The physical activity at work (PAW) study protocol: a cluster randomised trial of a multicomponent short-break intervention to reduce sitting time and increase physical activity among office workers in Thailand

Cynthia Chen, Anna Valeria Dieterich, Jemima Jia En Koh, Katika Akksilp, Eunice Huiying Tong, Nuttakarn Budtarad, Andre Matthias Müller, Thunyarata Anothaisintawee, Bee Choo Tai, Waranya Rattanavipapong, Wanrudee Isaranuwatchai, Thomas Rouyard, Ryota Nakamura, Falk Müller-Riemenschneider, Yot Teerawattananon, Cynthia Chen, Anna Valeria Dieterich, Jemima Jia En Koh, Katika Akksilp, Eunice Huiying Tong, Nuttakarn Budtarad, Andre Matthias Müller, Thunyarata Anothaisintawee, Bee Choo Tai, Waranya Rattanavipapong, Wanrudee Isaranuwatchai, Thomas Rouyard, Ryota Nakamura, Falk Müller-Riemenschneider, Yot Teerawattananon

Abstract

Background: High levels of sedentary behaviour (SB) are associated with non-communicable diseases. In 2016, the estimated total healthcare expenditure from physical activity (PA) in Thailand added up to $190 million in international dollars. The challenge to reduce SB and increase PA among office workers is more urgent now than ever as Thailand is transforming itself from a predominantly rural country to an increasingly urban one. This study will investigate the effectiveness of a multicomponent short break intervention on the reduction of SB during office hours.

Methods/design: This two-armed Physical Activity at Work (PAW) cluster randomised controlled trial will recruit 360 office workers from 18 offices in the Thailand's Ministry of Public Health (MOPH). Offices will be randomised to either the intervention group or the control group. The multicomponent intervention is informed by the Social Ecological Model and Behaviour Change Techniques (BCTs) and contains four components: (i) organisational, including heads of the participating divisions leading exercises, sending encouragement text messages and acknowledging efforts; (ii) social, including team movement breaks and team-based incentives; (iii) environmental, including posters to encourage exercise; and (iv) individual components including real-time PA feedback via an individual device. The main intervention component will be a short break intervention. The primary outcome of this study is the sedentary time of office workers. Secondary outcomes include time spent on PA, cardiometabolic outcomes, work productivity, musculoskeletal pain, and quality of life. The study also includes process and economic evaluations from the individual and societal perspective.

Discussion: The study will be the first experimental study in Thailand to investigate the effect of a short-break intervention at the workplace on SBs of office workers and health outcomes. The study will also include a cost-effectiveness analysis to inform investments on short break interventions under the Universal Healthcare Coverage in Thailand, which includes health promotion and disease prevention component.

Trial registration: The PAW study has been registered at the Thai Clinical Trials Registry (TCTR) under the study ID TCTR20200604007 . Registered 02 June 2020,.

Keywords: Behaviour change techniques; Cost-effectiveness; Multicomponent intervention; Non-communicable diseases; Physical activity; Productivity; Quality of life; Sedentary behaviour.

Conflict of interest statement

The authors do not have conflicts of interest to report.

Figures

Fig. 1
Fig. 1
Study Overview
Fig. 2
Fig. 2
The Decision tree and Markov model for assessing costs and outcomes of PAW compared to the current situation (no PAW implemented)

References

    1. Powell C, Herring MP, Dowd KP, Donnelly AE, Carson BP. The cross-sectional associations between objectively measured sedentary time and cardiometabolic health markers in adults - a systematic review with meta-analysis component. Obes Rev. 2018;19(3):381–395.
    1. Patterson R, McNamara E, Tainio M, de Sa TH, Smith AD, Sharp SJ, et al. Sedentary behaviour and risk of all-cause, cardiovascular and cancer mortality, and incident type 2 diabetes: a systematic review and dose response meta-analysis. Eur J Epidemiol. 2018;33(9):811–829.
    1. Boberska M, Szczuka Z, Kruk M, Knoll N, Keller J, Hohl DH, et al. Sedentary behaviours and health-related quality of life. A systematic review and meta-analysis. Health Psychol Rev. 2018;12(2):195–210.
    1. Wilmot EG, Edwardson CL, Achana FA, Davies MJ, Gorely T, Gray LJ, et al. Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia. 2012;55(11):2895–2905.
    1. Biswas A, Oh PI, Faulkner GE, Bajaj RR, Silver MA, Mitchell MS, et al. Sedentary time and its association with risk for disease incidence, mortality, and hospitalization in adults: a systematic review and meta-analysis. Ann Intern Med. 2015;162(2):123–132.
    1. Zhai L, Zhang Y, Zhang D. Sedentary behaviour and the risk of depression: a meta-analysis. Br J Sports Med. 2015;49(11):705–709.
    1. Chau JY, Grunseit AC, Chey T, Stamatakis E, Brown WJ, Matthews CE, et al. Daily sitting time and all-cause mortality: a meta-analysis. PLoS One. 2013;8:11.
    1. Saunders TJ, Larouche R, Colley RC, Tremblay MS. Acute sedentary behaviour and markers of cardiometabolic risk: a systematic review of intervention studies. J Nutr Metab. 2012;2012(12):1–12.
    1. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9):498–504.
    1. Sedentary Behaviour Research Network Sedentary behaviour research network letter to the editor: standardized use of the terms “sedentary” and “sedentary behaviours”. Appl Physiol Nutr Metab. 2012;37:540–542.
    1. Tremblay MS, Aubert S, Barnes JD, Saunders TJ, Carson V, Latimer-Cheung AE, et al. Sedentary behavior research network (SBRN) - terminology consensus project process and outcome. Int J Behav Nutr Phys Act. 2017;14:75.
    1. Liangruenrom N, Suttikasem K, Craike M, Bennie JA, Biddle SJH, Pedisic Z. Physical activity and sedentary behaviour research in Thailand: a systematic scoping review. BMC Public Health. 2018;18:1.
    1. Ding D, Lawson KD, Kolbe-Alexander TL, Finkelstein EA, Katzmarzyk PT, van Mechelen W, et al. The economic burden of physical inactivity: a global analysis of major non-communicable diseases. Lancet. 2016;388(10051):1311–1324.
    1. Thanamee S, Pinyopornpanish K, Wattanapisit A, Suerungruang S, Thaikla K, Jiraporncharoen W, et al. A population-based survey on physical inactivity and leisure time physical activity among adults in Chiang Mai, Thailand, 2014. Arch Public Health. 2017;75:41.
    1. Gottmann J. Urbanisation and employment: towards a general theory. Town Plan Rev. 1978;49:3.
    1. Parry S, Straker L. The contribution of office work to sedentary behaviour associated risk. BMC Public Health. 2013;13(296):1471–2458.
    1. Ryan CG, Dall PM, Granat MH, Grant PM. Sitting patterns at work: objective measurement of adherence to current recommendations. Ergonomics. 2011;54(6):531–538.
    1. Straker L, Mathiassen SE. Increased physical work loads in modern work--a necessity for better health and performance? Ergonomics. 2009;52(10):1215–1225.
    1. Thorpe A, Dunstan D, Clark B, Gardiner P, Healy G, Keegel T, et al. Stand up Australia: sedentary behaviour in workers. Australia: Medibank Private; 2009.
    1. Hamilton MT, Hamilton DG, Zderic TW. Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes. 2007;56(11):2655–2667.
    1. World Health Organisation (WHO). Global Recommendations on Physical Activity for Health. . Accessed 10 June 2020.
    1. Mailey EL, Rosenkranz SK, Casey K, Swank A. Comparing the effects of two different break strategies on occupational sedentary behavior in a real world setting: a randomized trial. Prev Med Rep. 2016;4(1):423–428.
    1. Evans RE, Fawole HO, Sheriff SA, Dall PM, Grant PM, Ryan CG. Point-of-choice prompts to reduce sitting time at work: a randomized trial. Am J Prev Med. 2012;43(3):293–297.
    1. Mailey EL, Rosenkranz SK, Ablah E, Swank A, Casey K. Effects of an intervention to reduce sitting at work on arousal, fatigue, and mood among sedentary female employees: a parallel-group randomized trial. J Occup Environ Med. 2017;59(12):1166–1171.
    1. Pedersen SJ, Cooley PD, Mainsbridge C. An e-health intervention designed to increase workday energy expenditure by reducing prolonged occupational sitting habits. Work. 2014;49(2):289–295.
    1. Sui W, Prapavessis H. Standing up for student health: an application of the health action process approach for reducing student sedentary behavior-randomised control pilot trial. Appl Psychol Health Well Being. 2018;10(1):87–107.
    1. Swartz AM, Rote AE, Welch WA, Maeda H, Hart TL, Cho YI, et al. Prompts to disrupt sitting time and increase physical activity at work, 2011–2012. Prev Chronic Dis. 2014;11:E73.
    1. Priebe CS, Spink KS. Less sitting and more moving in the office: using descriptive norm messages to decrease sedentary behavior and increase light physical activity at work. Psychol Sport Exerc. 2015;19(1):76–84.
    1. Hutchinson J, Headley S, Matthews T, Spicer G, Dempsey K, Wooley S, et al. Changes in sitting time and sitting fragmentation after a workplace sedentary behaviour intervention. Int J Environ Res Public Health. 2018;15:6.
    1. Taylor WC, Paxton RJ, Shegog R, Coan SP, Dubin A, Page TF, et al. Impact of booster breaks and computer prompts on physical activity and sedentary behavior among desk-based workers: a cluster-randomized controlled trial. Prev Chronic Dis. 2016;13:12.
    1. Thai Clinical Trials Registry (TCTR). . Accessed 27 Apr 2020.
    1. Owen N, Sugiyama T, Eakin EE, Gardiner PA, Tremblay MS, Sallis JF. Adults' sedentary behavior determinants and interventions. Am J Prev Med. 2011;41(2):189–196.
    1. Mullane SL, Toledo MJL, Rydell SA, Feltes LH, Vuong B, Crespo NC, et al. Social ecological correlates of workplace sedentary behavior. Int J Behav Nutr Phys Act. 2017;14:1.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med. 2013;46(1):81–95.
    1. Fitbit. How does Fitbit Device Calculate my Daily Activity? Accessed 11 June 2020..
    1. Patel MS, Asch DA, Rosin R, Small DS, Bellamy SL, Eberbach K, et al. Individual versus team-based financial incentives to increase physical activity: a randomized, controlled trial. J Gen Intern Med. 2016;31(7):746–754.
    1. Kullgren JT, Troxel AB, Loewenstein G, Asch DA, Norton LA, Wesby L, et al. Individual- versus group-based financial incentives for weight loss: a randomized, controlled trial. Ann Intern Med. 2013;158(7):505–514.
    1. Steve. The Line Phenomenon in Thailand by the Numbers. . Accessed 23 Aprl 2020.
    1. Muller AM, Tan CS, Chu AHY, van Dam RM, Muller-Riemenschneider F. Associations between psychological factors and accelerometer-measured physical activity in urban Asian adults. Int J Public Health. 2019;64(5):659–668.
    1. Sasaki JE, John D, Freedson PS. Validation and comparison of ActiGraph activity monitors. J Sci Med Sport. 2011;14(5):411–416.
    1. Bull FC, Maslin TS, Armstrong T. Global physical activity questionnaire (GPAQ): nine country reliability and validity study. J Phys Act Health. 2009;6(6):790–804.
    1. Pickering TG, Hall JE, Appel LJ, Falkner BE, Graves J, Hill MN, et al. Recommendations for blood pressure measurement in humans and experimental animals: part 1: blood pressure measurement in humans: a statement for professionals from the Subcommittee of Professional and Public Education of the American Heart Association Council on high blood pressure research. Hypertension. 2005;45(1):142–161.
    1. Nhealth Asia . Accessed 3 June 2020.
    1. EuroQol Research Foundation. EQ-5D-5L-English-User-Guide. . Accessed 22 May 2020.
    1. Kuorinka I, Jonsson B, Kilborn A, Vinterberg H, Biering-Soerensen F, Andersson G, et al. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl Ergon. 1987;18(3):233–237.
    1. Riewpaiboon A. PRM3 standard cost list for economic evaluation in Thailand. Value Health. 2012;15:7.
    1. Mahidol University (MU). Rama-EGAT haert score . Accessed 27 April 2020.
    1. Yingchoncharoen T, Limpijankit T, Jongjirasiri S, Laothamatas J, Yamwong S, Sritara P. Arterial stiffness contributes to coronary artery disease risk prediction beyond the traditional risk score (RAMA-EGAT score) Heart Asia. 2012;4(1):77–82.
    1. Wilkinson T, Sculpher MJ, Claxton K, Revill P, Briggs A, Cairns JA, et al. The international decision support initiative reference case for economic evaluation: an aid to thought. Value Health. 2016;19(8):921–928.
    1. Wang NX, Chen J, Wagner LN, Rebello SA, Petrunoff NA, Owen N, et al. Understanding and influencing occupational sedentary behavior: a mixed-methods approach in a multiethnic Asian population. Health Educ Behav. 2020;47(6):419–429.
    1. Muller AM, Wang NX, Yao J, Tan CS, Low ICC, Lim N, et al. Heart rate measures from wrist-worn activity trackers in a laboratory and free-living setting: validation study. JMIR Mhealth Uhealth. 2019;7:10.
    1. Chu AH, Ng SH, Tan CS, Win AM, Koh D, Muller-Riemenschneider F. A systematic review and meta-analysis of workplace intervention strategies to reduce sedentary time in white-collar workers. Obes Rev. 2016;17(5):467–481.
    1. Muller AM, Chen B, Wang NX, Whitton C, Direito A, Petrunoff N, et al. Correlates of sedentary behaviour in Asian adults: a systematic review. Obes Rev. 2020;21:4.
    1. Ministry of Health (MOH) Singapore. National Step Challenge Community Challenge. . Accessed 23 Apr 2020.
    1. International Committee of Medical Jouranl Editing (ICMJE). Defining the Roles of Authors and Contributors . Accessed 4 June 2020.

Source: PubMed

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