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Objectives: To validate the two-factor structure (i.e., cognitive and somatic) of the Health and Behaviour Inventory (HBI), a widely used post-concussive symptom (PCS) rating scale, through factor analyses using bifactor and correlated factor models and by examining measurement invariance (MI). Methods: PCS ratings were obtained from children aged 8–16.99 years, who presented to the emergency department with concussion (n = 565) or orthopedic injury (OI) (n = 289), and their parents, at 10-days, 3-months, and 6-months post-injury. Item-level HBI ratings were analyzed separately for parents and children using exploratory and confirmatory factor analyses (CFAs). Bifactor and correlated models were compared using various fit indices and tested for MI across time post-injury, raters (parent vs. child), and groups (concussion vs. OI). Results: CFAs showed good fit for both a three-factor bifactor model, consisting of a general factor with two subfactors (i.e., cognitive and somatic), and a correlated two-factor model with cognitive and somatic factors, at all time points for both raters. Some results suggested the possibility of a third factor involving fatigue. All models demonstrated strict invariance across raters and time. Group comparisons showed at least strong or strict invariance. Conclusions: The findings support the two symptom dimensions measured by the HBI. The three-factor bifactor model showed the best fit, suggesting that ratings on the HBI also can be captured by a general factor. Both correlated and bifactor models showed substantial MI. The results provide further validation of the HBI, supporting its use in childhood concussion research and clinical practice. [ABSTRACT FROM AUTHOR]

Depopulation is one of the important interventions for the outbreak of animal diseases. Simulation models using actual case scenarios conclude that early depopulation is the most efficient in preventing the spread of foot-and-mouth disease (FMD). However, the long delay in its initiation was often seen in the actual cases and the theoretical analyses of FMD epidemiology with depopulation needs further elaboration. Here, we investigated the qualitative features of epidemic models when depopulation at a fixed capacity was delayed. We built a simple deterministic model for FMD based on state-transition, the SEIIR model whose unit is a single farm. The model settings and parameters were determined using the data from the 2010 epidemic in Miyazaki, Japan. By numerical calculation, we showed the existence of the threshold phenomenon with respect to delays in the initiation of depopulation and if the initiation of full-fledged depopulation surpasses the certain critical timing, the final size of the epidemic rapidly increases leading to a "catastrophic situation". We also revealed the mechanism of the threshold phenomenon from the relationship between the depopulation capacity and the increasing rate of infection. Although it can be delayed with lower transmission coefficients, the threshold phenomenon still exists. Thus, the existence of the critical timing for depopulation appears to be a universal feature of FMD epidemiology when depopulation is used as the main treatment for disease control.