Back

Supervised land- and water-based exercis intervention in women with fibromyalgia: CERT- based exercise study protocol of the al-Andalus physical activity randomised controlled trial

Alvarez-Gallardo, I. C.; Gavilan-Carrera, B.; Carbonell-Baeza, A.; Segura-Jimenez, V.; Camiletti-Moiron, D.; Borges-Cosic, M.; Aparicio, V.; Delgado-Fernandez, M.

2024-01-26 sports medicine
10.1101/2024.01.24.24301515 medRxiv
Show abstract

BackgroundExercise is recommended for managing fibromyalgia; however, the scant details provided about exercise programs (EP) in the available literature make standardization, replicability, and interpretation of results difficult. The aim of the present report is to provide a comprehensive CERT (Consensus on Exercise Reporting Template)-based description of the rationale and details of the land- and water-based EP implemented in the al-Andalus Randomized Controlled Trial (RCT). MethodsWomen aged 35-65 with fibromyalgia (n=180) were planned to be recruited in Southern Spain (Andalucia). The study design was composed of three groups: the usual care (control) group, the land- and the water-based supervised exercise intervention groups (n=60 for each group). Participants allocated in the exercise intervention groups undertook a 24-week supervised multicomponent (strength, aerobic and flexibility) EP (three non-consecutive sessions per week, 45-60 min/session). The rationale of the exercise program is described in detail following the CERT criteria detailing its 16 key items. DiscussionThis study details the supervised EP of the al-Andalus RCT project, which may serve: 1) exercise professionals who would like to implement an evidence-based supervised EP for people with fibromyalgia in land- and water-based settings, and 2) as an example of the application of the CERT criteria. Trial registrationClinicalTrials.gov ID: NCT01490281

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.