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.

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.

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.

The ability to acquire knowledge helps humans to cope with the demands of the environment. Supporting knowledge acquisition processes is among the main goals of education. Empirical research in educational psychology has identified several processes mediated through that prior knowledge affects learning. However, the majority of studies investigated cognitive mechanisms mediating between prior knowledge and learning and neglected that motivational processes might also mediate the influence. In addition, the impact of successful knowledge acquisition on patients’ health has not been comprehensively studied. This dissertation aims at closing knowledge gaps on these topics with the use of three studies. The first study is a meta-analysis that examined motivation as a mediator of individual differences in knowledge before and after learning. The second study investigated in greater detail the extent to which motivation mediated the influence of prior knowledge on knowledge gains in a sample of university students. The third study is a second-order meta-analysis synthesizing the results of previous meta-analyses on the effects of patient education on several health outcomes. The findings of this dissertation show that (a) motivation mediates individual differences in knowledge before and after learning; (b) interest and academic self-concept stabilize individual differences in knowledge more than academic self-efficacy, intrinsic motivation, and extrinsic motivation; (c) test-oriented instruction closes knowledge gaps between students; (d) students’ motivation can be independent of prior knowledge in high aptitude students; (e) knowledge acquisition affects motivational and health-related outcomes; and (f) evidence on prior knowledge and motivation can help develop effective interventions in patient education. The results of the dissertation provide insights into prerequisites, processes, and outcomes of knowledge acquisition. Future research should address covariates of learning and environmental impacts for a better understanding of knowledge acquisition processes.

Heterogenität ist Teil des (Schul-)Alltags, was sich in den Lerngruppen widerspiegelt, die Lehrkräfte in der Schule vorfinden. Unterschiedlichen Bedürfnissen auf Seiten der Schüler/-innenschaft soll – und das ist in zahlreichen der Öffentlichkeit zugänglichen Dokumenten, wie Schulgesetzen, Schulordnungen und Standards für die Lehrerbildung festgeschrieben – in Form von Differenzierung begegnet werden. Innerhalb dieser Dissertation wird untersucht, wie Binnendifferenzierung auf Mikroebene in der Schulpraxis implementiert wird. Dabei werden die Einsatzhäufigkeit binnendifferenzierender Maßnahmen und Kontextvariablen von Binnendifferenzierung untersucht. Anhand einer Stichprobe von N = 295 Lehrkräften verschiedener Schulformen, die die Fächer Deutsch und/oder Englisch unterrichten, wurde u.a. gezeigt, dass Binnendifferenzierung allgemein nicht (sehr) häufig eingesetzt wird, dass manche Maßnahmen häufiger Einsatz finden als andere, dass an Gymnasien Binnendifferenzierung nicht so häufig eingesetzt wird, wie an anderen Schulformen und dass die Einsatzhäufigkeit bedingende Kontextfaktoren bspw. kollegiale Zusammenarbeit bei der Unterrichtsplanung und -durchführung, die wahrgenommene Qualität der Lehramtsausbildung hinsichtlich des Umgangs mit Heterogenität und die Bereitschaft zur Implementation von Binnendifferenzierung sind und auch Einstellungen zu Binnendifferenzierung und (Lehrer/-innen)Selbstwirksamkeitserwartungen in Zusammenhang mit dem Maßnahmeneinsatz stehen. Die durchgeführte Post-hoc Analyse zeigte bzgl. Einsatzhäufigkeit weiterhin Zusammenhänge zwischen der Persönlichkeit der Lehrkräfte und der Schulform, an der diese unterrichten. Die Ergebnisse entstammen der Schulpraxis und liefern deshalb praktische Implikationen, wie bspw. Hinweise zur Steigerung der Qualität der Lehramtsausbildung, die neben zukünftigen Forschungsansätzen im Rahmen dieser Arbeit expliziert werden.