Society of Pediatric Psychology Workforce Survey: Updated Factors Related to Compensation

2020 ◽  
Vol 45 (4) ◽  
pp. 434-444
Author(s):  
Jessica C Kichler ◽  
Jessica Valenzuela ◽  
Dave Barker ◽  
Amy E Noser ◽  
Cheryl L Brosig ◽  
...  
Keyword(s):  
Prediction Models ◽  
American Psychological Association ◽  
Doctoral Degree ◽  
Pediatric Psychology ◽  
Parametric Models ◽  
Academic Rank ◽  
Annual Conference ◽  
Group Status ◽  
Race Ethnicity ◽  
Racial Ethnicity

Abstract Objective The 2017 Society of Pediatric Psychology (SPP) Workforce Survey provides self-reported compensation by pediatric psychologists, identifies predictors of compensation, and establishes a better understanding of compensation within the context of gender and race/ethnicity minority status. Methods SPP members who attended the SPP Annual Conference (SPPAC; April 2017) were invited to complete the survey at the conference through electronic tablets provided on-site by the Workforce Survey Committee. The survey was subsequently distributed online to SPP members who did not complete the survey at SPPAC. The statistical analyses used for this salary data employed flexible semi-parametric models, cross-validation, and prediction models for both the overall sample and academic rank subgroups. Results Of 27 potential demographic and employment-related predictors from the 2017 SPP Workforce Survey, significant predictors of salary emerged within this sample: academic rank, time since obtaining doctoral degree, managing internal and external funds (of at least $50,000), years in primary employment position, obtaining Fellowship status in the American Psychological Association (APA), and managing other employees (at least 10 people). Given low response rates for males and individuals who identify as belonging to racial and ethnic minority subgroups, only limited, exploratory results are reported for these subgroups. Conclusions These findings suggest that not only is longevity in one’s career important but managing funds/personnel and obtaining professional designations are also predictors of higher salaries for pediatric psychologists, in general. Specific implications of salary according to the psychologist’s academic rank, gender, and racial/ethnicity group status are also explored.

Beyond Deep Learning: An Econometric Example

2020 ◽  
Vol 28 (Supp01) ◽  
pp. 31-38 ◽  
Author(s):  
Ruofan Liao ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Original Data ◽  
Parametric Model ◽  
Parametric Models ◽  
The Past ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Linear And Nonlinear

In the past, in many areas, the best prediction models were linear and nonlinear parametric models. In the last decade, in many application areas, deep learning has shown to lead to more accurate predictions than the parametric models. Deep learning-based predictions are reasonably accurate, but not perfect. How can we achieve better accuracy? To achieve this objective, we propose to combine neural networks with parametric model: namely, to train neural networks not on the original data, but on the differences between the actual data and the predictions of the parametric model. On the example of predicting currency exchange rate, we show that this idea indeed leads to more accurate predictions.

scholarly journals Racial/Ethnic Disparities in Cancer-Associated Thrombosis: A Population-Based Study

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 53-55
Author(s):  
Tatini Datta ◽  
Ann M Brunson ◽  
Anjlee Mahajan ◽  
Theresa Keegan ◽  
Ted Wun
Keyword(s):  
Racial Differences ◽  
Ethnic Differences ◽  
Brain Cancer ◽  
Lower Risk ◽  
Prediction Models ◽  
Population Based ◽  
Risk Prediction Models ◽  
Cancer Types ◽  
Race Ethnicity ◽  
Racial Ethnic

Introduction Risk factors for cancer-associated venous thromboembolism (CAT) include tumor type, stage at diagnosis, age, and patient comorbidities. In the general population, race/ethnicity has been identified as a risk factor for venous thromboembolism (VTE), with an increased risk of VTE in African Americans (AA) and a lower risk in Asians/Pacific Islanders (API) and Hispanics compared to non-Hispanic Whites (NHW) after adjustment for confounders such as demographic characteristics and patient comorbidities. However, the impact of race/ethnicity on the incidence of CAT has not been as well-studied. Methods We performed an observational cohort study using data from the California Cancer Registry linked to the California Patient Discharge Dataset and Emergency Department Utilization database. We identified a cohort of patients of all ages with first primary diagnosis of the 13 most common cancers in California between 2005-2014, including breast, prostate, lung, colorectal, bladder, uterine, kidney, pancreatic, stomach, ovarian, and brain cancer, Non-Hodgkin lymphoma, and multiple myeloma, and followed them for a diagnosis of VTE using specific ICD-9-CM codes. The 12-month cumulative incidences of VTE [pulmonary embolism (PE) alone, PE + lower extremity deep venous thrombosis (LE DVT), proximal LE DVT alone, and isolated distal DVT (iDDVT)] were determined by race/ethnicity, adjusted for the competing risk of death. Multivariable Cox proportional hazards regression models were performed to determine the effect of race/ethnicity on the risk of CAT adjusted for age, sex, cancer stage, type of initial therapy (surgery, chemotherapy, radiation therapy), neighborhood socioeconomic status, insurance type, and comorbidities. Patients with VTE prior to cancer diagnosis were excluded. Results A total of 736,292 cancer patients were included in the analysis cohort, of which 38,431 (5.2%) developed CAT within 12 months of diagnosis. When comparing the overall cancer cohort to those that developed VTE, AA (7.2 vs 10.5%) and NHW (61.9 vs 64.3%) appear to be over-represented, and API (11.6 vs 7.6%) under-represented in VTE cohort (Figure 1). The greatest disparities in incidence by race/ethnicity were seen in PE. AA had the highest and API had the lowest 12-month cumulative incidences for all cancer types except for brain cancer (Figure 2). These racial/ethnic differences were also seen among cumulative incidences of proximal LE DVT. For iDDVT, AA again had the highest cumulative incidence compared to the other racial groups among all cancer types except for myeloma. Racial differences were not as prominent when examining cumulative incidence of all VTE (PE+DVT). In adjusted multivariable models of overall CAT, compared to NHW, AA had the highest risk of CAT across all cancer types except for brain cancer and myeloma. API had significantly lower risk of CAT than NHW for all cancer types. When examining PE only in multivariable models, AA had significantly higher risk of PE compared to NHW in all cancer types except for kidney, stomach, brain cancer, and myeloma (Hazard Ratio (HR) ranging from 1.36 to 2.09). API had significantly lower risk of PE in all cancer types except uterine, kidney, and ovarian cancer (HR ranging from 0.45 to 0.87). Hispanics had lower risk of PE than NHW in breast, prostate, colorectal, bladder, pancreatic cancer, and myeloma (HR ranging from 0.64 to 0.87). [Figure 3] Conclusion In this large, diverse, population-based cohort of cancer patients, race/ethnicity was associated with risk of CAT even after adjusting for cancer stage, type of treatment, sociodemographic factors, and comorbidities. Overall, AA had a significantly higher incidence and API had a significantly lower incidence of CAT than NHW. These racial/ethnic differences were especially prominent when examining PE only, and PE appears to be the main driver for the racial differences observed in overall rates of CAT. Current risk prediction models for CAT do not include race/ethnicity as a parameter. Future studies might examine if incorporation of race/ethnicity into risk prediction models for CAT may improve their predictive value, as this may have important implications for thromboprophylaxis in this high-risk population. Disclosures Wun: Glycomimetics, Inc.: Consultancy.

scholarly journals Two decades of little change: An analysis of U.S. medical school basic science faculty by sex, race/ethnicity, and academic rank

PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0235190
Author(s):  
Christopher L. Bennett ◽  
Raquel Y. Salinas ◽  
Joseph J. Locascio ◽  
Edward W. Boyer
Keyword(s):  
Medical School ◽  
Basic Science ◽  
Academic Rank ◽  
Science Faculty ◽  
Race Ethnicity

scholarly journals Development of Tanner Stage–Age Adjusted CDC Height Curves for Research and Clinical Applications

2020 ◽  
Vol 4 (9) ◽  
Author(s):  
Bradley S Miller ◽  
Kyriakie Sarafoglou ◽  
O Yaw Addo
Keyword(s):  
National Health ◽  
Pubertal Development ◽  
Tanner Stage ◽  
Growth Patterns ◽  
Parametric Models ◽  
Maturation Stage ◽  
Health Examination ◽  
Pubertal Status ◽  
Health And Nutrition ◽  
Race Ethnicity

Abstract Background and Objective Variations in normal pubertal development, pubertal disorders, and race/ethnicity can lead to differences in growth patterns and timing that are not captured by the Centers for Disease Control and Prevention (CDC) height-for-chronological age (CAHeight) charts. Therefore, we sought to develop new Tanner stage–adjusted height-for-age (TSAHeight) charts accounting for these differences. Study Design Population-based Tanner staging and anthropometric data for 13 358 children age 8 to 18 years from 3 large US national surveys: National Health Examination Surveys (NHES cycle III); the Hispanic Health and Nutrition Examination Surveys (HHANES) and the third National Health and Nutrition Examination Surveys (NHANES III) were analyzed. TSAHeight semi-parametric models with additive age splines were used to develop smoothed TSAHeight curves accounting for maturation stage and calendar age. Results As expected, the TSAHeight curves did not track along the respective percentile curves for the CDC 2000 CAHeight curves. We generated race/ethnicity–nonspecific and race/ethnicity–specific TSAHeight charts stratified by sex and plotted against the CDC 2000 CAHeight curves to account for the pubertal status differences between these models. An online calculator to adjust height for pubertal status was created. Conclusions TSAHeight charts provide a much-needed tool to assess and manage linear growth for US children over the course of puberty. These tools may be useful in clinical management of children with pubertal timing variations.

Selection of Value-at-Risk models for MENA Islamic indices

2020 ◽  
Vol 11 (9) ◽  
pp. 1689-1708
Author(s):  
Wassim Ben Ayed ◽  
Ibrahim Fatnassi ◽  
Abderrazak Ben Maatoug
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Prediction Models ◽  
Market Risk ◽  
Parametric Models ◽  
Arch Model ◽  
Var Models ◽  
Content Type ◽  
Cent Level

Purpose The purpose of this study is to investigate the performance of Value-at-Risk (VaR) models for nine Middle East and North Africa Islamic indices using RiskMetrics and VaR parametric models. Design/methodology/approach The authors test the performance of several VaR models using Kupiec and Engle and Manganelli tests at 95 and 99 per cent levels for long and short trading positions, respectively, for the period from August 10, 2006 to December 14, 2014. Findings The authors’ findings show that the VaR under Student and skewed Student distribution are preferred at a 99 per cent level VaR. However, at 95 per cent level, the VaR forecasts obtained under normal distribution are more accurate than those generated using models with fat-tailed distributions. These results suggest that VaR is a good tool for measuring market risk. The authors support the use of RiskMetrics during calm periods and the asymmetric models (Generalized Autoregressive Conditional Heteroskedastic and the Asymmetric Power ARCH model) during stressed periods. Practical implications These results will be useful to investors and risk managers operating in Islamic markets, because their success depends on the ability to forecast stock price movements. Therefore, because a few Islamic financial institutions use internal models for their capital calculations, the regulatory committee should enhance market risk disclosure. Originality/value This study contributes to the knowledge in this area by improving our understanding of market risk management for Islamic assets during the stress periods. Then, it highlights important implications regarding financial risk management. Finally, this study fills a gap in the literature, as most empirical studies dealing with evaluating VaR prediction models have focused on quantifying the model risk in the conventional market.

scholarly journals Discrimination in healthcare as a barrier to care: experiences of socially disadvantaged populations in France from a nationally representative survey

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Joshua G. Rivenbark ◽  
Mathieu Ichou
Keyword(s):  
Healthcare Setting ◽  
Sub Saharan Africa ◽  
Representative Survey ◽  
Group Status ◽  
Healthcare Settings ◽  
Socially Disadvantaged ◽  
Race Ethnicity ◽  
Nationally Representative ◽  
Sub Saharan ◽  
Using Data

Abstract Background People in socially disadvantaged groups face a myriad of challenges to their health. Discrimination, based on group status such as gender, immigration generation, race/ethnicity, or religion, are a well-documented health challenge. However, less is known about experiences of discrimination specifically within healthcare settings, and how it may act as a barrier to healthcare. Methods Using data from a nationally representative survey of France (N = 21,761) with an oversample of immigrants, we examine rates of reported discrimination in healthcare settings, rates of foregoing healthcare, and whether discrimination could explain disparities in foregoing care across social groups. Results Rates of both reporting discrimination within healthcare and reporting foregone care in the past 12 months were generally highest among women, immigrants from Africa or Overseas France, and Muslims. For all of these groups, experiences of discrimination potentially explained significant proportions of their disparity in foregone care (Percent disparity in foregone care explained for: women = 17%, second-generation immigrants = 8%, Overseas France = 13%, North Africa = 22%, Sub-Saharan Africa = 32%, Muslims = 26%). Rates of foregone care were also higher for those of mixed origin and people who reported “Other Religion”, but foregone healthcare was not associated with discrimination for those groups. Conclusions Experiences of discrimination within the healthcare setting may present a barrier to healthcare for people that are socially disadvantaged due to gender, immigration, race/ethnicity, or religion. Researchers and policymakers should consider barriers to healthcare that lie within the healthcare experience itself as potential intervention targets.

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