While partnerships for health delivery and improvement are frequently described by their structure, goals, and plans, less attention is paid to the interactive relationships among partners or for larger stakeholder groups’ coalition memberships. The Give-Get Grid group process tool can be used to assess each stakeholders’ expected benefits (“gets”) and contributions (“gives”) needed to establish and maintain long-term, mutually advantageous community–academic partnerships. This article describes three case study experiences using the Give-Get Grid in real-world context to understand and generate ideas to address contemporary health promotion opportunities among a variety of stakeholders. The case studies address three distinct community health promotion opportunities: prevention of school-based adolescent obesity disparities, higher education health professions training programs in rural community-based settings, and methods for engaging community coalitions in state Comprehensive Cancer Control Programs. The case studies demonstrate the Give-Get Grid’s utility in both planning and evaluating partnerships and documenting key elements for progress in health promotion initiatives built on long-term community–academic relationships. Steps are explained with practical lessons learned in using the Grid.

Master of Public Health - MPH / One hundred and fifty two (152) countries in the world can be classified as developing or low-resourced countries (LR Cs) according to the World Bank. 1 In the majority of these countries the Gross Domestic Product (GDP) is below $1000. Given these limited resources it stands to reason that there is less money available to spend on healthcare and health research

Chronic non-cancer pain (CNCP) is a complex phenomenon that affects multiple dimensions of daily life. Optimal therapies for managing CNCP must, then, demonstrate clinically important benefits that go beyond reductions in pain and adverse events. The Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) has recommended that clinical trialists who are evaluating treatments for chronic pain consider reporting treatment effects across nine patient-important outcome domains. This thesis begins with an investigation of the extent to which clinical trials evaluating the effects of opioids for CNCP report IMMPACT-recommended core outcome domains. Further, it explores optimal therapeutic strategies for specific CNCP conditions; specifically, it features a systematic review of randomized controlled trials of all pharmacological and non-pharmacological therapies for central post-stroke pain, as well as a plan for a network meta-analysis of all therapies for all chronic neuropathic pain syndromes. Chronic pain is also a common reason for disability, and this thesis concludes with a retrospective cohort study focused on identifying predictors of claim duration following acceptance for disability benefits among Canadian workers. / Thesis / Doctor of Philosophy (PhD)

Symptomatic spinal disorders affect a large proportion of the population and are associated with substantial morbidity, social burden, and economic impact. Spine surgery interventions can provide excellent results in carefully selected patients whose symptoms fail to improve with non-operative management, but an evidence-based approach is paramount to optimize outcomes and rigorous standards of health research methodology are critical to avoid misleading conclusions. This thesis aimed to investigate and apply modern innovations in health research methodology to the field of spine surgery. It consists of seven chapters divided between three sections: randomized controlled trials, observational studies, and systematic reviews and meta-analyses. By applying the findings of each chapter, clinicians, researchers, and other evidence users can advance the credibility of future research and enhance the care of patients with spinal disorders. / Thesis / Doctor of Philosophy (PhD)

Yes / Involving patients and the public in all stages of research has been the focus of the SHARED study. Patient and public involvement (PPI) is an important strategic priority for the Department of Health and funders such as the National Institute for Health Research. The aim of this paper is to describe the benefits, challenges and costs involved in setting up the research study with lay members as part of the research team. The study focused on developing service user-led recommendations for people with memory loss and their carers, on discharge from acute hospital to the community. Methods: This began with a discussion of an initial research idea with a lay group of carers and people living with dementia. Once funded, approval was sought from the Research Ethics Committee and NHS Trusts to conduct the research including the active involvement of lay co-researchers. Finally, to recruit, train and pay lay co-researchers in their role. Results: The benefits of PPI have included developing ideas which are important to people living with memory loss; support for PPI received from the funders and research ethics committee, high levels of interest from volunteer groups, and lasting enthusiasm from many of the co-researchers. Organisational challenges were met in the requirement for research passports and with payment methods for the co-researchers. Training was beneficial but incurred extra costs for repeated training days. Discussion: Overall the benefits outweighed the challenges which were overcome to varying degrees. The lay co-researchers gained membership of a study group and a beneficial partnership developed with the third sector. The biggest challenge was in overcoming the differences in approach to lay co-researchers between NHS Trusts. Organisational culture has been slow to incorporate PPI and this has not yet been fully addressed. It has the potential to delay the start of projects, affect recruitment time, incur extra research costs and disadvantage PPI.

No description available.

M.Cur. / Please refer to full text to view abstract

Esta dissertação é fruto da inserção da pesquisadora na Rede-Observatório do Programa Mais Médicos, cujas pesquisas permitiram conhecer além do que os objetivos de um projeto são capazes de prescrever. Composta por narrativas, esta dissertação tem por objetivo tornar visíveis os conhecimentos evocados pela experiência de pesquisa que tendem a não compor os relatórios finais e que não são reconhecidos como produções científicas. Trata-se, então, da visibilidade da dimensão micropolítica do fazer pesquisa e do conhecimento sobre a implantação do Programa, de fragmentos sobre o pesquisar e sobre o próprio Programa Mais Médicos. É com inspiração nas produções brasileiras no campo da Saúde Coletiva, nas proposições de pistas metodológicas da cartografia, na Análise Institucional de Lourau, na narratividade de Benjamin, na Esquizoanálise de Gilles Deleuze e Félix Guattari, entre outras obras e autores, buscando disjunções e interfaces entre eles, que esta dissertação constrói seu alicerce teórico. Flanando por Brasília, pelos interiores das salas da universidade e pela imensidão da Floresta Amazônica, as narrativas que compõem esta dissertação foram construídas a partir de quatro cenas-narrativas, que buscam apontar o desvio do majoritário na ciência, descolar a produção de conhecimento de uma subordinação ao cartesiano. As cenas-narrativas tornaram visíveis efeitos do Programa Mais Médicos na produção de cuidado e no cotidiano de trabalho das equipes de saúde, que os indicadores epidemiológicos não conseguiram revelar, bem como dimensões do fazer pesquisa que são apreendidas em ato. / This work is the result of the researcher’s participation in the Observatory-Network of the More Doctors Program (Rede-Observatório do Programa Mais Médicos), whose studies allowed me to encounter more than what the objectives of a project can prescribe. Composed by narratives, this work aims to make visible the knowledge evoked by the research experience which tend not to compose the final reports and which is not recognized as scientific production. It regards, therefore, to the visibility of the micropolitical dimension in research practices and the knowledge about the implementation of the Program, fragments of the act of researching and of the More Doctors Program itself. It is inspired by Brazilian productions in the field of Saúde Coletiva (Public Health), the cartography’s indications of methodological tracks, Lourau’s Institutional Analysis, Benjamin’s narrativity, Gilles Deleuze and Félix Guattari’s schizoanalysis, among other works and authors, pursuing disjunctions and interfaces between them, that this work builds its theoretical grounds. Wandering through Brasília, the interiors of university rooms or the immensity of the Amazon Forest, these narratives aim to indicate a detour from the majoritary in Science, liberating the production of knowledge from a subordination to the Cartesian.

Finite mixture modeling is a useful statistical technique for clustering individuals based on patterns of responses. The fundamental idea of the mixture modeling approach is to assume there are latent clusters of individuals in the population which each generate their own distinct distribution of observations (multivariate or univariate) which are then mixed up together in the full population. Hence, the name mixture comes from the fact that what we observe is a mixture of distributions. The goal of this model-based clustering technique is to identify what the mixture of distributions is so that, given a particular response pattern, individuals can be clustered accordingly. Commonly, finite mixture models, as well as the special case of latent class analysis, are used on data that inherently involve repeated measures. The purpose of this dissertation is to extend the finite mixture model to allow for the number of repeated measures to be incorporated and contribute to the clustering of individuals rather than measures. The dimension of the repeated measures or simply the count of responses is assumed to follow a truncated Poisson distribution and this information can be incorporated into what we call a dimension informative finite mixture model (DIMM). The outline of this dissertation is as follows. Paper 1 is entitled, "Dimension Informative Mixture Modeling (DIMM) for questionnaire data with an informative number of repeated measures." This paper describes the type of data structures considered and introduces the dimension informative mixture model (DIMM). A simulation study is performed to examine how well the DIMM fits the known specified truth. In the first scenario, we specify a mixture of three univariate normal distributions with different means and similar variances with different and similar counts of repeated measurements. We found that the DIMM predicts the true underlying class membership better than the traditional finite mixture model using a predicted value metric score. In the second scenario, we specify a mixture of two univariate normal distributions with the same means and variances with different and similar counts of repeated measurements. We found that that the count-informative finite mixture model predicts the truth much better than the non-informative finite mixture model. Paper 2 is entitled, "Patterns of Physical Activity in the Northern Manhattan Study (NOMAS) Using Multivariate Finite Mixture Modeling (MFMM)." This is a study that applies a multivariate finite mixture modeling approach to examining and elucidating underlying latent clusters of different physical activity profiles based on four dimensions: total frequency of activities, average duration per activity, total energy expenditure and the total count of the number of different activities conducted. We found a five cluster solution to describe the complex patterns of physical activity levels, as measured by fifteen different physical activity items, among a US based elderly cohort. Adding in a class of individuals who were not doing any physical activity, the labels of these six clusters are: no exercise, very inactive, somewhat inactive, slightly under guidelines, meet guidelines and above guidelines. This methodology improves upon previous work which utilized only the total metabolic equivalent (a proxy of energy expenditure) to classify individuals into inactive, active and highly active. Paper 3 is entitled, "Complex Drug Use Patterns and Associated HIV Transmission Risk Behaviors in an Internet Sample of US Men Who Have Sex With Men." This is a study that applies the count-informative information into a latent class analysis on nineteen binary drug items of drugs consumed within the past year before a sexual encounter. In addition to the individual drugs used, the mixture model incorporated a count of the total number of drugs used. We found a six class solution: low drug use, some recreational drug use, nitrite inhalants (poppers) with prescription erectile dysfunction (ED) drug use, poppers with prescription/non-prescription ED drug use and high polydrug use. Compared to participants in the low drug use class, participants in the highest drug use class were 5.5 times more likely to report unprotected anal intercourse (UAI) in their last sexual encounter and approximately 4 times more likely to report a new sexually transmitted infection (STI) in the past year. Younger men were also less likely to report UAI than older men but more likely to report an STI.

In the last few decades as American society and urban life have changed dramatically, public health and urban sociological research have increasingly focused on the effect of residential location on individual well-being. In recent years, social capital has been viewed as an important pathway in understanding the associations between where one lives and health and social outcomes. Although there is not one, single definition of social capital, researchers within public health have often relied on three schools of thought labeled after Pierre Bourdieu, James Coleman, and Robert Putnam to define social capital and hypothesize its relationship with health and behaviors. However, for many years, public health researchers have often relied on Putnam's theory (1993, 1995, 2000) and a communitarian approach to defining social capital and its possible relationship to health and well-being. Many researchers and sociologists have criticized this over-reliance and overuse of Putnam's social capital constructs as they have been criticized for lacking depth and their inability to explain the causal pathways in which social capital and health operate. Additionally, the measures used to operationalize the most widely used Putnam social capital constructs often focus only on a few dimensions of his theory; generalized trust, shared norms and values, reciprocity, and civic engagement. These measures have been criticized for simultaneously being overly theoretically broad and limited in its measurement. In this research, I use a more recent paradigm of social capital theory that conceptualizes social capital as having several dimensions thereby enabling one to examine the possibility that different forms of social capital and cohesion have different impacts (both negative and positive) on health behaviors and well-being. This paper compares a Putnam-based social capital model as measured by the most commonly used variables based on his work against a broader, multi-dimensional model that measures social capital across several constructs and variables. I have evaluated the "expanded" multi-dimensional model and the smaller, Putnam-only model with a different dataset to examine the relationships between these dimensions of social capital and health behaviors and outcomes. Additionally, recent sociological research using this expanded approach has highlighted the important role of individual attachment to the neighborhood as an important mediator in the association between social capital and health outcomes. Using data from the Fragile Families and Child Wellbeing Study (FFCWS), a longitudinal birth cohort study of families in 20 cities with populations of 200,000 or more people, I investigated the role of social capital as measured across four dimensions, social cohesion (the Putnam-based Traditional Model), individual neighborhood attachment, and neighborhood socio-economic conditions on the likelihood of maternal smoking and alcohol use. Moreover, this multi-dimensional model was enhanced by the addition of another feature of social capital that was not extensively addressed in prior research, bridging social capital. Bridging social capital has been defined as relationships among individuals who are not alike in social identity or characteristics. In recent years, bridging social capital at times has been further refined to highlight the relationships within heterogeneous networks who do not share the same power structures and institutions, and economic spheres. This has been referred to as "linking" social capital. Additionally, sociologist Mario Small has extensively documented that importance of both weak ties (an aspect of "bridging" social capital) and organizational embeddedness in the relationship between social capital and health and well- being for residents in poor communities. This underrepresented dimension in the public health literature is addressed in this paper. In this research, I incorporated a measure of bridging social capital and organizational ties to highlight the possible role this form of social capital may play in understanding the association of social capital and health outcomes. This research extends the current literature by applying a recently developed model of social capital to the analysis of health outcomes using a different data set. The goal of this study was not only to explore smoking and alcohol use, neighborhood socioeconomic conditions, indicators of social capital (including social support, social leverage, informal social control, neighborhood organization participation, and bridging social capital), and the role of individual neighborhood attachment but also highlight the importance for public health researchers to use a multidimensional approach rather than rely on utilizing a few social capital constructs retrieved from Putnam's extensive published work. The multi-dimensional approach which broadens the lens in which researchers use to aid them in the understanding the association between social capital and health and well-being is more beneficial than a narrow focus that relies on a few social capital domains to examine this relationship. The association of these different dimensions was statistically tested through multiple logistic regression analyses which examined a hypothesized interaction effect between organizational embeddedness and social capital and its association with health outcomes and behaviors. It is hoped that this research will further advance the public health discourse regarding the association between health outcomes and social capital, measured across several dimensions and conceptualized through an access to resources and networks based lens.