Shared Medical Appointments: An Academic-Community Partnership to Improve Care Among Adults With Type 2 Diabetes in California Central Valley Region.

PurposeThe purpose of the study was to evaluate the effectiveness of ALDEA (Latinos con Diabetes en Acción), a Shared Medical Appointment (SMA) intervention, compared to usual primary care (UPC) for the treatment of adults with type 2 diabetes over a 6-month period. It was hypothesized that participants in the SMA will have greater reductions in A1C at 6 months post-intervention compared to the control group.MethodsThis study was a quasi-experimental design with a non-randomized matched control group that followed participants prospectively for 6 months. All adults living with type-2 diabetes receiving primary care at a 2 FQHC clinics were eligible for inclusion. Participants in the control group were matched retrospectively on baseline A1C and age.ResultsThe reductions in A1C were greater in the ALDEA SMA intervention group relative to the UPC control group at 6 months in both of the FQHC centers and in the combined sample.ConclusionsThis study demonstrated that patients in the ALDEA program had a significantly greater reduction in A1C at 6 months compared to the control group. Despite its limitations, the ALDEA SMA program was successful in empowering patients and improving glycemic control

Diagnosis Measurement Error and Corrected Instrumental Variables

Health diagnosis indicators used as explanatory variables in econometric models often suffer from substantial measurement error. This measurement error can lead to seriously biased inferences about the effects of health conditions on the outcome measure of interest, and the bias generally spills over into inferences about the effects of policy/treatment variables. We generalize an existing instrumental variables (IV) method to make it compatible with the types of instruments typically available in large datasets containing health diagnoses. In particular, we relax the classical IV assumption that the instruments must have uncorrelated measurement errors. We identify and estimate the covariance matrix of the measurement errors and then use this information to derive a correction term to mitigate or eliminate the bias associated with classical IV. Our Monte Carlo simulations suggest that this corrected IV method can produce estimates far superior to those produced by OLS or classical IV.

The effect of diet on midgut and resulting changes in infectiousness of AcMNPV baculovirus in Trichoplusia ni

The cabbage looper, Trichoplusia ni, a global generalist lepidopteran pest, has developed resistance to many synthetic and biological insecticides, requiring effective and environmentally acceptable alternatives. One possibility is the Autographa californica multicapsid nucleopolyhedrovirus (AcMNPV). This baculovirus is highly infectious for T. ni, with potential as a biocontrol agent, however, its effectiveness is strongly influenced by dietary context. In this study, microscopy and transcriptomics were used to examine how the efficacy of this virus was affected when T. ni larvae were raised on different diets. Larvae raised on potato host plants had lower chitinase and chitin deacetylase transcript levels and thickened, multilayered peritrophic membranes than those reared on either cabbage or artificial diet. These changes help explain the significantly lower susceptibility of potato reared individuals to baculovirus, underlining the importance of considering the dietary influences on insect susceptibility to pathogens when applying biological control agents in integrated pest management strategies

Lessons from Hybridity: A Look into the Coupling of Image and Text in Karen Tei Yamashita’s \u3cem\u3eLetters to Memory\u3c/em\u3e, Claudia Rankine’s \u3cem\u3eCitizen: An American Lyric\u3c/em\u3e, and Ilya Kaminsky’s \u3cem\u3eDeaf Republic\u3c/em\u3e

The spoken and written word has always been a platform for voices to be heard, but being heard is not always enough. This thesis focuses on the use of hybrid forms in recent publications that address this issue, placing images alongside the written word, letting readers also personally visualize and interpret a perspective different from their own. Specifically, it will look into three examples of hybrid literary works: the placement of photographs beside epistolary writing in Karen Tei Yamashita‘s Letters to Memory (2017), the blend of visual art and lyric prose poetryfound in Citizen: An American Lyric(2014) by Claudia Rankine, and the instructional sign language placed beside the poems in Deaf Republic(2019) by Ilya Kaminsky. I argue that these contemporary writers use the hybrid format to move beyond being ―heard,‖ in their attempt to ―teach‖ its audience about underrepresented realities in a way which reminds us of how illustrations help children understand and imagine stories before their transition to imageless texts.In looking at these three works, new possibilities for understanding the marginalized come to being, shedding light onto the importance and immediacy of the subject matter. While these three works each emerge from distinctively different backgrounds,I place them in conversation with one another to demonstrate different ways in which their words unfold the spectacle beside the existence of the spectator

Online Updating of Statistical Inference in the Big Data Setting

We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models and estimating equations that update as new data arrive. These algorithms are computationally efficient, minimally storage-intensive, and allow for possible rank deficiencies in the subset design matrices due to rare-event covariates. Within the linear model setting, the proposed online-updating framework leads to predictive residual tests that can be used to assess the goodness-of-fit of the hypothesized model. We also propose a new online-updating estimator under the estimating equation setting. Theoretical properties of the goodness-of-fit tests and proposed estimators are examined in detail. In simulation studies and real data applications, our estimator compares favorably with competing approaches under the estimating equation setting.Comment: Submitted to Technometric