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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)

Previous research has revealed heterogeneity in outcome trajectories among individuals seeking psychotherapy. However, questions remain as to the number, nature, and predictors of these trajectories. Therefore, the present study had three aims: 1) to identify heterogeneous latent groups among treatment trajectories of 212 clients with major depressive disorder (MDD) seeking psychotherapy at a community mental health training clinic; 2) to identify significant associations between clinical and demographic variables and group membership; and 3) to identify correlations between trajectory shape and positive treatment outcome. Prior to treatment, participants provided demographic information and completed symptom severity ratings. Once in treatment, participants completed a self-report of distress via the Outcome Questionnaire (OQ-45) at every session. Growth mixture modeling was utilized to identify distinct patient subgroups based on outcome trajectories among the sample. Three distinct latent classes of treatment trajectory were identified, providing evidence of heterogeneity in treatment trajectories among individuals with MDD. Baseline distress, pre-treatment work problems, and sleep difficulties were found to be predictive of an individual's membership in a specific trajectory group. Finally, specific shapes of change, namely early response and sudden gains, were associated with positive treatment outcome. Findings from this study can be used to identify patients at risk for treatment failure, allowing clinicians to intervene earlier to enhance mid-treatment feedback and prognosis.

L’étude cherche à provoquer la convergence des regards sur des enjeux méthodologiques fondamentaux, soit les enjeux de mesure, de décision et d’impact inhérents à toute démarche de sélection académique. À cet effet, elle explorera la capacité de prédiction de certaines variables non cognitives envers la compétence de professionnalisme observée chez les étudiants du doctorat professionnel de premier cycle en pharmacie. La sélection des candidats au sein des programmes académiques en santé repose en grande partie sur une évaluation de la capacité cognitive des étudiants. Tenant compte du virage compétence pris par la majorité des programmes en santé, la pertinence et la validité des critères traditionnels de sélection sont remises en question. La présente étude propose de valider l’utilisation des échelles de mesure de la personnalité, des valeurs et de l’autodétermination pour guider l’optimalité et l’équité des décisions de sélection. Les enjeux de mesure de ces variables seront abordés principalement par la modélisation dichotomique et polytomique de Rasch. L’application de la méthode des strates permettra, par la suite, de répondre aux enjeux de décision en procédant à une différenciation et un classement des étudiants. Puis, les enjeux d’impact seront, à leur tour, explorés par le modèle de régression par classes latentes. L’étude démontre notamment que le recours à la modélisation a permis une différenciation précise des étudiants. Cependant, la violation de certaines conditions d’application des modèles et la faible différenciation établie entre les étudiants sur la base des critères de professionnalisme, rendent l’évaluation de la capacité de prédiction de la personnalité, des valeurs et de l’autodétermination hasardeuse. À cet effet, les modèles identifiés par les analyses de régression par classes latentes s’avèrent peu concluants. Les classes latentes ainsi identifiées ne présentent pas de distinctions marquées et utiles à la sélection. Bien que les diverses procédures de modélisation proposées présentent des avantages intéressants pour une utilisation en contexte de sélection académique, des recherches additionnelles sur la qualité des critères de professionnalisme et sur la qualité des échelles de mesure des variables non cognitives demeurent nécessaires. / The study seeks to draw attention on fundamental issues of any academic admission procedures, specifically on measurement, decision and impact issues. Therefore, it will explore the predictive ability of three non-cognitive variables toward the observed professionalism of PharmD students. Admitting student in the health sciences often rely solely on the student cognitive ability. Taking into account that health sciences program have moved toward competency oriented curriculum, the relevance and validity of traditional admission criteria are challenged. This study proposes to validate the use of personality , values and self-determination measurement scales to pursue effective and equitable admission decisions. The challenges of measuring these variables will be addressed primarily by the dichotomous and polytomous Rasch models. The Strata method will, thereafter, provide methodological basis for decision issues by enabling for student ranking and classification. Then, impact issues will, in turn, be explored by latent class regression analysis. The study demonstrates that the use of such modeling procedures has allowed accurate differentiation, ranking and classification of students. However, the violation of certain basic model requirements and the lack of differentiation made between students on the basis of the criteria of professionalism, made the assessment of the predictive power of personality, values and self-determination hazardous. In fact, the latent class models identified were non conclusive. They showed no marked distinctions useful to guide admission procedures. Although, the Rasch modeling, the latent class regression model and the Strata procedure shows interesting benefits for admission procedures, additional research on the quality of professionalism criteria and non-cognitive variables measurement scales are required.

Nous présentons une nouvelle méthode pour étudier les relations entre la structure génétique des populations et l'environnement. Cette méthode repose sur des modèles hiérarchiques bayésiens qui utilisent conjointement des données génétiques multi-locus et des données spatiales, environnementales et/ou culturelles. Elle permet d'estimer la structure génétique des populations, d'évaluer ses liens avec des covariables non génétiques, et de projeter la structure génétique des populations en fonction de ces covariables. Dans un premier temps, nous avons appliqué notre approche à des données de génétique humaine pour évaluer le rôle de la géographie et des langages dans la structure génétique des populations amérindiennes. Dans un deuxième temps, nous avons étudié la structure génétique des populations pour 20 espèces de plantes alpines et nous avons projeté les modifications intra spécifiques qui pourront être causées par le réchauffement climatique. / We introduce a new method to study the relationships between population genetic structure and environment. This method is based on Bayesian hierarchical models which use both multi-loci genetic data, and spatial, environmental, and/or cultural data. Our method provides the inference of population genetic structure, the evaluation of the relationships between the structure and non-genetic covariates, and the prediction of population genetic structure based on these covariates. We present two applications of our Bayesian method. First, we used human genetic data to evaluate the role of geography and languages in shaping Native American population structure. Second, we studied the population genetic structure of 20 Alpine plant species and we forecasted intra-specific changes in response to global warming. STAR

Mapping of mortality rates has been a valuable public health tool. We describe novel Bayesian methods for constructing maps which do not depend on a post stratification of the estimated rates. We also construct posterior modal maps rather than posterior mean maps. Our methods are illustrated using mortality data from chronic obstructive pulmonary diseases (COPD) in the continental United States. Poisson regression models have attracted much attention in the scientific community for their superiority in modeling rare events (including mortality counts from COPD). Christiansen and Morris (JASA 1997) described a hierarchical Bayesian model for heterogeneous Poisson counts under the exchangeability assumption. We extend this model to include latent classes (groups of similar Poisson rates unknown to an investigator). Also, it is standard practice to construct maps using quantiles (e.g., quintiles) of the estimated mortality rates. For example, based on quintiles, the mortality rates are cut into 5 equal size groups, each containing $20\%$ of the data, and a different color is applied to each of them on the map. A potential problem is that, this method assumes an equal number of data in each group, but this is often not the case. The latent class model produces a method to construct maps without using quantiles, providing a more natural representation of the colors. Typically, for rare events, the posterior densities of the rates are skewed, making the posterior mean map inappropriate and inaccurate. Thus, although it is standard practice to present the posterior mean maps, we also develop a method to provide the joint posterior modal map (i.e., the map with the highest posterior probability over the ensemble). For the COPD data, collected 1988-1992 over 798 health service areas, we use Markov chain Monte Carlo methods to fit the model, and an output analysis is used to construct the new maps.

This thesis examines family formation in Scotland, with a focus on having a first birth. I argue that fertility behaviour must be researched as part of a process of family formation across the life course and informed by the conceptual framework of the Theory of Planned Behaviour. Starting from geographical patterns in fertility rates, housing and partnership, I establish relationships between shared social attitudes, partnership, housing, and family formation behaviour. I use cross-sectional and panel data from the Scottish Social Attitude Survey, the Scottish Census, the Scottish Longitudinal Study and the British Household Panel Study. The methodological contribution lies in the use of a Latent Class Analysis to identify shared social attitudes groups, which are then incorporated in more generic models predicting fertility intentions and first birth outcomes. The findings indicate that social attitudes and norms are important for family formation. While the Second Demographic Transition Theory argued that social norms are being replaced by more independent choices, more recent fertility literature has called for more attention to social norms. The current thesis thus supports these recent calls by showing how social norms might be (indirectly) measured in quantitative research. A key focus is on relationships between housing and family formation, especially normative ideas of 'proper' family housing. I demonstrate that family housing is a significant predictor of first births, at least for women. The gendered nature of family formation is also demonstrated by the different indicators found to predict men's and women's fertility intentions and realisations. I conclude that improved understanding of fertility behaviour requires longitudinal research that goes beyond the usual fertility indicators such as partnership and recognises the importance of gender differences, housing, shared social attitudes, and, above all, the continuing relevance of social norms in the family formation process.

According to previous research, internalizing and externalizing problems tend to be comorbid or co-occur at different ages in development (Angold, Costello, & Erkanli, 1999). The question that this dissertation addresses is how and why internalizing and externalizing problems, two disorders that represent separate forms of psychopathology, co-occur in children. This is an important question for the developmental psychopathology perspective because an appreciation of the concept of co-occurrence is essential for explaining the development and taxonomy of internalizing and externalizing psychopathology, and for understanding the etiology and course of these symptoms (Achenbach, 1990). Attempts to explain co-occurrence have proposed that co-occurring psychopathology might represent distinct, meaningful syndromes (Angold & Costello, 1992; O’Connor et al., 1998), and in support of this idea, evidence of the existence of pure and co-occurring internalizing and externalizing problems has been found (Keiley et al., 2003). However, no previous study has identified heterogeneous developmental patterns of pure or combined internalizing and externalizing problems within a dynamic framework by taking trajectories of change into account. This dissertation uses data from the NICHD study of Early Child Care to explore the co-occurrence between internalizing and externalizing problems from age 2 to 12 with the use of Latent Class Growth Analysis. The sample included 1232 children (52% male). Different groups of children exhibiting low/normative, pure internalizing, pure externalizing, and co-occurring internalizing and externalizing problems across the 10 year period were identified. The higher risk groups deviated from the low/normative group in terms of antecedents, SES risk, medical risk, difficult temperament, and home environment. Moreover, children who exhibited pure moderate externalizing problems, and children who exhibited chronic externalizing problems, with and without co-occurring internalizing problems, engaged in more risky behaviors and were more likely to have friends who also engaged in risky behaviors. Furthermore, the pure chronic externalizing group and the groups scoring high on internalizing problems, with and without co-occurring externalizing problems, were more asocial with peers. Finally, children exhibiting chronic co-occurring externalizing and internalizing problems were more excluded by peers in comparison to the rest of the sample’s population.

Understanding the development of adolescent sexual risk behavior is complicated by the co-occurrence of sexual risk with substance use and delinquency, conceptualized as “problem behavior syndrome,” with common causes and influences underlying all three problem behaviors (Jessor & Jessor, 1977). Explaining the development of sexual risk becomes even more complex given the changing patterns of adaptation and maladaptation over the course of adolescence (Sroufe & Rutter, 1984). Research also suggests that multiple pathways may forecast adolescent engagement in sexual risk behavior, underscoring the ideas of equifinality and multifinality in developmental psychopathology (Cicchetti & Rogosh, 1996). To understand the diverse nature of sexual risk taking, researchers must identify these pathways and disentangle co-occurring problem behaviors from sexual risk. Revealing the course of sexual risk taking and the early risk and protective processes through which problem behavior develops allows researchers to identify the developmental periods that would be most amenable to intervention efforts (Rolf et al., 1990). Using data from the National Longitudinal Survey of Youth (NLSY79), this study aimed to disentangle problem behavior syndrome by identifying the unique developmental pathways of adolescent sexual risk, alcohol use and delinquency. This study also investigated how early adolescent processes of risk and protection were associated with the growth of these risk behaviors during adolescence. Using a developmental psychopathology and resilience framework, risk trajectories were measured with adolescents aged 15 to 24, and antecedents were measured with early adolescents ages 10 to 14 (N= 1778). Using Latent Class Growth Analyses (LCGA), joint trajectory analyses revealed five distinct adolescent risk taking groups: high sex and alcohol, moderate problem behavior, problem behavior, alcohol-only, and alcohol and delinquency experimentation. Early adolescent externalizing problems were particularly important in understanding adolescent risk group membership. The co-occurrence between sexual risk and alcohol use, the diversity of problem behavior syndrome, and potential intervention and prevention efforts are discussed.