As children learn to read they become sensitive to context-dependent vowel pronunciations in words, considered a form of statistical learning. The work of Treiman and colleagues demonstrated that readers’ vowel pronunciations depend on the consonantal context in which the vowel occurs and reading experience. We examined child- and nonword-factors associated with children’s assignment of more vs. less frequent grapheme-phoneme correspondences (GPC) to vowel pronunciations as a function of rime coda in monosyllabic nonwords. Students (N=96) in grades 2–5 read nonwords in which more vs. less frequent vowel GPCs were wholly supported or partially favored by the rime unit. Two explanatory item-response models were developed using alternative nonword scoring procedures. Use of less frequent vowel GPCs was predicted by set for variability, word reading, and rime support for the context-dependent vowel pronunciation. We interpret the results within a developmental word reading model in which initially incomplete and oversimplified GPC representations become more context-dependent with reading experience.
Although evidence suggests that successive climate disasters are on the rise, few studies have documented the disproportionate impacts on communities of color. Through the unique lens of successive disaster events (Hurricane Harvey and Winter Storm Uri) coupled with the COVID-19 pandemic, we assessed disaster exposure in minority communities in Harris County, Texas. A mixed methods approach employing qualitative and quantitative designs was used to examine the relationships between successive disasters (and the role of climate change), population geography, race, and health disparities-related outcomes. This study identified four communities in the greater Houston area with predominantly non-Hispanic African American residents. We used data chronicling the local community and environment to build base maps and conducted spatial analyses using Geographic Information System (GIS) mapping. We complemented these data with focus groups to assess participants’ experiences in disaster planning and recovery, as well as community resilience. Thematic analysis was used to identify key patterns. Across all four communities, we observed significant Hurricane Harvey flooding and significantly greater exposure to 10 of the 11 COVID-19 risk factors examined, compared to the rest of the county. Spatial analyses reveal higher disease burden, greater social vulnerability, and significantly higher community-level risk factors for both pandemics and disaster events in the four communities, compared to all other communities in Harris County. Two themes emerged from thematic data analysis: (1) Prior disaster exposure prepared minority populations in Harris County to better handle subsequent disaster suggesting enhanced disaster resilience, and (2) social connectedness was key to disaster resiliency. Long-standing disparities make people of color at greater risk for social vulnerability. Addressing climate change offers the potential to alleviate these health disparities.
Background: The past year has severely curtailed social interactions among older adults given their high rates of COVID-19 morbidity and mortality. This study examined social, behavioral, and medical correlates of social isolation among community-dwelling older adults during the COVID-19 pandemic and stratified findings to explore unique differences in two typically neglected populations, African American and Hispanic older adults.Methods: Working with community-based organizations and senior living centers, the research team administered a survey to older adults 55 years of age and older (n = 575). The survey assessed COVID-19 prevention behaviors, medical conditions, and lived experiences, including feelings of social isolation, in the target population. Responses to a previously validated social isolation question informed a dichotomous social isolation dependent variable. Multivariable logistic regression was used to adjust for sociodemographic characteristics, medical conditions, unmet caregiving needs, and COVID-19 prevention behaviors. Results from the regression model were stratified by race/ethnicity to examine correlates of social isolation in African American and Hispanic older adults, separately.Results: Overall, female sex and a higher level of education were also positively associated with social isolation (OR = 2.46, p = 0.04; OR = 5.49, p = 0.02) while having insurance exhibited an inverse relationship (OR = 0.25, p = 0.03). Unmet caregiving needs were strongly associated with social isolation (OR = 6.41, p < 0.001) as was having any chronic conditions (OR = 2.99, p = 0.02). Diabetes was the single strongest chronic condition predictor of social isolation. Among minority older adults, a different pattern emerged. For Hispanic older adults, language, unmet caregiving needs, and social distancing were strongly associated with social isolation; while unmet caregiving needs, having 1+ chronic conditions and adhering to social distancing guidelines were significant predictors in African American older adults.Conclusion: These findings suggest that social isolation affects older adults in a myriad of ways and support the need for culturally sensitive initiatives to mitigate the effect of social isolation in these vulnerable populations.
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