Between 20% and 57% of patients at community mental health centers miss their first mental health appointment, resulting in wasted resources and longer wait times for other patients. To date, only one peer-reviewed quantitative study examined the relationship between appointment reminder practices and children's and adolescents' first appointment attendance rates for community mental health centers. The purpose of this quantitative study was to examine the relationship between first appointment wait times, electronic appointment reminders, phone appointment reminders, and first appointment attendance for U.S. community mental health centers, along with the potential moderating effects of age, ethnicity, and gender. Blumer's symbolic interaction theory served as the theoretical framework. Secondary data on was collected from 12 Texas-based community mental health centers covering 5,260 patients. Binary logistic regression uncovered the following key study findings: (a) wait time and message type significantly predicted appointment attendance; (b) e-mail appointment and text reminders were significantly more effective than were phone reminders; and (c) age, gender, and ethnicity moderated the relationship between wait time and message type, and first appointment attendance. The implications for positive social change include improving our understanding of the optimal appointment reminder tactics that increase children's and adolescents' mental health appointment attendance rates, improve operating efficiency of community health centers, and increase the likelihood that children and adolescents will receive needed mental health services.

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The crew scheduling problem with attendance rates is highly relevant for regional passenger rail transport in Germany. Its major characteristic is that only a certain percentage of trains have to be covered by crew members or conductors, causing a significant increase in complexity. Despite being commonly found in regional transport networks, discussions regarding this issue remain relatively rare in the literature. We propose a novel hybrid column generation approach for a real-world problem in railway passenger transport. To the best of our knowledge, several realistic requirements that are necessary for successful application of generated schedules in practice have been integrated for the first time in this study. A mixed integer programming model is used to solve the master problem, whereas a genetic algorithm is applied for the pricing problem. Several improvement strategies are applied to accelerate the solution process; these strategies are analyzed in detail and are exemplified. The effectiveness of the proposed algorithm is proven by a comprehensive computational study using real-world instances, which are made publicly available. Further we provide real optimality gaps on average less than 10 % based on lower bounds generated by solving an arc flow formulation. The developed approach is successfully used in practice by DB Regio AG.

This study was interested in investigating the factors contributing to low completion rates at a TVET college in the North-West Province. There is not much research conducted on the low completion rates at TVET Colleges in South Africa. The study sought to explore the understanding of completion rates at TVET Colleges, the current completion rates and the causes and the strategies that might be employed to increase the completion rates. Qualitative methodology was used to collect data, using semi-structured interviews for all the focus group interviews. Collected data were transcribed, interpreted, analysed and the findings were presented. The study revealed that factors contributing to the low completion rates are finance and management issues, staff problems, policy factors, socio-economic factors and students’ personal factors that require attention in order to increase the completion rates. These include lecturer qualifications, student funding, inadequate infrastructure, drug and substance abuse, involvement of stakeholders and lack of adherence to policies. The study recommends proper administration of students’ bursaries, effective Quality Management System (QMS), lecturer development, adequate infrastructure and efficient policies to be implemented. The study might draw the attention of the DHET, the college management and other stakeholders in order to come up with interventions to remedy the low completion rates at TVET Colleges. / Educational Management and Leadership / M. Ed. (Educational Management)