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abstract: Background: Unmanaged stress is a major contributing factor to the development of disease in both men and women. Middle-aged adults (40-64) have some of the highest stress of all age groups and the use of meditation may provide relief for conditions such as stress. A smartphone application (app) may help limit the magnitude of the perceived challenges of meditation. The purpose of this study is to determine the feasibility of a consumer-based meditation app (i.e., Calm) to reduce stress in middle-aged adults who self-report elevated stress. The preliminary effects of Calm on stress and health outcomes related to stress were explored as well as the preliminary effects of Calm on mindfulness and coping behaviors for stress were explored. Methods: Adults were recruited to a 4-week app-based health and well-being study. Participants were randomized into either a mindfulness meditation (i.e. Calm) group or a health education (POD) control group. Participants were asked to participate at least 10 minutes per day. Assessments were conducted for stress, anxiety, depression, mindfulness, physical activity, eating habits, and coping behaviors at pre- and post-intervention and voluntary phone interviews were held post-intervention. App usage data were collected subjectively through weekly participation logs and through objective app usage data provided by Calm. Results: Eighty-three participants were enrolled into the study and 60 completed the intervention and were analyzed. Feasibility and demand benchmarks were met with 96% of participants satisfied with the intervention and 93% found it enjoyable, appropriate, and useful. There was a 70% adherence (minutes/week) to the meditation intervention. Recruitment of men into the intervention group was 38.1% and retention of men was 81.3%. Significant changes were not observed in stress, anxiety, depression, or mindfulness, physical activity, eating habits, and coping behaviors. Conclusion: The findings of this study support the feasibility of a 4-week, mobile app-based mindfulness meditation intervention (i.e. Calm) in middle-aged adults. These finding do not demonstrate preliminary efficacy of Calm to reduce stress, anxiety, and depression or improvement of mindfulness, physical activity, eating habits, or coping behaviors among middle-aged adults who report elevated stress. These results can be applied for improved design of future studies. / Dissertation/Thesis / Masters Thesis Behavioral Health 2020

<div>The app-based taxi services (ATS) has disrupted the traditional (street-hailing) taxi services (TTS) leading to transformative changes in the urban taxi markets and its impacts on mobility, design and environment. However, the current modeling of these new mobility markets is limited in its understanding of: (1) the underlying factors that influence the growth of the ATS market; (2) the competition of ATS and TTS markets; (3) pricing in the ATS market; (4) system wide tools to understand the impacts of the market. The overarching goal of this dissertation is to address four fundamental processes of taxi system, ranging from demand generation, supply generation and exiting, dynamic pricing generation, and vehicle-passenger matching over road network. This dissertation achieves these goals by using original large scale datasets to characterize disruptive changes in mobility, understand strategic behaviors of stakeholders, and formulate system dynamics.</div><div> </div><div>This dissertation develops various modeling structures and estimation methods, motivated from statistical, econometric, machine learning, and stochastic approaches. First, we adapt multiple econometric models for demand, supply, and platform-exiting (offline) behaviors, including mixture model of spatial lag and Poisson regression and mixture model of spatial lag and panel regression. It is apparent that all proposed econometric models should be corrected with spatial lag due to significant spatial autocorrelations. The results indicate effectiveness of dynamic pricing in controlling demand, however, it also shows no impacts on driver's online and offline behaviors. Then a dynamic pricing generation problem is formulated with multi-class classification. This model is empirically validated for the impacts of demand and supply in dynamic price generation and the significant spatial and temporal heterogeneity. Last, we propose a queueing network consisting of taxi service queues for vehicle-passenger matching and road service queue for vehicle movements at homogeneous spatial units. The method captures stochasticity in vehicle-passenger matching process, and more importantly, formulates the interactions with urban road traffic.</div><div> </div><div>In summary, this dissertation provides a holistic understanding of fundamental processes that govern the rapid rise in ATS markets and in developing quantitative tools for the system wide impacts of this evolving taxi markets. Taken together, these tools are transformative and useful for city agencies to make various decisions in the smart mobility landscape. </div>