Objectives/Goals: To explore the caregivers’ lived experiences related to facilitators of and barriers to effective primary care or neurology follow-up for children discharged from the pediatric emergency department (PED) with headaches. Methods/Study Population: We used the descriptive phenomenology qualitative study design to ascertain caregivers’ lived experiences with making follow-up appointments after their child’s PED visit. We conducted semi-structured interviews with caregivers of children with headaches from 4 large urban PEDs over HIPAA-compliant Zoom conferencing platform. A facilitator/co-facilitator team (JH and SL) guided all interviews, and the audio of which was transcribed using the TRINT software. Conventional content analysis was performed by two coders (JH and AS) to generate new themes, and coding disputes were resolved by team members using Atlas TI (version 24). Results/Anticipated Results: We interviewed a total of 11 caregivers (9 mothers, 1 grandmother, and 1 father). Among interviewees, 45% identified as White non-Hispanic, 45% Hispanic, 9% as African-American, and 37% were publicly insured. Participants described similar experiences in obtaining follow-up care that included long waits to obtain neurology appointments. Participants also described opportunities to overcome wait times that included offering alternative healthcare provider types as well as telehealth options. Last, participants described desired action while awaiting neurology appointments such as obtaining testing and setting treatment plans. Discussion/Significance of Impact: Caregivers perceived time to appointment as too long and identified practical solutions to ease frustrations while waiting. Future research should explore sharing caregiver experiences with primary care providers, PED physicians, and neurologists while developing plans to implement caregiver-informed interventions.

Objectives/Goals: The goal of the RC2 Systems Marketing Analysis for Research Translation (SMART) special innovation program is to develop and test a structured approach for working with research teams and communities to accelerate the translation of clinical and community innovations to address health inequities by integrating social marketing with community-based system dynamics. Methods/Study Population: The SMART program is a consultancy service for CTS teams focused on selecting and tailoring implementation strategies for advancing equity. We use social marketing for understanding the alignment of practice innovation feature sets with community priorities for advancing health equity; and community-based system dynamics to understand and refine the dynamics of scaling up and sustaining the implementation of innovations with sufficient reach to address regional health inequities. The program is implemented as community-engaged group model-building workshops with research teams, with follow-up marketing analyses and computer simulation of implementation strategies of innovations and development of implementation roadmaps. We use developmental program evaluation to revise the SMART program. Results/Anticipated Results: Anticipated results from piloting the SMART innovation program with four research teams include (1) design matrices pre and post-workshop for each innovation; (2) system dynamics simulation models and analyses of implementation and scale-up of innovations; (3) analysis of the SMART program for highest impact, with priors for estimating subsequent SMART program performance; and (4) a revised SMART program based on results from the developmental program evaluation. Discussion/Significance of Impact: This work highlights the feasibility and benefits of combining methods that have been cited in implementation science for understanding the complexity of implementation to accelerate the translation of innovations into clinical and community settings for advancing health equity.

In the last few decades, the study of ordinal data in which the variable of interest is not exactly observed but only known to be in a specific ordinal category has become important. To emphasize that the problem is not specific to a specific discipline we will use the neutral term coarsened observation. For single-equation models estimation of the latent linear model by Maximum Likelihood (ML) is routine. But, for higher-dimensional multivariate models it is computationally cumbersome as estimation requires the evaluation of multivariate normal distribution functions on a large scale. Our proposed alternative estimation method, based on the Generalized Method of Moments (GMM), circumvents this multivariate integration problem. It can be implemented by repeated application of standard techniques and provides a simpler and faster approach than the usual ML approach. It is applicable to multiple-equation models with $K$-dimensional error correlation matrices and ${J}_k$ response categories for the kth equation. It also yields a simple method to estimate polyserial and polychoric correlations. Comparison of our method with the outcomes of the Stata ML procedure cmp yields estimates that are not statistically different, while estimation by our method requires only a fraction of the computing time.

The spotted hyaena Crocuta crocuta is relatively understudied across its range despite evidence of widespread declines. It is therefore essential that robust baseline population density assessments are conducted to inform current management and future conservation policy. In Mozambique this is urgent as decades of armed conflict followed by unchecked poaching have resulted in large-scale wildlife declines and extirpations. We conducted the first robust population density estimate for a spotted hyaena population in Mozambique using spatially explicit capture–recapture methodologies. We recorded a relatively low population density of 0.8–2.1 hyaenas/100 km2 in the wildlife management area Coutada 11 in the Zambezi Delta of central Mozambique in 2021. These densities are well below the estimated carrying capacity for the landscape and are comparable to published densities in high human-impact, miombo woodland-dominated and arid environments. The combination of historical armed conflict, marginal trophy hunting and bushmeat poaching using wire snares and gin traps (with physical injuries evident in 9% of identified individuals) presents persistent anthropogenic pressure, limiting the post-war recovery of this resident hyaena population. We provide insights into the dynamics of hyaena population status and recovery in such post-war landscapes, adding to mounting evidence that the species is less resilient to severe anthropogenic disturbances than previously believed. We recommend long-term monitoring of this and other carnivore populations in post-war landscapes to ascertain demographic trends and implement effective conservation interventions for population recovery.

The modern idea of purebred dogs has come under increasing critical scrutiny over recent decades. In light of this critical focus and other developments in society, some new trends in how companion dogs are bred and acquired have emerged. This means a diminishing influence from traditional kennel clubs with more dogs being sold without a pedigree, stricter legal restrictions on dog breeding, growing popularity of deliberate crosses of established breeds (i.e. so-called designer breeds) and growing hype around the benefits of mixed-breed dogs. We give an overview of these trends and discuss to what extent they will serve to promote dogs that are innately healthy, have good welfare and function well in their various roles in today’s world. We argue that newly invented designer breeds and mixed breeds also have worrying health and behavioural problems, and that the predictability of purebred dogs with respect to body size, basic behaviours, known need for grooming, disorder profiles and other attributes may well offer some benefits for a satisfying human-dog relationship seen from both sides. The optimal future seems to lie in the middle ground, where the future organised dog world (i.e. kennel and breed clubs or their successor organisations) will need to re-open the breed registries, remove wording from breed standards that currently promotes extreme conformation, support selection against disease-predisposing genotypes and phenotypes and refocus dog showing and breeding to promote health and appropriate behaviour.

The European Clozapine Task Force is a group of psychiatrists and pharmacologists practicing in 18 countries under European Medicines Agency (EMA) regulation, who are deeply concerned about the underuse of clozapine in European countries. Although clozapine is the most effective antipsychotic for people with treatment-resistant schizophrenia, a large proportion of them do not have access to this treatment. Concerns about clozapine-induced agranulocytosis and stringent blood monitoring rules are major barriers to clozapine prescribing and use. There is a growing body of evidence that the incidence of clozapine-induced agranulocytosis is very low after the first year of treatment. Maintaining lifelong monthly blood monitoring after this period contributes to unjustified discontinuation of clozapine. We leverage recent and replicated evidence on the long-term safety of clozapine to call for the revision and updating of the EMA’s blood monitoring rules, thus aiming to overcome this major barrier to clozapine prescribing and use. We believe the time has come for relaxing the rules without increasing the risks for people using clozapine in Europe.

We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a finite mixture of normal distributions. This approach combines the flexibility of semiparametric, latent class models that assume common parameters for each sub-population and the parsimony of random effects models that assume normal distributions for the regression parameters. The number of subpopulations is selected to maximize the posterior probability of the model being true. Simulations are presented which document the performance of the methodology for synthetic data with known heterogeneity and number of sub-populations. An application is presented concerning preferences for various aspects of personal computers.

The key assumption of conditional independence of item responses given latent ability in item response theory (IRT) models is addressed for multistage adaptive testing (MST) designs. Routing decisions in MST designs can cause patterns in the data that are not accounted for by the IRT model. This phenomenon relates to quasi-independence in log-linear models for incomplete contingency tables and impacts certain types of statistical inference based on assumptions on observed and missing data. We demonstrate that generalized residuals for item pair frequencies under IRT models as discussed by Haberman and Sinharay (J Am Stat Assoc 108:1435–1444, 2013. https://doi.org/10.1080/01621459.2013.835660) are inappropriate for MST data without adjustments. The adjustments are dependent on the MST design, and can quickly become nontrivial as the complexity of the routing increases. However, the adjusted residuals are found to have satisfactory Type I errors in a simulation and illustrated by an application to real MST data from the Programme for International Student Assessment (PISA). Implications and suggestions for statistical inference with MST designs are discussed.

Two revisions of interactive MDS data selection procedures are presented. One revision improves the estimates of the MDS parameters by adding an analysis of the volume of the spatial coordinates of stimuli. Frames of stimuli augmented by an analysis of volume should more nearly surround the swarm of stimulus points. The second revision, based on randomly ordering the list of stimuli, permits more efficient data designs to be selected by reducing the number of judgments collected but never analyzed.

Multiple regression is frequently used across the various social sciences to analyze cross-sectional data. However, it can often times be challenging to justify the assumption of common regression coefficients across all respondents. This manuscript presents a heterogeneous Bayesian regression model that enables the estimation of individual-level-regression coefficients in cross-sectional data involving a single observation per response unit. A Gibbs sampling algorithm is developed to implement the proposed Bayesian methodology. A Monte Carlo simulation study is constructed to assess the performance of the proposed methodology across a number of experimental factors. We then apply the proposed method to analyze data collected from a consumer psychology study that examines the differential importance of price and quality in determining perceived value evaluations.

We propose a generalization of the speed–accuracy response model (SARM) introduced by Maris and van der Maas (Psychometrika 77:615–633, 2012). In these models, the scores that result from a scoring rule that incorporates both the speed and accuracy of item responses are modeled. Our generalization is similar to that of the one-parameter logistic (or Rasch) model to the two-parameter logistic (or Birnbaum) model in item response theory. An expectation–maximization (EM) algorithm for estimating model parameters and standard errors was developed. Furthermore, methods to assess model fit are provided in the form of generalized residuals for item score functions and saddlepoint approximations to the density of the sum score. The presented methods were evaluated in a small simulation study, the results of which indicated good parameter recovery and reasonable type I error rates for the residuals. Finally, the methods were applied to two real data sets. It was found that the two-parameter SARM showed improved fit compared to the one-parameter SARM in both data sets.

Herbicides have been placed in global Herbicide Resistance Action Committee (HRAC) herbicide groups based on their sites of action (e.g., acetolactate synthase–inhibiting herbicides are grouped in HRAC Group 2). A major driving force for this classification system is that growers have been encouraged to rotate or mix herbicides from different HRAC groups to delay the evolution of herbicide-resistant weeds, because in theory, all active ingredients within a herbicide group physiologically affect weeds similarly. Although herbicide resistance in weeds has been studied for decades, recent research on the biochemical and molecular basis for resistance has demonstrated that patterns of cross-resistance are usually quite complicated and much more complex than merely stating, for example, a certain weed population is Group 2-resistant. The objective of this review article is to highlight and describe the intricacies associated with the magnitude of herbicide resistance and cross-resistance patterns that have resulted from myriad target-site and non–target site resistance mechanisms in weeds, as well as environmental and application timing influences. Our hope is this review will provide opportunities for students, growers, agronomists, ag retailers, regulatory personnel, and research scientists to better understand and realize that herbicide resistance in weeds is far more complicated than previously considered when based solely on HRAC groups. Furthermore, a comprehensive understanding of cross-resistance patterns among weed species and populations may assist in managing herbicide-resistant biotypes in the short term by providing growers with previously unconsidered effective control options. This knowledge may also inform agrochemical company efforts aimed at developing new resistance-breaking chemistries and herbicide mixtures. However, in the long term, nonchemical management strategies, including cultural, mechanical, and biological weed management tactics, must also be implemented to prevent or delay increasingly problematic issues with weed resistance to current and future herbicides.

During a 2019 Chilean Antarctic Scientific Expedition (ECA 55) studying crustose coralline algae (CCA) diversity on the Antarctic Peninsula, bleaching of these algae was observed for the first time in this region. Here, we present initial findings on the physiological state of bleached and normally pigmented CCA (Clathromorphum sp.) assessed using chlorophyll-a fluorescence induction pulse amplitude modulation. The study site experienced high light exposure and salinity in the water column. Our analyses found that bleached CCA have relatively healthy photophysiology responses but lower photosynthetic efficiency, which could be associated with the low salinities recorded in the study area. However, seasonal monitoring and mesocosm experiments across the southern polar latitudes are urgently required to confirm this hypothesis.

Evidence on the effectiveness and implementation of mental health and psychosocial support (MHPSS) interventions for men in humanitarian settings is limited. Moreover, engagement and retention of men in such interventions has been challenging. Adaptations may therefore be required to improve the appropriateness and acceptability of these interventions for men. This study conducted formative research and examined the feasibility of combining an MHPSS intervention, Self-Help Plus, with a brief intervention to reduce harmful alcohol use among refugee men in Uganda. We conducted a cluster randomized feasibility trial comparing the combined alcohol intervention and Self-Help Plus, Self-Help Plus alone and enhanced usual care. Participants were 168 South Sudanese refugee men in Rhino Settlement who reported moderate or high levels of psychological distress. Session attendance was adequate: all sessions had at least 69% of participants present. Participant outcome measures, including symptoms of psychological distress, functional impairment, self-defined problems, depressive symptoms, post-traumatic stress symptoms, overall substance use risk, substance specific risk (alcohol, cannabis, stimulants and sedatives) and well-being, were sensitive to change. A combined approach to addressing mental health and alcohol use appears feasible among men in refugee settings, but further research is needed to examine the effectiveness of combined interventions among men.