PREFACE: The purpose of this Master’s thesis was to determine which attributes of an early intervention (EI) mental health service would encourage treatment initiation and sustained engagement. This research was motivated by the bourgeoning interest in patient-centered care, particularly the incorporation of patient preferences into service design and implementation. Additionally, the research was inspired by the use of marketing research methodology in healthcare. Two conjoint surveys were formulated with the purpose of asking two questions: what EI service attributes will increase the likelihood of someone (1) initiating contact with an EI service and attending their first appointment, and (2) remaining engaged in treatment. A literature search determined which attributes would be the most relevant and important for conceptualizing an EI service. These attributes were narrowed down with the help of focus groups, key informant interviews, the expertise of the authors, and in the case of the second survey, was also informed by the first survey’s results. Each attribute was assigned four levels and these multi-level attributes were formulated into the two aforementioned surveys that were completed by mental health patients, their families, and mental health professionals. Chapter 1 of this thesis contains a short overview of the research literature investigating the benefits of EI services, some of the reasons why many patients may not receive such services, and some potential strategies to enhance patients’ initial contact and ongoing engagement with such services. In particular, the central tenet of this thesis is that patient engagement with EI services will be enhanced if service design considers and incorporates the preferences of patients and their families with regard to the attributes that characterize the service and its delivery. This hypothesis is explored using discrete choice conjoint experimental (DCE) methods to identify important service attributes regarding patient initiation and engagement. Given that DCEs are the central methodology of this thesis, Chapter 1 also includes an introduction to these methods and their unique benefits. Each of these service attribute questions posed above is addressed in a separate survey and experiment. Therefore, the rationale, methods, results and conclusions of each experiment are described in separate chapters (Chapters 2 & 3). It should be noted that these two chapters are written in the form of stand-alone scientific reports, each of which is about to be submitted for publication to peer-reviewed journals. Finally, the thesis concludes with a General Discussion (Chapter 4), which attempts to frame the two studies, and this line of inquiry more generally, in the broader research literature and highlight their clinical and policy implications. It should also be noted that, given that there exists substantial conceptual overlap between the two experiments and the main issues described in both the General Introduction and General Discussion, the reader may encounter some repetition throughout the thesis. / Mental illness places a large burden on individuals and society-at-large, a problem that becomes much worse the longer it is left untreated. Early intervention (EI) can mitigate this burden; however, those experiencing emerging mental illnesses often do not seek help promptly. Patient-centered care, such as shared-decision making models of mental healthcare, may reduce barriers to treatment. A central tenet of patient-centered care is that patient engagement and service utilization increases when patient preferences are incorporated into clinical services. In the current thesis, discrete choice conjoint experiments (DCE) were used to elicit the preferences of patients and their families, as well as the hypothesized preferences of patients according to mental health professionals, in two surveys. The first survey aimed to identify the attributes of an EI service that would encourage people experiencing psychiatric symptoms to initiate contact with a service and attend their first appointment (Chapter 2). The second survey sought to determine which service attributes would encourage someone to remain engaged with mental health treatment (Chapter 3). Both surveys used Latent Class Analysis to segment the study populations into identifiable subgroups based on shared preferences, and Randomized First Choice simulations to predict which service delivery model each of these identified groups would most likely use. The results of these studies have several implications for current and future mental health services. Effective EI mental health services should include rapid access to services, a range of treatment options, and effective crisis response. Moreover, future DCE studies should focus on replicating these results using more heterogeneous samples and improving DCE methods. / Thesis / Master of Science (MSc)