The experiences and attitudes of family caregivers of adults with intellectual and developmental disabilities at different timepoints in the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic has resulted in increased pressures for family caregivers of adults with intellectual and developmental disabilities (IDD). However, little is known about how their attitudes and perceptions have changed over the course of the pandemic. OBJECTIVE: To compare the COVID-19 experiences and attitudes of two groups of family caregivers, reported at different timepoints in the pandemic: prior to vaccine availability and after. METHODS: As part of a larger research study, family caregivers of adults with IDD from across Canada completed surveys on their COVID-19 experiences. Survey questions included responses about access to supports, stressors, self-efficacy, mental wellbeing, and pandemic impacts on their family member with IDD. Respondents were assigned to either of two groups based on the time of questionnaire completion: late 2020/early 2021 for Group 1 and mid 2022 for Group 2. Descriptive statistics and analysis between groups were reported. RESULTS: Despite being surveyed at different timepoints in the pandemic, both groups indicated concerns regarding lack of professional support and resources, lack of programming, and experiences of loneliness for their family members. However, Group 2 reported greater self-efficacy dealing with COVID-19 related challenges and greater overall mental wellbeing, compared to Group 1. Group 2 caregivers, after which vaccines were widely available in Canada, were largely vaccinated (96.4%). CONCLUSIONS: Despite the COVID-19 pandemic persisting for over two years, family caregivers of adults with IDD reported facing the same challenges as families who reported on their experiences a year prior. Notwithstanding, family caregivers surveyed later in the pandemic described a greater sense of self-efficacy and mental wellbeing.

Predicting Severity of Head Collision Events in Elite Soccer Using Preinjury Data: A Machine Learning Approach.

OBJECTIVE: To develop machine learning (ML) models that predict severity of head collision events (HCEs) based on preinjury variables and to investigate which variables are important to predicting severity. DESIGN: Data on HCEs were collected with respect to severity and 23 preinjury variables to create 2 datasets, a male dataset using men's tournaments and mixed dataset using men's and women's tournaments, to perform ML analysis. Machine learning analysis used a random forest classifier based on preinjury variables to predict HCE severity. SETTING: Four elite international soccer tournaments. PARTICIPANTS: Elite athletes participating in analyzed tournaments. INDEPENDENT VARIABLES: The 23 preinjury variables collected for each HCE. MAIN OUTCOME MEASURES: Predictive ability of the ML models and association of important variables. RESULTS: The ML models had an average area under the receiver operating characteristic curve for predicting HCE severity of 0.73 and 0.70 for the male and mixed datasets, respectively. The most important variables for prediction were the mechanism of injury and the event before injury. In the male dataset, the mechanisms "head-to-head" and "knee-to-head" were together significantly associated ( P = 0.0244) with severity; they were not significant in the mixed dataset ( P = 0.1113). In both datasets, the events "corner kicks" and "throw-ins" were together significantly associated with severity (male, P = 0.0001; mixed, P = 0.0004). CONCLUSIONS: ML models accurately predicted the severity of HCE. The mechanism and event preceding injury were most important for predicting severity of HCEs. These findings support the use of ML to inform preventative measures that will mitigate the impact of these preinjury factors on player health.

Effect of a new concussion substitute rule on medical assessment of head collision events in Premier League football.

OBJECTIVE: To investigate the utilisation of additional permanent concussion substitutes (APCSs) and its efficacy with regards to rate and duration of medical assessment of head collision events (HCEs) in the 2020-2021 Premier League season. The present APCS rule allows players with a suspected concussion to be removed from a match without counting towards a team's allocated substitutions. METHODS: Eighty Premier League matches, 40 prior to additional permanent concussion substitutes implementation (Pre-APCS) and 40 after (Post-APCS), were randomly selected and analysed by a team of trained reviewers for HCEs. Data on HCE incidence, rates of medical assessment, duration of medical assessment and return to play were collected for each match. Data for the Pre-APCS and Post-APCS groups were compared to analyse differences in assessment of HCEs. RESULTS: During the 2020-2021 Premier League season, three APCSs were used. There were 38 HCEs identified in the Pre-APCS group (0.95 per match, 28.79 per 1000 athlete-hours of exposure) and 42 in the Post-APCS group (1.05 per match, 31.82 per 1000 athlete-hours of exposure). Incidence of HCEs (p=0.657), rates of medical assessment (23.7% Pre-APCS vs 21.4% Post-APCS; p=0.545) and duration of medical assessment (median 81 s Pre-APCS vs 102 s Post-APCS; p=0.466) did not significantly differ between the two groups. CONCLUSIONS: The implementation of APCSs in the Premier League did not impact the rate or duration of medical assessement of HCEs. Despite the introduction of APCSs, the consensus protocols for HCE assessment were rarely followed. We recommend changes to APCS and its implementation that would be aimed at protecting player health.