Abstract. Ensemble filters implement sequential Bayesian estimation by representing the probability distribution by an ensemble mean and covariance. Unbiased square root ensemble filters use deterministic algorithms to produce an analysis (posterior) ensemble with a prescribed mean and covariance, consistent with the Kalman update. This includes several filters used in practice, such as the Ensemble Transform Kalman Filter (ETKF), the Ensemble Adjustment Kalman Filter (EAKF), and a filter by Whitaker and Hamill. We show that at every time index, as the number of ensemble members increases to infinity, the mean and covariance of an unbiased ensemble square root filter converge to those of the Kalman filter, in the case of a linear model and an initial distribution of which all moments exist. The convergence is in all L p , 1 ≤ p < ∞, and the convergence rate does not depend on the model or data dimensions. The result holds in infinitely dimensional Hilbert spaces as well.
Positive child health assessed using a quantitative PCHI was associated with QoL across the ELGAN cohort at school age. In the current study, the PCHI encompassed 11 outcomes assessed in ELGANs. Future research could include an enhanced panel of child health outcomes to support the use of PCHI as an indicator of positive child health.
Objective.To identify modifiable antecedents during pre-pregnancy and pregnancy windows associated with a positive child health at 10 years of age.Study design.Data on 889 children enrolled in the Extremely Low Gestational Age Newborn (ELGAN) study in 2002–2004 were analyzed for associations between potentially modifiable maternal antecedents during pre-pregnancy and pregnancy time windows and a previously described positive child health index (PCHI) score at 10 years of age. Stratification by race was also investigated for associations with investigated antecedents.Results.Factors associated with higher PCHI (more positive health) included greater gestational age, birth weight, multiple gestation, and medical interventions, including assisted reproduction, and cervical cerclage. Factors associated with lower PCHI included correlates of lower socioeconomic status, pre-pregnancy chronic medical disorders in the mother like pre-pregnancy BMI, maternal asthma. When stratified by race, variation in significant results was observed.Conclusions.Among children born extremely preterm, medical interventions and higher SES were associated with improved PCHI while chronic illness and high BMI in the mother is associated with lower PCHI at 10 years of age. Knowledge of such antecedent factors could inform efforts to develop interventions that promote positive child health outcomes in future pregnancies.
Rapid changes in the natural and social environments of the Arctic region have led to increased scientific presence across the Arctic. Simultaneously, the importance of involving local Indigenous peoples in research activities is increasingly recognized for several reasons, including knowledge sharing and sustainable development. This study explores Arctic early career researchers’ (ECRs) perceptions on involving local Indigenous peoples in their research. The results, based on 108 online survey respondents from 22 countries, show that ECRs value the knowledge of local Indigenous peoples and generally wish to extend the involvement of this group in their research. ECRs in North America and in the social sciences have more experience working with Indigenous communities and value it more than researchers in the Nordic area and in the natural sciences. Respondents cited more funding, networking opportunities, and time as the main needs for increasing collaborations. The results of this study are helpful for developing strategies to build good relationships between scientists and Indigenous peoples and for increasing the involvement of Arctic Indigenous peoples in science and engagement of their knowledge systems. The complementary views from Arctic Indigenous peoples are, however, needed for a full understanding of how to effectively achieve this.
INTRODUCTION: Research progress on neurocognitive disorders requires donation of both healthy and diseased brains. Here we describe attitudes towards brain donation among a large community sample in Florida. METHODS: HealthStreet, a community engagement program at the University of Florida, used Community Health Workers to assess community attitudes towards research participation, including brain donation. RESULTS: Over 60% of people, primarily Caucasian and employed, indicated that they would be likely or somewhat likely to donate their brain for research. Those who would be willing to donate were also more likely to be willing to participate in other research studies and to have participated in research. DISCUSSION: Brain donation will add to the science of disorders of aging, including accurate diagnoses and validation of in vivo biomarkers. Increasing willingness to donate is a first step toward donation. Community populations are willing; CHWs can educate others about the need for this initiative in communities.
BACKGROUND
Although drug use is common in the population, drug users are sometimes excluded from research without justification. Two models of individualized study matching were compared for effectiveness in enrolling people who “endorsed current drug use” and those who “did not” into appropriate research.
METHODS
Participants in the NIDA-funded Transformative Approach to Reduce Research Disparities Towards Drug Users study (Navigation Study) were recruited through a Clinical and Translational Science Award (CTSA) community engagement model. Of the 614 community-recruited adults, 326 endorsed current drug use (cases); 288 did not (controls). Participants were randomized to one of two intervention groups: Navigation as Usual (NAU) [individualized study matching through a Study Navigator] or Enhanced Navigation (N+) [individualized study matching plus transportation and other assistance through an Ambassador]. Rates of enrollment into research studies were compared.
RESULTS
At 90 days, N+ vs. the NAU intervention was associated with higher enrollment among both drug users (36.0% N+ vs. 24.9% NAU) and non-drug users (45.5% N+ vs. 25.2% NAU). NAU attained the same rate of enrollment for users of drugs (24.9%) and non-users (25.2%); N+ had similar rates as well (36.0% drug users vs. 45.5% non-drug users). In addition, high rates of enrollment were achieved among all groups of participants, from 24.9% (drug users in NAU) to 45.5% (non-drug users in N+).
CONCLUSIONS
Both the NAU and N+ methods can reduce barriers and help users and non-users become part of the population that participates in research. Working with the local CTSA adds significant value to the research enterprise.
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