Characterizing nutrient patterns of food items in adolescent diet using data from a novel citizen science project and the US National Health and Nutrition Examination Survey (NHANES).

Introduction: A healthy diet is essential for promoting good health during adolescence and mitigating disease risks in adulthood. This underscores the need for improved nutrition education and increased access to healthier food choices. However, the accuracy of dietary data poses a significant challenge in nutritional research. Methods: We utilized and analyzed a novel dietary record dataset collected through a high school citizen science project to address this issue. We focused on nutrients rather than food groups to characterize adolescent dietary patterns. The same analyses were performed on the 2019-2021 National Health and Nutrition Examination Survey data for comparison. Results: Based on the U.S. Food and Drug Administration's recommended daily value (DV) for nutrients, the majority of food items in our citizen science dataset are low (i.e., <5% DV) in lipids, fiber, potassium, calcium, iron, sugar, and cholesterol. Only a minority of items are high (i.e., >20% DV) in macro and micronutrients. The clustering analysis identified nine food clusters with distinct nutrient profiles that vary significantly in size. The analyses on the NHANES data yielded similar findings, but with higher proportions of foods high in energy, lipids, carbohydrates, sugar, iron, and sodium compared with those of the citizen science dataset. Discussion: This study demonstrates the potential of citizen science projects in gathering valuable dietary data and understanding adolescent nutrient intake. Identifying critical nutrient gaps can guide targeted nutrition education and the provision of accessible healthier food options, leading to positive health outcomes during adolescence and beyond.

Patient Dietary Supplements Use: Do Results from Natural Language Processing of Clinical Notes Agree with Survey Data?

There is widespread use of dietary supplements, some prescribed but many taken without a physician's guidance. There are many potential interactions between supplements and both over-the-counter and prescription medications in ways that are unknown to patients. Structured medical records do not adequately document supplement use; however, unstructured clinical notes often contain extra information on supplements. We studied a group of 377 patients from three healthcare facilities and developed a natural language processing (NLP) tool to detect supplement use. Using surveys of these patients, we investigated the correlation between self-reported supplement use and NLP extractions from the clinical notes. Our model achieved an F1 score of 0.914 for detecting all supplements. Individual supplement detection had a variable correlation with survey responses, ranging from an F1 of 0.83 for calcium to an F1 of 0.39 for folic acid. Our study demonstrated good NLP performance while also finding that self-reported supplement use is not always consistent with the documented use in clinical records.

Leveraging Self-Determination Theory to Understand Which Preschool Teachers Benefit Most from a Professional Development Intervention.

Effective professional development (PD) interventions that promote high quality teacher-child interactions are important mechanisms to support social-emotional and cognitive development in early childhood. One PD intervention that has shown to be effective is MyTeachingPartner (MTP); however, previous research has suggested that both teacher and contextual factors may moderate the effectiveness of PD interventions like MTP. In the current study, we used a self-determination theoretical (SDT) framework to identify subgroups of teachers (N = 401) through latent class analysis based on the fulfillment of their three basic needs: competence, autonomy, and relatedness. We found three latent classes of teachers: 1) Unconfident and Unsupported; 2) Unconfident but Supported; 3) Confident and Supported. We tested the effect of MTP, latent class membership, and the MTP by latent class interaction on the quality of teacher emotional and instructional support to identify which teachers benefitted most from the MTP intervention. While MTP benefitted teachers on emotional support similarly across classes, MTP was most effective for instructional support for teachers from the Confident and Supported class. As these were the only teachers who had all their basic needs met our results suggest teacher and contextual factors in concert are important in optimizing the effectiveness of PD.

Healthy Lifestyle and Mood: A Biomedical Informatics Citizen Science Project in a High School Classroom.

Mental health is an increasing concern in adolescents. Mental health disorders can affect academic performance, affect the cultivation of healthy relationships, and even lead to suicide. Healthy lifestyle can improve mental health, though there are gaps in the research, partly resulted from the lack of detailed longitudinal datasets on lifestyle and mental health. To inform and engage students in the research on adolescent lifestyle and mood, the George Washington University and the T.C. Williams High School in Alexandria, Virginia teamed up in a citizen science project. Students generated questions, collected data on themselves, analyzed the data, and produced research reports relating to their mental health and lifestyle. Student feedbacks suggest that the students find the project to be generally interesting and some students (46%) reported that the participation in the project may influence their college and career plans. The anonymized dataset resulted from the project provides another contribution to science.

Higher incidence of retinopathy of prematurity in extremely preterm infants associated with improved survival rates.

AIM: This study assessed possible reasons for the increasing incidence of retinopathy of prematurity (ROP) since mid-2015 at our institution. METHODS: Retrospective analysis of all preterm infants born July 2013 to June 2017 with a gestational age (GA) <29 completed weeks admitted to the neonatal intensive care unit at the University Hospital Zurich during the first 28 days of life. The primary outcome measures were severest ROP stage. Statistical analysis was performed using generalised additive models in R. RESULTS: During the study period, survival increased in extremely preterm infants. Significant predictors for severest ROP stage were GA, days of mechanical ventilation and multiple gestation (P = .0322). A composite of severe comorbidities had no significant effect on severest ROP stage. GA was identified as the only significant risk factor the for severest ROP stage (P = .0045). CONCLUSION: Increased survival rate of extremely preterm infants was associated with an increased incidence of ROP at our institution. Despite the increase, the incidence is still very low compared with other countries. No other additive factors were identified.