Statistical analysis
ankle sprain, pain
REGRESSION, EVENT, RECURRENCE, SECONDARY
Differences between the two groups were analysed following the intention-to-treat principle. Cox regression analysis, with adjustment for sex, was performed for comparing recurrence risk between groups and presented as a hazard ratio (HR) with a 95% confidence interval (CI). The first self-reported recurrent LAS was used as the event. Differences between continuous secondary outcomes were examined with linear mixed models using regression techniques for repeated measures and adjusted for age, sex, body mass index (BMI), educational level, and treatment of ankle sprain by GP at baseline. The covariance structure ‘Unstructured’, with the lowest Akaike’s information criterion, was chosen as a data structure in the analyses to model the covariance of repeated measures. The time-point of follow-up were fixed effects. All outcomes measured at the time points before the time-point of interest (including baseline values) were included in the analyses. The intervention effect on continuous secondary outcomes was quantified as the mean difference between trial arms. Mixed-multilevel models, estimated using restricted maximum likelihood, were fitted to analyse repeated measures data as they allow inclusion of participants that provide outcome data in at least one study wave.Logistic regression models, adjusted for sex, BMI, treatment of ankle sprain by GP at baseline, pain at rest, pain during exercise, FADI, and AFS, were fitted to compare binary outcomes between the trial groups. Differences in subjective recovery and return to the same sport and the same level of sport between the groups were presented as odds ratios (ORs) with their 95% CI. In case of statistically significant differences in the categorical secondary outcomes between the groups, the number needed to treat was calculated (defined as 1 divided by the risk difference between the groups). All analyses were performed in SPSS Statistics (version 25) and 