An Ethnographic Interpretation of Latino Perspectives on Family Engagement in Education

In this period of intense demographic change and educational reform that strongly emphasizes the imperative of family engagement, yet implicates minority culture parents as not being involved, it behooves the field of education to take a closer look at the rigidity that schools utilize in their normalized perceptions and practices of parental involvement. Effective involvement can consist of a number of different activities, but only a few are acknowledged in educational discourse. Therefore, it is important to hear the perspectives of families of other cultures in order to bring to light new understanding that will assist schools in building stronger partnerships with under-served families. Much research surrounding family engagement has been conducted, including some that focuses on immigrant populations. However, engagement between rural northwest Iowa schools and the rapidly growing Latino population has not been studied. At the same time, Iowa academic outcomes for Latino youth continue to lag behind those of the majority population. A possible solution to this issue is to enhance school-family partnerships, but we must also consider the culturally distinct ways that we perceive and practice engagement. This study provided space for the voices of marginalized families to be heard in this important conversation regarding barriers that hinder Latino families full access to partnerships with their local schools. By listening to the responses of the Latino community regarding their perspective on family engagement using in-depth interviews via an ethnographic approach, I was able to uncover new insight that will enhance school efforts to foster a deeper sense of community which could positively impact student outcomes

Exploring Newcomer Settlement and Integration Supports in Brantford, and Brant-Haldimand-Norfolk Counties: Community-Based Participatory Research

Much of the literature on recent immigrants focuses on a needs analysis from a deficit model where primarily formal services and programs related to employment issues are analyzed from a post-positivist or interpretivist framework. Using a strength-based approach this study examined other settlement issues including employment that are vital to the long-term viability of newcomers and the host society such as access to education, training (language and/or vocational), health care, and social network. Using Community Based Participatory Research (CBPR) philosophical framework and methodology, data were generated from various sources—quantitative and qualitative text in the survey questionnaire (service providers and newcomers), discussions with Immigrant Settlement Transition Employment and Partnership (ISTEP) members, community meetings, dialogues with immigrant elders, and the researcher’s reflexive journal. The questionnaire responses and the community discussions suggest that although the majority of the newcomers were university educated and had knowledge of English and/or French they face many settlement challenges such as unemployment, language, communication, underemployment, and social isolation. Of particular importance were the observed discrepancies between the newcomers’ perceptions and the service providers’ perceptions when answering the survey questions. This highlights the importance of consulting representative newcomers directly on all community and policy matters which will affect them. Moreover, the results reveal that the services available in this community are incompatible in relation to the needs of this highly skilled cohort of newcomers. Now that newcomers are settling in areas outside of Canada’s metropolitan cities, the results of this research provide pivotal information that will assist community service providers in planning programs and services to foster the integration of newcomers in this particular region as well as in other smaller communities. The findings of this study carry important messages for researchers and policy makers

Substance Abuse Treatment for Persons With Co-Occurring Disorders

Summary: This TIP, Substance Abuse Treatment for Persons With Co-Occurring Disorders, revises TIP 9, Assessment and Treatment of Patients With Coexisting Mental Illness and Alcohol and Other Drug Abuse. The revised TIP provides information about new developments in the rapidly growing field of co-occurring substance use and mental disorders and captures the state-of-the-art in the treatment of people with co-occurring disorders. The TIP focuses on what the substance abuse treatment clinician needs to know and provides that information in an accessible manner. The TIP synthesizes knowledge and grounds it in the practical realities of clinical cases and real situations so the reader will come away with increased knowledge, encouragement, and resourcefulness in working with clients with co-occurring disorders. View book on publisher\u27s websit

Developing artificial intelligence and machine learning to support primary care research and practice

This thesis was motivated by the potential to use everyday data , especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support for chronic conditions in high-income countries, with low levels of primary care involvement and model evaluation in real-world settings. Our second objective was to demonstrate how AI methods can be applied to problems in descriptive epidemiology. To achieve this, we collaborated with the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario to clients who experience barriers to regular care. We described sociodemographic, clinical, and healthcare use characteristics of their adult primary care population using EHR data from 2009-2019. We used both simple statistical and unsupervised learning techniques, applied with an epidemiological lens. In addition to substantive findings, we identified potential avenues for future learning initiatives, including the development of decision support tools, and methodological considerations therein. Our third objective was to advance interpretable AI methodology that is well-suited for heterogeneous data, and is applicable in clinical epidemiology as well as other settings. To achieve this, we developed a new hybrid feature- and similarity-based model for supervised learning. There are two versions, fit by convex optimization with a sparsity-inducing penalty on the kernel (similarity) portion of the model. We compared our hybrid models with solely feature- and similarity-based approaches using synthetic data and using CHC data to predict future loneliness or social isolation. We also proposed a new strategy for kernel construction with indicator-coded data. Altogether, this thesis progressed AI for primary care in general and for a particular health care organization, while making research contributions to epidemiology and to computer science

BRIDGE: The Heritage of Connecting Places and Cultures, Conference Proceedings

Official Conference Proceedings for the international conference BRIDGE: The Heritage of Connecting Places and Cultures (6-10 July 2017, Ironbridge Gorge World Heritage Site, UK) Organised by the Ironbridge International Institute for Cultural Heritage, University of Birmingham, and the Ironbridge Gorge Museum Trust