We found low- quality evidence that different work-break frequencies may have no effect on participant-reported musculoskeletal pain , discomfort and fatigue .
For productivity and work performance , evidence was of very low- quality that different work-break frequencies may have a positive effect .
For different types of break , there may be no effect on participant-reported musculoskeletal pain , discomfort and fatigue according to low- quality evidence .
Furthermore , work-break interventions should be reconsidered , taking into account worker population s other than office workers , and taking into account the possibility of combining work-break intervention with other interventions such as ergonomic training or counselling , which may may possibly have an effect on musculoskeletal outcomes and work performance
BACKGROUND Work-related musculoskeletal disorders are a group of musculoskeletal disorders that comprise one of the most common disorders related to occupational sick leave worldwide .
Musculoskeletal disorders accounted for 21 % to 28 % of work absenteeism days in 2017/2018 in the Netherl and s , Germany and the UK .
There are several interventions that may be effective in tackling the high prevalence of work-related musculoskeletal disorders among workers , such as physical , cognitive and organisational interventions .
In this review , we will focus on work breaks as a measure of primary prevention , which are a type of organisational intervention .
OBJECTIVES To compare the effectiveness of different work-break schedules for preventing work-related musculoskeletal symptoms and disorders in healthy workers , when compared to conventional or alternate work-break schedules .
How to design efficient cluster randomised trials
Cluster r and omised trials have diminishing returns in power and precision as cluster size increases . Making the cluster a lot larger while keeping the number of clusters fixed might yield only a very small increase in power and precision , owing to the intracluster correlation . Identifying the point at which observations start making a negligible contribution to the power or precision of the study —which we call the point of diminishing returns — is important for design ing efficient trials . Current methods for identifying this point are potentially useful as rules of thumb but do n’t generally work well . We introduce several practical aids to help research ers design cluster r and omised trials  in which all observations make a material contribution to the study . Power curves enable identification of the point at which observations begin to make a negligible contribution to a study for a given target difference . Under this paradigm , the number needed per arm under individual r and omisation gives an upper bound on the cluster size , which should not be exceeded . Corresponding precision curves can be useful for accommodating flexibility in the choice of target difference and show the point at which confidence intervals around the estimated effect size no longer decrease . To design efficient trials , the number of clusters and cluster size should be determined concurrently , not independently . Funders and research ers should be aware of diminishing returns in cluster trials . Research ers should routinely plot power or precision curves when performing sample size calculations so that the implication s of cluster sizes can be transparent . Even when data appear to be “ free , ” in the sense that few re sources are needed to obtain the data , excessive cluster sizes can have important
We found low- quality evidence that different work-break frequencies may have no effect on participant-reported musculoskeletal pain , discomfort and fatigue .
For productivity and work performance , evidence was of very low- quality that different work-break frequencies may have a positive effect .
For different types of break , there may be no effect on participant-reported musculoskeletal pain , discomfort and fatigue according to low- quality evidence .
Furthermore , work-break interventions should be reconsidered , taking into account worker population s other than office workers , and taking into account the possibility of combining work-break intervention with other interventions such as ergonomic training or counselling , which may may possibly have an effect on musculoskeletal outcomes and work performance
BACKGROUND Work-related musculoskeletal disorders are a group of musculoskeletal disorders that comprise one of the most common disorders related to occupational sick leave worldwide .
Musculoskeletal disorders accounted for 21 % to 28 % of work absenteeism days in 2017/2018 in the Netherl and s , Germany and the UK .
There are several interventions that may be effective in tackling the high prevalence of work-related musculoskeletal disorders among workers , such as physical , cognitive and organisational interventions .
In this review , we will focus on work breaks as a measure of primary prevention , which are a type of organisational intervention .
OBJECTIVES To compare the effectiveness of different work-break schedules for preventing work-related musculoskeletal symptoms and disorders in healthy workers , when compared to conventional or alternate work-break schedules .