Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among UK adolescents: A cluster randomised controlled trial

English version

Autoři: Kirsten Corder ^aff001; Stephen J. Sharp ^aff001; Stephanie T. Jong ^aff001; Campbell Foubister ^aff001; Helen Elizabeth Brown ^aff001; Emma K. Wells ^aff001; Sofie M. Armitage ^aff001; Caroline H. D. Croxson ^aff004; Anna Vignoles ^aff005; Paul O. Wilkinson ^aff006; Edward C. F. Wilson ^aff008; Esther M. F. van Sluijs ^aff001
Působiště autorů: UKCRC Centre for Diet and Activity Research, University of Cambridge, Cambridge, United Kingdom ^aff001; MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom ^aff002; Faculty of Medicine and Health Sciences, University of East Anglia, Norwich, United Kingdom ^aff003; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom ^aff004; Faculty of Education, University of Cambridge, Cambridge, United Kingdom ^aff005; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom ^aff006; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, United Kingdom ^aff007; Health Economics Group, Norwich Medical School, University of East Anglia, Norwich, United Kingdom ^aff008
Vyšlo v časopise: Effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among UK adolescents: A cluster randomised controlled trial. PLoS Med 17(7): e32767. doi:10.1371/journal.pmed.1003210
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pmed.1003210

Souhrn

Background

Less than 20% of adolescents globally meet recommended levels of physical activity, and not meeting these recommended levels is associated with social disadvantage and rising disease risk. The determinants of physical activity in adolescents are multilevel and poorly understood, but the school’s social environment likely plays an important role. We conducted a cluster randomised controlled trial to assess the effectiveness of a school-based programme (GoActive) to increase moderate-to-vigorous physical activity (MVPA) among adolescents.

Methods and findings

Non-fee-paying, co-educational schools including Year 9 students in the UK counties of Cambridgeshire and Essex were eligible for inclusion. Within participating schools (n = 16), all Year 9 students were eligible and invited to participate. Participants were 2,862 13 -⁠ to 14-year-olds (84% of eligible students). After baseline assessment, schools were computer-randomised, stratified by school-level pupil premium funding (below/above county-specific median) and county (control: 8 schools, 1,319 participants, mean [SD] participants per school n = 165 [62]; intervention: 8 schools, 1,543 participants, n = 193 [43]). Measurement staff were blinded to allocation. The iteratively developed, feasibility-tested 12-week intervention, aligned with self-determination theory, trained older adolescent mentors and in-class peer-leaders to encourage classes to conduct 2 new weekly activities. Students and classes gained points and rewards for engaging in any activity in or out of school. The primary outcome was average daily minutes of accelerometer-assessed MVPA at 10-month follow-up; a mixed-methods process evaluation evaluated implementation. Of 2,862 recruited participants (52.1% male), 2,167 (76%) attended 10-month follow-up measurements; we analysed the primary outcome for 1,874 participants (65.5%). At 10 months, there was a mean (SD) decrease in MVPA of 8.3 (19.3) minutes in the control group and 10.4 (22.7) minutes in the intervention group (baseline-adjusted difference [95% confidence interval] −1.91 minutes [−5.53 to 1.70], p = 0.316). The programme cost £13 per student compared with control; it was not cost-effective. Overall, 62.9% of students and 87.3% of mentors reported that GoActive was fun. Teachers and mentors commented that their roles in programme delivery were unclear. Implementation fidelity was low. The main methodological limitation of this study was the relatively affluent and ethnically homogeneous sample.

Conclusions

In this study, we observed that a rigorously developed school-based intervention was no more effective than standard school practice at preventing declines in adolescent physical activity. Interdisciplinary research is required to understand educational-setting-specific implementation challenges. School leaders and authorities should be realistic about expectations of the effect of school-based physical activity promotion strategies implemented at scale.

Trial registration

ISRCTN Registry ISRCTN31583496.

Klíčová slova:

Adolescents – Body weight – Ethnicities – Exercise – Physical activity – Schools – Teachers – Sedentary behavior

Zdroje

1. World Health Organization. Global health risks: mortality and burden of disease attributable to selected major risks. Geneva: World Health Organization; 2009.

2. Guthold R, Stevens GA, Riley LM, Bull FC. Global trends in insufficient physical activity among adolescents: a pooled analysis of 298 population-based surveys with 1.6 million participants. Lancet Child Adolesc Health. 2020;4(1):23–35. doi: 10.1016/S2352-4642(19)30323-2 31761562

3. Poitras VJ, Gray CE, Borghese MM, Carson V, Chaput J-P, Janssen I, et al. Systematic review of the relationships between objectively measured physical activity and health indicators in school-aged children and youth. Appl Physiol Nutr Metab. 2016;41(6):S197–239. doi: 10.1139/apnm-2015-0663 27306431

4. Aberg MA, Pedersen NL, Toren K, Svartengren M, Backstrand B, Johnsson T, et al. Cardiovascular fitness is associated with cognition in young adulthood. Proc Natl Acad Sci U S A. 2009;106(49):20906–11. doi: 10.1073/pnas.0905307106 19948959

5. Shrestha R, Copenhaver M. Long-term effects of childhood risk factors on cardiovascular health during adulthood. Clin Med Rev Vasc Health. 2015;7 : 1–5. doi: 10.4137/CMRVH.S29964 26312015

6. Koivusilta L, Rimpela A, Rimpela M. Health status: does it predict choice in further education? J Epidemiol Community Health. 1995;49(2):131–8. doi: 10.1136/jech.49.2.131 7798039

7. Koivusilta L, Rimpela A, Rimpela M. Health related lifestyle in adolescence predicts adult educational level: a longitudinal study from Finland. J Epidemiol Community Health. 1998;52(12):794–801. doi: 10.1136/jech.52.12.794 10396520

8. Koivusilta L, Rimpela A, Vikat A. Health behaviours and health in adolescence as predictors of educational level in adulthood: a follow-up study from Finland. Soc Sci Med. 2003;57(4):577–93. doi: 10.1016/s0277-9536(02)00405-7 12821008

9. Koivusilta LK, Rimpela AH, Rimpela M, Vikat A. Health behavior-based selection into educational tracks starts in early adolescence. Health Educ Res. 2001;16(2):201–14. doi: 10.1093/her/16.2.201 11345662

10. Koivusilta LK, Rimpela AH, Rimpela MK. Health-related lifestyle in adolescence—origin of social class differences in health? Health Educ Res. 1999;14(3):339–55. doi: 10.1093/her/14.3.339 10539226

11. Koivusilta LK, West P, Saaristo VM, Nummi T, Rimpela AH. From childhood socio-economic position to adult educational level—do health behaviours in adolescence matter? A longitudinal study. BMC Public Health. 2013;13 : 711. doi: 10.1186/1471-2458-13-711 23915293

12. Brooke HL, Atkin AJ, Corder K, Ekelund U, van Sluijs EM. Changes in time-segment specific physical activity between ages 10 and 14 years: a longitudinal observational study. J Sci Med Sport. 2016;19(1):29–34. doi: 10.1016/j.jsams.2014.10.003 25459234

13. Corder K, Schiff A, Kesten JM, van Sluijs EM. Development of a universal approach to increase physical activity among adolescents: the GoActive intervention. BMJ Open. 2015;5(8):e008610. doi: 10.1136/bmjopen-2015-008610 26307618

14. Love R, Adams J, van Sluijs EMF. Are school-based physical activity interventions effective and equitable? A meta-analysis of cluster randomized controlled trials with accelerometer-assessed activity. Obes Rev. 2019;20(6):859–70. doi: 10.1111/obr.12823 30628172

15. Borde R, Smith JJ, Sutherland R, Nathan N, Lubans DR. Methodological considerations and impact of school-based interventions on objectively measured physical activity in adolescents: a systematic review and meta-analysis. Obes Rev. 2017;18(4):476–90. doi: 10.1111/obr.12517 28187241

16. Sutherland R, Reeves P, Campbell E, Lubans DR, Morgan PJ, Nathan N, et al. Cost effectiveness of a multi-component school-based physical activity intervention targeting adolescents: the ‘Physical Activity 4 Everyone’ cluster randomized trial. Int J Behav Nutr Phys Act. 2016;13 : 94. doi: 10.1186/s12966-016-0418-2 27549382

17. Harrington DM, Davies MJ, Bodicoat DH, Charles JM, Chudasama YV, Gorely T, et al. Effectiveness of the ‘Girls Active’ school-based physical activity programme: a cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2018;15(1):40. doi: 10.1186/s12966-018-0664-6 29695250

18. Duncan E, O’Cathain A, Rousseau N, Croot L, Sworn K, Turner KM, et al. Guidance for reporting intervention development studies in health research (GUIDED): an evidence-based consensus study. BMJ Open. 2020;10(4):e033516. doi: 10.1136/bmjopen-2019-033516 32273313

19. van Sluijs EM, Kriemler S, McMinn AM. The effect of community and family interventions on young people’s physical activity levels: a review of reviews and updated systematic review. Br J Sports Med. 2011;45(11):914–22. doi: 10.1136/bjsports-2011-090187 21836175

20. Corder K, Atkin AJ, Ekelund U, van Sluijs EM. What do adolescents want in order to become more active? BMC Public Health. 2013;13 : 718. doi: 10.1186/1471-2458-13-718 23914878

21. Corder K, Brown HE, Schiff A, van Sluijs EM. Feasibility study and pilot cluster-randomised controlled trial of the GoActive intervention aiming to promote physical activity among adolescents: outcomes and lessons learnt. BMJ Open. 2016;6(11):e012335. doi: 10.1136/bmjopen-2016-012335 27836873

22. Shochet IM, Dadds MR, Holland D, Whitefield K, Harnett PH, Osgarby SM. The efficacy of a universal school-based program to prevent adolescent depression. J Clin Child Psychol. 2001;30(3):303–15. doi: 10.1207/S15374424JCCP3003_3 11501248

23. Ryan D, Deci E. Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000;55 : 68–78. doi: 10.1037//0003-066x.55.1.68 11392867

24. Brown HE, Whittle F, Jong ST, Croxson C, Sharp SJ, Wilkinson P, et al. A cluster randomised controlled trial to evaluate the effectiveness and cost-effectiveness of the GoActive intervention to increase physical activity among adolescents aged 13–14 years. BMJ Open. 2017;7(9):e014419. doi: 10.1136/bmjopen-2016-014419 28963278

25. Department for Education, Education and Skills Funding Agency. Pupil premium: effective use and accountability. London: Department of Education; 2019 [cited 2019 Sep 5]. Available from: https://www.gov.uk/guidance/pupil-premium-information-for-schools-and-alternative-provision-settings.

26. Bartholomew LK, Parcel GS, Kok G, Gottlieb NH. Planning health promotion programs: an intervention mapping approach. 2nd edition. San Francisco: Jossey-Bass; 2006.

27. Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337:a1655. doi: 10.1136/bmj.a1655 18824488

28. Sallis JF, Owen N, Fotheringham MJ. Behavioral epidemiology: a systematic framework to classify phases of research on health promotion and disease prevention. Ann Behav Med. 2000;22(4):294–8. doi: 10.1007/BF02895665 11253440

29. Jong ST, Croxson CHD, Guell C, Lawlor ER, Foubister C, Brown HE, et al. Adolescents’ perspectives on a school-based physical activity intervention: a mixed method study. J Sport Health Sci. 2020;9(1):28–40. doi: 10.1016/j.jshs.2019.06.007 31921478

30. White T, Westgate K, Wareham NJ, Brage S. Estimation of physical activity energy expenditure during free-living from wrist accelerometry in UK adults. PLoS ONE. 2016;11(12):e0167472. doi: 10.1371/journal.pone.0167472 27936024

31. Scott JJ, Rowlands AV, Cliff DP, Morgan PJ, Plotnikoff RC, Lubans DR. Comparability and feasibility of wrist -⁠ and hip-worn accelerometers in free-living adolescents. J Sci Med Sport. 2017;20(12):1101–6. doi: 10.1016/j.jsams.2017.04.017 28501418

32. Collings PJ, Wijndaele K, Corder K, Westgate K, Ridgway CL, Dunn V, et al. Levels and patterns of objectively-measured physical activity volume and intensity distribution in UK adolescents: the ROOTS study. Int J Behav Nutr Phys Act. 2014;11 : 23. doi: 10.1186/1479-5868-11-23 24564949

33. Ricardo LIC, Wendt A, Galliano LM, de Andrade Muller W, Nino Cruz GI, Wehrmeister F, et al. Number of days required to estimate physical activity constructs objectively measured in different age groups: findings from three Brazilian (Pelotas) population-based birth cohorts. PLoS ONE. 2020;15(1):e0216017. doi: 10.1371/journal.pone.0216017 31923194

34. Saunders R, Pate R, Felton G, Dowda M, Weinrich M, Ward D, et al. Development of questionnaires to measure psychosocial influences on children’s physical activity. Prev Med. 1997;26(2):241–7. doi: 10.1006/pmed.1996.0134 9085394

35. Ommundsen Y, Page A, Po-Wen K, Cooper AR. Cross-cultural, age and gender validation of a computerised questionnaire measuring personal, social and environmental associations with children’s physical activity: the European Youth Heart Study. Int J Behav Nutr Phys Act. 2008;5 : 29. doi: 10.1186/1479-5868-5-29 18489736

36. Goodyer IM, Herbert J, Tamplin A, Secher SM, Pearson J. Short-term outcome of major depression: II. Life events, family dysfunction, and friendship difficulties as predictors of persistent disorder. J Am Acad Child Adolesc Psychiatry. 1997;36(4):474–80. doi: 10.1097/00004583-199704000-00009 9100421

37. Clarke A, Friede T, Putz R, Ashdown J, Martin S, Blake A, et al. Warwick-Edinburgh Mental Well-being Scale (WEMWBS): validated for teenage school students in England and Scotland. A mixed methods assessment. BMC Public Health. 2011;11 : 487. doi: 10.1186/1471-2458-11-487 21693055

38. Rosenberg M. Conceiving the self. New York: Basic Books; 1979.

39. Corder K, van Sluijs EM, Wright A, Whincup P, Wareham NJ, Ekelund U. Is it possible to assess free-living physical activity and energy expenditure in young people by self-report? Am J Clin Nutr. 2009;89(3):862–70. doi: 10.3945/ajcn.2008.26739 19144732

40. Cole TJ, Bellizzi MC, Flegal KM, Dietz WH. Establishing a standard definition for child overweight and obesity worldwide: international survey. BMJ. 2000;320(7244):1240–3. doi: 10.1136/bmj.320.7244.1240 10797032

41. Jong ST, Brown HE, Croxson CHD, Wilkinson P, Corder KL, van Sluijs EMF. GoActive: a protocol for the mixed methods process evaluation of a school-based physical activity promotion programme for 13-14year old adolescents. Trials. 2018;19(1):282. doi: 10.1186/s13063-018-2661-0 29784016

42. Johnson MRD, Bhopal RS, Ingleby JD, Gruer L, Petrova-Benedict RS. A glossary for the first World Congress on Migration, Ethnicity, Race and Health. Public Health. 2019;172 : 85–8. doi: 10.1016/j.puhe.2019.05.001 31204074

43. Currie C, Molcho M, Boyce W, Holstein B, Torsheim T, Richter M. Researching health inequalities in adolescents: the development of the Health Behaviour in School-Aged Children (HBSC) family affluence scale. Soc Sci Med. 2008;66(6):1429–36. doi: 10.1016/j.socscimed.2007.11.024 18179852

44. Voracova J, Sigmund E, Sigmundova D, Kalman M. Family affluence and the eating habits of 11 -⁠ to 15-year-old Czech adolescents: HBSC 2002 and 2014. Int J Environ Res Public Health. 2016;13(10):1034. doi: 10.3390/ijerph13101034 27783063

45. Stevens K, Ratcliffe J. Measuring and valuing health benefits for economic evaluation in adolescence: an assessment of the practicality and validity of the child health utility 9D in the Australian adolescent population. Value Health. 2012;15(8):1092–9. doi: 10.1016/j.jval.2012.07.011 23244812

46. Corder K, Sharp SJ, Atkin AJ, Griffin SJ, Jones AP, Ekelund U, et al. Change in objectively measured physical activity during the transition to adolescence. Br J Sports Med. 2015;49(11):730–6. doi: 10.1136/bjsports-2013-093190 24273308

47. Howie EK, Straker LM. Rates of attrition, non-compliance and missingness in randomized controlled trials of child physical activity interventions using accelerometers: a brief methodological review. J Sci Med Sport. 2016;19(10):830–6. doi: 10.1016/j.jsams.2015.12.520 26874648

48. StataCorp. Stata Statistical Software. Release 15. College Station (TX): StataCorp; 2017.

49. White IR, Thompson SG. Adjusting for partially missing baseline measurements in randomized trials. Stat Med. 2005;24(7):993–1007. doi: 10.1002/sim.1981 15570623

50. White IR, Carpenter J, Horton NJ. Including all individuals is not enough: lessons for intention-to-treat analysis. Clin Trials. 2012;9(4):396–407. doi: 10.1177/1740774512450098 22752633

51. McCrabb S, Lane C, Hall A, Milat A, Bauman A, Sutherland R, et al. Scaling-up evidence-based obesity interventions: a systematic review assessing intervention adaptations and effectiveness and quantifying the scale-up penalty. Obes Rev. 2019;20(7):964–82. doi: 10.1111/obr.12845 30868745

52. Beets MW, Okely A, Weaver RG, Webster C, Lubans D, Brusseau T, et al. The theory of expanded, extended, and enhanced opportunities for youth physical activity promotion. Int J Behav Nutr Phys Act. 2016;13(1):120. doi: 10.1186/s12966-016-0442-2 27852272

53. Trost S, Pate R, Sallis J, Freedson P, Taylor W, Dowda M, et al. Age and gender differences in objectively measured physical activity in youth. Med Sci Sports Exerc. 2002;25(6):350–5.

54. Drenowatz C, Eisenmann JC, Pfeiffer KA, Welk G, Heelan K, Gentile D, et al. Influence of socio-economic status on habitual physical activity and sedentary behavior in 8 -⁠ to 11-year old children. BMC Public Health. 2010;10 : 214. doi: 10.1186/1471-2458-10-214 20423487

55. Sherar LB, Griffin TP, Ekelund U, Cooper AR, Esliger DW, van Sluijs EMF, et al. Association between maternal education and objectively measured physical activity and sedentary time in adolescents. J Epidemiol Community Health. 2016;70(6):541–8. doi: 10.1136/jech-2015-205763 26802168

56. Love R, Adams J, Atkin A, van Sluijs E. Socioeconomic and ethnic differences in children’s vigorous intensity physical activity: a cross-sectional analysis of the UK Millennium Cohort Study. BMJ Open. 2019;9(5):e027627. doi: 10.1136/bmjopen-2018-027627 31133593

57. Wiltshire G, Lee J, Williams O. Understanding the reproduction of health inequalities: physical activity, social class and Bourdieu’s habitus. Sport Educ Soc. 2019;24(3):226–40. doi: 10.1080/13573322.2017.1367657

58. Stringhini S, Sabia S, Shipley M, Brunner E, Nabi H, Kivimaki M, et al. Association of socioeconomic position with health behaviors and mortality. JAMA. 2010;303(12):1159–66. doi: 10.1001/jama.2010.297 20332401

59. United Nations. Sustainable Development Goals. New York: United Nations; 2020 [cited 2020 Jul 7]. Available from: https://www.un.org/sustainabledevelopment/sustainable-development-goals/.

60. Sutherland RL, Campbell EM, Lubans DR, Morgan PJ, Nathan NK, Wolfenden L, et al. The Physical Activity 4 Everyone cluster randomized trial: 2-year outcomes of a school physical activity intervention among adolescents. Am J Prev Med. 2016;51(2):195–205. doi: 10.1016/j.amepre.2016.02.020 27103495

61. Dumith SC, Gigante DP, Domingues MR, Kohl HW 3rd. Physical activity change during adolescence: a systematic review and a pooled analysis. Int J Epidemiol. 2011;40(3):685–98. doi: 10.1093/ije/dyq272 21245072

62. Brooke HL, Corder K, Atkin AJ, van Sluijs EM. A systematic literature review with meta-analyses of within -⁠ and between-day differences in objectively measured physical activity in school-aged children. Sports Med. 2014;44(10):1427–38. doi: 10.1007/s40279-014-0215-5 24981243

63. Education and Skills Funding Agency. Pupil premium: allocations and conditions of grant 2018 to 2019. Coventry: Education and Skills Funding Agency; 2019 [cited 2019 Jul 23]. Available from: https://www.gov.uk/government/publications/pupil-premium-conditions-of-grant-2018-to-2019.

64. Office for National Statistics. Population of England and Wales. London: Office for National Statistics; 2019 [cited 2019 Jul 23]. Available from: https://www.ethnicity-facts-figures.service.gov.uk/uk-population-by-ethnicity/national-and-regional-populations/population-of-england-and-wales/latest.

65. All-Party Commission on Physical Activity. Tackling physical inactivity—a coordinated approach. London: All-Party Commission on Physical Activity; 2014 [cited 2019 Jul 18]. Available from: https://parliamentarycommissiononphysicalactivity.files.wordpress.com/2014/04/apcopa-final.pdf.

66. Centers for Disease Control and Prevention. Increasing physical education and physical activity: a framework for schools. Atlanta: Centers for Disease Control and Prevention; 2019 [cited 2020 Jul 6]. Available from: https://www.cdc.gov/healthyschools/physicalactivity/pdf/2019_04_25_PE-PA-Framework_508tagged.pdf.

67. World Health Organization. Health Promoting School: an effective approach for early action on NCD risk factors. Geneva: World Health Organization; 2017 [cited 2020 Jun 5]. Available from: https://www.who.int/healthpromotion/publications/health-promotion-school/en/.

68. Daly-Smith A, Quarmby T, Archbold VSJ, Corrigan N, Wilson D, Resaland GK, et al. Using a multi-stakeholder experience-based design process to co-develop the Creating Active Schools Framework. Int J Behav Nutr Phys Act. 2020;17(1):13. doi: 10.1186/s12966-020-0917-z 32028968

69. Breheny K, Adab P, Passmore S, Martin J, Lancashire E, Hemming K, et al. A cluster randomised controlled trial evaluating the effectiveness and cost-effectiveness of the daily mile on childhood obesity and wellbeing; the Birmingham daily mile protocol. BMC Public Health. 2018;18(1):126. doi: 10.1186/s12889-017-5019-8 29325517

70. Chesham RA, Booth JN, Sweeney EL, Ryde GC, Gorely T, Brooks NE, et al. The Daily Mile makes primary school children more active, less sedentary and improves their fitness and body composition: a quasi-experimental pilot study. BMC Med. 2018;16(1):64. doi: 10.1186/s12916-018-1049-z 29743076

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