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BackgroundCertain medications may increase the risk of death or death from specific causes (eg, sudden cardiac death), but these risks may not be identified in premarket randomized trials. Having the capacity to examine death in postmarket safety surveillance activities is important to the US Food and Drug Administration’s (FDA) mission to protect public health. Distributed networks of electronic health plan databases used by the FDA to conduct multicenter research or medical product safety surveillance studies often do not systematically include death or cause-of-death information. ObjectiveThis study aims to develop reusable, generalizable methods for linking multiple health plan databases with the Centers for Disease Control and Prevention’s National Death Index Plus (NDI+) data. MethodsWe will develop efficient administrative workflows to facilitate multicenter institutional review board (IRB) review and approval within a distributed network of 6 health plans. The study will create a distributed NDI+ linkage process that avoids sharing of identifiable patient information between health plans or with a central coordinating center. We will develop standardized criteria for selecting and retaining NDI+ matches and methods for harmonizing linked information across multiple health plans. We will test our processes within a use case comprising users and nonusers of antiarrhythmic medications. ResultsWe will use the linked health plan and NDI+ data sets to estimate the incidences and incidence rates of mortality and specific causes of death within the study use case and compare the results with reported estimates. These comparisons provide an opportunity to assess the performance of the developed NDI+ linkage approach and lessons for future studies requiring NDI+ linkage in distributed database settings. This study is approved by the IRB at Harvard Pilgrim Health Care in Boston, MA. Results will be presented to the FDA at academic conferences and published in peer-reviewed journals. ConclusionsThis study will develop and test a reusable distributed NDI+ linkage approach with the goal of providing tested NDI+ linkage methods for use in future studies within distributed data networks. Having standardized and reusable methods for systematically obtaining death and cause-of-death information from NDI+ would enhance the FDA’s ability to assess mortality-related safety questions in the postmarket, real-world setting. International Registered Report Identifier (IRRID)DERR1-10.2196/21811

BackgroundA distributed data network approach combined with distributed regression analysis (DRA) can reduce the risk of disclosing sensitive individual and institutional information in multicenter studies. However, software that facilitates large-scale and efficient implementation of DRA is limited. ObjectiveThis study aimed to assess the precision and operational performance of a DRA application comprising a SAS-based DRA package and a file transfer workflow developed within the open-source distributed networking software PopMedNet in a horizontally partitioned distributed data network. MethodsWe executed the SAS-based DRA package to perform distributed linear, logistic, and Cox proportional hazards regression analysis on a real-world test case with 3 data partners. We used PopMedNet to iteratively and automatically transfer highly summarized information between the data partners and the analysis center. We compared the DRA results with the results from standard SAS procedures executed on the pooled individual-level dataset to evaluate the precision of the SAS-based DRA package. We computed the execution time of each step in the workflow to evaluate the operational performance of the PopMedNet-driven file transfer workflow. ResultsAll DRA results were precise (

BackgroundThe use of rapid qualitative methods has increased substantially over the past decade in quality improvement and health services research. These methods have gained traction in implementation research and practice, wherein real-time adjustments are often made to optimize processes and outcomes. This brisk increase begs the questions: what does rigor entail in projects that use rapid qualitative analysis (RQA)? How do we define a pragmatic framework to help research teams design and conduct rigorous and valid rapid qualitative projects? How can authors articulate rigor in their methods descriptions? Lastly, how can reviewers evaluate the rigor of rapid qualitative projects?.MethodsA team of seven interdisciplinary qualitative methods experts developed a framework for ensuring rigor and validity in RQA and methods suitable for this analytic approach. We conducted a qualitative evidence synthesis to identify gaps in the literature and then drew upon literature, standard procedures within our teams, and a repository of rapid qualitative training materials to create a planning and reporting framework. We iteratively refined this framework through 11 group working meetings (60-90 minutes each) over the course of one year and invited feedback on items to ensure their completeness, clarity, and comprehensibility.ResultsThe Planning for and Assessing Rigor in Rapid Qualitative Analysis (PARRQA) framework is organized progressively across phases from design to dissemination, as follows: 1) rigorous design (rationale and staffing), 2) semi-structured data collection (pilot and planning), 3) RQA: summary template development (accuracy and calibration), 4) RQA: matrix analysis (matrices), and 5) rapid qualitative data synthesis. Eighteen recommendations across these sections specify best practices for rigor and validity.ConclusionsRapid qualitative methods play a central role in implementation evaluations, with the potential to yield prompt information and insights about context, processes, and relationships. However, guidance on how to assess rigor is nascent. The PARRQA framework enhances the literature by offering criteria to ensure appropriate planning for and assessment of rigor in projects that involve RQA. This framework provides a consensus-based resource to support high-level qualitative methodological rigor in implementation science.

BACKGROUND: Per- and polyfluoroalkyl substances (PFAS) may disrupt mammary gland development and function; thereby inhibiting milk supply and breastfeeding duration. However, conclusions on the potential effects of PFAS and breastfeeding duration are limited by prior epidemiologic studies that inconsistently adjusted for past cumulative breastfeeding duration and by a lack of examination of the joint effects of PFAS mixtures. METHODS: In Project Viva, a longitudinal cohort that enrolled pregnant participants from 1999 to 2002 in the greater Boston, MA area, we studied 1079 women who ever attempted to lactate. We investigated associations of plasma concentrations of select PFAS in early pregnancy (mean: 10.1 weeks gestation) with breastfeeding termination by 9 months, after which women typically cite self-weaning as the reason for terminating breastfeeding. We used Cox regression for single-PFAS models and quantile g-computation for mixture models, adjusting for sociodemographics, prior breastfeeding duration, and weeks of gestation at the time of blood draw. RESULTS: We detected 6 PFAS [perfluorooctane sulfonate; perfluorooctanoate (PFOA); perfluorohexane sulfonate; perfluorononanoate; 2-(N-ethyl-perfluorooctane sulfonamido) acetate (EtFOSAA); 2-(N-methyl-perfluorooctane sulfonamide) acetate (MeFOSAA)] in >98 % of samples. Sixty percent of lactating women terminated breastfeeding by 9 months postpartum. Women with higher plasma concentrations of PFOA, EtFOSAA, and MeFOSAA had a greater hazard of terminating breastfeeding in the first 9 months postpartum [HR (95 % CI) per doubling concentration: 1.20 (1.04, 1.38) for PFOA; 1.10 (1.01, 1.20) for EtFOSAA; 1.18 (1.08, 1.30) for MeFOSAA]. In the quantile g-computation model, simultaneously increasing all PFAS in the mixture by one quartile was associated with 1.17 (95 % CI: 1.05, 1.31) greater hazard of terminating breastfeeding in the first 9 months. CONCLUSION: Our findings suggest that exposure to PFAS may be associated with reduced breastfeeding duration and draw further attention to environmental chemicals that may dysregulate human lactation.

Data collection and analysis (DCA) skills apply mathematical knowledge, such as counting, sorting, and classifying, to investigations of real-world questions. This pursuit lays the foundation for learners to develop flexible problem-solving skills with data. This pilot study tested a preschool intervention intended to support teachers in promoting young children's DCA skills using a technology-integrated approach. A key component therein was a teacher-facing digital app that facilitated collaboration between preschool teachers and children to more easily collect data, create simple graphs, and use graphed data to engage in real-world questions and discussions. As part of a design-based research approach, this study tested the intervention's developmental appropriateness and feasibility in four preschool classrooms (n = 5). Findings suggest that the intervention curriculum (i.e., investigations) and inclusion of the app supported teachers and children to answer data-focused questions by engaging in each step of the DCA process while applying numerous mathematics skills. Teachers reported that the app complemented curricular implementation and children demonstrated readiness to engage with, and benefit from, the investigations. Findings also indicated the developmental appropriateness and feasibility of applying this DCA approach in preschools and suggest further study of the approach.

This exploratory, mixed-methods study examines first-year general chemistry students' written responses on a belonging survey. Responses were thematically analyzed to identify students' sources of belonging, which may help instructors choose effective strategies for enhancing belonging during the transition into college. Qualitative analysis generated a codebook containing 21 codes from 6 categories: Course Attributes, Interest, Perceptions, Social, Student Attributes, and Value. The qualitative coding data were transformed into quantitative frequency data, allowing identification of the most frequent themes across all participants on each of four surveys: early- and late-semester General Chemistry 1 and 2. Additional analyses explored how belonging explanations varied based on student characteristics that might influence their experience of this large introductory STEM course at a selective, high-income, predominantly White institution. Unique sources of belonging were expected to emerge for groups marginalized in STEM (i.e., Black and Hispanic students, women) and groups who might feel discouraged by a selective institutional and course culture (i.e., students with no credit-bearing AP scores, low course grades, or high belonging uncertainty). Results indicate the importance of interest for all participants' course-level belonging. Students' career goals, perceptions of the course content, and social dynamics with peers also proved universally influential. Some patterns were especially pronounced for marginalized or discouraged groups, who were disproportionately likely to discuss social comparisons and interactions, self-evaluate, and describe the utility-value of the course. These groups were also less likely to express positive cognitive and affective engagement in the course. Implications for supporting student belonging throughout the course sequence are discussed.

Increasingly, studies suggest benefits of natural environments or greenness on childrens health. However, little is known about cumulative exposure or windows of susceptibility to greenness exposure. Using inverse probability weighting of marginal structural models (IPW/MSM), we estimated effects of greenness exposure from birth through adolescence on executive function and behavior. We analyzed data of 908 children from Project Viva enrolled at birth in 1999-2002 and followed up until early adolescence. In mid-childhood (median 7.7 years) and early adolescence (13.1 years), executive function and behavior were assessed using the Behavior Rating Inventory of Executive Function and the Strengths and Difficulties Questionnaire (SDQ). Greenness was measured at birth, early childhood, mid-childhood, and early adolescence, using the Normalized Difference Vegetation Index. We used inverse probability weighting of marginal structural models to estimate effects of interventions that ensure maximum greenness exposure versus minimum through all intervals; and that ensure maximum greenness only in early childhood (vs. minimum through all intervals). Results of the effects of maximum (vs. minimum) greenness at all timepoints did not suggest associations with mid-childhood outcomes. Estimates of maximum greenness only in early childhood (vs. minimum) suggested a beneficial association with mid-childhood SDQ (-3.21, 99 %CI: -6.71,0.29 mother-rated; -4.02, 99 %CI: -7.87,-0.17 teacher-rated). No associations were observed with early adolescent outcomes. Our results for persistent maximum greenness exposure on behavior, were not conclusive with confidence intervals containing the null. The results for maximum greenness only in early childhood may shed light on sensitive periods of greenness exposure for behavior regulation.

This study seeks to examine the effectiveness of peer-led team learning (PLTL) pedagogy when it is implemented in an entirely online environment. Past evaluations of PLTL have demonstrated the effectiveness of this approach when used with in-person teaching, but an online environment is expected to pose unique challenges to students, and therefore, the past work may not generalize to an online environment. The study implemented PLTL within four classes of second-semester general chemistry each offered online. The classes were evaluated in reference to six classes of the same course, also taught exclusively online, that relied primarily on didactic instruction. The evaluation showed the average score for students with online PLTL ranged from 0.15 to 0.20 standard deviations better than students with online didactic across the tests and final exams and that this difference was partially explained by past performance. Further, online PLTL students had a higher likelihood of earning a passing grade in the class which corresponded with a lower proportion of students failing and a lower proportion of students withdrawing from the course. The results indicate that PLTL was an effective instructional technique within an online modality at the research setting.

Biogeochemical processes capable of altering global carbon systems occur frequently in Earth’s Critical Zone–the area spanning from vegetation canopy to saturated bedrock–yet many of these phenomena are difficult to detect. Observation of these processes is limited by the seasonal inaccessibility of remote ecosystems, such as those in mountainous, snow- and ice-dominated areas. This isolation leads to a distinct gap in biogeochemical knowledge that ultimately affects the accuracy and confidence with which these ecosystems can be computationally modeled for the purpose of projecting change under different climate scenarios. To examine a high-altitude, headwater ecosystem’s role in methanogenesis, sulfate reduction, and groundwater-surface water exchange, water samples were continuously collected from the river and hyporheic zones (HZ) during winter isolation in the East River (ER), CO watershed. Measurements of continuously collected ER surface water revealed up to 50 μM levels of dissolved methane in July through September, while samples from 12 cm deep in the hyporheic zone at the same location showed a spring to early summer peak in methane with a strong biogenic signature (