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This article describes the development of priorities and actions to improve the state of research, policy, and practice related to accessible housing in Canada for persons with disability or with accessible housing needs. A modified Delphi approach with an expert cross-sectoral panel was used to gain convergence on a set of priorities for advancing the accessible housing field in Canada. This included circulating an anonymous pre-meeting survey (N = 49) followed by an in-person planning meeting (N = 45). The expert panel at the in-person meeting identified three clusters of priorities from an initial list of 21 priorities, which included: 1) engaging with all levels of government to support accessible housing efforts; 2) developing educational resources to raise awareness about accessible housing, and creating services to facilitate locating and acquiring accessible housing; and 3) fostering meaningful engagement across key interest groups and sectors to find solutions to enact positive change in this space. The findings provide an initial roadmap for bringing greater cohesion to the accessible housing field, which will enable cross-sectoral partnerships and collective action towards informing the next generation of accessible housing standards, regulations and practices for people with accessible housing needs., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Hitzig et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Understanding the immune response kinetics to SARS-CoV-2 infection and COVID-19 vaccination is important in nursing home (NH) residents, a high-risk population., Methods: An observational longitudinal evaluation of 37 consenting vaccinated NH residents with/without SARS-CoV-2 infection from October 2020 to July 2022 was conducted to characterize the immune response to spike protein due to infection and/or mRNA COVID-19 vaccine. Antibodies (IgG) to SARS-CoV-2 full-length spike, nucleocapsid, and receptor binding domain protein antigens were measured, and surrogate virus neutralization capacity was assessed using Meso Scale Discovery immunoassays. The participant's spike exposure status varied depending on the acquisition of infection or receipt of a vaccine dose. Longitudinal linear mixed effects modeling was used to describe trajectories based on the participant's last infection or vaccination; the primary series mRNA COVID-19 vaccine was considered two spike exposures. Mean antibody titer values from participants who developed an infection post receipt of mRNA COVID-19 vaccine were compared with those who did not. In a subset of participants (n = 15), memory B cell (MBC) S-specific IgG (%S IgG) responses were assessed using an ELISPOT assay., Results: The median age of the 37 participants at enrollment was 70.5 years; 30 (81%) had prior SARS-CoV-2 infection, and 76% received Pfizer-BioNTech and 24% Moderna homologous vaccines. After an observed augmented effect with each spike exposure, a decline in the immune response, including %S IgG MBCs, was observed over time; the percent decline decreased with increasing spike exposures. Participants who developed an infection at least two weeks post-receipt of a vaccine were observed to have lower humoral antibody levels than those who did not develop an infection post-receipt., Conclusions: These findings suggest that understanding the durability of immune responses in this vulnerable NH population can help inform public health policy regarding the timing of booster vaccinations as new variants display immune escape., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

The problem of identifying common concepts in the sciences and deciding when new ideas have emerged is an open one. Metascience researchers have sought to formalize principles underlying stages in the life cycle of scientific research, understand how knowledge is transferred between scientists and stakeholders, and explain how new ideas are generated and take hold. Here, we model the state of scientific knowledge immediately preceding new directions of research as a metastable state and the creation of new concepts as combinatorial innovation. Through a novel approach combining natural language clustering and citation graph analysis, we predict the evolution of ideas over time and thus connect a single scientific article to past and future concepts in a way that goes beyond traditional citation and reference connections., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Koneru et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Construct definitions of empathy have sought to distinguish between different dimensions of empathetic capacity that are significantly associated with psychological distress or wellbeing. Research has provided substantial evidence differentiating affective and cognitive empathy; however, more recent research has cited the importance of a third domain represented by empathetic behaviors and compassionate intent to comfort others. Examining developmental and maturational stage during the rapid transitional period of early adolescence is needed to model developmental trajectories, mechanisms of change and mental health outcomes. This study aims to assess relationships between pubertal developmental stage, dimensions of empathy, and depression, anxiety and externalizing behaviors among early adolescents. A cross-sectional survey among young adolescents ages 9-12 years was conducted in Dar es Salaam, Tanzania. The relationships between pubertal developmental stage, affective, cognitive, and behavioral empathy scores and internalizing and externalizing symptoms were evaluated using hierarchical regression modeling. Structural equation modeling was used to test a theoretical model of structural paths between these variables. A sample of 579 very young adolescents (270 boys and 309 girls) aged 9-12 years participated in the study. Pubertal development scale scores were associated with affective, cognitive, and behavioral empathy. Adolescents who had greater behavioral empathy scores reported lower internalizing and externalizing symptoms. Adolescents who had transitioned further through puberty and had higher cognitive empathy scores and reported higher internalizing symptoms. These findings support the importance of pubertal developmental stage in assessing risk and protective paths to mental health during adolescence. While empathetic capacity is widely perceived to be a positive trait, dimensional analysis of empathy among early adolescents indicates that behavioral skills and compassionate acts may be particularly protective and promote positive mental health outcomes., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Cherewick et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

As we uncover the ubiquity of hybridization in nature, determining how natural selection acts on hybrids has newfound importance for speciation. A study in PLOS Biology uses threespine stickleback to detect a genomic signature of ecological incompatibilities., Competing Interests: The authors have declared that no competing interests exist.

Enhanced immune functioning in response to biodiversity may explain potential health benefits from exposure to green space. Using unique data on urban forest biodiversity at the zip code level for California measured from 2014 to 2019 we test whether greater diversity of street trees is associated with reduced death from cardiovascular disease. We find that urban forests with greater biodiversity measured via the Shannon Index at the genus level are associated with a lower mortality rate for heart disease and stroke. Our estimates imply that increasing the Shannon Index by one standard deviation (0.64) is associated with a decrease in the mortality rate of 21.4 per 100,000 individuals for heart disease or 13% and 7.7 per 100,000 individuals for stroke or 16%. Our estimates remain robust across several sensitivity checks. A policy simulation for tree planting in Los Angeles based on our estimates suggests that if these relationships were causal, investment in planting for a more biodiverse set of street trees would be a cost-effective way to reduce mortality related to cardiovascular disease in urban areas., Competing Interests: No authors have competing interests.

Background: Penalised regression methods are a useful atheoretical approach for both developing predictive models and selecting key indicators within an often substantially larger pool of available indicators. In comparison to traditional methods, penalised regression models improve prediction in new data by shrinking the size of coefficients and retaining those with coefficients greater than zero. However, the performance and selection of indicators depends on the specific algorithm implemented. The purpose of this study was to examine the predictive performance and feature (i.e., indicator) selection capability of common penalised logistic regression methods (LASSO, adaptive LASSO, and elastic-net), compared with traditional logistic regression and forward selection methods., Design: Data were drawn from the Australian Temperament Project, a multigenerational longitudinal study established in 1983. The analytic sample consisted of 1,292 (707 women) participants. A total of 102 adolescent psychosocial and contextual indicators were available to predict young adult daily smoking., Findings: Penalised logistic regression methods showed small improvements in predictive performance over logistic regression and forward selection. However, no single penalised logistic regression model outperformed the others. Elastic-net models selected more indicators than either LASSO or adaptive LASSO. Additionally, more regularised models included fewer indicators, yet had comparable predictive performance. Forward selection methods dismissed many indicators identified as important in the penalised logistic regression models., Conclusions: Although overall predictive accuracy was only marginally better with penalised logistic regression methods, benefits were most clear in their capacity to select a manageable subset of indicators. Preference to competing penalised logistic regression methods may therefore be guided by feature selection capability, and thus interpretative considerations, rather than predictive performance alone., Competing Interests: The authors have declared that no competing interests exist.

Background: To optimize patient education, it is important to understand what healthcare professionals perceive to be ideal oncology medication education for patients to receive, and what they feel is their role and the role of others in its delivery. Education provided to patients is an important component of chemotherapy as it has been shown to benefit and positively impact patients who receive it. Educational interventions are often provided by multidisciplinary teams with the goal of improving patient care. However, few studies have explored the roles of healthcare professionals in delivering oncology medication education., Objective: To explore the perspectives of healthcare professionals working in medical, gynaecological or hematological oncology to identify what they perceive to be optimal oncology medication education for patients., Methods: Healthcare professionals (physicians, nurses and pharmacists) working in medical, gynaecological or hematological oncology at the Nova Scotia Health Authority, Central Zone were invited to participate in one-on-one, semi-structured interviews which were audio-recorded, transcribed and analyzed using thematic analysis., Findings: Fifteen interviews, including five physicians, four nurses and six pharmacists were conducted from February to April 2018. Four major themes were identified: Delivery of oncology medication education, Facilitating the patient learning process, Multidisciplinary Approach and Understanding barriers to the healthcare professional in providing education., Conclusion: The identified themes uncovered novel ideas about how healthcare professionals felt oncology medication education could ideally be delivered to patients, and supported findings in the literature. Although participants discussed barriers to their ability to deliver optimal education, they also identified ways in which they can facilitate patient learning, for example, through the reinforcement of education. Participants recognized the importance of increasing collaboration and communication with the multidisciplinary team. This research will inform the design of any new models for oncology medication education at the Nova Scotia Health Authority, Central Zone and potentially other sites., Competing Interests: The authors have declared that no competing interests exist.

Objective: Working through a depressive illness can improve mental health but also carries risks and costs from reduced concentration, fatigue, and poor on-the-job performance. However, evidence-based recommendations for managing work attendance decisions, which benefit individuals and employers, are lacking. Therefore, this study has compared the costs and health outcomes of short-term absenteeism versus working while ill ("presenteeism") amongst employed Australians reporting lifetime major depression., Methods: Cohort simulation using state-transition Markov models simulated movement of a hypothetical cohort of workers, reporting lifetime major depression, between health states over one- and five-years according to probabilities derived from a quality epidemiological data source and existing clinical literature. Model outcomes were health service and employment-related costs, and quality-adjusted-life-years (QALYs), captured for absenteeism relative to presenteeism, and stratified by occupation (blue versus white-collar)., Results: Per employee with depression, absenteeism produced higher mean costs than presenteeism over one- and five-years ($42,573/5-years for absenteeism, $37,791/5-years for presenteeism). However, overlapping confidence intervals rendered differences non-significant. Employment-related costs (lost productive time, job turnover), and antidepressant medication and service use costs of absenteeism and presenteeism were significantly higher for white-collar workers. Health outcomes differed for absenteeism versus presenteeism amongst white-collar workers only., Conclusions: Costs and health outcomes for absenteeism and presenteeism were not significantly different; service use costs excepted. Significant variation by occupation type was identified. These findings provide the first occupation-specific cost evidence which can be used by clinicians, employees, and employers to review their management of depression-related work attendance, and may suggest encouraging employees to continue working is warranted.

In human vision, acuity and color sensitivity are greatest at the center of fixation and fall off rapidly as visual eccentricity increases. Humans exploit the high resolution of central vision by actively moving their eyes three to four times each second. Here we demonstrate that it is possible to classify the task that a person is engaged in from their eye movements using multivariate pattern classification. The results have important theoretical implications for computational and neural models of eye movement control. They also have important practical implications for using passively recorded eye movements to infer the cognitive state of a viewer, information that can be used as input for intelligent human-computer interfaces and related applications.