AIM: Evaluations of participatory ergonomic interventions are often challenging as these types of interventions are tailored to the context and need of the workplace in which they are implemented. We aimed to describe how time flow analysis can be used to describe changes in work behaviours following a participatory ergonomic intervention. METHOD: This study was based on data from a two-arm cluster-randomized controlled trial with 29 childcare institutions and 116 workers (intervention: n = 60, control: n = 56). Physical behaviours at work were technically measured at baseline and 4-month follow-up. Physical behaviours were expressed in terms of relative work time spent forward bending of the back ≥30°, kneeling, active (i.e. walking, stair climbing and running) and sedentary. Average time flow from baseline to follow-up were calculated for both groups to investigate if work time was allocated differently at follow-up. RESULTS: A total of 116 workers (60 in the intervention and 56 in the control group) had valid accelerometer at baseline and follow-up. The largest group difference in time flowing from baseline to follow-up was observed for forward bending of the back and time spent kneeling. Compared to the control, the intervention group had less time flowing from forward bending of the back to kneeling (intervention: +11 min day, control: +16 min day) and more time flowing from kneeling to sedentary behaviours (intervention: +15 min day, control: +10 min day). CONCLUSION: The results of this study showed that time flow analysis can be used to reveal changes in work time-use following a participatory ergonomic intervention. For example, the analysis revealed that the intervention group had replaced more work time spent kneeling with sedentary behaviours compared to the control group. This type of information on group differences in time reallocations would not have been possible to obtain by comparing group differences in work time-use following the intervention, supporting the usefulness of time flow analysis as a tool to evaluate complex, context-specific interventions.

Alliance for Research in Exercise Nutrition and Activity Allied Health and Human Performance University of South Australia Adelaide South Australia Australia

Department of Mathematical Analysis and Applications of Mathematics Palacký University Olomouc Olomouc Czech Republic

Department of Public Health and Nursing Norwegian University of Science and Technology Trondheim Norway

Faculty of Physical Culture Palacký University Olomouc Olomouc Czech Republic

National Research Centre for the Working Environment Lersø Parkalle 105 2100 Copenhagen Denmark

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Aitchison J. (1982) The statistical-analysis of compositional data. J R Stat Soc Ser B Methodol; 44: 139–77.

Bates D, Mächler M, Bolker Bet al. (2015) Fitting Linear Mixed-Effects Models using lme4. J Stat Softw; 67: 1–48.

Bolker B. (2012) Multivariate analysis with mixed model tools in R. Book Multivariate Analysis with Mixed Model Tools in R, City. https://rpubs.com/bbolker/3336#:~:text=Multivariate%20analysis%20with%20mixed%20modeling%20tools%20in%20R&text=It%20can%20be%20implemented%20by,identical%20and%20non%2Dnegative. Accessed 08 August 2022.

Durlak JA, DuPre EP. (2008) Implementation matters: a review of research on the influence of implementation on program outcomes and the factors affecting implementation. Am J Community Psychol; 41: 327–50. PubMed

Egozcue JJ, Pawlowsky-Glahn V, Mateu-Figueras Get al. (2003) Isometric logratio transformations for compositional data analysis. Math Geol; 35: 279–300.

Gu Z, Gu L, Eils Ret al. (2014) circlize Implements and enhances circular visualization in R. Bioinformatics (Oxford, England); 30: 2811–2. PubMed

Korshøj M, Skotte JH, Christiansen CSet al. (2014) Validity of the Acti4 software using ActiGraph GT3X+accelerometer for recording of arm and upper body inclination in simulated work tasks. Ergonomics; 57: 247–53. PubMed

Martin-Fernandez JA, Hron K, Templ Met al. (2012) Model-based replacement of rounded zeros in compositional data: classical and robust approaches. Comput Stat Data Anal; 56: 2688–704.

Olds T, Burton NW, Sprod Jet al. (2018) One day you’ll wake up and won’t have to go to work: the impact of changes in time use on mental health following retirement. PLoS One; 13: e0199605. PubMed PMC

Palarea-Albaladejo J, Martín-Fernández JA. (2008) A modified EM alr-algorithm for replacing rounded zeros in compositional data sets. Comput Geosci; 34: 902–17.

Palarea-Albaladejo J, Martin-Fernandez JA. (2015) zCompositions—R Package for multivariate imputation of left-censored data under a compositional approach. Chemometr Intell Lab Syst; 143: 85–96.

Pawlowsky-Glahn V, Egozcue JJ, Tolosana-Delgado R. (2015) Modeling and Analysis of Compositional Data. New Jersey, USA: John Wiley & Sons.

Rasmussen CDN, Hendriksen PR, Svendsen MJet al. (2018) Improving work for the body—a participatory ergonomic intervention aiming at reducing physical exertion and musculoskeletal pain among childcare workers (the TOY-project): study protocol for a wait-list cluster-randomized controlled trial. Trials; 19: 411. PubMed PMC

Rasmussen CDN, Sørensen OH, van der Beek AJet al. (2020) The effect of training for a participatory ergonomic intervention on physical exertion and musculoskeletal pain among childcare workers (the TOY project)—a wait-list cluster-randomized controlled trial. Scand J Work Environ Health; 46: 429–36. PubMed PMC

Rivilis I, Van Eerd D, Cullen Ket al. (2008) Effectiveness of participatory ergonomic interventions on health outcomes: a systematic review. Appl Ergon; 39: 342–58. PubMed

Skotte J, Korshøj M, Kristiansen Jet al. (2014) Detection of physical activity types using triaxial accelerometers. J Phys Act Health; 11: 76–84. PubMed

Stemland I, Ingebrigtsen J, Christiansen CSet al. (2015) Validity of the Acti4 method for detection of physical activity types in free-living settings: comparison with video analysis. Ergonomics; 58: 953–65. PubMed

R Core Team. (2022) R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.

Templ M, Hron K, Filzmoser P. (2011) robCompositions: an R-package for robust statistical analysis of compositional data. In Pawlowsky-Glahn V, Buccianti A editors. Compositional Data Analysis . New Jersey, USA: John Wiley & Sons, Ltd.

van den Boogaart KG, Tolosana-Delgado R. (2008) “compositions”: a unified R package to analyze compositional data. Comput Geosci; 34: 320–38.

van Eerd D, Cole D, Irvin Eet al. (2010) Process and implementation of participatory ergonomic interventions: a systematic review. Ergonomics; 53: 1153–66. PubMed

Ware JE. (1993) SF-36 Health Survey: Manual and Interpretation Guide. Health Institute. Boston, MA: New England Medical Center.