Mental health problems are common in the general population and are associated with high individual and economic burden. To reduce this burden, psychotherapy research and practice have been increasingly professionalized since the latter half of the 20th century and evidence-based psychotherapeutic treatments have been made widely available. Despite the costly efforts to provide evidence-based psychotherapy on a large scale, a significant number of patients remain untreated or do not respond to available interventions. With the integration of computers into everyday life in the 1990s, research has increasingly focused on computer-based interventions (CBIs) to improve both the provision and the quality of evidence-based treatments for all patients. In the last two decades, numerous studies have demonstrated the effectiveness of CBIs for the treatment of mental health problems. In the 21st century, technology is rapidly progressing, and smartphones have gradually taken the place of personal computers in the general population. As a result, smartphone-based interventions (SBIs) are widely discussed as possible aids for the treatment of mental health problems, and there already exists a plethora of SBIs for various patient groups. However, the majority of available SBIs lack empirical evidence as they have not been evaluated in experimental studies. Hence, there exists considerable uncertainty regarding the benefits and possible treatment effects of SBIs. Moreover, most SBIs lack quality in terms of their interventional content, their use of the smartphone’s technological facilities, and their utilization of strategies that engage the patient to use the SBI regularly. Therefore, this dissertation addresses the development and evaluation of an SBI approach that uses evidence-based strategies, seizes upon the smartphones’ technological features, and applies gamification elements to increase patient engagement. Based on the promising findings for blended interventions that combine traditional face-to-face cognitive-behavioral therapy (CBT) with computerized approach-avoidance modification training (AAMT) in the treatment of alcohol use disorders and depression, the SBI approach introduced in this dissertation makes use of intervention techniques from both CBT and smartphone-based AAMT. In six studies, problem-specific SBIs that apply this combined approach are evaluated for their usability and possible effects in the treatment of various mental health problems. Study 7 presents emotion regulation (ER) as a possible common factor in psychopathology that can be targeted by a single SBI addressing patients suffering from various mental health problems. Study 1 examines the feasibility and explores possible effects of an intervention that combines a brief individual counseling session with two weeks of smartphone-based AAMT. This approach is evaluated in a sample of college students meeting criteria for problematic alcohol use. Findings on both usability and treatment effects provide preliminary evidence that the intervention can significantly reduce dysfunctional beliefs about alcohol, craving of alcohol, and alcohol consumption. Study 2 is a multi-center study that assesses the effect of smartphone-based AAMT combined with a brief individual counseling session for participants with elevated levels of body dissatisfaction. Results show that the intervention significantly reduces body dissatisfaction and symptoms of eating disorders. Study 3 evaluates a blended intervention for the reduction of procrastination. Results from this study provide preliminary evidence that a blended intervention that combines two group counseling sessions with 14 days of smartphone-based AAMT can significantly reduce both general and academic procrastination. In Study 4, the blended intervention is comprised of a brief individual psychoeducation session and smartphone-based AAMT for the training of inter- and intraindividual emotion recognition skills in alexithymic individuals. Results show that the intervention improved computer-assessed emotion recognition skills and demonstrated additional effects over a psychoeducation-only control condition. Studies 5 and 6 evaluate SBIs in samples of individuals reporting heightened levels of depression. While results from Study 5 provide preliminary efficacy for an intervention that combines 14-days of smartphone-based AAMT in combination with a psychoeducation group session, Study 6 examines the effectiveness of a stand-alone SBI targeting depressive symptoms using an automated approach that includes an increased degree of gamification. Results of Study 6 demonstrate that 14 days of training with this stand-alone SBI could significantly reduce depressive symptoms. Study 7 comprises two studies that focus on the cross-sectional assessment of deficits in ER skills with the aim to identify common factors that may be targeted by a single, transdiagnostic SBI. Comparisons between two clinical samples and a sample from the general population indicated that participants that met diagnostic criteria for a mental disorder reported lower ER skills than participants from the general population and that ER skills differed across the clinical subgroups. In conclusion, the present dissertation provides evidence that: (1) the AAMT paradigm can be successfully transferred from computers to smartphone devices as indicated by high acceptance scores, high usability ratings, and the frequent use of the SBIs by participants included in the pilot studies; (2) problem-specific SBIs that incorporate face-to-face CBT techniques with AAMT principles may be efficacious for the reduction of symptoms in the targeted mental health problems; (3) a standalone SBI that applies automated CBT techniques and technologically enriched AAMT variants may effectively reduce symptoms of depression; and that (4) ER skills are promising transdiagnostic processes that may be successfully trained in a single SBI that targets a broad range of mental health problems. Further research using larger, more heterogeneous samples including participants that meet diagnostic criteria for mental disorders is necessary to confirm the findings from this dissertation.