Longitudinal associations between passions and adjustment in adolescence: Positive mood and unstructured leisure activities as mediators

Passions are activities that people find important, like or enjoy, and on which they spend large amounts of time. Research examining passions in adolescence has been limited, despite a tendency for adolescents to explore their identity by trying new activities (Dworkin et aI., 2003). The purpose of the present study was to examine the association between adolescent passions and positive adjustment (psychological well-being, optimism, purpose in life, and low risktaking), as well as investigate possible underlying mechanisms for the link between passions and adjustment. High school students (N=2270, 48.7% female) from Southern Ontario completed questionnaires in grades 10, 11, and 12. Path analyses were conducted to examine cross-lag paths among all study variables. Passions predicted higher optimism and purpose, as well as lower negative risk-taking, over time, but these adjustment indicators in tum did not predict higher passions over time. Additionally, positive mood and unstructured leisure activities partially mediated these associations. Passions appears to be important for adolescent adjustment, and may serve as a protective factor or help to foster thriving

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Geometry of spiking patterns in early visual cortex: a topological data analytic approach

International audienceIn the brain, spiking patterns live in a high-dimensional space of neurons and time. Thus, determining the intrinsic structure of this space presents a theoretical and experimental challenge. To address this challenge, we introduce a new framework for applying topological data analysis (TDA) to spike train data and use it to determine the geometry of spiking patterns in the visual cortex. Key to our approach is a parametrized family of distances based on the timing of spikes that quantifies the dissimilarity between neuronal responses. We applied TDA to visually driven single-unit and multiple single-unit spiking activity in macaque V1 and V2. TDA across timescales reveals a common geometry for spiking patterns in V1 and V2 which, among simple models, is most similar to that of a low-dimensional space endowed with Euclidean or hyperbolic geometry with modest curvature. Remarkably, the inferred geometry depends on timescale and is clearest for the timescales that are important for encoding contrast, orientation and spatial correlations

Caregiver burden assessed with: Zarit Burden Interview (ZBI).

Caregiver burden assessed with: Zarit Burden Interview (ZBI).</p

Review studies not included in meta-analysis.

Continuing education for dementia has been shown to be beneficial by improving informal caregiver knowledge, dementia care, management, and caregiver physical and mental health. Technology-based dementia education has been noted to have equivalent effects as in-person education, but with the added benefit of asynchronous and/or remote delivery, which increases accessibility. Using Cochrane review methodology, this study systematically reviewed the literature on technology-based dementia education and its impacts on caregivers. Technology-based delivery included dementia education delivered via the Internet, telephone, telehealth, videophone, computer, or digital video device (DVD). In the review, twenty-eight studies were identified with fourteen included in a meta-analysis, and these data revealed a significant small effect of technologically based dementia education on reducing caregiver depression, and a medium effect on reducing caregiver distress in response to caregivers’ observations of behavioral problems displayed by persons with dementia. No evidence was found for a significant effect of the educational intervention on caregiver burden or self-efficacy, which are known to be gendered aspects of caregiving. None of the studies included in the meta-analysis reported separate outcomes for male and female care providers, which has implications for gendered caregiving norms and aspects of care.Registration number: PROSPERO 2018 CRD42018092599.</div

Caregiving self-efficacy assessed with: Caregiving Self-Efficacy Scale (CSES).

Caregiving self-efficacy assessed with: Caregiving Self-Efficacy Scale (CSES).</p

Adapted quality rating criteria for non-randomized controlled trial studies (studies not included in meta-analysis).

Adapted quality rating criteria for non-randomized controlled trial studies (studies not included in meta-analysis).</p

Teaching and learning approaches.

Continuing education for dementia has been shown to be beneficial by improving informal caregiver knowledge, dementia care, management, and caregiver physical and mental health. Technology-based dementia education has been noted to have equivalent effects as in-person education, but with the added benefit of asynchronous and/or remote delivery, which increases accessibility. Using Cochrane review methodology, this study systematically reviewed the literature on technology-based dementia education and its impacts on caregivers. Technology-based delivery included dementia education delivered via the Internet, telephone, telehealth, videophone, computer, or digital video device (DVD). In the review, twenty-eight studies were identified with fourteen included in a meta-analysis, and these data revealed a significant small effect of technologically based dementia education on reducing caregiver depression, and a medium effect on reducing caregiver distress in response to caregivers’ observations of behavioral problems displayed by persons with dementia. No evidence was found for a significant effect of the educational intervention on caregiver burden or self-efficacy, which are known to be gendered aspects of caregiving. None of the studies included in the meta-analysis reported separate outcomes for male and female care providers, which has implications for gendered caregiving norms and aspects of care.Registration number: PROSPERO 2018 CRD42018092599.</div