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The effectiveness of parenting on child outcomes may be dependent on other contextual factors. To date, few studies have focused on the potential moderating effect of maternal stress on the relationship between parenting and youth externalizing behaviors. This study extends prior work by assessing how the relationship between parenting and youth outcomes varies by the presence of maternal stress, while focusing on the developmental period of adolescence and two dimensions of parenting, parental knowledge and maternal warmth. Data were collected from 278 Mother-adolescent dyads (Madolescent age = 14.05; 53.2% females; 61.9% minority) on maternal stress, maternal warmth and parental knowledge, and youth aggression and delinquency. Multi-level regression models found significant two-way interactions between parental knowledge and maternal stress on aggression and between maternal warmth and maternal stress on both outcomes. Parental knowledge was associated with lower aggression in the context of high maternal stress, but warmth only attenuated the risk of youth outcomes among low maternal stress. This study highlights the importance of considering how contextual factors impact the relationship between parenting and youth externalizing behaviors.

Anthropogenically induced warming is transforming Arctic ecosystems across a geologically short timescale, but earlier episodes of Earth history provide insights on the nature and limitations of biotic change in a rapidly warming Arctic. Late early Eocene strata (~52 Ma) of the Margaret Formation on Ellesmere Island, Nunavut, Canada sample a warm temperate ecosystem with a polar light regime situated at ~77°N paleolatitude. This extinct boreal ecosystem hosted a diversity of early Cenozoic vertebrates, including thermophilic taxa such as crocodilians and tapiroid perissodactyls. Here we describe two new species of the early primatomorphan Ignacius from Ellesmere, which are by far the northernmost known records for Paleogene Primatomorpha. Ellesmere species of Ignacius are sister taxa, indicating a single colonization of Ellesmere from farther south in North America coincident with the onset of the hyperthermal Early Eocene Climatic Optimum (EECO). The Ellesmere Ignacius clade differs from closely related taxa inhabiting mid-latitudes in being larger (thereby conforming to Bergmann’s rule) and having modified dentition and muscles of mastication for a dietary regime emphasizing hard objects, possibly reflecting an increased reliance on fallback foods during long polar winters. The late early Eocene mammalian fauna of Ellesmere indicates that its unique paleoenvironment rendered it uninhabitable to some clades, including euprimates, while selected taxa were able to adapt to its challenging conditions and diversify.

Despite established relationships between diabetic status and an increased risk for COVID-19 severe outcomes, there is a limited number of studies examining the relationships between diabetes complications and COVID-19-related risks. We use the Adapted Diabetes Complications Severity Index to define seven diabetes complications. We aim to understand the risk for COVID-19 infection, hospitalization, mortality, and longer length of stay of diabetes patients with complications. We perform a retrospective case-control study using Electronic Health Records (EHRs) to measure differences in the risks for COVID-19 severe outcomes amongst those with diabetes complications. Using multiple logistic regression, we calculate adjusted odds ratios (OR) for COVID-19 infection, hospitalization, and in-hospital mortality of the case group (patients with diabetes complications) compared to a control group (patients without diabetes). We also calculate adjusted mean difference in length of stay between the case and control groups using multiple linear regression. Adjusting demographics and comorbidities, diabetes patients with renal complications have the highest odds for COVID-19 infection (OR = 1.85, 95% CI = [1.71, 1.99]) while those with metabolic complications have the highest odds for COVID-19 hospitalization (OR = 5.58, 95% CI = [3.54, 8.77]) and in-hospital mortality (OR = 2.41, 95% CI = [1.35, 4.31]). The adjusted mean difference (MD) of hospital length-of-stay for diabetes patients, especially those with cardiovascular (MD = 0.94, 95% CI = [0.17, 1.71]) or peripheral vascular (MD = 1.72, 95% CI = [0.84, 2.60]) complications, is significantly higher than non-diabetes patients. African American patients have higher odds for COVID-19 infection (OR = 1.79, 95% CI = [1.66, 1.92]) and hospitalization (OR = 1.62, 95% CI = [1.39, 1.90]) than White patients in the general diabetes population. However, White diabetes patients have higher odds for COVID-19 in-hospital mortality. Hispanic patients have higher odds for COVID-19 infection (OR = 2.86, 95% CI = [2.42, 3.38]) and shorter mean length of hospital stay than non-Hispanic patients in the general diabetes population. Although there is no significant difference in the odds for COVID-19 hospitalization and in-hospital mortality between Hispanic and non-Hispanic patients in the general diabetes population, Hispanic patients have higher odds for COVID-19 hospitalization (OR = 1.83, 95% CI = [1.16, 2.89]) and in-hospital mortality (OR = 3.69, 95% CI = [1.18, 11.50]) in the diabetes population with no complications. The presence of diabetes complications increases the risks of COVID-19 infection, hospitalization, and worse health outcomes with respect to in-hospital mortality and longer hospital length of stay. We show the presence of health disparities in COVID-19 outcomes across demographic groups in our diabetes population. One such disparity is that African American and Hispanic diabetes patients have higher odds of COVID-19 infection than White and Non-Hispanic diabetes patients, respectively. Furthermore, Hispanic patients might have less access to the hospital care compared to non-Hispanic patients when longer hospitalizations are needed due to their diabetes complications. Finally, diabetes complications, which are generally associated with worse COVID-19 outcomes, might be predominantly determining the COVID-19 severity in those infected patients resulting in less demographic differences in COVID-19 hospitalization and in-hospital mortality.

Enterovirus D68 (EV-D68) causes cyclical outbreaks of respiratory disease and acute flaccid myelitis. EV-D68 is primarily transmitted through the respiratory route, but the duration of shedding in the respiratory tract is unknown. We prospectively enrolled 9 hospitalized children with EV-D68 respiratory infection and 16 household contacts to determine EV-D68 RNA shedding dynamics in the upper respiratory tract through serial midturbinate specimen collections and daily symptom diaries. Five (31.3%) household contacts, including 3 adults, were EV-D68–positive. The median duration of EV-D68 RNA shedding in the upper respiratory tract was 12 (range 7–15) days from symptom onset. The most common symptoms were nasal congestion (100%), cough (92.9%), difficulty breathing (78.6%), and wheezing (57.1%). The median illness duration was 20 (range 11–24) days. Understanding the duration of RNA shedding can inform the expected rate and timing of EV-D68 detection in associated acute flaccid myelitis cases and help guide public health measures.

\"Providing a comprehensive approach to cognitive interviewing in the field of survey methodology, Cognitive Interviewing Methodology delivers a clear guide that draws upon modern, cutting-edge research from a variety of fields. Each chapter begins by summarizing the prevailing paradigms that currently dominate the field of cognitive interviewing. Then underlying theoretical foundations are presented, which supplies readers with the necessary background to understand newly-evolving techniques in the field. The theories lead into developed and practiced methods by leading practitioners, researchers, and/or academics. Finally, the edited guide lays out the limitations of cognitive interviewing studies and explores the benefits of cognitive interviewing with other methodological approaches.\"--

The rising concentration of plastics due to extensive disposal and inefficient recycling of plastic waste poses an imminent and critical threat to the environment and ecological systems. Photocatalytic reforming of plastic derivatives to value-added chemicals under ambient conditions proceeds at lower oxidation potential which galvanizes the hydrogen evolution. We report the synthesis of a narrow band gap NCN-functionalized O-bridged carbon nitride (MC) through condensation polymerization of hydrogen-bonded melem (M)-cyameluric acid (C) macromolecular aggregate. The MC scaffold hosts well-dispersed Ir single atom (MCIrSA) sites which catalyze oxidative photoreforming of alkali-treated polylactic acid (PLA) and polyethylene terephthalate (PET) derivatives to produce H 2 at a rate of 147.5 and 29.58 μmol g −1 cat h −1 under AM1.5G irradiation. Solid-state electron paramagnetic resonance (EPR) and time-resolved photoluminescence (TRPL) reveals efficient charge carrier generation and separation in MCIrSA. X-ray absorption spectroscopy (XAS) and Bader charge analysis reveal undercoordinated IrN 2 O 2 SA sites pinned in C 6 N 7 moieties leading to efficient hole quenching. The liquid phase EPR, in situ FTIR and density functional theory (DFT) studies validate the facile generation of •OH radicals due to the evolution of O-Ir-OH transient species with weak Ir--OH desorption energy barrier. The photocatalytic reforming of plastics into value-added chemicals offers a promising strategy to address environmental challenges while providing significant energy benefits. Here, the authors develop modified carbon nitride with enhanced visible light absorption, effectively anchoring under-coordinated IrN 2 O 2 sites to catalyze the oxidation of persistent plastic derivatives.

Patients diagnosed with differentiated thyroid cancer (DTC) who receive radioactive iodine (RAI) treatment experience acute, medium, and late treatment effects. The timing and severity of these effects varies by individual; common post-treatment effects include dry mouth, salivary gland swelling, dry eyes, and nose bleeds. The nature of symptoms that patients experience after RAI treatment can significantly and negatively impact health-related quality of life (HRQOL). Adequate information during the post-primary treatment phase remains an unmet need among the population of patients diagnosed with DTC. This qualitative study aimed to identify and understand self-management strategies for RAI-specific symptom burden from the perspectives of patients and stakeholders (cancer care providers and patient advocates).‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ An additional aim included assessing the features and functionalities desirable in the development of a web-based intervention to engage patients in their self-management and thyroid cancer survivorship care. Following Social Cognitive Theory framework and person-based principles, we conducted 6 focus groups with 22 patients diagnosed with DTC who completed RAI treatment and individual interviews with 12 stakeholders in DTC care. The interviews focused on participants' perspectives on current self-management strategies and mockups of a symptom management web-based intervention. Prior to the focus groups and interviews, participants completed a demographics survey. Focus group discussions and interviews were transcribed and coded using content analysis. Inter-rater reliability was satisfactory (α=0.88). A total of 34 individuals (patients and stakeholders) participated in the study; mean age was 45 (SD 13.4) and 45.3 (SD 13) years, respectively. Three domains emerged from qualitative interviews: 1) Difficult-to-manage RAI symptoms: Short, medium, and late treatment effects; 2) Key intervention structure and content feedback on mockups; and 3) Intervention content to promote RAI symptom management and survivorship care. Focus group participants identified the most prevalent RAI symptoms that were difficult to manage as: dry mouth (11/22, 50%), salivary gland swelling (8/22, 36.4%), and changes in taste (12/22, 54.5%). Feedback elicited from both groups found education and symptom management mockup videos to be helpful in patient self-management of RAI symptoms, whereas patients and stakeholders provided mixed feedback on the benefits of a draft frequently asked questions page. Across focus groups and stakeholder interviews, nutrition-based symptom management strategies, communication with family members, and practical survivorship follow-up information emerged as helpful content to include on a future web-based supportive care intervention. Results suggest education and symptom management videos can empower patients with DTC to self-manage mild to moderate RAI symptoms on a web-based platform. Findings emphasized the need for additional information for patients related to ongoing care following RAI treatment including social support and thyroid cancer surveillance. The findings provide insights for theoretically informed interventions and recommendations for refinements in thyroid cancer survivorship from patient and provider perspectives.

Approximately 20-50% of adolescent and young adult-aged childhood cancer survivors (AYA-CCS) experience sexual dysfunction (SD), although this healthcare need is widely underrecognized. Previous research from both AYA-CCS patients and their providers report that SD needs are unaddressed despite patient desires for SD discussions to be incorporated as part of their care. Patients and providers agree that standardized use of a patient-reported outcome measure may facilitate SD discussions; an SD screening approach was developed with patient and provider input. This study will measure the effectiveness of a standardized SD screening intervention and assess implementation outcomes and multilevel barriers and facilitators to guide future research. This multi-site, mixed methods, type 1 effectiveness-implementation hybrid trial will be evaluated using a pre-post design (NCT05524610). The trial will enroll 86 AYA-CCS (ages 15-39) from two cancer centers in the United States. The SD intervention consists of core fundamental functions with a \"menu\" of intervention options to allow for flexibility in delivery and tailoring in variable contexts. Effectiveness of the intervention on facilitating SD communication will be measured through patient surveys and clinical data; multivariable logistic regression will be used for the binary outcome of self-reported SD screening, controlling for patient-level predictors. Implementation outcomes will be assessed using mixed methods (electronic health record abstraction, patient and provider surveys, and provider interviews. Quantitative and qualitative findings will be merged using a joint display to understand factors affecting intervention success. Identification and treatment of SD in AYA-CCS is an important and challenging quality of life concern. The type 1 hybrid design will facilitate rapid translation from research to practice by testing the effects of the intervention while simultaneously identifying multilevel barriers and facilitators to real-world implementation. This approach will inform future testing and dissemination of the SD screening intervention.

Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay. This study aims to explore the potential of machine learning and natural language processing techniques in improving diagnostic safety surveillance. We conducted a rigorous evaluation of the feasibility and potential to use electronic health records clinical notes and existing case review data. Safety Learning System case review data from 1 large health system composed of 10 hospitals in the mid-Atlantic region of the United States from February 2016 to September 2021 were analyzed. The case review outcome included opportunities for improvement including diagnostic opportunities for improvement. To supplement case review data, electronic health record clinical notes were extracted and analyzed. A simple logistic regression model along with 3 forms of logistic regression models (ie, Least Absolute Shrinkage and Selection Operator, Ridge, and Elastic Net) with regularization functions was trained on this data to compare classification performances in classifying patients who experienced diagnostic errors during hospitalization. Further, statistical tests were conducted to find significant differences between female and male patients who experienced diagnostic errors. In total, 126 (7.4%) patients (of 1704) had been identified by case reviewers as having experienced at least 1 diagnostic error. Patients who had experienced diagnostic error were grouped by sex: 59 (7.1%) of the 830 women and 67 (7.7%) of the 874 men. Among the patients who experienced a diagnostic error, female patients were older (median 72, IQR 66-80 vs median 67, IQR 57-76; P=.02), had higher rates of being admitted through general or internal medicine (69.5% vs 47.8%; P=.01), lower rates of cardiovascular-related admitted diagnosis (11.9% vs 28.4%; P=.02), and lower rates of being admitted through neurology department (2.3% vs 13.4%; P=.04). The Ridge model achieved the highest area under the receiver operating characteristic curve (0.885), specificity (0.797), positive predictive value (PPV; 0.24), and F -score (0.369) in classifying patients who were at higher risk of diagnostic errors among hospitalized patients. Our findings demonstrate that natural language processing can be a potential solution to more effectively identifying and selecting potential diagnostic error cases for review and therefore reducing the case review burden.