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Our study aimed to describe patient experience of information coordination between their primary care physician and specialists and to examine the associations between their experience and their personal and primary care characteristics. We conducted a cross-sectional study of Ontario residents rostered to a primary care physician and visited a specialist physician in the previous 12 months by linking population-based health administrative data to the Health Care Experience Survey collected between 2013 and 2020. We described respondents' sociodemographic and health care utilization characteristics and their experience of information coordination between their primary care physician and specialists. We measured the adjusted association between patient-reported measures of information coordination before and after respondents received care from a specialist physician and their type of primary care model. 1,460 out 20,422 (weighted 7.5%) of the respondents reported that their specialist physician did not have basic medical information about their visit from their primary care physician in the previous 12 months. 2,298 out of 16,442 (weighted 14.9%) of the respondents reported that their primary care physician seemed uninformed about the care they received from the specialist. Females, younger individuals, those with a college or undergraduate level of education, and users of walk-in clinics had a higher likelihood of reporting a lack of information coordination between the primary care and specialist physicians. Only respondents rostered to an enhanced fee-for-service model had a higher odds of reporting that the specialist physician did not have basic medical information about their visit compared to those rostered to a Family Health Team (OR 1.22, 95% Cl 1.12–1.40). We found no significant association between respondent's type of primary care model and that their primary care physician was uninformed about the care received from the specialist physician. In this population-based health study, respondents reported high information coordination between their primary care physician and specialists. Except for respondents rostered to an enhanced fee-for-service model of care, we did not find any difference in information coordination across other primary care models. [ABSTRACT FROM AUTHOR]

Introduction: Maintaining quality of life (QoL) has been identified as the primary goal of care services for person living with dementia (PLWD). Methods: A secondary analysis was conducted on five rounds of the National Health and Aging Trends Study (NHATS) over 4 years. A generalized estimating equation (GEE) was used to examine the prediction of relationship type on older adults' QoL through four domains: mental health, general health, functional limitations, and pain. Results: older adults cared for by an adult-child or multiple caregivers predicted increased risk for functional limitations after adjustment for their socio-demographic and dementia status (IRR = 1.53, CI [1.26, 1.86]; IRR = 1.36, CI [1.14, 1.61], respectively). The interaction between the relationship type and education was significant. Older adults with a high school education or below, who were cared for by an adult child, had a significantly higher risk of increasing functional limitations over 4 years compared to those cared for by a spouse/partner (contrast =.50, P =.01, 95% CI [.07,.93]; contrast=.52, P =.03, 95% CI [.03, 1.02]; respectively). Similarly, older adults with a high school education, who were cared for by multiple caregivers, also experienced a significantly higher risk of increasing functional limitations than those cared for by a spouse/partner (contrast =.44, P =.03, 95% CI [.02,.85]). Conclusion: Our findings provide evidence of the significant contribution of relationship type on PLWD's QoL changes over time. They also help to prioritize resource allocation while addressing PLWD's demands by socio-demographics such as education level. [ABSTRACT FROM AUTHOR]

Objectives: Determine whether levels of anxiety and depression, cognitive ability, and self-quarantining during and prior to the pandemic predict decreases in perceived functional ability. Design and Setting: Longitudinal data collected from the Canadian Longitudinal Study on Aging (CLSA) COVID-19 Questionnaire Study (2020) and core CLSA study (Follow-Up 1; 2014-2018). Participants: 17 541 CLSA participants. Measurements: Self-quarantining behaviours from questionnaires administered at Baseline (April 2020), Monthly, and Exit (December 2020) time points of the CLSA COVID-19 Questionnaire Study, levels of anxiety and depression at Baseline, perceived change in functional ability at Exit, and performance on neuropsychological tests (Rey Auditory Verbal Learning Task, Mental Alternation Task, Animal Fluency Test) and functional ability (Older Americans Resources and Services [OARS] Multidimensional Assessment Questionnaire) from the core CLSA study. Results: Greater cognitive ability pre-pandemic (B = −.003, P <.01), higher levels of anxiety (B = −.024, P <.01) and depressive symptoms (B = −.110, P <.01) at Baseline, and higher frequency of engaging in self-quarantining throughout the COVID-19 survey period (B = −.098, P <.01) were associated with perceived loss in functional ability at Exit. Self-quarantining behaviour was associated with perceived loss in functional ability only at average and high levels of depressive symptoms (B = −.013, P <.01). Conclusions: Older adults with higher cognitive and lower functional ability prior to the pandemic were at greater risk of decreased perceived functional ability during the first year of the pandemic, as were those who experienced greater levels of anxiety and depressive symptoms during the pandemic. Strategies/interventions to preserve functional ability in older adults with cognitive independence prior to future pandemics are warranted. [ABSTRACT FROM AUTHOR]

Increases in organic carbon within agricultural soils are widely recognized as a "negative emission" that removes CO2 from the atmosphere. Accurate quantification of soil organic carbon (SOC) to a certain depth in the spatial domain is critical for the effective implementation of improved land management practices in croplands. Currently, there is a lack of understanding regarding what depth strategy should be used to estimate SOC at 0–30 cm when sample datasets come from multiple depths. Furthermore, few studies have examined depth strategies for mapping SOC at the agricultural management level (i.e., field level), opting instead for point-based analysis. Here, three types of approaches with different depth strategies were evaluated for their ability to quantify 0–30 cm SOC content based on soil samples from 0–5 (surface), 5–30 (subsurface), and 0–30 cm (full column). These approaches involved the generalized additive model and machine learning techniques, i.e., artificial neural networks, random forest, and XGBoost. The soil samples used for the model evaluation and selection consisted of the newly collected samples in 2020–2022 and the Rapid Carbon Assessment (RaCA) legacy samples collected in 2010–2011. Environmental covariates corresponding to these SOC measurements were used in model training, including long-term physical climate, short-term weather, topographic and edaphic, and remotely sensed variables. Among the models evaluated in this study, the XGB regression model with a full column depth assignment strategy yielded the best prediction performance for 0–30 cm SOC content, with an r2 (squared Pearson correlation coefficient) of 0.48, an RMSE (root mean square error) of 0.29%, an ME (mean error) of 0.06%, an MAE of 0.25%, and an MEC (modeling efficiency coefficient) of 0.36 at the pixel level and an r2 of 0.64, an RMSE of 0.32%, an ME of −0.20%, an MAE of 0.28%, and an MEC of 0.48 at the field level. This study highlights that machine learning models with a full column depth strategy should be used to quantify 0–30 cm SOC content in agricultural soils over the continental United States (CONUS). [ABSTRACT FROM AUTHOR]