Catherine M. Elliott

Description:Background: Increasing financial pressures, resulting from a period of high inflation in 2022 and sustained into 2024, may have exacerbated food insecurity among Australian university students. This study aimed to determine the change in prevalence and severity of food insecurity among Australian university students between 2022 and 2024. Methods: Repeated cross-sectional, online surveys measured food insecurity using the United States Department of Agriculture Household Food Security Survey Module six-item short form (USDA HFSSM) in addition to six demographic and education characteristics. Students were categorised as being food secure or being marginally, moderately, or severely food insecure. Using a binary variable (food secure vs. food insecure), multivariate logistic regression identified students at higher risk of food insecurity. Independent proportions and logistic regression, adjusting for relevant predictors of food insecurity, measured change in the prevalence of food insecurity between 2022 and 2024. Results: In 2022 (n = 1249 students) and 2024 (n = 1603), younger, on campus, and international students experienced significantly higher odds of food insecurity. Marginal and moderate food insecurity were unchanged between 2022 and 2024. Severe food insecurity increased from 17% in 2022 to 29% in 2024 (95% CI -0.07, -0.13, p < 0.001), contributing to an overall significant increase in total food insecurity from 42% to 53% (Adjusted Odds Ratio: 1.6; 95% CI: 1.3, 1.8; p < 0.001). Conclusions: This study has identified a high prevalence and worsening severity of food insecurity among Australian university students during a period of high and sustained inflation. SO WHAT?: There is a need for immediate action, including health promotion initiatives and policies to uphold Australian university students' right to food.

Description:Background: Early detection of cerebral palsy (CP) risk is possible from 12 weeks corrected gestational age (CGA) using standardised assessments; however, up to half of children at risk are not referred early, missing out on early intervention. We investigated the barriers and facilitators to accessing early intervention from the perspective of parents of children who did not receive services by 6 months CGA. Methods: Parents of children with CP were invited to participate in qualitative semistructured interviews. Reflexive thematic analysis was used to analyse the data and develop themes. Results: Eight mothers of children who did not receive standardised screening participated in interviews, from which three themes, 'responding to delays', 'systemic barriers' and 'complexities of diagnosis', were developed from the data. Conclusions: Parents require more support to access and engage in early detection services; health system processes are difficult to navigate, and health professionals require education and training to recognise risk factors for CP in all health settings and refer promptly. Improving system processes, education and training and partnering early with parents to improve their experience when interacting with the health system may increase early engagement and optimise long-term outcomes for children at risk of CP and their families.

Description:Objective: To test the efficacy of Hand Arm Bimanual Intensive Therapy Including Lower Extremity (HABIT-ILE) to improve gross motor function, manual ability, goal performance, walking endurance, mobility, and self-care for children with bilateral cerebral palsy. Methods: This prospective, waitlist randomized controlled trial included children with bilateral cerebral palsy, aged 6-to-16-years and classified Gross Motor Function Classification System levels II to IV. HABIT-ILE delivered for 2 weeks (65 hours) was compared with usual care. Primary outcomes postintervention were gross motor function (Gross Motor Function Measure-66) and manual ability (ABILHAND-Kids). Secondary outcomes were goal performance (Canadian Occupational Performance Measure), self-care and mobility (Pediatric Evaluation of Disability Inventory-Computer Adapted Test), bimanual hand performance (Both Hands Assessment), and walking endurance (6 Minute Walk Test). Linear regression models were used to determine between group differences, adjusted for baseline scores. Results: Ninety-two children were recruited; 2 were deemed ineligible after randomization and were excluded. Ninety children (HABIT-ILE n = 46, usual care n = 44), mean age 10.4 (SD 3.0) years, Gross Motor Function Classification System II = 32; III = 31; IV = 27 were included. HABIT-ILE led to superior gains in manual ability (mean difference 0.85, 95% CI 0.38-1.33; P < .001) but not gross motor function. HABIT-ILE led to superior changes on goal performance, self-care, and mobility. Conclusions: HABIT-ILE was effective in improving manual ability, mobility, self-care, and goal performance, but not gross motor function. Significant gains were immediately retained at 26 weeks postintervention. Large individual variability suggests further analyses need to be performed to understand characteristics of children who achieved clinically meaningful gains across outcomes.

Description:Typically developing infants, between the corrected age of 9-20 weeks, produce fidgety movements. These movements can be identified with the General Movement Assessment, but their identification requires trained professionals to conduct the assessment from video recordings. Since trained professionals are expensive and their demand may be higher than their availability, computer vision-based solutions have been developed to assist practitioners. However, most solutions to date treat the problem as a direct mapping from video to infant status, without modeling fidgety movements throughout the video. To address that, we propose to directly model infants' short movements and classify them as fidgety or non-fidgety. In this way, we model the explanatory factor behind the infant's status and improve model interpretability. The issue with our proposal is that labels for an infant's short movements are not available, which precludes us to train such a model. We overcome this issue with active learning. Active learning is a framework that minimizes the amount of labeled data required to train a model, by only labeling examples that are considered "informative" to the model. The assumption is that a model trained on informative examples reaches a higher performance level than a model trained with randomly selected examples. We validate our framework by modeling the movements of infants' hips on two representative cohorts: typically developing and at-risk infants. Our results show that active learning is suitable to our problem and that it works adequately even when the models are trained with labels provided by a novice annotator.

Description:Objective: To compare efficacy of constraint-induced movement therapy (Baby-CIMT) with bimanual therapy (Baby-BIM) in infants at high risk of unilateral cerebral palsy. Methods: This was a single-blind, randomized-comparison-trial that had the following inclusion criteria: (1) asymmetric brain lesion (2) absent fidgety General Movements, (3) Hammersmith Infant Neurological Examination below cerebral palsy cut-points, (4) entry at 3-9 months of corrected age, and (5) >3-point difference between hands on Hand Assessment Infants (HAI). Infants were randomized to Baby-CIMT or Baby-BIM, which comprised 6-9 months of home-based intervention. Daily dose varied from 20 to 40 minutes according to age (total 70-89.2 hours). Primary outcome measure was the HAI after intervention, with secondary outcomes Mini-Assisting Hand Assessment and Bayley III cognition at 24 months of corrected age. Results: In total, 96 infants (51 male, 52 right hemiplegia) born median at 37-weeks of gestation were randomized to Baby-CIMT (n = 46) or Baby-BIM (n = 50) and commenced intervention at a mean 6.5 (SD 1.6) months corrected age. There were no between group differences immediately after intervention on HAI (mean difference [MD] 0.98 HAI units, 95% CI 0.94-2.91; P = .31). Both groups demonstrated significant clinically important improvements from baseline to after intervention (Baby-BIM MD 3.48, 95% CI 2.09-4.87; Baby-CIMT MD 4.42, 95% CI 3.07-5.77). At 24 months, 64 infants were diagnosed with unilateral cerebral palsy (35 Baby-CIMT, 29 Baby-BIM). Infants who entered the study between 3 and 6 months of corrected age had greater change in HAI Both Hands Sum Score compared with those who entered at ≥6 months of corrected age (MD 7.17, 95% CI 2.93-11.41, P = .001). Conclusions: Baby-CIMT was not superior to Baby-BIM, and both interventions improved hand development. Infants commencing intervention at <6 months corrected age had greater improvements in hand function.