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The shortage of secondary STEM teachers has led to periodic calls over the past four decades for federal intervention. For more than 15 years, the National Science Foundation Robert Noyce Teacher Scholarship Program has constituted the most important response at the national level to these calls. The main activity is direct support to undergraduate students and degree holders to become K-12 STEM teachers. Here we examine the Noyce program by looking beyond the qualities of particular university programs and measuring long-term outcomes on a statewide level. We accomplished this through a collaboration of eight Texas universities that pooled data on Noyce scholars supported as far back as 2003. Making use of a state longitudinal dataset, we examined whether recipients of Noyce Scholarships are more likely than other math and science teachers to remain in teaching, determined where Noyce scholars taught, and estimated student learning in classes taught by Noyce Scholars. Noyce Scholars are more likely than other STEM teachers from the same universities to teach marginalized students, and students of Noyce Scholars obtained higher value-added scores in mathematics than students of other teachers at the same schools. These are some of the most important intended outcomes. However, Noyce Scholars did not stay in teaching as long as other STEM teachers from their universities, and they were more likely to switch away from schools with low-income students. The Noyce program currently operates far below the scale needed to start reducing national STEM teacher shortages. We conclude with prospects for expansion and modification of the Noyce program.

ObjectivesClinical artificial intelligence and machine learning (ML) face barriers related to implementation and trust. There have been few prospective opportunities to evaluate these concerns. System for High Intensity EvaLuation During Radiotherapy (NCT03775265) was a randomised controlled study demonstrating that ML accurately directed clinical evaluations to reduce acute care during cancer radiotherapy. We characterised subsequent perceptions and barriers to implementation.MethodsAn anonymous 7-question Likert-type scale survey with optional free text was administered to multidisciplinary staff focused on workflow, agreement with ML and patient experience.Results59/71 (83%) responded. 81% disagreed/strongly disagreed their workflow was disrupted. 67% agreed/strongly agreed patients undergoing intervention were high risk. 75% agreed/strongly agreed they would implement the ML approach routinely if the study was positive. Free-text feedback focused on patient education and ML predictions.ConclusionsRandomised data and firsthand experience support positive reception of clinical ML. Providers highlighted future priorities, including patient counselling and workflow optimisation.

BackgroundArtificial intelligence (AI) and machine learning (ML) have resulted in significant enthusiasm for their promise in healthcare. Despite this, prospective randomized controlled trials and successful clinical implementation remain limited. One clinical application of ML is mitigation of the increased risk for acute care during outpatient cancer therapy. We previously reported the results of the System for High Intensity EvaLuation During Radiation Therapy (SHIELD-RT) study (NCT04277650), which was a prospective, randomized quality improvement study demonstrating that ML based on electronic health record (EHR) data can direct supplemental clinical evaluations and reduce the rate of acute care during cancer radiotherapy with and without chemotherapy. The objective of this study is to report the workflow and operational challenges encountered during ML implementation on the SHIELD-RT study.ResultsData extraction and manual review steps in the workflow represented significant time commitments for implementation of clinical ML on a prospective, randomized study. Barriers include limited data availability through the standard clinical workflow and commercial products, the need to aggregate data from multiple sources, and logistical challenges from altering the standard clinical workflow to deliver adaptive care.ConclusionsThe SHIELD-RT study was an early randomized controlled study which enabled assessment of barriers to clinical ML implementation, specifically those which leverage the EHR. These challenges build on a growing body of literature and may provide lessons for future healthcare ML adoption.Trial registrationNCT04277650. Registered 20 February 2020. Retrospectively registered quality improvement study.

PurposePatients undergoing outpatient radiotherapy (RT) or chemoradiation (CRT) frequently require acute care (emergency department evaluation or hospitalization). Machine learning (ML) may guide interventions to reduce this risk. There are limited prospective studies investigating the clinical impact of ML in health care. The objective of this study was to determine whether ML can identify high-risk patients and direct mandatory twice-weekly clinical evaluation to reduce acute care visits during treatment.Patients and methodsDuring this single-institution randomized quality improvement study (ClinicalTrials.gov identifier: NCT04277650), 963 outpatient adult courses of RT and CRT started from January 7 to June 30, 2019, were evaluated by an ML algorithm. Among these, 311 courses identified by ML as high risk (> 10% risk of acute care during treatment) were randomized to standard once-weekly clinical evaluation (n = 157) or mandatory twice-weekly evaluation (n = 154). Both arms allowed additional evaluations on the basis of clinician discretion. The primary end point was the rate of acute care visits during RT. Model performance was evaluated using receiver operating characteristic area under the curve (AUC) and decile calibration plots.ResultsTwice-weekly evaluation reduced rates of acute care during treatment from 22.3% to 12.3% (difference, -10.0%; 95% CI, -18.3 to -1.6; relative risk, 0.556; 95% CI, 0.332 to 0.924; P = .02). Low-risk patients had a 2.7% acute care rate. Model discrimination was good in high- and low-risk patients undergoing standard once-weekly evaluation (AUC, 0.851).ConclusionIn this prospective randomized study, ML accurately triaged patients undergoing RT and CRT, directing clinical management with reduced acute care rates versus standard of care. This prospective study demonstrates the potential benefit of ML in health care and offers opportunities to enhance care quality and reduce health care costs.

Lung cancer screening (LCS) is currently advocated in a subset of current or former smokers with a thirty pack-year smoking history or higher. Studies report that few patients meeting the criteria for screening are undergoing LCS. We conducted a survey to assess if barriers to LCS (race, ethnicity, and socioeconomic status) affect the perceptions about LCS that could influence screening uptake. We did not detect different perceptions based on race, ethnicity, or socioeconomic status; however, our survey found that fewer barriers and more benefits to LCS may be perceived in patients who undergo other types of health screening and more benefits for those with internet capable devices., Author(s): Sarah Ellen Stephens [sup.1] , Kristie Long Foley [sup.2] , David Miller [sup.3] , Christina R. Bellinger [sup.4] Author Affiliations: (1) Memorial Health Lung and Sleep Care, Memorial Health, [...]

Previous studies have shown associations between single nucleotide polymorphisms (SNPs) in gamma aminobutyric acid receptor alpha 2 (GABRA2) and adolescent conduct disorder (CD) and alcohol dependence in adulthood, but not adolescent alcohol dependence. The present study was intended as a replication and extension of this work, focusing on adolescent CD, adolescent alcohol abuse and dependence (AAD), and adult AAD. Family based association tests were run using Hispanics and non-Hispanic European American subjects from two independent longitudinal samples. Although the analysis provided nominal support for an association with rs9291283 and AAD in adulthood and CD in adolescence, the current study failed to replicate previous associations between two well replicated GABRA2 SNPs and CD and alcohol dependence. Overall, these results emphasize the utility of including an independent replication sample in the study design, so that the results from an individual sample can be weighted in the context of its reproducibility. © 2014 Springer Science+Business Media New York.

The practical application of embryo transfer in pigs could benefit from using embryo donors for multiple cycles. Thus, raising the need to investigate feeding strategies for donors which will not be required to recover body condition lost during previous lactation. The objective was to evaluate the effects of temporary feed restriction, from d 6 to 14 of the estrous cycle, on growth, blood variables and reproductive performance in replacement gilts. Replacement gilts (n = 20; TN70, Topigs Norsvin, Oak Bluff, Canada) were assigned equally across 2 feeding regimens following a randomized complete block design where the block was backfat thickness. The feeding regimens were based on the first day of the estrous cycle: CON, recommended feeding levels from d 0 to 14 and a flush feeding (25% above recommended levels) from d 15 until d 21; or RES, CON but with restricted feeding (25% below recommended levels) from d 6 to 14. The CON treatment was based on the recommendations of the Feed Manual TN70 (Topigs Norsvin, 2015). On d 0, 5, 14 and 20 of the cycle, body weight and backfat thickness were measured. On d 21 (detected estrus), gilts were inseminated and on d 27 they were euthanized to collect embryos, ovaries and uterus. The uterus and ovaries were weighed whereas corpora lutea were counted and weighed. Blood serum was collected on d 14, and 20 for chemical analyses. Data were analyzed using the mixed procedure of SAS where each gilt was the experimental unit. Feeding regimens were considered as the fixed effect and backfat block as the random effect. Means were obtained with the LSMEANS statement. No differences (P > 0.05) were observed on growth performance among feeding regimens. However, when comparing the average daily gain (ADG) within feeding regimens between feeding periods, no differences (P > 0.05) were observed among gilts fed CON whereas gilts fed RES showed a decreased (P < 0.05) ADG during d 6 to 14 compared with d 0 to 5 and d 15 to 21. Regarding blood serum variables, gilts fed RES had greater (P < 0.05) total protein and potassium but less (P < 0.05) sodium-to-potassium ratio than gilts fed CON on d 14. On d 20, Gilts fed RES had greater (P < 0.05) cholesterol values than gilts fed CON. No differences (P > 0.05) were observed on the number of corpora lutea, number of embryos collected or on collection efficiency. Similarly, no differences (P > 0.05) were observed on the weight of reproductive organs or on measurements of ovaries among feeding regimens. In conclusion, restricting feed intake of replacement gilts by 25% of the recommendation from d 6 to 14 of the estrous cycle reduced ADG without compromising their reproductive performance. [ABSTRACT FROM AUTHOR]