150 Psychologie
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Background: Dialectical behaviour therapy for posttraumatic stress disorder (DBT-PTSD), which is tailored to treat adults with PTSD and co-occurring emotion regulation difficulties, has already demonstrated its efficacy, acceptance and safety in an inpatient treatment setting. It combines elements of DBT with trauma-focused cognitive behavioural interventions.
Objective: To investigate the feasibility, acceptance and safety of DBT-PTSD in an outpatient treatment setting by therapists who were novice to the treatment, we treated 21 female patients suffering from PTSD following childhood sexual abuse (CSA) plus difficulties in emotion regulation in an uncontrolled clinical trial.
Method: The Clinician Administered PTSD Symptom Scale (CAPS), the Davidson Trauma Scale (DTS), the Borderline Section of the International Personality Disorder Examination (IPDE) and the Borderline Symptom List (BSL-23) were used as primary outcomes. For secondary outcomes, depression and dissociation were assessed. Assessments were administered at pretreatment, post-treatment and six-week follow-up.
Results: Improvement was significant for PTSD as well as for borderline personality symptomatology, with large pretreatment to follow-up effect sizes for completers based on the CAPS (Cohens d = 1.30), DTS (d = 1.50), IPDE (d = 1.60) and BSL-23 (d = 1.20).
Conclusion: The outcome suggests that outpatient DBT-PTSD can safely be used to reduce PTSD symptoms and comorbid psychopathology in adults who have experienced CSA.
Objectives: To investigate whether citizens’ adherence to health-protective non-pharmaceutical interventions (NPIs) during the COVID-19 pandemic is predicted by identity leadership, wherein leaders are perceived to create a sense of shared national identity.
Design: Observational two-wave study. Hypotheses testing was conducted with structural equation modelling.
Setting: Data collection during the COVID-19 pandemic in China, Germany, Israel and the USA in April/May 2020 and four weeks later.
Participants: Adults in China (n=548, 66.6% women), Germany (n=182, 78% women), Israel (n=198, 51.0% women) and the USA (n=108, 58.3% women).
Measures: Identity leadership (assessed by the four-item Identity Leadership Inventory Short-Form) at Time 1, perceived shared national identification (PSNI; assessed with four items) and adherence to health-protective NPIs (assessed with 10 items that describe different health-protective interventions; for example, wearing face masks) at Time 2.
Results: Identity leadership was positively associated with PSNI (95% CI0.11 to 0.30, p<0.001) in all countries. This, in turn, was related to more adherence to health-protective NPIs in all countries (95% CI 0.03 to 0.36, 0.001≤p≤0.017) except Israel (95% CI−0.03 to 0.27, p=0.119). In Germany, the more people saw Chancellor Merkel as engaging in identity leadership, the more they adhered to health-protective NPIs (95% CI 0.04 to 0.18, p=0.002). In the USA, in contrast, the more people perceived President Trump as engaging in identity leadership, the less they adhered to health-protective NPIs (95% CI−0.17 to −0.04, p=0.002).
Conclusions: National leaders can make a difference by promoting a sense of shared identity among their citizens because people are more inclined to follow health-protective NPIs to the extent that they feel part of a united ‘us’. However, the content of identity leadership (perceptions of what it means to be a nation’s citizen) is essential, because this can also encourage people to disregard such recommendations.
Die vorliegende Arbeit beschreibt die Entwicklung eines interaktionalen Simulationsmodells zum späteren Einsatz in der VR-Simulation Clasivir 2.0 (Classroom Simulator in Virtual Reality), welche in der Lehrkräftebildung eingesetzt werden soll. Das Clasivir-Simulationsmodell wurde im Rahmen eines Prototyps implementiert und zwei anderen Simulationsmodellen in einem Fragebogen entgegengestellt. Ein Simulationsmodell beschreibt im Kontext einer digitalen Schulunterrichtssimulation, wie sich SuS in der Simulation verhalten.
Die drei Simulationsmodelle wurden über zwei unterschiedliche Typen von Video-Visualisierungen, genannt Mockup-Videos, dargestellt: Zum einen über eine 2D-Darstellung aus Vogelperspektive, zum anderen über eine 3D-Darstellung, in welcher 3D-Modelle von SuS animiert wurden. Bei dem realen Simulationsmodell handelt es sich um eine Übertragung einer authentischen Videoaufzeichnung von Unterricht einer hessischen Realschule in 2D/3D-Visualisierungen. Im randomisierten Simulationsmodell führen SuS ihre Verhalten zufällig aus. Alle Modelle basieren auf zweisekündigen Intervallen. Im Falle des realen Simulationsmodells wurde dies durch Analyse aller beobachtbaren einundzwanzig SuS gewonnen, im Falle des Clasivir-Simulationsmodells wurden die Vorhersagen des Simulationsmodells übertragen. Das Simulationsmodell von Clasivir basiert auf behavior trees, stellt eine Art von künstlicher Intelligenz dar und modelliert das SuS-Verhalten größtenteils in Abhängigkeit von Lehrkrafthandlungen. Die Entwicklung des interaktionalen Simulationsmodells von Clasivir ist eine Kernkomponente dieser Arbeit. Das Simulationsmodell basiert auf empirischen Ergebnissen aus den Bereichen der Psychometrie, der pädagogischen Psychologie, der Pädagogik und Ergebnissen der Simulations-/KI-Forschung. Ziel war die Entwicklung eines Modells, das nicht nur auf normativen Vorhersagen basiert, sondern empirisch und theoretisch valide ist. Nur wenige Simulationsmodelle in Unterrichtssimulationen werden mit dieser Art von Transparenz beschrieben, was eines der Alleinstellungsmerkmale dieser Arbeit ist. Es wurden Anstrengungen unternommen die vorliegenden empirischen Ergebnisse in einen kausalen Zusammenhang zu bringen, der mathematisch modelliert wurde. Im Zentrum steht die Konzentration von SuS, welche Ein uss auf Stör-, Melde- und Antwortverhalten hat. Diese Variable wird durch andere situative und personenbezogene Variablen (im Sinne von traits) ergänzt. Wo keine direkten empirischen Ergebnisse vorlagen wurde versucht plausibles Verhalten anhand der Übertragung von Konzeptionsmodellen zu gewinnen.
Da die bisherige Verwendung der angrenzenden Begriffe rund um die Simulationsentwicklung bislang sehr inkonsistent war, wurde es notwendig diese Termini zu definieren. Hervorzuheben ist die Entwicklung einer Taxonomie digitaler Unterrichtssimulationen, die so bislang nicht existierte. Anhand dieser Taxonomie und der erarbeiteten Fachtermini wurden Simulationen in der Lehrkräftebildung auf ihre Modellierung des Simulationsmodells hin untersucht. Die Untersuchung der Simulationen simSchool und VCS war, da sie einen verwandten Ansatz zu Clasvir verfolgen, besonders ergiebig.
Nach der Generierung der Mockup-Videos wurden N=105 Studierende, N=102 davon Lehramtsstudierende, aufgefordert, in einem Online-Fragebogen zwei der Simulationsmodelle miteinander zu vergleichen. Lehramtsstudierende wurden ausgewählt, da sie die Zielgruppe der Simulation sind. Welche Modelle die Partizipantinnen verglichen, war abhängig von der Gruppe der sie zugeteilt wurden. Hierbei wurde neben den Simulationsmodellen auch die visuelle Darstellung variiert. Insbesondere wurden die Partizipantinnen darum gebeten, den Fidelitätsgrad des Simulationsmodells, also den Maßstab, wie realistisch die Partizipantinnen das Verhalten der SuS in der Simulation fanden, zu bewerten. Inferenzstatistisch bestätigte sich, dass Partizipantinnen keinen Unterschied zwischen dem realen Simulationsmodell und dem Clasivir-Simulationsmodell erkennen konnten (t=1.463, df=178.9, p=.1452), aber das randomisierte Simulationsmodell mit einer moderaten Effektstärke von d=.634 als signifikant schlechter einschätzten (t=-2.5231, df=33.581, p=.008271). Die Art der Darbietung (2D oder 3D) hatte keinen statistisch signifikanten Einfluss auf die wahrgenommene Schwierigkeit der Bewertung (z=1.2426, p=.107). Damit kann festgestellt werden, dass eine komplexe und zeitintensive 3D-Visualisierung eines Simulationsmodells bei noch nicht vorliegender Simulation nicht erforderlich ist. Das Clasivir-Simulationsmodell wird als realistisch wahrgenommen. Es kann damit empfohlen werden, es in der VR-Simulation zu verwenden.
Im Ausblick werden bereits während des Schreibens der Arbeit gemachte Entwicklungen beschrieben und Konzepte zum weiteren Einsatz der Ergebnisse entwickelt. Es wird darauf verwiesen, dass eine erste Version eines VR-Simulators entwickelt wurde (Clasivir 1.0), der jedoch rein deterministisch funktioniert und noch nicht das in dieser Arbeit entwickelte Simulationsmodell inkludiert.
Efficient processing of visual environment necessitates the integration of incoming sensory evidence with concurrent contextual inputs and mnemonic content from our past experiences. To delineate how this integration takes place in the brain, we studied modulations of feedback neural patterns in non-stimulated areas of the early visual cortex in humans (i.e., V1 and V2). Using functional magnetic resonance imaging and multivariate pattern analysis, we show that both, concurrent contextual and time-distant mnemonic information, coexist in V1/V2 as feedback signals. The extent to which mnemonic information is reinstated in V1/V2 depends on whether the information is retrieved episodically or semantically. These results demonstrate that our stream of visual experience contains not just information from the visual surrounding, but also memory-based predictions internally generated in the brain.
Systemic therapy considers the complex dynamics of relational factors and resources contributing to psychological symptoms. Negative maintaining factors have been well researched for people suffering from Alcohol-use Disorders (AUD). However, we know little about the complex dynamics of these negative factors and resources. We interviewed fifty-five participants suffering or fully remitted from Alcohol-use disorders in this cross-sectional study (M = 52 years; 33% female). The interviews focused on relational factors (e.g., social support and social negativity) referring to a Support Social Network and a Craving Social Network (CSN). The CSN included all significant others who were associated with craving situations. We compared the network characteristics of the group suffering from Alcohol-use Disorders (n = 38) to a fully remitted control group (n = 17). The abstinent group with full remission named on average fewer individuals in the CSNs. They had lower social negativity mean scores in the Support Social Network compared to the non-remitted group (d = 0.74). In the CSN, the mean scores of social support were significantly higher than the median for both groups (d = 2.50). These findings reveal the complex interplay of relational patterns contributing to the etiology, maintenance, and recovery from Alcohol-use disorders. A successful recovery can be linked to increased social resources and reduced relations associated with craving. However, craving-associated relations represent an important source of social support. Future research should investigate this ambivalence for the systemic perspective on the explanation and treatment of Alcohol-use disorders.
Cultural and biographical influences on the expression of emotions manifest themselves in so-called “display rules.” These rules determine the time, intensity, and situations in which an emotion is expressed. To date, only a small number of empirical studies deal with this transformation of how migrants, who are faced with a new culture, may change their emotional expression. The present, cross-sectional study focuses on changes in anger expression as part of a complex acculturation process among Iranian migrants. To this end, Iranian citizens in Iran (n = 61), German citizens (n = 61), and Iranian migrants in Germany (n = 60) were compared in terms of anger expression behavior and acculturation strategy (assimilation, separation, integration, marginalization) was assessed among the migrants, using the Frankfurt Acculturation Scale (FRACC). A questionnaire developed in a preliminary study was used to measure anger expression via subjective anger experience and anger expression within 16 hypothetical situations. Multivariate Analyses of Variance (MANOVA) revealed that Iranians and Iranian migrants reported higher anger experience ratings than Germans and directed their anger more often inward (anger-in). Further findings suggest that transformation processes may have affected Iranian migrants in terms of suppressed anger (anger-in): Iranian migrants with a higher orientation toward German culture reported lower average anger-in scores. These results suggest that there was different emotional expression among Iranian migrants, depending on their acculturation. The results provide new insight into socio-cultural and individual adjustment processes.
Trajectories of internalizing disorders and behavioral addictions are still largely unknown. Research shows that both disorders are highly comorbid. Previous longitudinal studies have focused on associations between internalizing disorders and behavioral addictions using screening instruments. Our aim was to develop and examine a theory-based model of trajectories, according to which internalizing disorders foster symptoms of Internet use disorders, mediated by a reward deprivation and maladaptive emotion regulation. We applied clinically relevant measures for depression and social anxiety in a prospective longitudinal study with a 12-month follow-up investigation. On the basis of an at-risk population of 476 students (mean age = 14.99 years, SD = 1.99), we investigated the predictive influence of clinically relevant depression and social anxiety at baseline (t1) on Internet use disorder symptoms at 12-month follow-up (t2) using multiple linear regression analyses. Our results showed that both clinically relevant depression and social anxiety significantly predicted symptom severity of Internet use disorders one year later after controlling for baseline symptoms of Internet use disorders, gender and age. These results remained robust after including both depression and social anxiety simultaneously in the model, indicating an independent influence of both predictors on Internet use disorder symptoms. The present study enhances knowledge going beyond a mere association between internalizing disorders and Internet use disorders. To our knowledge, this is the first study investigating clinically relevant depression and social anxiety to predict future Internet use disorder symptoms at 12-month follow-up. In line with our model of trajectories, a significant temporal relationship between clinically relevant internalizing disorders and Internet use disorder symptoms at 12-month follow-up was confirmed. Further studies should investigate the mediating role of reward deprivation and maladaptive emotion regulation, as postulated in our model. One implication of these findings is that clinicians should pay particular attention to the increased risk of developing behavioral addictions for adolescents with depression and social anxiety.
Interest is an important factor for successful learning that has been the subject of intensive research for decades. Although interest in nature is of great importance for environmental education, to date there is no valid and reliable measurement tool. Therefore, the purpose of this study was to develop and test a scale for interest in nature, the Nature Interest Scale (NIS). In study 1, nine items were selected based on the three dimensions of the psychological interest construct to represent interest in nature. The factor structure of this new measurement instrument, was tested using confirmatory factor analyses. The results show that the instrument represents the three dimensions of the interest construct well. In study 2 the validity (discriminant and convergent validity) as well as the reliability (internal consistency, composite reliability, test-retest reliability) of the NIS were demonstrated. In study 3, the applicability of the NIS was tested with a different target group, students with learning disabilities. The results of this factor analysis also confirm the factor structure of the scale. Thus, this study provides a valid and reliable measurement tool for individual interest in nature that can be used for future research.
Highlights
• Brain connectivity states identified by cofluctuation strength.
• CMEP as new method to robustly predict human traits from brain imaging data.
• Network-identifying connectivity ‘events’ are not predictive of cognitive ability.
• Sixteen temporally independent fMRI time frames allow for significant prediction.
• Neuroimaging-based assessment of cognitive ability requires sufficient scan lengths.
Abstract
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10 min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual's network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.
Human functional brain connectivity can be temporally decomposed into states of high and low cofluctuation, defined as coactivation of brain regions over time. Rare states of particularly high cofluctuation have been shown to reflect fundamentals of intrinsic functional network architecture and to be highly subject-specific. However, it is unclear whether such network-defining states also contribute to individual variations in cognitive abilities – which strongly rely on the interactions among distributed brain regions. By introducing CMEP, a new eigenvector-based prediction framework, we show that as few as 16 temporally separated time frames (< 1.5% of 10min resting-state fMRI) can significantly predict individual differences in intelligence (N = 263, p < .001). Against previous expectations, individual’s network-defining time frames of particularly high cofluctuation do not predict intelligence. Multiple functional brain networks contribute to the prediction, and all results replicate in an independent sample (N = 831). Our results suggest that although fundamentals of person-specific functional connectomes can be derived from few time frames of highest connectivity, temporally distributed information is necessary to extract information about cognitive abilities. This information is not restricted to specific connectivity states, like network-defining high-cofluctuation states, but rather reflected across the entire length of the brain connectivity time series.