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This chapter describes the implementation of two service-learning courses within the setting of a primary-care clinic for homeless and indigent individuals. The two courses are a campus-wide Introduction to Community Service and a Community Health Nursing Practicum. Although these two courses have different learning outcomes, they both address the primary goals of service-learning, including (1) developing students' understanding about the responsibility of citizenship and preparing students for effective roles in society; (2) improving students' communication skills, problem-solving skills, and project-specific skills; (3) enhancing students' self esteem and sense of social reality; and (4) providing an interdisciplinary perspective (Kendall and Associates 1990). The sections that follow describe the setting that the two service-learning courses share, the university-wide course, and the community health nursing practicum. Common issues faced in both courses that are discussed include reflective learning practices, community/client impact, communicating expectations to the student and the site personnel, collaboration to accomplish both service and learning outcomes, and practical issues associated with service-learning in a clinic for the homeless and indigent.

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Despite a call by researchers for estimates of the treatment clinical and cost effectiveness for relational problems, very little has been done to answer this call. The present study is an examination of actual treatment costs and recidivism rates for patients treated for a relational problem (either in individual or conjoint therapy sessions) in the CIGNA network. Despite the fact that this study compares treatment provider cost-effectiveness for treating relational problems, analyses do not control for average amounts paid by provider license type. Policymakers and third-party payers may use such clinical-effectiveness and cost-effectiveness data to make decisions regarding treatment of relational problems and funding allocation. The present study is also the first to compare the costs of couples therapy versus family therapy for relational problems.

Recently the direction of consumer mental health care in the United States has shifted in terms of its approach to recovery. In this sense recovery is not thought to be a complete amelioration of symptoms, but rather the acquisition of meaningful relationships, independent living, and fulfilling work. In response to these changes, the Utah division of the National Alliance for the Mentally Ill (NAMI-Utah) conducted consumer focus groups for the purpose of developing a tool to monitor this new conceptualization of recovery. The focus groups generated 10 recovery indicators based on recovery as the Substance Abuse and Mental Health Services Administration have defined it. This study explored initial psychometric reliability and validity estimates for these recovery indicators and their ability to track changes in recovery over time. In addition, the study also explored the relationship between distress reduction and recovery both concurrently and over time.

Computer-based instructors, just like their human counterparts, should monitor the emotional and cognitive states of their students in order to adapt instructional technique. Doing so requires a model of student state to be available at run time, but this has historically been difficult. Because people are different, generalized models have not been able to be validated. As a person’s cognitive and affective state vary over time of day and seasonally, individualized models have had differing difficulties. The simultaneous creation and execution of an individualized model, in real time, represents the last option for modeling such cognitive and affective states. This dissertation presents and evaluates four differing techniques for the creation of cognitive and affective models that are created on-line and in real time for each individual user as alternatives to generalized models. Each of these techniques involves making predictions and modifications to the model in real time, addressing the real time datastream problems of infinite length, detection of new concepts, and responding to how concepts change over time. Additionally, with the knowledge that a user is physically present, this work investigates the contribution that the occasional direct user query can add to the overall quality of such models. The research described in this dissertation finds that the creation of a reasonable quality affective model is possible with an infinitesimal amount of time and without “ground truth” knowledge of the user, which is shown across three different emotional states. Creation of a cognitive model in the same fashion, however, was not possible via direct AI modeling, even with all of the “ground truth” information available, which is shown across four different cognitive states.