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OBJECTIVES: To understand the postmortem decision-making needs and preferences of parents of a stillborn. METHODS: A qualitative content analysis was conducted. Patients who received stillbirth care at the University of Utah in the last 5 years, were 18 years of age or older, and English speakers, were invited to participate via an email and follow-up phone call. Participants were interviewed about their experiences, values, beliefs, decision-making experience regarding the postmortem examinations of their stillborn, and suggestions for how to assist their decision-making needs. RESULTS: Nineteen participants who consented to one or more postmortem examination of their stillborn were interviewed. They expressed needing information, altruism, and/or a belief in science as reasons for consenting. The most common reason for declining was already knowing the stillbirth cause. Recommendations for a decision aid included a description of all stillbirth evaluation options, risks and benefits, and a timeline. CONCLUSION: Participants had a variety of reasons for consenting to or declining postmortem examinations of their stillborn. Recommendations for a decision aid include a full description of each examination, the risks and benefits, and a timeline. PRACTICAL IMPLICATIONS: An example decision aid was created from recommendations, which presents balanced information to help support couple's decision-making.
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Padres , Mortinato , Embarazo , Femenino , Humanos , Adolescente , Adulto , Autopsia , Técnicas de Apoyo para la DecisiónRESUMEN
BACKGROUND: Environmental exposures are implicated in diabetes etiology, but are poorly understood due to disease heterogeneity, complexity of exposures, and analytical challenges. Machine learning and data mining are artificial intelligence methods that can address these limitations. Despite their increasing adoption in etiology and prediction of diabetes research, the types of methods and exposures analyzed have not been thoroughly reviewed. OBJECTIVE: We aimed to review articles that implemented machine learning and data mining methods to understand environmental exposures in diabetes etiology and disease prediction. METHODS: We queried PubMed and Scopus databases for machine learning and data mining studies that used environmental exposures to understand diabetes etiology on September 19th, 2022. Exposures were classified into specific external, general external, or internal exposures. We reviewed machine learning and data mining methods and characterized the scope of environmental exposures studied in the etiology of general diabetes, type 1 diabetes, type 2 diabetes, and other types of diabetes. RESULTS: We identified 44 articles for inclusion. Specific external exposures were the most common exposures studied, and supervised models were the most common methods used. Well-established specific external exposures of low physical activity, high cholesterol, and high triglycerides were predictive of general diabetes, type 2 diabetes, and prediabetes, while novel metabolic and gut microbiome biomarkers were implicated in type 1 diabetes. DISCUSSION: The use of machine learning and data mining methods to elucidate environmental triggers of diabetes was largely limited to well-established risk factors identified using easily explainable and interpretable models. Future studies should seek to leverage machine learning and data mining to explore the temporality and co-occurrence of multiple exposures and further evaluate the role of general external and internal exposures in diabetes etiology.
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Diabetes Mellitus Tipo 1 , Diabetes Mellitus Tipo 2 , Humanos , Inteligencia Artificial , Diabetes Mellitus Tipo 2/epidemiología , Diabetes Mellitus Tipo 2/etiología , Aprendizaje Automático , Minería de Datos/métodos , Exposición a Riesgos Ambientales/efectos adversosRESUMEN
INTRODUCTION: Rapid advances in prenatal genetic screening technology make it difficult for providers to deliver adequate prenatal counseling. The aim of this study was to understand how prenatal screening educational approaches can meet the needs of patients. METHODS: Qualitative content analysis was conducted on a diverse population who were interviewed to explore their perceived experiences and preferences for prenatal screening educational delivery. RESULTS: Twenty-two women from three US sites were interviewed. Participants were racially/ethnically diverse with 22.7% identifying as Black or African American (n = 5), 40.9% as Hispanic (n = 9), and 4.5% as Pacific Islander (n = 1). Four themes were identified: prenatal screening education, prenatal screening decision-making, return of results, and suggestions for creating a decision aid. Most results were consistent with previous research not targeting a diverse population. DISCUSSION/CONCLUSION: Our results indicate that learning style preferences vary between patients and that current methods are not consistently satisfying patient's desire for understanding, particularly with 'high-risk' results, suggesting that a standardized tool could improve knowledge and decrease decisional conflict. This diverse cohort suggested a list and description of each of the testing options offered, information about each condition being screened for, a timeline for the testing and return of results, costs associated, and non-technical language.
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Pruebas Genéticas , Diagnóstico Prenatal , Femenino , Humanos , Embarazo , Hispánicos o Latinos , Diagnóstico Prenatal/métodos , Nativos de Hawái y Otras Islas del Pacífico , Negro o AfroamericanoRESUMEN
Informed consent is crucial for participant understanding, engagement, and partnering for research. However, current written informed consents have significant limitations, particularly for complex topics such as genomics and biobanking. Our goal was to identify how participants visually conceptualize terminology used in genomics and biobanking research studies, which might provide a novel approach for informed consent. An online convenience sample was used from May to July 2020 to collect data. Participants were asked to draw 10 randomly chosen words out of 32 possible words commonly used in consent forms for genomics and biobanking research. An electronic application captured drawings that were downloaded into a qualitative software program for analysis. A total of 739 drawings by 269 participants were captured. Participants were mostly female (61.3%), eight different race/ethnicities were represented (15.6% Black, 13.8% Hispanic), and most had some college education (68.8%). Some words had consistent visual themes such as different types of risky activities for risk or consistent specific images such as a double helix for DNA. Several words were frequently misunderstood (e.g., ascend for assent), while others returned few submissions (e.g., phenotype or whole genome sequencing). We found that although some words used in genomics and biobanking research were visually conceptualized in a common fashion, but misunderstood or less well-known words had no, few, or mistaken drawings. Future research can explore the incorporation of visual images to improve participant comprehension during consent processes, and how to utilize visual imagery to address more challenging concepts.
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Natural hazards (NHs) associated with climate change have been increasing in frequency and intensity. These acute events impact humans both directly and through their effects on social and environmental determinants of health. Rather than relying on a fully reactive incident response disposition, it is crucial to ramp up preparedness initiatives for worsening case scenarios. In this perspective, we review the landscape of NH effects for human health and explore the potential of health informatics to address associated challenges, specifically from a preparedness angle. We outline important components in a health informatics agenda for hazard preparedness involving hazard-disease associations, social determinants of health, and hazard forecasting models, and call for novel methods to integrate them toward projecting healthcare needs in the wake of a hazard. We describe potential gaps and barriers in implementing these components and propose some high-level ideas to address them.
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Cambio Climático , Informática , Humanos , PredicciónRESUMEN
The characteristics of a person's health status are often guided by how they live, grow, learn, their genetics, as well as their access to health care. Yet, all too often, studies examining the relationship between social determinants of health (behavioral, sociocultural, and physical environmental factors), the role of demographics, and health outcomes poorly represent these relationships, leading to misinterpretations, limited study reproducibility, and datasets with limited representativeness and secondary research use capacity. This is a profound hurdle in what questions can or cannot be rigorously studied about COVID-19. In practice, gene-environment interactions studies have paved the way for including these factors into research. Similarly, our understanding of social determinants of health continues to expand with diverse data collection modalities as health systems, patients, and community health engagement aim to fill the knowledge gaps toward promoting health and wellness. Here, a conceptual framework is proposed, adapted from the population health framework, socioecological model, and causal modeling in gene-environment interaction studies to integrate the core constructs from each domain with practical considerations needed for multidisciplinary science.
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BACKGROUND: There is a need to evaluate how the choice of time interval contributes to the lack of consistency of SDoH variables that appear as important to COVID-19 disease burden within an analysis for both case counts and death counts. METHODS: This study identified SDoH variables associated with U.S county-level COVID-19 cumulative case and death incidence for six different periods: the first 30, 60, 90, 120, 150, and 180 days since each county had COVID-19 one case per 10,000 residents. The set of SDoH variables were in the following domains: resource deprivation, access to care/health resources, population characteristics, traveling behavior, vulnerable populations, and health status. A generalized variance inflation factor (GVIF) analysis was used to identify variables with high multicollinearity. For each dependent variable, a separate model was built for each of the time periods. We used a mixed-effect generalized linear modeling of counts normalized per 100,000 population using negative binomial regression. We performed a Kolmogorov-Smirnov goodness of fit test, an outlier test, and a dispersion test for each model. Sensitivity analysis included altering the county start date to the day each county reached 10 COVID-19 cases per 10,000. RESULTS: Ninety-seven percent (3059/3140) of the counties were represented in the final analysis. Six features proved important for both the main and sensitivity analysis: adults-with-college-degree, days-sheltering-in-place-at-start, prior-seven-day-median-time-home, percent-black, percent-foreign-born, over-65-years-of-age, black-white-segregation, and days-since-pandemic-start. These variables belonged to the following categories: COVID-19 related, vulnerable populations, and population characteristics. Our diagnostic results show that across our outcomes, the models of the shorter time periods (30 days, 60 days, and 900 days) have a better fit. CONCLUSION: Our findings demonstrate that the set of SDoH features that are significant for COVID-19 outcomes varies based on the time from the start date of the pandemic and when COVID-19 was present in a county. These results could assist researchers with variable selection and inform decision makers when creating public health policy.
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COVID-19 , Segregación Social , Adulto , COVID-19/epidemiología , Humanos , Políticas , SARS-CoV-2 , Determinantes Sociales de la Salud , Estados Unidos/epidemiologíaRESUMEN
Air pollution (AP) has been shown to increase the risk of type 2 diabetes mellitus, as well as other cardiometabolic diseases. AP is characterized by a complex mixture of components for which the composition depends on sources and metrological factors. The US Environmental Protection Agency (EPA) monitors and regulates certain components of air pollution known to have negative consequences for human health. Research assessing the health effects of these components of AP often uses traditional regression models, which might not capture more complex and interdependent relationships. Machine learning has the capability to simultaneously assess multiple components and find complex, non-linear patterns that may not be apparent and could not be modeled by other techniques. Here we use k-means clustering to assess the patterns associating PM2.5, PM10, CO, NO2, O3, and SO2 measurements and changes in annual diabetes incidence at a US county level. The average age adjusted annual decrease in diabetes incidence for the entire US populations is -0.25 per 1000 but the change shows a significant geographic variation (range: -17.2 to 5.30 per 1000). In this paper these variations were compared with the local daily AP concentrations of the pollutants listed above from 2005 to 2015, which were matched to the annual change in diabetes incidence for the following year. A total of 134,925 daily air quality observations were included in the cluster analysis, representing 125 US counties and the District of Columbia. K-means successfully clustered AP components and indicated an association between exposure to certain AP mixtures with lower decreases on T2D incidence.
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Contaminantes Atmosféricos , Contaminación del Aire , Diabetes Mellitus Tipo 2 , Contaminantes Atmosféricos/análisis , Contaminantes Atmosféricos/toxicidad , Contaminación del Aire/análisis , Análisis por Conglomerados , Diabetes Mellitus Tipo 2/inducido químicamente , Diabetes Mellitus Tipo 2/epidemiología , Exposición a Riesgos Ambientales/análisis , Humanos , Incidencia , Dióxido de Nitrógeno/análisis , Material Particulado/análisis , Material Particulado/toxicidadRESUMEN
PURPOSE: State-run newborn screening programs screen nearly all babies born in the United States at the time of delivery. After newborn screening has been completed, some states store the residual dried bloodspots. It is unknown how they have been used to address health disparities-related research. METHODS: In 2017-2018, a scoping review was conducted to evaluate the extent, type, and nature of how residual dried bloodspots. The review included 654 eligible publications, worldwide, published before May 2017. A post hoc analysis of the US-based studies using residual dried bloodspots (n = 192) were analyzed. RESULTS: There were 32 (16.7%) articles identified that studied a condition of a known health disparity or focused on a key population: 25 studies assessed a disease or condition, 6 expressly enrolled a key population, and 1 study included both (i.e., heart disease and African American/Black). CONCLUSION: Excluding 12 studies that researched leukemia or a brain tumor, only 20 studies addressed a known health disparity, with 6 stating a specific aim to address a health disparity. This resource could be used to gain further knowledge about health disparities, but is currently underutilized.
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Negro o Afroamericano , Tamizaje Neonatal , Humanos , Recién Nacido , Estados UnidosRESUMEN
OBJECTIVE: Decision-making and patient experiences with embryo selection during in vitro fertilization often include genetic testing options. The purpose of this study was to gain insight about the experiences and perspectives of women using in vitro fertilization and genetic technologies. METHODS: Interviews (n = 37) were conducted among female patients who had undergone in vitro fertilization, underwent expanded carrier screening, and were offered pre-implantation genetic testing for aneuploidy between July 2016 and July 2017. The interviews were transcribed and a content analysis was conducted on the transcripts. RESULTS: Categories that emerged from the data analysis included unexpected outcomes, uncertainty, unanticipated emotional consequences, too much emphasis on the woman's contributions and questions about embryo viability. Patient experiences with genetic technologies during in vitro fertilization played a significant role within these results. CONCLUSION: The emotional and psychological impacts of infertility during in vitro fertilization were the primary concerns discussed by participants. Future research is needed to identify ways to help manage unexpected outcomes and continuous uncertainty, including the increasing use of genetic technologies, to not add to the psychological burden of infertility. There is a need to explore more support options or counseling services for patients struggling with infertility during in vitro fertilization treatment.
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Obtaining informed consent for bloodspot research from newborn screening is particularly challenging due to the hectic environment of the postnatal period and the relatively abstract nature of future, unspecified research on the biospecimens. A randomized controlled trial was conducted in three Michigan hospitals to compare two different consent processes (video and interactive tablet "app") with standard brochure-based consent in the Michigan BioTrust for Health. Results indicated higher knowledge scores for the video and app groups as well as significantly higher scores on satisfaction, amount of information, and clarity with the information provided. More research is needed to find the right amount of information for informed decision-making, and additional feasibility studies are needed to assess implementation strategies.
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Aplicaciones Móviles , Humanos , Recién Nacido , Consentimiento Informado , Michigan , MultimediaRESUMEN
PURPOSE: Residual newborn screening dried bloodspots (DBS) are a valuable resource for research but the extent, type, and nature of uses are unknown. The objective of this research was to systematically review the published literature about secondary research uses of residual DBS using a scoping review protocol. METHODS: A total of 654 publications meeting the inclusion criteria with a 94% interrater reliability were identified. A coding template was created with input from expert advisory board to summarize the data. Electronic literature search of Ovid MEDLINE, Embase (via Embase.com), CINAHL (EBSCO),and Science and Social Sciences Citation Indices (via Web of Science) was conducted. RESULTS: A large proportion of the secondary research with DBS was conducted within the United States (30%). The number of published studies utilizing DBS are increasing each year, primarily with observational or case-control designs. Only a small number of studies reported whether or not consent was obtained and if the DBS were identifiable or not. CONCLUSION: Outcomes of this research indicate that residual DBS are well utilized worldwide for research addressing individual and public health issues. Future analyses will summarize outcomes of disease-specific research and provide evidence of the use of residual DBS in research on health outcomes.
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Investigación Biomédica , Pruebas con Sangre Seca , Investigación Biomédica/tendencias , Humanos , Recién Nacido , Reproducibilidad de los ResultadosRESUMEN
PURPOSE: Embryo testing to improve pregnancy outcomes among individuals who are seeking assisted reproduction technologies is increasing. The purpose of this study was to assess decisional factors through in-depth interviews for why women would accept or decline preimplantation genetic testing for aneuploidy (PGT-A) with in vitro fertilization (IVF). METHODS: Semi-structured telephone interviews were conducted with 37 women who were offered PGT-A with IVF during the summer 2017. Interviews lasted on average 40 min and were audio-recorded, transcribed, and analyzed using a content analysis. RESULTS: Results identified a number of decisional factors related to values about conception, disability, and pregnancy termination, past pregnancy experiences, optimism toward technology, and cost. Other key issues that were identified include the use of expanded carrier screening prior to IVF, maternal age, and limited education about PGT-A due to the complexity about education for IVF alone. CONCLUSION: There is a need to develop decision support tools for the increasing choices of genetic testing options for patients seeking IVF. Including patients' values, past pregnancy experiences and attitudes toward science into the decision-making process may help promote a more informed decision.
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Fertilización In Vitro/tendencias , Pruebas Genéticas/métodos , Diagnóstico Preimplantación/métodos , Técnicas Reproductivas Asistidas/tendencias , Aneuploidia , Toma de Decisiones , Implantación del Embrión/genética , Femenino , Humanos , Edad Materna , Embarazo , Resultado del EmbarazoRESUMEN
As state newborn screening programs develop approaches to parental permission for the storage and use of residual dried newborn screening samples, it is important to understand how the public comprehends the consent elements. Focus groups in Utah, California, and Michigan ( n = 7 groups, 69 participants) were conducted to evaluate the language on a shortened consent form. Outcomes from the analysis included barriers to conceptualizing biospecimen research, the overly cautious tone and awkwardness of the consent form, and perceptions of community versus individual benefit. This research offers insight on public response to, and comprehension of, commonly used consent language for the storage and use of dried blood spot research in a shortened consent form.
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Actitud Frente a la Salud , Bancos de Muestras Biológicas , Comprensión , Formularios de Consentimiento , Lenguaje , Tamizaje Neonatal , Consentimiento Paterno , Sangre , California , Femenino , Grupos Focales , Humanos , Recién Nacido , Masculino , Michigan , Padres , Investigación , UtahRESUMEN
BACKGROUND AND PURPOSE: Carotid intima-media thickness (IMT), a valid measure of atherosclerotic disease, has been proposed to be included in the algorithms for cardiovascular risk stratification. However, assessment of carotid IMT is still not easily performed in an office setting. In the present study, we evaluated the reproducibility of a standardized protocol for carotid artery atherosclerosis screening. METHODS: Carotid arteries of 30 patients were scanned twice (interval 1-10 days) by six trained sonographers, using portable ultrasound systems. A screening protocol was adapted from methods used in clinical trials in which carotid IMT was the primary outcome measure. To test the reproducibility of the method, variability between the two scans was analyzed. RESULTS: A high level of agreement was found between the scans for measurement of mean common carotid IMT [mean difference S0.002, 95% confidence interval (CI) S0.011 to 0.006, PU0.435], maximum region common carotid IMT (mean difference S0.002, 95% CIS0.017 to 0.014, PU0.779) and mean maximum IMT including the common, bifurcation and internal carotid arteries (mean differences 0.021, 95% CI S0.006 to 0.047, PU0.166). No significant differences were found between scans with regard to the average number of carotid segments visualized, the number of atherosclerotic plaques or plaque burden. CONCLUSION: Reliable IMT measurements can be obtained using a standardized protocol performed by trained sonographers using a digital portable ultrasound system in an office setting.