People simultaneously entangled in multiple state systems are often subject to contradictory legal mandates that can foster distrust and incentivize system avoidance. This study focuses on those indebted to both the child support system and the criminal legal system, a situation we describe as dual debt. We ask whether and how the imposition of legal debts with punitive surveillance and collections mechanisms fosters alienation in the form of legal cynicism and estrangement, which we refer to jointly as legal anomie. Drawing from interview data in Minnesota, we find that legal anomie and system avoidance are mutually reinforcing processes, as debts in these systems triggered consequences that pushed people out of the formal labor market and heightened their distrust of legal institutions. The case of dual debt demonstrates how alienating and contradictory policy systems can foster both legal anomie and system avoidance, particularly in the context of economic and social precarity.

According to International Union for the Conservation of Nature (IUCN) guidelines, all species must be assessed against all criteria during the Red Listing process. For organismal groups that are diverse and understudied, assessors face considerable challenges in assembling evidence due to difficulty in applying definitions of key terms used in the guidelines. Challenges also arise because of uncertainty in population sizes (Criteria A, C, D) and distributions (Criteria A2/3/4c, B). Lichens, which are often small, difficult to identify, or overlooked during biodiversity inventories, are one such group for which specific difficulties arise in applying Red List criteria. Here, we offer approaches and examples that address challenges in completing Red List assessments for lichens in a rapidly changing arena of data availability and analysis strategies. While assessors still contend with far from perfect information about individual species, we propose practical solutions for completing robust assessments given the currently available knowledge of individual lichen life-histories.

A vast amount of clinical data are still stored in unstructured text. Automatic extraction of medical information from these data poses several challenges: high costs of clinical expertise, restricted computational resources, strict privacy regulations, and limited interpretability of model predictions. Recent domain adaptation and prompting methods using lightweight masked language models showed promising results with minimal training data and allow for application of well-established interpretability methods. We are first to present a systematic evaluation of advanced domain-adaptation and prompting methods in a lower-resource medical domain task, performing multi-class section classification on German doctor’s letters. We evaluate a variety of models, model sizes (further-pre)training and task settings, and conduct extensive class-wise evaluations supported by Shapley values to validate the quality of small-scale training data and to ensure interpretability of model predictions. We show that in few-shot learning scenarios, a lightweight, domain-adapted pretrained language model, prompted with just 20 shots per section class, outperforms a traditional classification model, by increasing accuracy from $48.6\%$ to $79.1\%$. By using Shapley values for model selection and training data optimization, we could further increase accuracy up to $84.3\%$. Our analyses reveal that pretraining of masked language models on general-language data is important to support successful domain-transfer to medical language, so that further-pretraining of general-language models on domain-specific documents can outperform models pretrained on domain-specific data only. Our evaluations show that applying prompting based on general-language pretrained masked language models combined with further-pretraining on medical-domain data achieves significant improvements in accuracy beyond traditional models with minimal training data. Further performance improvements and interpretability of results can be achieved, using interpretability methods such as Shapley values. Our findings highlight the feasibility of deploying powerful machine learning methods in clinical settings and can serve as a process-oriented guideline for lower-resource languages and domains such as clinical information extraction projects.

The Accelerating COVID-19 Therapeutic Interventions and Vaccines (ACTIV) Cross-Trial Statistics Group gathered lessons learned from statisticians responsible for the design and analysis of the 11 ACTIV therapeutic master protocols to inform contemporary trial design as well as preparation for a future pandemic. The ACTIV master protocols were designed to rapidly assess what treatments might save lives, keep people out of the hospital, and help them feel better faster. Study teams initially worked without knowledge of the natural history of disease and thus without key information for design decisions. Moreover, the science of platform trial design was in its infancy. Here, we discuss the statistical design choices made and the adaptations forced by the changing pandemic context. Lessons around critical aspects of trial design are summarized, and recommendations are made for the organization of master protocols in the future.

The war in Ukraine raises concerns for potential hazards of radiological and nuclear incidents. Children are particularly vulnerable in these incidents and may need pharmaceutical countermeasures, including antidotes and cytokines. Searches found no published study comparing pediatric indications and dosing among standard references detailing pediatric medications for these incidents. This study addresses this gap by collecting, tabulating, and disseminating this information to healthcare professionals caring for children. Expert consensus chose the following references to compare their pediatric indications and dosing of medical countermeasures for radiation exposure and internal contamination with radioactive materials: Advanced Hazmat Life Support (AHLS) for Radiological Incidents and Terrorism, DailyMed, Internal Contamination Clinical Reference, Medical Aspects of Radiation Incidents, and Medical Management of Radiological Casualties, as well as Micromedex, POISINDEX, and Radiation Emergency Medical Management (REMM). This is the first study comparing pediatric indications and dosing for medical countermeasures among commonly used references for radiological and nuclear incidents.

OBJECTIVES/GOALS: Community-based participatory research is a “gold standard” methodology, yet many researchers lack the experience or resources to implement this approach. To make engagement more accessible, we developed and implemented a 3-part training series highlighting engagement as a spectrum with many options to meaningfully engage partners. METHODS/STUDY POPULATION: Staff at UNC-Chapel Hill’s CTSA and Cancer Center collaborated with patient and community partners to co-develop training content, structure, and delivery. Sessions were free and open to the public and covered key components of research engagement and its benefits, debunked common myths and misconceptions about engagement, outlined specific methods along the spectrum of engagement (from low to high touch), and described nuances of building and maintaining partnerships. Partners determined how to best incorporate their perspectives, developed content (including videos, audio clips, and quotes), and co-presented with UNC staff. Evaluations were collected after each session and feedback was incorporated into future iterations. RESULTS/ANTICIPATED RESULTS: 194 individuals from over 20 institutions have participated in the training. Of all survey respondents to date (n=74), 93% were very or extremely satisfied, 77% felt the training was very or extremely relevant to their work, and 76% were very or extremely likely to use information learned in the next year. Most helpful parts of the training were differentiating research engagement from participation; explaining engagement as a spectrum with varied methodologies; providing tools and resources to implement different approaches; and hearing directly from community co-presenters about their experiences engaging in research. Based on feedback, we created a workshop for researchers to develop engagement plans and an additional training for partners to build capacity and knowledge about engaging in research. DISCUSSION/SIGNIFICANCE: Engaging partners who are impacted by research can be instrumental to the success of a study. This training can help researchers identify engagement approaches that align with their goals, experience, and resources, as well as the interests and capacity of potential partners, and can serve as a model for those interested in training co-development.

The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery (WCPCCS) will be held in Washington DC, USA, from Saturday, 26 August, 2023 to Friday, 1 September, 2023, inclusive. The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery will be the largest and most comprehensive scientific meeting dedicated to paediatric and congenital cardiac care ever held. At the time of the writing of this manuscript, The Eighth World Congress of Pediatric Cardiology and Cardiac Surgery has 5,037 registered attendees (and rising) from 117 countries, a truly diverse and international faculty of over 925 individuals from 89 countries, over 2,000 individual abstracts and poster presenters from 101 countries, and a Best Abstract Competition featuring 153 oral abstracts from 34 countries. For information about the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery, please visit the following website: [www.WCPCCS2023.org]. The purpose of this manuscript is to review the activities related to global health and advocacy that will occur at the Eighth World Congress of Pediatric Cardiology and Cardiac Surgery.

Acknowledging the need for urgent change, we wanted to take the opportunity to bring a common voice to the global community and issue the Washington DC WCPCCS Call to Action on Addressing the Global Burden of Pediatric and Congenital Heart Diseases. A copy of this Washington DC WCPCCS Call to Action is provided in the Appendix of this manuscript. This Washington DC WCPCCS Call to Action is an initiative aimed at increasing awareness of the global burden, promoting the development of sustainable care systems, and improving access to high quality and equitable healthcare for children with heart disease as well as adults with congenital heart disease worldwide.

In engineering and architecture, different approaches have been developed that share the use of graph transformation to automate design processes or to search for design solutions by means of computational design synthesis. In order to give an overview of these approaches, we provide a review of articles published in the last decade. Forty-eight articles were reviewed to determine similarities and differences of these approaches. Research fields in method development for the representation of design problems and the processing of graph transformations, as well as the application of graph transformations in engineering, architecture, and shape grammars were identified. Different approaches for the documentation of the vocabulary and the rules were examined. Finally, different approaches for rule applications were analyzed. Based on found limitations, future research directions are suggested.

Background: Healthcare facilities have experienced many challenges during the COVID-19 pandemic, including limited personal protective equipment (PPE) supplies. Healthcare personnel (HCP) rely on PPE, vaccines, and other infection control measures to prevent SARS-CoV-2 infections. We describe PPE concerns reported by HCP who had close contact with COVID-19 patients in the workplace and tested positive for SARS-CoV-2. Method: The CDC collaborated with Emerging Infections Program (EIP) sites in 10 states to conduct surveillance for SARS-CoV-2 infections in HCP. EIP staff interviewed HCP with positive SARS-CoV-2 viral tests (ie, cases) to collect data on demographics, healthcare roles, exposures, PPE use, and concerns about their PPE use during COVID-19 patient care in the 14 days before the HCP’s SARS-CoV-2 positive test. PPE concerns were qualitatively coded as being related to supply (eg, low quality, shortages); use (eg, extended use, reuse, lack of fit test); or facility policy (eg, lack of guidance). We calculated and compared the percentages of cases reporting each concern type during the initial phase of the pandemic (April–May 2020), during the first US peak of daily COVID-19 cases (June–August 2020), and during the second US peak (September 2020–January 2021). We compared percentages using mid-P or Fisher exact tests (α = 0.05). Results: Among 1,998 HCP cases occurring during April 2020–January 2021 who had close contact with COVID-19 patients, 613 (30.7%) reported ≥1 PPE concern (Table 1). The percentage of cases reporting supply or use concerns was higher during the first peak period than the second peak period (supply concerns: 12.5% vs 7.5%; use concerns: 25.5% vs 18.2%; p Conclusions: Although lower percentages of HCP cases overall reported PPE concerns after the first US peak, our results highlight the importance of developing capacity to produce and distribute PPE during times of increased demand. The difference we observed among selected groups of cases may indicate that PPE access and use were more challenging for some, such as nonphysicians and nursing home HCP. These findings underscore the need to ensure that PPE is accessible and used correctly by HCP for whom use is recommended.

Funding: None

Disclosures: None

Voluntary asymptomatic severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing was provided by the NIH Clinical Center over 1 year. Among 105,927 tests, 0.2% were positive. Among eligible staff, 79% participated with variable frequency and 61% of positive individuals had symptoms at the time of testing. Saliva specimen collection was chosen as an option less frequently than midturbinate collection.

Adhering to a Mediterranean diet (MD) is associated with reduced CVD risk. This study aimed to explore methods of increasing MD adoption in a non-Mediterranean population at high risk of CVD, including assessing the feasibility of a developed peer support intervention. The Trial to Encourage Adoption and Maintenance of a MEditerranean Diet was a 12-month pilot parallel group RCT involving individuals aged ≥ 40 year, with low MD adherence, who were overweight, and had an estimated CVD risk ≥ 20 % over ten years. It explored three interventions, a peer support group, a dietician-led support group and a minimal support group to encourage dietary behaviour change and monitored variability in Mediterranean Diet Score (MDS) over time and between the intervention groups, alongside measurement of markers of nutritional status and cardiovascular risk. 118 individuals were assessed for eligibility, and 75 (64 %) were eligible. After 12 months, there was a retention rate of 69 % (peer support group 59 %; DSG 88 %; MSG 63 %). For all participants, increases in MDS were observed over 12 months (P < 0·001), both in original MDS data and when imputed data were used. Improvements in BMI, HbA1c levels, systolic and diastolic blood pressure in the population as a whole. This pilot study has demonstrated that a non-Mediterranean adult population at high CVD risk can make dietary behaviour change over a 12-month period towards an MD. The study also highlights the feasibility of a peer support intervention to encourage MD behaviour change amongst this population group and will inform a definitive trial.

Combining agility and convergence in the development of physical products is a major challenge. Rooted in a design thinking approach, Stanford's ME310 process model attempts to resolve the conflicting priorities of these two design principles. To investigate how successful Stanford's hybrid process model is in doing so, we have used a qualitative case study approach. Our paper begins by outlining this process model's fundamental principles in terms of engineering design methodology. Subsequently, we present the results of our empirical analysis, which tracks the coevolution of problem and solution space by meticulously examining all prototype paths in ten of Stanford's ME310 student projects. We have discovered that convergence during solution finding does not correspond to the process model's theoretical specifications. Even in the phase of the final prototype, both the technical concept and the underlying problem formulation changed frequently. Further research should focus on combining the prototype-based ME310 approach with methods from systems engineering which allow for a more comprehensive theoretical exploration of the solution space. This could lead to improved convergence during solution development.