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This experiment was conducted to determine the maximum dietary energy levels on growth performance and carcass characteristics of White Pekin duck. the Six dietary treatments were formulated based on their apparent metabolizable energy (AME) concentrations from 2,700 to 3,200 kcal/kg with a 100 kcal/kg gap to evaluate the accurate dietary AME requirement to address current knowledge and further issues for fulfilling the genetic potential of meat-type white Pekin ducklings. A total of 432 one-day-old male White Pekin ducklings were randomly allocated into one of six dietary treatments with six replicates (12 birds per pen). The diets were formulated as corn-soybean meal-based diets to meet or exceed the Nutrient Requirement of Poultry specification for meat-type ducks. Growth performance indices (i.e. average daily gain [ADG], average daily feed intake, feed conversion ratio) were measured weekly. Medium body weight (BW) ducklings from each pen were sacrificed to analyze the carcass traits and abdominal fat content on day 21. Obtained data were analyzed to estimate significant effect using the one-way ANOVA of IBM SPSS Statistics (Version, 25). If the p-value of the results were significant, differences in means among treatments were separated by Tukey’s post hoc test. Significant differences were then analyzed with a linear and quadratic broken model to estimate the accurate concentration of AME. Ducklings fed higher dietary AME diets increased (p < 0.05) BW, ADG. Ducklings fed higher AME than 2,900 kcal/kg diets increased abdominal fat accumulation and leg meat portion. The estimated requirement by linear plateau method showed from 3,000.00 kcal/kg to 3,173.03 kcal/kg whereas the requirement by quadratic plateau method indicated from 3,100.00 kcal/kg to 3,306.26 kcal/kg. Collectively, estimated dietary requirements exhibit diverse results based on the measured traits and analysis methods. All the estimated requirements in this experiment present higher than previous research, the maximum requirement for the next diet formulation should be selected by the purpose of the diet.

OBJECTIVE: This study aimed to assess the causal effect of a change in employment status on suicidal ideation and depressive symptoms by applying marginal structural models (MSM) with machine-learning (ML) algorithms. METHODS: We analyzed data from the 8–15^th waves (2013–2020) of the Korean Welfare Panel Study, a nationally representative longitudinal dataset. Our analysis included 13 294 observations from 3621 participants who had standard employment at baseline (2013–2019). Based on employment status at follow-up year (2014–2020), respondents were classified into two groups: (i) maintained standard employment (reference group), (ii) changed to non-standard employment. Suicidal ideation during the past year and depressive symptoms during the past week were assessed through self-report questionnaire. To apply the ML algorithms to the MSM, we conducted eight ML algorithms to build the propensity score indicating a change in employment status. Then, we applied the MSM to examine the causal effect by using inverse probability weights calculated based on the propensity score from ML algorithms. RESULTS: The random forest algorithm performed best among all algorithms, showing the highest area under the curve 0.702, 95% confidence interval (CI) 0.686–0.718. In the MSM with the random forest algorithm, workers who changed from standard to non-standard employment were 2.07 times more likely to report suicidal ideation compared to those who maintained standard employment (95% CI 1.16–3.70). A similar trend was observed in the analysis of depressive symptoms. CONCLUSIONS: This study found that a change in employment status could lead to a higher risk of suicidal ideation and depressive symptoms.

OBJECTIVES This study examined the association between lack of compensation for COVID-19-related overtime work (LCCOW) and burnout among emergency medical service (EMS) providers in Seoul, Korea. METHODS We conducted a cross-sectional survey of 693 EMS providers in Seoul, Korea. Participants were classified into 3 groups according to their experience of coronavirus disease 2019 (COVID-19)-related overtime work and LCCOW: (1) “did not experience,” (2) “experienced and was compensated,” and (3) “experienced and was not compensated.” Burnout was measured using the Korean version of the Copenhagen Burnout Inventory, which has 3 subdomains: personal burnout (PB), work-related burnout (WRB), and citizen-related burnout (CRB). Multiple linear regression was applied to examine whether LCCOW was associated with burnout after adjusting for potential confounders. RESULTS In total, 74.2% of participants experienced COVID-19-related overtime work, and 14.6% of those who worked overtime experienced LCCOW. COVID-19-related overtime work showed a statistically non-significant association with burnout. However, the association differed by LCCOW. Compared to the “did not experience” group, the “experienced and was not compensated” group was associated with PB (β=10.519; 95% confidence interval [CI], 3.455 to 17.584), WRB (β=10.339; 95% CI, 3.398 to 17.280), and CRB (β=12.290; 95% CI, 6.900 to 17.680), whereas no association was observed for the “experienced and was compensated” group. Furthermore, an analysis restricted to EMS providers who worked overtime due to COVID-19 showed that LCCOW was associated with PB (β=7.970; 95% CI, 1.064 to 14.876), WRB (β=7.276; 95% CI, 0.270 to 14.283), and CRB (β=10.000; 95% CI, 3.435 to 16.565). CONCLUSIONS This study suggests that LCCOW could be critical in worsening burnout among EMS providers who worked overtime due to COVID-19.