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In this article, we present an extension of the formulation recently developed by the authors to the structural dynamics setting. Inspired by a structure‐preserving family of variational integrators, our new formulation relies on a discrete balance equation that establishes the dynamic equilibrium. From this point of departure, we first derive an ""exact"" discrete‐continuous nonlinear optimization problem that works directly with data sets. We then develop this formulation further into an ""approximate"" nonlinear optimization problem that relies on a general constitutive model. This underlying model can be identified from a data set in an offline phase. To showcase the advantages of our framework, we specialize our methodology to the case of a geometrically exact beam formulation that makes use of all elements of our approach. We investigate three numerical examples of increasing difficulty that demonstrate the excellent computational behavior of the proposed framework and motivate future research in this direction.

ObjectivePatients with limited health literacy (LHL) and limited English proficiency (LEP) experience suboptimal communication and health outcomes. Electronic health record implementation in safety net clinics may affect communication with LHL and LEP patients.We investigated the associations between safety net clinician computer use and patient-provider communication for patients with LEP and LHL.Materials and methodsWe video-recorded encounters at 5 academically affiliated US public hospital clinics between English- and Spanish-speaking patients with chronic conditions and their primary and specialty care clinicians. We analyzed changes in communication behaviors (coded with the Roter Interaction Analysis System) with each additional point on a clinician computer use score, controlling for clinician type and visit length and stratified by English proficiency and health literacy status.ResultsGreater clinician computer use was associated with more biomedical statements (+12.4, P = .03) and less positive affect (-0.6, P

© 2016 Garg et al. Background: Text messaging is an affordable, ubiquitous, and expanding mobile communication technology. However, safety net health systems in the United States that provide more care to uninsured and low-income patients may face additional financial and infrastructural challenges in utilizing this technology. Formative evaluations of texting implementation experiences are limited. We interviewed safety net health systems piloting texting initiatives to study facilitators and barriers to real-world implementation. Methods: We conducted telephone interviews with various stakeholders who volunteered from each of the eight California-based safety net systems that received external funding to pilot a texting-based program of their choosing to serve a primary care need. We developed a semi-structured interview guide based partly on the Consolidated Framework for Implementation Research (CFIR), which encompasses several domains: The intervention, individuals involved, contextual factors, and implementation process. We inductively and deductively (using CFIR) coded transcripts, and categorized themes into facilitators and barriers. Results: We performed eight interviews (one interview per pilot site). Five sites had no prior texting experience. Sites applied texting for programs related to medication adherence and monitoring, appointment reminders, care coordination, and health education and promotion. No site texted patient-identifying health information, and most sites manually obtained informed consent from each participating patient. Facilitators of implementation included perceived enthusiasm from patients, staff and management belief that texting is patient-centered, and the early identification of potential barriers through peer collaboration among grantees. Navigating government regulations that protect patient privacy and guide the handling of protected health information emerged as a crucial barrier. A related technical challenge in five sites was the labor-intensive tracking and documenting of texting communications due to an inability to integrate texting platforms with electronic health records. Conclusions: Despite enthusiasm for the texting programs from the involved individuals and organizations, inadequate data management capabilities and unclear privacy and security regulations for mobile health technology slowed the initial implementation and limited the clinical use of texting in the safety net and scope of pilots. Future implementation work and research should investigate how different texting platform and intervention designs affect efficacy, as well as explore issues that may affect sustainability and the scalability.

OBJECTIVE - Food insecurity is hypothesized to make diabetes self-management more difficult. We conducted a longitudinal assessment of food insecurity with several diabetes self-care measures. RESEARCH DESIGN AND METHODS - We conducted a secondary, observational analysis of 665 low-income patients with diabetes, all of whom received self-management support as part of a larger diabetes educational intervention. We analyzed baseline food insecurity (measured by the U.S. Department of Agriculture Food Security module) in relation to changes in hemoglobin A1c(HbA1c) as well as self-reported diabetes self-efficacy and daily fruit and vegetable intake. We examined longitudinal differences using generalized estimating equation linear regression models, controlling for time, age, sex, race, income, and intervention arm. RESULTS - Overall, 57% of the sample had an income

A probabilistic model of bone structure in the trabecular region of the femur head is constructed. In a first step, a probabilistic model for the bone density based on computed tomography (CT) scan data is developed. The data consist of a number of cubes cut from fresh-frozen bones belonging to three different patients. The model accounts for the spatial variability of the bone structure as well as the correlation between samples (inter-sample correlation). Based on the statistical analysis of the data, a homogeneous Gaussian field with separable autocorrelation coefficient function is developed for modeling the bone structure. The Finite Cell Method (FCM) is used for estimation of the mechanical properties of the bone. This method has shown advantages in terms of efficiency and accuracy compared to the classical finite element method for this type of applications. Monte Carlo samples of the mechanical properties of the bone are simulated based on the probabilistic model of the bone density. For each realization of the random field, density values at each location are obtained and further mapped to material values through empirical relationships. Furthermore, the homogenized material properties are computed using the FCM assuming an isotropic material. The sample elasticity moduli are compared with the ones obtained experimentally from laboratory tests in order to validate the applicability of the material models at different scales.

OBJECTIVE: To examine measures of need for health care and their relationship to utilization of health services in different racial and ethnic groups in California. DATA SOURCE: Telephone interviews obtained by random-digit dialing and conducted between April 1993 and July 1993 in California, with 7,264 adults (ages 18-64): 601 African Americans, 246 Asians, 917 Latinos interviewed in English; 1,045 Latinos interviewed in Spanish; and 4,437 non-Latino whites. STUDY DESIGN: A cross-sectional survey was conducted from a stratified, probability telephone sample. DATA COLLECTION: Interviews collected self-reported indicators of need for health care: self-rated health, activity limitation, major chronic conditions, need for ongoing treatment, bed days, and prescription medication. The outcome was self-reported number of physician visits in the previous three months. PRINCIPAL FINDINGS: Compared to whites, one or more of the other ethnic groups varied significantly (p < .05) on each of the six need-for-care measures after adjustment for health insurance, age, sex, and income. Latinos interviewed in Spanish reported lower percentages and means on five of the need measures but the highest percentage with fair or poor health (32 percent versus 7 percent in whites). Models regressing each need measure on the number of outpatient visits found significant interactions of ethnic group with need compared to whites. After adjustment for insurance and demographics, the estimated mean number of visits in those with the indicator of need was consistently lower in Latinos interviewed in Spanish, but the differences among the other ethnic groups varied depending on the measure used. CONCLUSION: No single valid estimate of the relationship between need for health care and outpatient visits was found for any of the six indicators across ethnic groups. Applying need adjustment to the use of health care services without regard for ethnic variability may lead to biased conclusions about utilization.