Correction: Dodd et al. Children's Play and Independent Mobility in 2020: Results from the British Children's Play Survey. Int. J. Environ. Hum. Health 2021, 18, 4334.

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Children's Play and Independent Mobility in 2020: Results from the British Children's Play Survey.

The British Children's Play Survey was conducted in April 2020 with a nationally representative sample of 1919 parents/caregivers with a child aged 5-11 years. Respondents completed a range of measures focused on children's play, independent mobility and adult tolerance of and attitudes towards risk in play. The results show that, averaged across the year, children play for around 3 h per day, with around half of children's play happening outdoors. Away from home, the most common places for children to play are playgrounds and green spaces. The most adventurous places for play were green spaces and indoor play centres. A significant difference was found between the age that children were reported to be allowed out alone (10.74 years; SD = 2.20 years) and the age that their parents/caregivers reported they had been allowed out alone (8.91 years; SD = 2.31 years). A range of socio-demographic factors were associated with children's play. There was little evidence that geographical location predicted children's play, but it was more important for independent mobility. Further, when parents/caregivers had more positive attitudes around children's risk-taking in play, children spent more time playing and were allowed to be out of the house independently at a younger age.

Design of a state of the art reporting system and process improvement for reporting of high complexity single antigen bead data for transplant patients to the electronic medical record.

The UCLA Immunogenetics Center is an Immunogenetics and Histocompatibility laboratory that performs testing for multiple transplant programmes within and outside of UCLA. The single antigen bead (SAB) test is a high complexity luminex bead test used to assess pretransplant and post-transplant patients for the presence of pathogenic human leucocyte antigen donor-specific antibody associated with allograft rejection. Efficient reporting of the SAB test has been difficult as data analysis and reports are generated in the laboratory information system (LIS) and uploaded to the electronic medical record (EMR) as PDFs. To solve this, we recently developed a state of the art reporting workflow allowing discrete reporting of SAB data (antibody specificity, mean fluorescent intensity and interpretative comments) from the LIS HistoTrac to UCLA Health System's EMR EPIC:CareConnect. However, a proportion of tests did not report to the EMR appropriately. Baseline system performance data evaluated over a 10-week period showed that ~4.5/100 tests resulted in EPIC as 'preliminary result' or 'in process' instead of 'final result' with only common cause variation. Quality improvement methods were employed to improve the process with the SMART Aim of reporting 100% of tests as 'final result'. Pareto analysis identified two errors accounting for 79% of common system-level failures-status errors and interface errors. We hypothesised that addressing the status error would reduce or eliminate the interface errors. We used the Model For Improvement to test a reprogramming intervention. Status and interface errors were completely resolved through the process improvement. Continuous monitoring revealed a system-level shift with only ~1.9/100 tests resulting inappropriately. Through the audit process, the remaining common system-level failures were identified and resolved. Therefore, 100% of tests result to EPIC as 'final result'. The study demonstrates that high complexity SAB bead data can be efficiently reported EPIC:CareConnect from HistoTrac as discrete data.

Quantitative sleep EEG and polysomnographic predictors of driving simulator performance in obstructive sleep apnea.

OBJECTIVES: To improve identification of obstructive sleep apnea (OSA) patients at risk of driving impairment, this study explored predictors of driving performance impairment in untreated OSA patients using clinical PSG metrics, sleepiness questionnaires and quantitative EEG markers from routine sleep studies. METHODS: Seventy-six OSA patients completed sleepiness questionnaires and driving simulator tests in the evening of their diagnostic sleep study. All sleep EEGs were subjected to quantitative power spectral analysis. Correlation and multivariate linear regression were used to identify the strongest predictors of driving simulator performance. RESULTS: Absolute EEG spectral power across all frequencies (0.5-32 Hz) throughout the entire sleep period and separately in REM and NREM sleep, (r range 0.239-0.473, all p<0.05), as well as sleep onset latency (r=0.273, p<0.017) positively correlated with driving simulator steering deviation. Regression models revealed that amongst clinical and qEEG variables, the significant predictors of worse steering deviation were greater total EEG power during NREM and REM sleep, greater beta EEG power in NREM and greater delta EEG power in REM (range of variance explained 5-17%, t range 2.29-4.0, all p<0.05) and sleep onset latency (range of variance explained 4-9%, t range 2.15-2.5, all p<0.05). CONCLUSIONS: In OSA patients, increased EEG power, especially in the faster frequency (beta) range during NREM sleep and slower frequency (delta) range in REM sleep were associated with worse driving performance, while no relationships were observed with clinical metrics e.g. apnea, arousal or oxygen indices. SIGNIFICANCE: Quantitative EEG analysis in OSA may provide useful markers of driving impairment risk. Future studies are necessary to confirm these findings and assess the clinical significance of quantitative EEG as predictors of driving impairment in OSA.