural mechanisms of intention-outcome interactions between SPP and TPP -helping to unravel the complex neurocognitive processes of costly punishment., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Since January 2020, the COVID-19 crisis has affected everyday life around the world, and rigorous government lockdown restrictions have been implemented to prevent the further spread of the pandemic. The consequences of the corona crisis and the associated lockdown policies for public health, social life, and the economy are vast. In view of the rapidly changing situation during this crisis, policymakers require timely data and research results that allow for informed decisions. Addressing the requirement for adequate databases to assess people's  life and work situations during the pandemic, the Institute for Employment Research (IAB) developed the High-frequency Online Personal Panel (HOPP). The HOPP study started in May 2020 and is based on a random sample of individuals drawn from the administrative data of the Federal Employment Agency in Germany, containing information on all labour market participants except civil servants and self-employed. The main goal of the HOPP study is to assess the short-term as well as long-term changes in people's social life and working situation in Germany due to the corona pandemic. To assess individual dynamics the HOPP collected data on a monthly (wave  one to four) and bi-monthly (wave five to seven) basis. Furthermore, respondents were divided into four groups. The different groups of a new wave were invited to the survey at weekly intervals (wave two to four) or bi-weekly intervals (wave five to seven). This gives us the advantage of being able to provide weekly data while each participant only had to participate on a monthly or bi-monthly basis. In this article, we delineate the HOPP study in terms of its main goals and features, topics, and survey design. Furthermore, we provide a summary of results derived from HOPP and the future prospects of the study., Competing Interests: Competing interestsThe authors declare that they have no competing interests., (© The Author(s) 2021.)

Memories formed in the context of an imagined survival scenario are more easily remembered, but the mechanisms underlying this effect are still under debate. We investigated the neurocognitive processes underlying the survival processing effect by examining event-related potentials (ERPs) during memory encoding. Participants imagined being either stranded in a foreign land and needing to survive, or in an overseas moving (control) scenario, while incidentally encoding a list of words. Words encountered in the survival context were associated with improved recall and reduced false-memory intrusions during a later memory test. Survival processing was associated with an increased frontal slow wave, while there was no effect on the overall P300 amplitude, relative to the control scenario. Furthermore, a subsequent memory effect in the P300 time window was found only in the control scenario. These findings suggest that survival processing leads to a shift away from lower level encoding processes, which are sensitive to motivation and stimulus salience and which were evident in the control scenario, to more active and elaborative forms of encoding. The results are consistent with a richness of encoding account of the survival processing effect and offer novel insights into the encoding processes that lead to enhanced memory for fitness-relevant information.

A strong personal relationship with God is theoretically and empirically associated with an enhanced sense of control. While a growing body of research is focused on understanding the neural mechanisms underlying religious belief, little is known about the brain basis of the link between a personal relationship with God and sense of control. Here, we used a sample of patients with focal brain lesions (N = 84) and matched healthy controls (N = 22) to determine whether damage to the ventromedial prefrontal cortex (vmPFC)-a region associated with emotionally meaningful religious experiences and with sense of control-will modulate self-reports of a personal relationship with God and sense of control. We also examined potential mediators for these associations. Voxel-based lesion symptom mapping revealed that damage to the right vmPFC resulted in a stronger personal relationship with God, and patients with damage to this region demonstrated an increased sense of control relative to patients with damage to posterior cortex and healthy controls. Moreover, the association between vmPFC damage and greater perceived sense of control was mediated by a stronger personal relationship with God. Collectively, these results suggest that a strong personal relationship with God can serve an important psychological function by affecting sense of control, with both enhanced following damage to the right vmPFC.

Investigating cognitive processes by analyzing mouse movements has become a popular method in many psychological disciplines. When creating mouse-tracking experiments, researchers face many design choices-for example, whether participants indicate responses by clicking a button or just by entering the button area. Hitherto, numerous different settings have been employed, but little is known about how these methodological differences affect mouse-tracking data. We systematically investigated the influences of three central design factors, using a classic mouse-tracking paradigm in which participants classified typical and atypical exemplars. In separate experiments, we manipulated the response indication, mouse sensitivity, and starting procedure. The core finding that mouse movements deviate more toward the nonchosen option for atypical exemplars was replicated in all conditions. However, the size of this effect varied. Specifically, it was larger when participants indicated responses via click and when they were instructed to initialize the movement early. Trajectory shapes also differed between setups. For example, a dynamic start led to mostly curved trajectories, responses via click led to a mix of straight and "change-of-mind" trajectories, and responses via touch led to mostly straight trajectories. Moreover, the distribution of curvature indices was classified as bimodal in some setups and as unimodal in others. Because trajectory curvature and shape are frequently used to make inferences about psychological theories, such as differentiating between dynamic and dual-system models, this study shows that the specific design must be carefully considered when drawing theoretical inferences. All methodological designs and analyses were implemented using open-source software and are available from https://osf.io/xdp7a/.

We study the political economy of allocation decisions within a major state investment bank. Our focus is the European Investment Bank (EIB) - "The Bank of the EU" - which is the largest multilateral lending (and borrowing) institution in the world. We study the behavior of about 500 national representatives at the EIB's Board of Directors - the bank's decisive body for loan approvals - and show that a representative's appointment increases the probability that the sub-national region where she works receives a loan by about 17 percentage points. This "home-bias" effect is driven by large loans financing infrastructure projects. We discuss several pieces of evidence, which are consistent with the hypothesis that this home-bias lending may be due to favoritism, however, we cannot conclusively demonstrate this case of resource misallocation., (© The Author(s) 2020.)

Mouse-tracking is an increasingly popular process-tracing method. It builds on the assumption that the continuity of cognitive processing leaks into the continuity of mouse movements. Because this assumption is the prerequisite for meaningful reverse inference, it is an important question whether the assumed interaction between continuous processing and movement might be influenced by the methodological setup of the measurement. Here we studied the impacts of three commonly occurring methodological variations on the quality of mouse-tracking measures, and hence, on the reported cognitive effects. We used a mouse-tracking version of a classical intertemporal choice task that had previously been used to examine the dynamics of temporal discounting and the date-delay effect (Dshemuchadse, Scherbaum, & Goschke, 2013). The data from this previous study also served as a benchmark condition in our experimental design. Between studies, we varied the starting procedure. Within the new study, we varied the response procedure and the stimulus position. The starting procedure had the strongest influence on common mouse-tracking measures, and therefore on the cognitive effects. The effects of the response procedure and the stimulus position were weaker and less pronounced. The results suggest that the methodological setup crucially influences the interaction between continuous processing and mouse movement. We conclude that the methodological setup is of high importance for the validity of mouse-tracking as a process-tracing method. Finally, we discuss the need for standardized mouse-tracking setups, for which we provide recommendations, and present two promising lines of research toward obtaining an evidence-based gold standard of mouse-tracking.

From an embodiment perspective, action and cognition influence each other constantly. This interaction has been utilized in mouse-tracking studies to infer cognitive states from movements, assuming a continuous manifestation of cognitive processing into movement. However, it is mostly unknown how this manifestation is affected by the variety of possible design choices in mouse-tracking paradigms. Here we studied how three design factors impact the manifestation of cognition into movement in a Simon task with mouse tracking. We varied the response selection (i.e., with or without clicking), the ratio between hand and mouse cursor movement, and the location of the response boxes. The results show that all design factors can blur or even prevent the manifestation of cognition into movement, as reflected by a reduction in movement consistency and action dynamics, as well as by the adoption of unsuitable movement strategies. We conclude that deliberate and careful design choices in mouse-tracking experiments are crucial to ensuring a continuous manifestation of cognition in movement. We discuss the importance of developing a standard practice in the design of mouse-tracking experiments.

Economic games are used to elicit a social, conflictual situation in which people have to make decisions weighing self-related and collective interests. Combining these games with task-based fMRI has been shown to be successful in investigating the neural underpinnings of cooperative behaviors. However, it remains elusive to which extent resting-state functional connectivity (RSFC) represents an individual's propensity to prosocial behaviors in the context of economic games. Here, we investigated whether task-free RSFC predicts individual differences in the propensity to trust and reciprocate in a one-round trust game (TG) employing a prediction-analytics framework. Our results demonstrated that individual differences in the propensity to trust and reciprocity could be predicted by individual differences in the RSFC. Different subnetworks of the default-mode network associated with mentalizing exclusively predicted trust and reciprocity. Moreover, reciprocity was further predicted by the frontoparietal and cingulo-opercular networks associated with cognitive control and saliency, respectively. Our results contribute to a better understanding of how complex social behaviors are enrooted in large-scale intrinsic brain dynamics, which may represent neuromarkers for impairment of prosocial behavior in mental health disorders.

To prospectively evaluate the possible loss of attention among console surgeons performing robotic-assisted procedures using a validated psychological test. The concentration of one console surgeon was assessed before and after 25 robotic-assisted procedures (radical prostatectomies) using the validated d2 attention test (computer-assisted, Hogrefe test systems, Germany). Error frequency, work rate, and accuracy of task performance were evaluated as parameters of the fluctuation in concentration. Data were correlated with clinical parameters, including console times, positive surgical margin rates and the use of a nerve-sparing procedure. Pre- and post-operative test results revealed no differences in the number of items performed, but a significant decline in the error-corrected performance between the pre- and post-operative tests was observed with increasing console time (p = 0.046; median console time 123 min.). No differences in the pre-operative tests for consecutive procedures (mean time between procedures 93 min.) were found, whereas the number of errors (missed items) increased in the post-operative tests (p = 0.0025). The measured differences in test results showed no association with the positive surgical margin rate. A planned nerve-sparing procedure tended to result in a lower level of concentration found in pre-operative testing (p = 0.07). Concentration decrease and loss of attention during robotic-assisted procedures can be measured validly using the d2 attention test. Longer console times lead to loss of attention but consecutive procedures do not decrease the test or surgical performance. Further studies need to address whether similar effects apply to the comparable open or other robotic procedures or to different levels of surgeons experience.

Mouse-tracking is an increasingly popular method to trace cognitive processes. As is common for a novel method, the exact methodological procedures employed in an individual study are still relatively idiosyncratic and the effects of different methodological setups on mouse-tracking measures have not been explored so far. Here, we study the impact of one commonly occurring methodological variation, namely whether participants have to initiate their mouse movements to trigger stimulus presentation (dynamic starting condition) or whether the stimulus is presented automatically after a fixed delay and participants can freely decide when to initiate their movements (static starting condition). We compared data from a previous study in which participants performed a mouse-tracking version of a Simon task with a dynamic starting condition to data from a new study that employed a static starting condition in an otherwise identical setup. Results showed reliable Simon effects and Congruency Sequence effects on response time (RT) and discrete trial-level mouse-tracking measures (i.e., average deviation) in both starting conditions. In contrast, within-trial continuous measures (i.e., extracted temporal segments) were weaker and occurred in a more temporally compressed way in the static compared to the dynamic starting condition. This was in line with generally less consistent movements within and across participants in the static compared to the dynamic condition. Our results suggest that studies that use within-trial continuous measures to assess dynamic aspects of mouse movements should apply dynamic starting procedures to enhance the leakage of cognitive processing into the mouse movements.

In surveys concerning sensitive behavior or attitudes, respondents often do not answer truthfully, because of social desirability bias. To elicit more honest responding, the randomized-response (RR) technique aims at increasing perceived and actual anonymity by prompting respondents to answer with a randomly modified and thus uninformative response. In the crosswise model, as a particularly promising variant of the RR, this is achieved by adding a second, nonsensitive question and by prompting respondents to answer both questions jointly. Despite increased privacy protection and empirically higher prevalence estimates of socially undesirable behaviors, evidence also suggests that some respondents might still not adhere to the instructions, in turn leading to questionable results. Herein we propose an extension of the crosswise model (ECWM) that makes it possible to detect several types of response biases with adequate power in realistic sample sizes. Importantly, the ECWM allows for testing the validity of the model's assumptions without any loss in statistical efficiency. Finally, we provide an empirical example supporting the usefulness of the ECWM.

The aims of this study are to assess patients' preferred and perceived decision-making roles and preference matching in a sample of German breast and colon cancer patients and to investigate how a shared decision-making (SDM) intervention for oncologists influences patients' preferred and perceived decision-making roles and the attainment of preference matches. This study is a post hoc analysis of a randomised controlled trial (RCT) on the effects of an SDM intervention. The SDM intervention was a 12-h SDM training program for physicians in combination with decision board use. For this study, we analysed a subgroup of 107 breast and colon cancer patients faced with serious treatment decisions who provided data on specific questionnaires with regard to their preferred and perceived decision-making roles (passive, SDM or active). Patients filled in questionnaires immediately following a decision-relevant consultation (t1) with their oncologist. Eleven of these patients' 27 treating oncologists had received the SDM intervention within the RCT. A majority of cancer patients (60%) preferred SDM. A match between preferred and perceived decision-making roles was reached for 72% of patients. The patients treated by SDM-trained physicians perceived greater autonomy in their decision making (p < 0.05) with more patients perceiving SDM or an active role, but their preference matching was not influenced. A SDM intervention for oncologists boosted patient autonomy but did not improve preference matching. This highlights the already well-known reluctance of physicians to engage in explicit role clarification., Trial Registration: German Clinical Trials Register DRKS00000539; Funding Source: German Cancer Aid.

Multinomial processing tree (MPT) models are a class of measurement models that account for categorical data by assuming a finite number of underlying cognitive processes. Traditionally, data are aggregated across participants and analyzed under the assumption of independently and identically distributed observations. Hierarchical Bayesian extensions of MPT models explicitly account for participant heterogeneity by assuming that the individual parameters follow a continuous hierarchical distribution. We provide an accessible introduction to hierarchical MPT modeling and present the user-friendly and comprehensive R package TreeBUGS, which implements the two most important hierarchical MPT approaches for participant heterogeneity-the beta-MPT approach (Smith & Batchelder, Journal of Mathematical Psychology 54:167-183, 2010) and the latent-trait MPT approach (Klauer, Psychometrika 75:70-98, 2010). TreeBUGS reads standard MPT model files and obtains Markov-chain Monte Carlo samples that approximate the posterior distribution. The functionality and output are tailored to the specific needs of MPT modelers and provide tests for the homogeneity of items and participants, individual and group parameter estimates, fit statistics, and within- and between-subjects comparisons, as well as goodness-of-fit and summary plots. We also propose and implement novel statistical extensions to include continuous and discrete predictors (as either fixed or random effects) in the latent-trait MPT model.

Background: Over the last 10 years the German pension system has undergone several reforms including the abandonment of early retirement policies and an increase in the statutory retirement age. Consequently, the average retirement age has increased and future retiree cohorts have adjusted the retirement expectations and preferences as to when they would like to retire., Objective: This study was carried out to examine discrepancies between the expected and the preferred retirement age of older workers in Germany and to investigate how these discrepancies differ between groups of older workers., Material and Methods: Based on data from the survey "Employment after retirement", the expected and preferred retirement ages of 1500 workers aged 55 years and older were compared. Regression analyses were used to investigate the influence of educational level and professional position on deviances between the expected and preferred retirement ages., Results: On average older workers would like to retire 1.75 years earlier than they actually expect to. The deviance is significantly larger for employees with a lower professional position, lower income and lower educational level., Conclusion: The discrepancy between expected and preferred retirement ages, in particular for older workers in vulnerable labor market positions, indicates a potential social inequality regarding the choice of retirement timing. This must be acknowledged when considering further reforms of the German pension system.

Mouse-tracking - the analysis of mouse movements in computerized experiments - is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os .

We introduce a novel platform for interactive studies, that is, any form of study in which participants' experiences depend not only on their own responses, but also on those of other participants who complete the same study in parallel, for example a prisoner's dilemma or an ultimatum game. The software thus especially serves the rapidly growing field of strategic interaction research within psychology and behavioral economics. In contrast to all available software packages, our platform does not handle stimulus display and response collection itself. Instead, we provide a mechanism to extend existing experimental software to incorporate interactive functionality. This approach allows us to draw upon the capabilities already available, such as accuracy of temporal measurement, integration with auxiliary hardware such as eye-trackers or (neuro-)physiological apparatus, and recent advances in experimental software, for example capturing response dynamics through mouse-tracking. Through integration with OpenSesame, an open-source graphical experiment builder, studies can be assembled via a drag-and-drop interface requiring little or no further programming skills. In addition, by using the same communication mechanism across software packages, we also enable interoperability between systems. Our source code, which provides support for all major operating systems and several popular experimental packages, can be freely used and distributed under an open source license. The communication protocols underlying its functionality are also well documented and easily adapted to further platforms. Code and documentation are available at https://github.com/psynteract/ .

In research on multiattribute decisions, information is typically preorganized in a well-structured manner (e.g., in attributes-by-options matrices). Participants can therefore conveniently identify the information needed for the decision strategy they are using. However, in everyday decision situations, we often face information that is not well-structured; that is, we not only have to search for, but we also need to organize the information. This latter aspect--subjective information organization--has so far largely been neglected in decision research. The few exceptions used crude experimental manipulations, and the assessment of subjective organization suffered from laborious methodology and a lack of objectiveness. We introduce a new task format to overcome these methodological issues, and we provide an organization index (OI) to assess subjective organization of information objectively and automatically. The OI makes it possible to assess information organization on the same scale as the strategy index (SI) typically used for assessing information search behavior. A simulation study shows that the OI has a similar distribution as the SI but that the two indices are a priori largely independent. In a validation experiment with instructed strategy use, we demonstrate the usefulness of the task to trace decision processes in multicue inference situations.

Multinomial processing tree (MPT) models are a family of stochastic models for psychology and related sciences that can be used to model observed categorical frequencies as a function of a sequence of latent states. For the analysis of such models, the present article presents a platform-independent computer program called multiTree, which simplifies the creation and the analysis of MPT models. This makes them more convenient to implement and analyze. Also, multiTree offers advanced modeling features. It provides estimates of the parameters and their variability, goodness-of-fit statistics, hypothesis testing, checks for identifiability, parametric and nonparametric bootstrapping, and power analyses. In this article, the algorithms underlying multiTree are given, and a user guide is provided. The multiTree program can be downloaded from http://psycho3.uni-mannheim.de/multitree.

This paper introduces the 'Survey of Health, Ageing and Retirement in Europe' (SHARE) to researchers on ageing. SHARE provides an infrastructure to help researchers better understand the individual and population ageing process: where we are, where we are heading to, and how we can influence the quality of life as we age, both as individuals and as societies. The baseline wave in 2004 provides data on the life circumstances of some 27,000 persons aged 50 and over in 11 European countries, ranging from Scandinavia across Western and Central Europe to the Mediterranean. SHARE has made great efforts to deliver truly comparable data, so we can reliably study how differences in cultures, living conditions and policy approaches shape the life of Europeans just before and after retirement. The paper first describes the SHARE data. In order to demonstrate its value, it then presents highlights from the three main research areas covered by SHARE, namely economics, sociology, and health.

Metastatic disease is a major problem in the management of the most frequent childhood brain tumors, in ependymoma and primitive neuroectodermal tumors (PNET). Today, contrast enhanced craniospinal MRI and careful analysis of craniospinal fluid are a prerequisite for correct staging of both tumors and imply therapeutic consequences. So far metastatic spread of medulloblastoma and some ependymomas is prevented by conventional chemotherapy and radiotherapy. However, some forms of diffuse metastatic dissemination in medulloblastoma are resistant to conventional therapeutic regimens and require new experimental strategies.

Direct volume rendering is a visualization method that allows display of all information hidden in three-dimensional data sets of, for example, computed tomography or magnetic resonance imaging (MRI). In contrast to commonly used surface rendering methods, these algorithms need no preprocessing but suffer from a high computational complexity. A real-time rendering system, VIRIM (Vitec: Visualization Technology GmbH, Mannheim, Germany), cuts down rendering times of minutes on normal workstations to an interactive rate of 1 second or less. The immediate visual feedback allows interactive steering of the visualization process to achieve insight into the internal three-dimensional structure of objects. Additional information is obtained by using an interactive gray-value segmentation tool that both allows segmentation of the data set according to bone, tissue, and liquor and display of multifunctional data sets (e.g., functional MRI [fMRI] data sets). Thus, real-time direct volume rendering allows segmentation and volume data processing of functional and anatomical MR data sets simultaneously. As this method can be integrated in the clinical routine, it is of great importance for real-time motion artifact detection and the interpretation of fMRI data acquired during cognitive experiments with normal subjects and psychiatric patients. Because of the free programmability of VIRIM, more complex matching procedures are currently being investigated for future implementation.