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Many processes in psychology are complex, such as dyadic interactions between two interacting partners (e.g. patient-therapist, intimate relationship partners). Nevertheless, many basic questions about interactions are difficult to investigate because dyadic processes can be within a person and between partners, they are based on multimodal aspects of behavior and unfold rapidly. Current analyses are mainly based on the behavioral coding method, whereby human coders annotate behavior based on a coding schema. But coding is labor-intensive, expensive, slow, focuses on few modalities. Current approaches in psychology use LIWC for analyzing couples' interactions. However, advances in natural language processing such as BERT could enable the development of systems to potentially automate behavioral coding, which in turn could substantially improve psychological research. In this work, we train machine learning models to automatically predict positive and negative communication behavioral codes of 368 German-speaking Swiss couples during an 8-minute conflict interaction on a fine-grained scale (10-seconds sequences) using linguistic features and paralinguistic features derived with openSMILE. Our results show that both simpler TF-IDF features as well as more complex BERT features performed better than LIWC, and that adding paralinguistic features did not improve the performance. These results suggest it might be time to consider modern alternatives to LIWC, the de facto linguistic features in psychology, for prediction tasks in couples research. This work is a further step towards the automated coding of couples' behavior which could enhance couple research and therapy, and be utilized for other dyadic interactions as well., Comment: 5 pages. Accepted at the 2nd Workshop on Social Affective Multimodal Interaction for Health (SAMIH) at ICMI 2021

In Fächern mit mathematischen Studieninhalten werden häufig Vorkurse angeboten, damit Studierende die Anforderungen besser bewältigen können. Die vorliegende Studie basiert auf einer Befragung Studierender der Wirtschaftswissenschaften (n = 163), Psychologie (n = 81), Physik (n = 39) und Chemie (n = 65) zu Beginn ihres dritten Semesters. Es wurde untersucht, auf welche Merkmale der Studierenden zu Studienbeginn sich der Besuch eines fachspezifischen mathematischen Vorkurses zurückführen lässt. In Wirtschaftswissenschaften besuchen weibliche Studierende, in Psychologie diejenigen, die sich durch die Schule unzureichend auf mathematische Anforderungen vorbereitet fühlen, und in Physik Studierende, die erst kürzlich ihr Abitur abgelegt haben, häufiger einen Vorkurs. Mathematiknoten, wahrgenommene Relevanz von und Informiertheit über mathematische Studieninhalte spielen wider Erwarten eine untergeordnete Rolle. Durch Regressionsanalysen wurden bei Studierenden, die keinen Vorkurs besuchten, fächerübergreifend Merkmale zu Studienbeginn identifiziert, die prädiktiv für den mathematischen Studienerfolg sind. Diese Zusammenhänge treten bei Vorkurs-Teilnehmenden mehrheitlich nicht, oder in entgegengesetzter Richtung auf. published

Supplemental material, sj-pdf-1-plj-10.1177_1475725720985223 for Determinants of Psychology Students’ Study Satisfaction by Sarah Bebermeier, Kim L. Austerschmidt and Fridtjof W. Nussbeck in Psychology Learning & Teaching

A correction to this paper has been published: https://doi.org/10.1007/s10578-021-01198-3

Supplemental Material, sj-pdf-1-spr-10.1177_02654075211029721 for I blame you, I hear you: Couples’ pronoun use in conflict and dyadic coping by Tabea Meier, Anne Milek, Matthias R. Mehl, Fridtjof W. Nussbeck, Mona Neysari, Guy Bodenmann, Mike Martin, Martina Zemp and Andrea B. Horn in Journal of Social and Personal Relationships

Communication and coordination represent central processes in healthcare action teams. However, we have a limited understanding of how expertise affects these processes and to what extent these effects are shaped by interprofessional differences. The current study addresses these questions by jointly investigating the influence of different aspects of expertise – individual expertise, team familiarity, and expertise asymmetry – on coordination quality and communication openness. We tested our propositions in two hospitals: one in Switzerland (CH, Sample 1) and one in the United Kingdom (UK, Sample 2). Both samples included two-person anesthesia action teams consisting of a physician and a nurse (N/CH = 47 teams, N/UK = 48 teams). We used a correlational design with two measurement points (i.e., pre- and postoperation). To consider potential interprofessional differences, we analyzed our data with actor-partner interdependence models. Moreover, we explored differences in the effects of expertise between both hospitals. Our findings suggest that nurses’ expertise is the most important predictor of coordination quality and communication openness. Overall, differences between the two hospitals were more prevalent than interprofessional differences between physicians and nurses. The current study provides a nuanced picture of the effects of expertise, and thereby extends our understanding of interprofessional teamwork.

In educational psychology, observational units are oftentimes nested within superordinate groups. Researchers need to account for hierarchy in the data by means of multilevel modeling, but especially in three-level longitudinal models, it is often unclear which sample size is necessary for reliable parameter estimation. To address this question, we generated a population dataset based on a study in the field of educational psychology, consisting of 3000 classrooms (level-3) with 55000 students (level-2) measured at 5 occasions (level-1), including predictors on each level and interaction effects. Drawing from this data, we realized 1000 random samples each for various sample and missing value conditions and compared analysis results with the true population parameters. We found that sampling at least 15 level-2 units each in 35 level-3 units results in unbiased fixed effects estimates, whereas higher-level random effects variance estimates require larger samples. Overall, increasing the level-2 sample size most strongly improves estimation soundness. We further discuss how data characteristics influence parameter estimation and provide specific sample size recommendations. published

This study investigated whether foster parents' reports of their dyadic coping competencies differ from biological parents, whether there are differences with regard to the temporal associations between maternal and paternal dyadic coping in the two samples, and whether parental dyadic coping competencies predict future mental health problems in children. A total of 94 foster children and 157 children living in their biological families, both samples aged 2-7 years, as well as their (foster) parents were assessed three times over a 12-month period. The mothers' and fathers' dyadic coping competencies were assessed using the Dyadic Coping Inventory (DCI). Child psychopathology was assessed using the Child Behavior Checklist (CBCL) and a standardized clinical interview (Kinder-DIPS), both mainly based on maternal report. Foster parents reported better dyadic coping competencies across the three assessments than did biological parents. There were no significant differences with regard to the temporal associations between mothers' and fathers' report over time between the two samples. Cross-lagged panel models yielded a high within person stability across the three assessments for both, mothers and fathers (actor effects), as well as some significant interpersonal effects primarily from paternal to maternal dyadic coping (partner effects). In contrast to the expectation, mothers' and fathers' dyadic coping did not predict child mental health problems at the third assessment. The results make an important contribution to the research on dyadic coping and on how child mental health problems affect parental dyadic coping competencies and vice versa.