BackgroundHealth promotion at the work site in terms of physical activity has proven positive effects but optimization of relevant exercise training protocols and implementation for high adherence are still scanty.Methods/DesignThe aim of this paper is to present a study protocol with a conceptual model for planning the optimal individually tailored physical exercise training for each worker based on individual health check, existing guidelines and state of the art sports science training recommendations in the broad categories of cardiorespiratory fitness, muscle strength in specific body parts, and functional training including balance training. The hypotheses of this research are that individually tailored worksite-based intelligent physical exercise training, IPET, among workers with inactive job categories will: 1) Improve cardiorespiratory fitness and/or individual health risk indicators, 2) Improve muscle strength and decrease musculoskeletal disorders, 3) Succeed in regular adherence to worksite and leisure physical activity training, and 3) Reduce sickness absence and productivity losses (presenteeism) in office workers. The present RCT study enrolled almost 400 employees with sedentary jobs in the private as well as public sectors. The training interventions last 2 years with measures at baseline as well as one and two years follow-up.DiscussionIf proven effective, the intelligent physical exercise training scheduled as well as the information for its practical implementation can provide meaningful scientifically based information for public health policy.Trial RegistrationClinicalTrials.gov, number: NCT01366950.
A conceptual model for worksite intelligent physical exercise training - IPET - intervention for decreasing life style health risk indicators among employees: a randomized controlled trial
G. Sjøgaard,Just Bendix Justesen,Mike Murray,Tina Dalager,K. Søgaard
Published 2014 in BMC Public Health
ABSTRACT
PUBLICATION RECORD
- Publication year
2014
- Venue
BMC Public Health
- Publication date
2014-06-26
- Fields of study
Medicine, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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