Filtern
Dokumenttyp
- Dissertation (20) (entfernen)
Sprache
- Englisch (20) (entfernen)
Volltext vorhanden
- ja (20) (entfernen)
Schlagworte
- Motivation (4)
- Knowledge (3)
- Stress (3)
- Stressreaktion (3)
- Therapieerfolg (3)
- Affektive Bindung (2)
- Handlungsorientierung (2)
- Immunsystem (2)
- Meta-Analysis (2)
- Metaanalyse (2)
- Neuroendokrines System (2)
- Prognose (2)
- Psychotherapie (2)
- Selbsteinschätzung (2)
- Selbstregulation (2)
- Therapieabbruch (2)
- Verhalten (2)
- Vorwissen (2)
- Wissen (2)
- Wissenserwerb (2)
- Academic Achievement (1)
- Achtsamkeit (1)
- Action vs. State Orientation (1)
- Adoption (1)
- Akzeptanz (1)
- Ambivalence (1)
- Ambivalenz (1)
- Angststörung (1)
- Annäherung (1)
- Arbeitsplatz (1)
- Attitude Formation (1)
- Auslöser (1)
- Autonomie (1)
- Bedrohung (1)
- Bedürfnisbefriedigung (1)
- Computerspiel (1)
- Demokratie (1)
- Depression (1)
- Drohung (1)
- Effektivität (1)
- Ehescheidung (1)
- Eindruck (1)
- Einfluss (1)
- Einstellung (1)
- Eltern (1)
- Emotionales Verhalten (1)
- Entfremdung (1)
- Fragebogen (1)
- Führungskraft (1)
- Gefühl (1)
- Gefühlsreaktion (1)
- Genetische Variabilität (1)
- Gesundheit (1)
- Gewalt (1)
- Gruppe (1)
- HPA (1)
- Handlungstheorie (1)
- Health Literacy (1)
- Higher Education (1)
- Hochschule (1)
- Hypothalamic-pituitary-adrenal axis (1)
- Immunoglobulin (1)
- Implizites Motiv (1)
- Implizites Wissen (1)
- Individuum (1)
- Information (1)
- Information Seeking (1)
- Informationsverhalten (1)
- Inkongruenz (1)
- Instruktion (1)
- Intelligenz (1)
- Intention Enactment (1)
- Internet (1)
- Jamsession (1)
- Klient (1)
- Kognition (1)
- Kognitive Kompetenz (1)
- Kognitive Verhaltenstherapie (1)
- League of Legends (1)
- Learning (1)
- Lebensereignis (1)
- Lebenskrise (1)
- Leistungstest (1)
- Macht (1)
- Maschinelles Lernen (1)
- Mathematik (1)
- Messenger-RNS (1)
- Messung (1)
- Minecraft (1)
- Motiv (1)
- Musikerlebnis (1)
- Patienteninformation (1)
- Patientenorientierte Medizin (1)
- Persönlichkeitsstörung (1)
- Pokémon (1)
- Politisches System (1)
- Power Motivation (1)
- Psychobiologie (1)
- Psychology (1)
- Psychometrie (1)
- Psychotherapeut (1)
- Reduktion (1)
- Reizantwort (1)
- Repertoire (1)
- Response Surface Analysis (1)
- Räumliche Anordnung (1)
- Selbstwirksamkeit (1)
- Self-Regulation (1)
- Sequenzanalyse (1)
- Soziale Unterstützung (1)
- Sozialpsychologie (1)
- Stresstest (1)
- Stroop Task (1)
- Structural Equation Modelling (1)
- Struktur (1)
- Students (1)
- Studienleistung (1)
- TSST-VR (1)
- Teilzeitbeschäftigung (1)
- Test (1)
- Therapeut (1)
- Tiermodell (1)
- Transfer (1)
- Trier Social Stress Test (1)
- Universität (1)
- Validierung (1)
- Vermeidung (1)
- Verstärkung (1)
- Virtual Reality (1)
- Virtuelle Realität (1)
- Zugehörigkeit (1)
- action versus state orientation, self-regulation, self-access, alienation, mindfulness meditation, social support, PSI theory (1)
- adherence (1)
- behavioral genetics (1)
- dropout (1)
- early change (1)
- games (1)
- internet intervention (1)
- motive disposition (1)
- psychologische Beratung (1)
- stress (1)
- threat, stress, trigger, needs (1)
Institut
- Fachbereich 1 (20) (entfernen)
Internet interventions have gained popularity and the idea is to use them to increase the availability of psychological treatment. Research suggests that internet interventions are effective for a number of psychological disorders with effect sizes comparable to those found in face-to-face treatment. However, when provided as an add-on to treatment as usual, internet interventions do not seem to provide additional benefit. Furthermore, adherence and dropout rates vary greatly between studies, limiting the generalizability of the findings. This underlines the need to further investigate differences between internet interventions, participating patients, and their usage of interventions. A stronger focus on the processes of change seems necessary to better understand the varying findings regarding outcome, adherence and dropout in internet interventions. Thus, the aim of this dissertation was to investigate change processes in internet interventions and the factors that impact treatment response. This could help to identify important variables that should be considered in research on internet interventions as well as in clinical settings that make use of internet interventions.
Study I (Chapter 5) investigated early change patterns in participants of an internet intervention targeting depression. Data from 409 participants were analyzed using Growth Mixture Modeling. Specifically a piecewise model was applied to model change from screening to registration (pretreatment) and early change (registration to week four of treatment). Three early change patterns were identified; two were characterized by improvement and one by deterioration. The patterns were predictive of treatment outcome. The results therefore indicated that early change should be closely monitored in internet interventions, as early change may be an important indicator of treatment outcome.
Study II (Chapter 6) picked up on the idea of analyzing change patterns in internet interventions and extended it by using the Muthen-Roy model to identify change-dropout patterns. A sligthly bigger sample of the dataset from Study I was analyzed (N = 483). Four change-dropout patterns emerged; high risk of dropout was associated with rapid improvement and deterioration. These findings indicate that clinicians should consider how dropout may depend on patient characteristics as well as symptom change, as dropout is associated with both deterioration and a good enough dosage of treatment.
Study III (Chapter 7) compared adherence and outcome in different participant groups and investigated the impact of adherence to treatment components on treatment outcome in an internet intervention targeting anxiety symptoms. 50 outpatient participants waiting for face- to-face treatment and 37 self-referred participants were compared regarding adherence to treatment components and outcome. In addition, outpatient participants were compared to a matched sample of outpatients, who had no access to the internet intervention during the waiting period. Adherence to treatment components was investigated as a predictor of treatment outcome. Results suggested that especially adherence may vary depending on participant group. Also using specific measures of adherence such as adherence to treatment components may be crucial to detect change mechanisms in internet interventions. Fostering adherence to treatment components in participants may increase the effectiveness of internet interventions.
Results of the three studies are discussed and general conclusions are drawn.
Implications for future research as well as their utility for clinical practice and decision- making are presented.
Evidence points to autonomy as having a place next to affiliation, achievement, and power as one of the basic implicit motives; however, there is still some research that needs to be conducted to support this notion.
The research in this dissertation aimed to address this issue. I have specifically focused on two issues that help solidify the foundation of work that has already been conducted on the implicit autonomy motive, and will also be a foundation for future studies. The first issue is measurement. Implicit motives should be measured using causally valid instruments (McClelland, 1980). The second issue addresses the function of motives. Implicit motives orient, select, and energize behavior (McClelland, 1980). If autonomy is an implicit motive, then we need a valid instrument to measure it and we also need to show that it orients, selects, and energizes behavior.
In the following dissertation, I address these two issues in a series of ten studies. Firstly, I present studies that examine the causal validity of the Operant Motive Test (OMT; Kuhl, 2013) for the implicit affiliation and power motives using established methods. Secondly, I developed and empirically tested pictures to specifically assess the implicit autonomy motive and examined their causal validity. Thereafter, I present two studies that investigated the orienting and energizing effects of the implicit autonomy motive. The results of the studies solidified the foundation of the OMT and how it measures nAutonomy. Furthermore, this dissertation demonstrates that nAutonomy fulfills the criteria for two of the main functions of implicit motives. Taken together, the findings of this dissertation provide further support for autonomy as an implicit motive and a foundation for intriguing future studies.
There is no longer any doubt about the general effectiveness of psychotherapy. However, up to 40% of patients do not respond to treatment. Despite efforts to develop new treatments, overall effectiveness has not improved. Consequently, practice-oriented research has emerged to make research results more relevant to practitioners. Within this context, patient-focused research (PFR) focuses on the question of whether a particular treatment works for a specific patient. Finally, PFR gave rise to the precision mental health research movement that is trying to tailor treatments to individual patients by making data-driven and algorithm-based predictions. These predictions are intended to support therapists in their clinical decisions, such as the selection of treatment strategies and adaptation of treatment. The present work summarizes three studies that aim to generate different prediction models for treatment personalization that can be applied to practice. The goal of Study I was to develop a model for dropout prediction using data assessed prior to the first session (N = 2543). The usefulness of various machine learning (ML) algorithms and ensembles was assessed. The best model was an ensemble utilizing random forest and nearest neighbor modeling. It significantly outperformed generalized linear modeling, correctly identifying 63.4% of all cases and uncovering seven key predictors. The findings illustrated the potential of ML to enhance dropout predictions, but also highlighted that not all ML algorithms are equally suitable for this purpose. Study II utilized Study I’s findings to enhance the prediction of dropout rates. Data from the initial two sessions and observer ratings of therapist interventions and skills were employed to develop a model using an elastic net (EN) algorithm. The findings demonstrated that the model was significantly more effective at predicting dropout when using observer ratings with a Cohen’s d of up to .65 and more effective than the model in Study I, despite the smaller sample (N = 259). These results indicated that generating models could be improved by employing various data sources, which provide better foundations for model development. Finally, Study III generated a model to predict therapy outcome after a sudden gain (SG) in order to identify crucial predictors of the upward spiral. EN was used to generate the model using data from 794 cases that experienced a SG. A control group of the same size was also used to quantify and relativize the identified predictors by their general influence on therapy outcomes. The results indicated that there are seven key predictors that have varying effect sizes on therapy outcome, with Cohen's d ranging from 1.08 to 12.48. The findings suggested that a directive approach is more likely to lead to better outcomes after an SG, and that alliance ruptures can be effectively compensated for. However, these effects
were reversed in the control group. The results of the three studies are discussed regarding their usefulness to support clinical decision-making and their implications for the implementation of precision mental health.
With the advent of highthroughput sequencing (HTS), profiling immunoglobulin (IG) repertoires has become an essential part of immunological research. The dissection of IG repertoires promises to transform our understanding of the adaptive immune system dynamics. Advances in sequencing technology now also allow the use of the Ion Torrent Personal Genome Machine (PGM) to cover the full length of IG mRNA transcripts. The applications of this benchtop scale HTS platform range from identification of new therapeutic antibodies to the deconvolution of malignant B cell tumors. In the context of this thesis, the usability of the PGM is assessed to investigate the IG heavy chain (IGH) repertoires of animal models. First, an innovate bioinformatics approach is presented to identify antigendriven IGH sequences from bulk sequenced bone marrow samples of transgenic humanized rats, expressing a human IG repertoire (OmniRatTM). We show, that these rats mount a convergent IGH CDR3 response towards measles virus hemagglutinin protein and tetanus toxoid, with high similarity to human counterparts. In the future, databases could contain all IGH CDR3 sequences with known specificity to mine IG repertoire datasets for past antigen exposures, ultimately reconstructing the immunological history of an individual. Second, a unique molecular identifier (UID) based HTS approach and network property analysis is used to characterize the CLLlike CD5+ B cell expansion of A20BKO mice overexpressing a natural short splice variant of the CYLD gene (A20BKOsCYLDBOE). We could determine, that in these mice, overexpression of sCYLD leads to unmutated subvariant of CLL (UCLL). Furthermore, we found that this short splice variant is also seen in human CLL patients highlighting it as important target for future investigations. Third, the UID based HTS approach is improved by adapting it to the PGM sequencing technology and applying a custommade data processing pipeline including the ImMunoGeneTics (IMGT) database error detection. Like this, we were able to obtain correct IGH sequences with over 99.5% confidence and correct CDR3 sequences with over 99.9% confidence. Taken together, the results, protocols and sample processing strategies described in this thesis will improve the usability of animal models and the Ion Torrent PGM HTS platform in the field if IG repertoire research.
Knowledge acquisition comprises various processes. Each of those has its dedicated research domain. Two examples are the relations between knowledge types and the influences of person-related variables. Furthermore, the transfer of knowledge is another crucial domain in educational research. I investigated these three processes through secondary analyses in this dissertation. Secondary analyses comply with the broadness of each field and yield the possibility of more general interpretations. The dissertation includes three meta-analyses: The first meta-analysis reports findings on the predictive relations between conceptual and procedural knowledge in mathematics in a cross-lagged panel model. The second meta-analysis focuses on the mediating effects of motivational constructs on the relationship between prior knowledge and knowledge after learning. The third meta-analysis deals with the effect of instructional methods in transfer interventions on knowledge transfer in school students. These three studies provide insights into the determinants and processes of knowledge acquisition and transfer. Knowledge types are interrelated; motivation mediates the relation between prior and later knowledge, and interventions influence knowledge transfer. The results are discussed by examining six key insights that build upon the three studies. Additionally, practical implications, as well as methodological and content-related ideas for further research, are provided.
Academic achievement is a central outcome in educational research, both in and outside higher education, has direct effects on individual’s professional and financial prospects and a high individual and public return on investment. Theories comprise cognitive as well as non-cognitive influences on achievement. Two examples frequently investigated in empirical research are knowledge (as a cognitive determinant) and stress (as a non-cognitive determinant) of achievement. However, knowledge and stress are not stable, what raises questions as to how temporal dynamics in knowledge on the one hand and stress on the other contribute to achievement. To study these contributions in the present doctoral dissertation, I used meta-analysis, latent profile transition analysis, and latent state-trait analysis. The results support the idea of knowledge acquisition as a cumulative and long-term process that forms the basis for academic achievement and conceptual change as an important mechanism for the acquisition of knowledge in higher education. Moreover, the findings suggest that students’ stress experiences in higher education are subject to stable, trait-like influences, as well as situational and/or interactional, state-like influences which are differentially related to achievement and health. The results imply that investigating the causal networks between knowledge, stress, and academic achievement is a promising strategy for better understanding academic achievement in higher education. For this purpose, future studies should use longitudinal designs, randomized controlled trials, and meta-analytical techniques. Potential practical applications include taking account of students’ prior knowledge in higher education teaching and decreasing stress among higher education students.
The present dissertation was developed to emphasize the importance of self-regulatory abilities and to derive novel opportunities to empower self-regulation. From the perspective of PSI (Personality Systems Interactions) theory (Kuhl, 2001), interindividual differences in self-regulation (action vs. state orientation) and their underlying mechanisms are examined in detail. Based on these insights, target-oriented interventions are derived, developed, and scientifically evaluated. The present work comprises a total of four studies which, on the one hand, highlight the advantages of a good self-regulation (e.g., enacting difficult intentions under demands; relation with prosocial power motive enactment and well-being). On the other hand, mental contrasting (Oettingen et al., 2001), an established self-regulation method, is examined from a PSI perspective and evaluated as a method to support individuals that struggle with self-regulatory deficits. Further, derived from PSI theory`s assumptions, I developed and evaluated a novel method (affective shifting) that aims to support individuals in overcoming self-regulatory deficits. Thereby affective shifting supports the decisive changes in positive affect for successful intention enactment (Baumann & Scheffer, 2010). The results of the present dissertation show that self-regulated changes between high and low positive affect are crucial for efficient intention enactment and that methods such as mental contrasting and affective shifting can empower self-regulation to support individuals to successfully close the gap between intention and action.
When humans encounter attitude objects (e.g., other people, objects, or constructs), they evaluate them. Often, these evaluations are based on attitudes. Whereas most research focuses on univalent (i.e., only positive or only negative) attitude formation, little research exists on ambivalent (i.e., simultaneously positive and negative) attitude formation. Following a general introduction into ambivalence, I present three original manuscripts investigating ambivalent attitude formation. The first manuscript addresses ambivalent attitude formation from previously univalent attitudes. The results indicate that responding to a univalent attitude object incongruently leads to ambivalence measured via mouse tracking but not ambivalence measured via self-report. The second manuscript addresses whether the same number of positive and negative statements presented block-wise in an impression formation task leads to ambivalence. The third manuscript also used an impression formation task and addresses the question of whether randomly presenting the same number of positive and negative statements leads to ambivalence. Additionally, the effect of block size of the same valent statements is investigated. The results of the last two manuscripts indicate that presenting all statements of one valence and then all statements of the opposite valence leads to ambivalence measured via self-report and mouse tracking. Finally, I discuss implications for attitude theory and research as well as future research directions.
Early life adversity (ELA) poses a high risk for developing major health problems in adulthood including cardiovascular and infectious diseases and mental illness. However, the fact that ELA-associated disorders first become manifest many years after exposure raises questions about the mechanisms underlying their etiology. This thesis focuses on the impact of ELA on startle reflexivity, physiological stress reactivity and immunology in adulthood.
The first experiment investigated the impact of parental divorce on affective processing. A special block design of the affective startle modulation paradigm revealed blunted startle responsiveness during presentation of aversive stimuli in participants with experience of parental divorce. Nurture context potentiated startle in these participants suggesting that visual cues of childhood-related content activates protective behavioral responses. The findings provide evidence for the view that parental divorce leads to altered processing of affective context information in early adulthood.
A second investigation was conducted to examine the link between aging of the immune system and long-term consequences of ELA. In a cohort of healthy young adults, who were institutionalized early in life and subsequently adopted, higher levels of T cell senescence were observed compared to parent-reared controls. Furthermore, the results suggest that ELA increases the risk of cytomegalovirus infection in early childhood, thereby mediating the effect of ELA on T cell-specific immunosenescence.
The third study addresses the effect of ELA on stress reactivity. An extended version of the Cold Pressor Test combined with a cognitive challenging task revealed blunted endocrine response in adults with a history of adoption while cardiovascular stress reactivity was similar to control participants. This pattern of response separation may best be explained by selective enhancement of central feedback-sensitivity to glucocorticoids resulting from ELA, in spite of preserved cardiovascular/autonomic stress reactivity.
Why they rebel peacefully: On the violence-reducing effects of a positive attitude towards democracy
Under the impression of Europe’s drift into Nazism and Stalinism in the first half of the 20th century, social psychological research has focused strongly on dangers inherent in people’s attachment to a political system. The dissertation at hand contributes to a more differentiated perspective by examining violence-reducing aspects of political system attachment in four consecutive steps: First, it highlights attachment to a social group as a resource for violence prevention on an intergroup level. The results suggest that group attachment fosters self-control, a well-known protective factor against violence. Second, it demonstrates violence-reducing influences of attachment on a societal level. The findings indicate that attachment to a democracy facilitate peaceful and prevent violent protest tendencies. Third, it introduces the concept of political loyalty, defined as a positive attitude towards democracy, in order to clarify the different approaches of political system attachment. A set of three studies show the reliability and validity of a newly developed political loyalty questionnaire that distinguishes between affective and cognitive aspects. Finally, the dissertation differentiates former findings with regard to protest tendencies using the concept of political loyalty. A set of two experiments show that affective rather than cognitive aspects of political loyalty instigate peaceful protest tendencies and prevent violent ones. Implications of this dissertation for political engagement and peacebuilding as well as avenues for future research are discussed.