Children with Autism in the Somali Population: Exploring the Inter-Relatedness of the Somali Immigrant and Refugee Experience Navigating Speech-Language Pathology Resources

Approximately 15,711 Somali immigrants resettled in Minnesota in 2016 (Rush, 2016). According to the Rochester Post Bulletin, the Med City ranks fourth place in number of Somali immigrants, 333, behind Minneapolis at 3,450, St. Cloud at 1,393, and St. Paul at 960 (Post Bulletin, 2017). In a study conducted by the Minnesota Department of Health in 2008, the most common services needed by Somali families was first housing, followed by speech therapy second (Minnesota Department of Health, 2014)

Cut Twice: Experiments in Kinetic, Interactive Sculpture

This thesis support paper is an exploration of the process, creative influences and philosophical framework surrounding the creation of the body of work contained in the art exhibition “Cut Twice” (Gales Gallery, May 4-9, 2015). Alongside a narrative describing the making of a large pile of kinetic lumber, two main areas of consideration are discussed; firstly, the desire of the artist to create sculpture that is interactive, framed in part as an extension of a career in the community arts, and secondly, an inquiry into a radical materialism that sees all matter as entangled intra-activity through the lenses of Jane Bennett’s eco-political Vibrant Matter and Karen Barad’s Agential Realism. How might an expanded sense of the aliveness of matter (in this case off-cuts and discarded lumber from construction sites) change our relationship to waste and possibly to each other? If matter is a “doing”, not a thing, can interactive, kinetic sculpture express this material vibrancy and enhance an art viewer’s awareness of their relationship to matter

The Value of Instability: An Investigation of Intra-Subject Variability in Brain Activity Among Obese Adolescent Girls

BACKGROUND: The present study investigated the value of intra-subject variability (ISV) as a metric for revealing differences in cognition and brain activation associated with an obese versus lean body mass. METHODS: Ninety-six adolescents with a lean body mass (BMI %-ile = 5-85), and 92 adolescents with an obese body mass (BMI %-ile \u3e=95), performed two tasks (Stroop and Go/NoGo) challenging response inhibition skills. The standard deviations and averages of their reaction time and P300 electroencephalographic responses to task stimuli were computed across trials. RESULTS: During the Go/NoGo task, the reaction times of subjects with an obese body mass were more variable than those of their lean body mass peers. Accompanying the greater ISV in reaction times was a group difference in P300 amplitude ISV in the opposite direction across both tasks. The effect sizes associated with these group differences in ISV were marginally greater than the effect sizes for the comparisons of the group means. CONCLUSIONS: ISV may be superior to the mean as a tool for differentiating groups without significant cognitive impairment. The co-occurrence of reduced ISV in P300 amplitude and elevated ISV in reaction time may indicate a constraint among obese adolescent girls in the range of information processing strategies and neural networks that can compete to optimize response output. It remains to be determined if this decrement in neural plasticity has implications for their problem solving skills as well as their response to weight management interventions

How do features of Electronic Health Records Impact Prescription of Nicotine Replacement Therapy?

Nicotine Replacement Therapy (NRT) is an effective medication to help patients quit smoking tobacco. Yet, 18% of adults in the United States still smoke cigarettes. With advancements in health technology and improved features within electronic health record (EHR) systems, it is crucial to understand how differences in EHR features influence the prescribing of NRT. We conducted a cross-sectional study of 174 primary care practices to better understand how EHR features, including drug reference databases in EHRs, were associated with NRT prescribing at a practice level. Regression models were created to understand NRT prescribing patterns among clinics with varying EHR features and found that practices using an EHR with a drug reference database were 2.3 times more likely to view NRT as a high priority for treating smokers. Use of NRT in primary care differs significantly in relation to the capability of a clinic’s technology. Clinics with more EHR features, specifically EHR drug reference databases, favored NRT. Our study suggests that pharmacotherapy could become the preferred activity in smoking cessation treatment, as EHR-integrated drug reference database prevalence increases

Share2Quit: Web-Based Peer-Driven Referrals for Smoking Cessation

BACKGROUND: Smoking is the number one preventable cause of death in the United States. Effective Web-assisted tobacco interventions are often underutilized and require new and innovative engagement approaches. Web-based peer-driven chain referrals successfully used outside health care have the potential for increasing the reach of Internet interventions. OBJECTIVE: The objective of our study was to describe the protocol for the development and testing of proactive Web-based chain-referral tools for increasing the access to Decide2Quit.org, a Web-assisted tobacco intervention system. METHODS: We will build and refine proactive chain-referral tools, including email and Facebook referrals. In addition, we will implement respondent-driven sampling (RDS), a controlled chain-referral sampling technique designed to remove inherent biases in chain referrals and obtain a representative sample. We will begin our chain referrals with an initial recruitment of former and current smokers as seeds (initial participants) who will be trained to refer current smokers from their social network using the developed tools. In turn, these newly referred smokers will also be provided the tools to refer other smokers from their social networks. We will model predictors of referral success using sample weights from the RDS to estimate the success of the system in the targeted population. RESULTS: This protocol describes the evaluation of proactive Web-based chain-referral tools, which can be used in tobacco interventions to increase the access to hard-to-reach populations, for promoting smoking cessation. CONCLUSIONS: Share2Quit represents an innovative advancement by capitalizing on naturally occurring technology trends to recruit smokers to Web-assisted tobacco interventions

Alcohol, Self-regulation, and Partner Physical Aggression: Actor-Partner Effects over a Three Year Time Frame

The question of how individual differences related to self-regulation interact with alcohol use patterns to predict intimate partner aggression (IPA) is examined. We hypothesized that excessive drinking will be related to partner aggression among those who have low self-regulation. In addition, we explored the extent to which differences in self-regulation in one partner may moderate the relationship between alcohol use and partner aggression. A sample of married or cohabitating community couples (N = 280) ages 18–45 was recruited according to their classification into four drinking groups: heavy drinking in both partners (n = 79), husband only (n = 80), wife only (n = 41), by neither (n = 80), and interviewed annually for 3 years. IPA, drinking, and scores on measures of negative affect, self-control, and Executive Cognitive Functioning (ECF) were assessed for both members of the couple. The Actor Partner Interdependence Model (APIM) was used to analyze longitudinal models predicting the occurrence of IPA from baseline alcohol use, negative affect, self-control and ECF. Actor self-control interacted with partner self-control such that IPA was most probable when both were low in self-control. Contrary to prediction, actors high in alcohol use and also high on self-control were more likely to engage in IPA. Partner alcohol use was predictive of actor IPA when the partner was also high in negative affect. Low partner ECF was associated with more actor IPA. These findings suggest that self-regulatory factors within both members of a couple can interact with alcohol use patterns to increase the risk for relationship aggression

Identification of Relationships Between Patients Through Elements in a Data Warehouse Using the Familial, Associational, and Incidental Relationship (FAIR) Initiative: A Pilot Study

BACKGROUND: Over the last several years there has been widespread development of medical data warehouses. Current data warehouses focus on individual cases, but lack the ability to identify family members that could be used for dyadic or familial research. Currently, the patient\u27s family history in the medical record is the only documentation we have to understand the health status and social habits of their family members. Identifying familial linkages in a phenotypic data warehouse can be valuable in cohort identification and in beginning to understand the interactions of diseases among families. OBJECTIVE: The goal of the Familial, Associational, and Incidental Relationships (FAIR) initiative is to identify an index set of patients\u27 relationships through elements in a data warehouse. METHODS: Using a test set of 500 children, we measured the sensitivity and specificity of available linkage algorithm identifiers (eg, insurance identification numbers and phone numbers) and validated this tool/algorithm through a manual chart audit. RESULTS: Of all the children, 52.4% (262/500) were male, and the mean age of the cohort was 8 years old (SD 5). Of the children, 51.6% (258/500) were identified as white in race. The identifiers used for FAIR were available for the majority of patients: insurance number (483/500, 96.6%), phone number (500/500, 100%), and address (497/500, 99.4%). When utilizing the FAIR tool and various combinations of identifiers, sensitivity ranged from 15.5% (62/401) to 83.8% (336/401), and specificity from 72% (71/99) to 100% (99/99). The preferred method was matching patients using insurance or phone number, which had a sensitivity of 72.1% (289/401) and a specificity of 94% (93/99). Using the Informatics for Integrating Biology and the Bedside (i2b2) warehouse infrastructure, we have now developed a Web app that facilitates FAIR for any index population. CONCLUSIONS: FAIR is a valuable research and clinical resource that extends the capabilities of existing data warehouses and lays the groundwork for family-based research. FAIR will expedite studies that would otherwise require registry or manual chart abstraction data sources

Familial, Associational, & Incidental Relationships (FAIR)

Identifying familial linkages in a phenotypic data warehouse can be valuable in cohort identification, and beginning to understand interactions of diseases among families. The goal of the Familial, Associational, & Incidental Relationships (FAIR) system is to identify an index set patients’ relationships through elements in a data warehouse. Using a test set of 500 children, we measured the sensitivity and specificity of available linkage algorithm (e.g.: insurance id and phone numbers) and validated this tool/algorithm through a manual chart audit. Sensitivity varied from 16% to 87%, and specificity from 70% to 100% using various combinations of identifiers. Using the “i2b2” warehouse infrastructure, we have now developed a web app that facilitates FAIR for any index population

Collective-Intelligence Recommender Systems: Advancing Computer Tailoring for Health Behavior Change Into the 21st Century

BACKGROUND: What is the next frontier for computer-tailored health communication (CTHC) research? In current CTHC systems, study designers who have expertise in behavioral theory and mapping theory into CTHC systems select the variables and develop the rules that specify how the content should be tailored, based on their knowledge of the targeted population, the literature, and health behavior theories. In collective-intelligence recommender systems (hereafter recommender systems) used by Web 2.0 companies (eg, Netflix and Amazon), machine learning algorithms combine user profiles and continuous feedback ratings of content (from themselves and other users) to empirically tailor content. Augmenting current theory-based CTHC with empirical recommender systems could be evaluated as the next frontier for CTHC. OBJECTIVE: The objective of our study was to uncover barriers and challenges to using recommender systems in health promotion. METHODS: We conducted a focused literature review, interviewed subject experts (n=8), and synthesized the results. RESULTS: We describe (1) limitations of current CTHC systems, (2) advantages of incorporating recommender systems to move CTHC forward, and (3) challenges to incorporating recommender systems into CTHC. Based on the evidence presented, we propose a future research agenda for CTHC systems. CONCLUSIONS: We promote discussion of ways to move CTHC into the 21st century by incorporation of recommender systems