Educational Outcomes of Childhood Survivors of Critical Illness-A Population-Based Linkage Study.

OBJECTIVES: Major postintensive care sequelae affect up to one in three adult survivors of critical illness. Large cohorts on educational outcomes after pediatric intensive care are lacking. We assessed primary school educational outcomes in a statewide cohort of children who survived PICU during childhood. DESIGN: Multicenter population-based study on children less than 5 years admitted to PICU. Using the National Assessment Program-Literacy and Numeracy database, the primary outcome was educational achievement below the National Minimum Standard (NMS) in year 3 of primary school. Cases were compared with controls matched for calendar year, grade, birth cohort, sex, socioeconomic status, Aboriginal and Torres Strait Islander status, and school. Multivariable logistic regression models to predict educational outcomes were derived. SETTING: Tertiary PICUs and mixed ICUs in Queensland, Australia. PATIENTS: Children less than 5 years admitted to PICU between 1998 and 2016. INTERVENTIONS: Not applicable. MEASUREMENTS AND MAIN RESULTS: Year 3 primary school data were available for 5,017 PICU survivors (median age, 8.0 mo at first PICU admission; interquartile range, 1.9-25.2). PICU survivors scored significantly lower than controls across each domain (p < 0.001); 14.03% of PICU survivors did not meet the NMS compared with 8.96% of matched controls (p < 0.001). In multivariate analyses, socioeconomic status (odds ratio, 2.14; 95% CI, 1.67-2.74), weight (0.94; 0.90-0.97), logit of Pediatric Index of Mortality-2 score (1.11; 1.03-1.19), presence of a syndrome (11.58; 8.87-15.11), prematurity (1.54; 1.09-2.19), chronic neurologic conditions (4.38; 3.27-5.87), chronic respiratory conditions (1.65; 1.24-2.19), and continuous renal replacement therapy (4.20; 1.40-12.55) were independently associated with a higher risk of not meeting the NMS. CONCLUSIONS: In this population-based study of childhood PICU survivors, 14.03% did not meet NMSs in the standardized primary school assessment. Socioeconomic status, underlying diseases, and severity on presentation allow risk-stratification to identify children most likely to benefit from individual follow-up and support.

Uneven impacts of COVID-19 on the attendance rates of secondary school students from different socioeconomic backgrounds in Australia: A quasi-experimental analysis of administrative data.

This paper contributes to the growing body of research that demonstrates uneven impacts of the COVID-19 pandemic on educational outcomes of students from different socioeconomic status (SES) backgrounds. We evaluate the early impacts of COVID-19 on student attendance in secondary school and show how these impacts depend on students' SES. We employ a quasi-experimental design, using difference-in-differences (DiD) estimation extended to incorporate third-order differences over time between low-SES and other students, and pre- versus during-COVID-19, leveraging robust administrative data extracted from the registers of the Tasmanian Department of Education. Using data from multiple cohorts of secondary school students in government schools in Tasmania (N = 14,135), we find that while the attendance rates were similar pre- and during-COVID-19 for high-SES students, there was a significant drop in attendance rates during COVID-19 among socioeconomically disadvantaged students, demonstrating the more pronounced impacts of COVID-19 for these students. The findings demonstrate that even "relatively short" lockdowns, as those in Tasmania in 2020 (30-40 days of home learning), can significantly affect the learning experiences of students from socioeconomically disadvantaged backgrounds. We discuss the implications of this for future pandemic planning in educational policy and practice and how this needs to be addressed in Australia's COVID-19 recovery.

Workplace factors associated with mental health of healthcare workers during the COVID-19 pandemic: an international cross-sectional study.

BACKGROUND: The association of workplace factors on mental health of healthcare workers (HCWs) during the COVID-19 pandemic needs to be urgently established. This will enable governments and policy-makers to make evidence-based decisions. This international study reports the association between workplace factors and the mental health of HCWs during the pandemic. METHODS: An international, cross-sectional study was conducted in 41 countries. The primary outcome was depressive symptoms, derived from the validated Patient Health Questionnaire-2 (PHQ-2). Multivariable logistic regression identified factors associated with mental health outcomes. Inter-country differences were also evaluated. RESULTS: A total of 2527 responses were received, from 41 countries, including China (n = 1213; 48.0%), UK (n = 891; 35.3%), and USA (n = 252; 10.0%). Of all participants, 1343 (57.1%) were aged 26 to 40 years, and 2021 (80.0%) were female; 874 (34.6%) were doctors, and 1367 (54.1%) were nurses. Factors associated with an increased likelihood of depressive symptoms were: working in the UK (OR = 3.63; CI = [2.90-4.54]; p < 0.001) and USA (OR = 4.10; CI = [3.03-5.54]), p < 0.001); being female (OR = 1.74; CI = [1.42-2.13]; p < 0.001); being a nurse (OR = 1.64; CI = [1.34-2.01]; p < 0.001); and caring for a COVID-19 positive patient who subsequently died (OR = 1.20; CI = [1.01-1.43]; p = 0.040). Workplace factors associated with depressive symptoms were: redeployment to Intensive Care Unit (ICU) (OR = 1.67; CI = [1.14-2.46]; p = 0.009); redeployment with perceived unsatisfactory training (OR = 1.67; CI = [1.32-2.11]; p < 0.001); not being issued with appropriate personal protective equipment (PPE) (OR = 2.49; CI = [2.03-3.04]; p < 0.001); perceived poor workplace support within area/specialty (OR = 2.49; CI = [2.03-3.04]; p < 0.001); and perceived poor mental health support (OR = 1.63; CI = [1.38-1.92]; p < 0.001). CONCLUSION: This is the first international study, demonstrating that workplace factors, including PPE availability, staff training pre-redeployment, and provision of mental health support, are significantly associated with mental health during COVID-19. Governments, policy-makers and other stakeholders need to ensure provision of these to safeguard HCWs' mental health, for future waves and other pandemics.

Parenting, Child Maltreatment, and Social Disadvantage: A Population-Based Implementation and Evaluation of the Triple P System of Evidence-Based Parenting Support.

Child Maltreatment (CM) is a widespread public health problem, with adverse outcomes for children, families, and communities. Evidence-based parenting support delivered via a public health approach may be an effective means to prevent CM. The Every Family 2 population trial applied a public health approach to delivering evidence-based parenting support to prevent CM in disadvantaged communities. Using a quasi-experimental design, 64 matched low socioeconomic communities in the Australian states of Queensland and New South Wales received either the full multi-level Triple P system (TPS) of parenting support, or Care as Usual (CAU). Two population indicators of CM, the number of substantiated cases of CM, and the number of notifications of CM to protective services were compared using Welch's t-test to evaluate intervention effectiveness. After two years of intervention, medium to large effect sizes favoring TPS communities were found for substantiations (d = 0.57, p < .05) and notifications (d = 1.86, p < .001). These findings show the value of the TPS, deployed using a public health approach, in efforts to prevent CM in socially disadvantaged communities. A number of uncontrolled contextual factors are described that may have contributed to some of the differences detected between TPS and CAU communities.

Machine learning to predict poor school performance in paediatric survivors of intensive care: a population-based cohort study.

PURPOSE: Whilst survival in paediatric critical care has improved, clinicians lack tools capable of predicting long-term outcomes. We developed a machine learning model to predict poor school outcomes in children surviving intensive care unit (ICU). METHODS: Population-based study of children < 16 years requiring ICU admission in Queensland, Australia, between 1997 and 2019. Failure to meet the National Minimum Standard (NMS) in the National Assessment Program-Literacy and Numeracy (NAPLAN) assessment during primary and secondary school was the primary outcome. Routine ICU information was used to train machine learning classifiers. Models were trained, validated and tested using stratified nested cross-validation. RESULTS: 13,957 childhood ICU survivors with 37,200 corresponding NAPLAN tests after a median follow-up duration of 6 years were included. 14.7%, 17%, 15.6% and 16.6% failed to meet NMS in school grades 3, 5, 7 and 9. The model demonstrated an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.8 (standard deviation SD, 0.01), with 51% specificity to reach 85% sensitivity [relative Area Under the Precision Recall Curve (rel-AUPRC) 3.42, SD 0.06]. Socio-economic status, illness severity, and neurological, congenital, and genetic disorders contributed most to the predictions. In children with no comorbidities admitted between 2009 and 2019, the model achieved a AUROC of 0.77 (SD 0.03) and a rel-AUPRC of 3.31 (SD 0.42). CONCLUSIONS: A machine learning model using data available at time of ICU discharge predicted failure to meet minimum educational requirements at school age. Implementation of this prediction tool could assist in prioritizing patients for follow-up and targeting of rehabilitative measures.

Subjective Wellbeing, Objective Wellbeing and Inequality in Australia.

In recent years policy makers and social scientists have devoted considerable attention to wellbeing, a concept that refers to people's capacity to live healthy, creative and fulfilling lives. Two conceptual approaches dominate wellbeing research. The objective approach examines the objective components of a good life. The subjective approach examines people's subjective evaluations of their lives. In the objective approach how subjective wellbeing relates to objective wellbeing is not a relevant research question. The subjective approach does investigate how objective wellbeing relates to subjective wellbeing, but has focused primarily on one objective wellbeing indicator, income, rather than the comprehensive indicator set implied by the objective approach. This paper attempts to contribute by examining relationships between a comprehensive set of objective wellbeing measures and subjective wellbeing, and by linking wellbeing research to inequality research by also investigating how subjective and objective wellbeing relate to class, gender, age and ethnicity. We use three waves of a representative state-level household panel study from Queensland, Australia, undertaken from 2008 to 2010, to investigate how objective measures of wellbeing are socially distributed by gender, class, age, and ethnicity. We also examine relationships between objective wellbeing and overall life satisfaction, providing one of the first longitudinal analyses linking objective wellbeing with subjective evaluations. Objective aspects of wellbeing are unequally distributed by gender, age, class and ethnicity and are strongly associated with life satisfaction. Moreover, associations between gender, ethnicity, class and life satisfaction persist after controlling for objective wellbeing, suggesting that mechanisms in addition to objective wellbeing link structural dimensions of inequality to life satisfaction.

Timing of Return to Work and Breastfeeding in Australia.

OBJECTIVE: To examine the effects of timing of return to work, number of hours worked, and their interaction, on the likelihood of breastfeeding at 6 months and predominant breastfeeding at 16 weeks. METHODS: A nationally representative sample of Australian mothers in paid employment in the 13 months before giving birth (n = 2300) were surveyed by telephone. Four multivariate logistic regression models were used to analyze the effects of timing of return to work and work hours, independently and in interaction, on any breastfeeding at 6 months and on predominant breastfeeding at 16 weeks, controlling for maternal sociodemographics, employment patterns, and health measures. RESULTS: Mothers who returned to work within 6 months and who worked for ≥20 hours per week were significantly less likely than mothers who had not returned to work to be breastfeeding at 6 months. However, returning to work for ≤19 hours per week had no significant impact on the likelihood of breastfeeding regardless of when mothers returned to work. Older maternal age, higher educational attainment, better physical or mental health, managerial or professional maternal occupation, and being self-employed all significantly contributed to the increased likelihood of any breastfeeding at 6 months. Similar patterns exist for predominant breastfeeding at 16 weeks. CONCLUSIONS: The effects of timing of return to work are secondary to the hours of employment. Working ≤19 hours per week is associated with higher likelihood of maintaining breastfeeding, regardless of timing of return to work.