A feasibility study of 'The StepSmart Challenge' to promote physical activity in adolescents

Rekesh Corepal, Paul Best, Roisin O'Neill, Frank Kee, Jennifer Badham, Laura Dunne, Sarah Miller, Paul Connolly, Margaret E Cupples, Esther M F van Sluijs, Mark A Tully, Ruth F Hunter, Rekesh Corepal, Paul Best, Roisin O'Neill, Frank Kee, Jennifer Badham, Laura Dunne, Sarah Miller, Paul Connolly, Margaret E Cupples, Esther M F van Sluijs, Mark A Tully, Ruth F Hunter

Abstract

Background: Inactive lifestyles are becoming the norm and creative approaches to encourage adolescents to be more physically active are needed. Little is known about how gamification techniques can be used in physical activity interventions for young people. Such approaches may stimulate interest and encourage physical activity behaviour. The study investigated the feasibility of implementing and evaluating a physical activity intervention for adolescents which included gamification techniques within schools. We tested recruitment and retention strategies for schools and participants, the use of proposed outcome measures, and explored intervention acceptability.

Methods: This school-based feasibility study of a randomised cluster trial recruited adolescents aged 12-14 years (n = 224) from five schools (three intervention; two control) in Belfast, Northern Ireland. The 22-week intervention (The StepSmart Challenge) informed by self-determination theory and incorporating gamification strategies involved a school-based pedometer competition. Outcomes, measured at baseline, and post-intervention (at 22 weeks post-baseline and 52 weeks post-baseline) included daily minutes of moderate to vigorous physical activity (MVPA) (measured using ActiGraph accelerometer), mental wellbeing (Warwick-Edinburgh Mental Wellbeing Scale), social support for physical activity, time preference (for delayed and larger rewards or immediate and smaller rewards), pro-social behaviour (Strengths and Difficulties Questionnaire (SDQ)) and the influence of social networks. The intervention's acceptability was explored in focus groups.

Results: We invited 14 schools to participate; eight showed interest in participating. We recruited the first five who responded; all five completed the trial. Of the 236 pupils invited, 224 participated (94.9%): 84.8% (190/224) provided valid MVPA (minutes/day) at baseline and 57.2% (123/215) at 52 weeks. All other outcomes were well completed apart from the SDQ (65% at baseline). Qualitative data highlighted that participants and teachers found The StepSmart Challenge to be an acceptable intervention.

Conclusions: The level of interest and high recruitment and retention rates provide support for the feasibility of this trial. The intervention, incorporating gamification strategies and the recruitment methods, using parental opt-out procedures, were acceptable to participants and teachers. Teachers also suggested that the implementation of The StepSmart Challenge could be embedded in a lifelong learning approach to health within the school curriculum. As young people's lives become more intertwined with technology, the use of innovative gamified interventions could be one approach to engage and motivate health behavioural change in this population.

Trial registration: NCT02455986 (date of registration: 28 May 2015).

Keywords: Adolescents; Behaviour change; Feasibility; Gamification; Intervention; Mixed methods; Physical activity; Randomised controlled trial; Schools.

Conflict of interest statement

Competing interestsThe authors declare that they have no competing interests.

© The Author(s). 2019.

Figures

Fig. 1
Fig. 1
The StepSmart Challenge logic model
Fig. 2
Fig. 2
CONSORT participant flow diagram

References

    1. Best P, Tully MA, Corepal R, Kee F, Hunter RF. Time to ‘re-think’ physical activity promotion for young people? Results from a repeated cross-sectional study. BMC Public Health. 2017;17:208. doi: 10.1186/s12889-017-4136-8.
    1. Bingham DD, Costa S, Clemes SA, Routen AC, Moore HJ, Barber SE. Accelerometer data requirements for reliable estimation of habitual physical activity and sedentary time of children during the early years - a worked example following a stepped approach. J Sports Sci. 2016;34:2005–2010. doi: 10.1080/02640414.2016.1149605.
    1. 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;18:476–490. doi: 10.1111/obr.12517.
    1. Braun V, Clarke V. Using thematic analysis in psychology. Qual Res Psychol. 2006;3:77–101. doi: 10.1191/1478088706qp063oa.
    1. Cain K, Geremia C. Accelerometer data collection and scoring manual for adult & senior studies. San Deiago: San Diego Stae University; 2012.
    1. Casey MM, Eime RM, Payne WR, Harvey JT. Using a socioecological approach to examine participation in sport and physical activity among rural adolescent girls. Qual Health Res. 2009;19:881–893. doi: 10.1177/1049732309338198.
    1. Coombes E, Jones A. Gamification of active travel to school: a pilot evaluation of the beat the street physical activity intervention. Health Place. 2016;39:62–69. doi: 10.1016/j.healthplace.2016.03.001.
    1. 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:e012335. doi: 10.1136/bmjopen-2016-012335.
    1. Corepal R, Best P, O'Neill R, Tully MA, Edwards M, Jago R, Miller SJ, Kee F, Hunter RF. Exploring the use of a gamified intervention for encouraging physical activity in adolescents: a qualitative longitudinal study in Northern Ireland. BMJ Open. 2018;8:e019663.
    1. Corepal R, Tully MA, Kee F, Miller SJ, Hunter RF. Behavioural incentive interventions for health behaviour change in young people (5-18years old): a systematic review and meta-analysis. Prev Med. 2018;110:55–66. doi: 10.1016/j.ypmed.2018.02.004.
    1. Csardi G, Nepusz T. The igraph software package for complex network research. InterJ Complex Syst. 2006;1695(5):1–9.
    1. Cugelman B. Gamification: what it is and why it matters to digital health behavior change developers. JMIR Serious Games. 2013;1:e3. doi: 10.2196/games.3139.
    1. Deterding S, Dixon D, Khaled R, Nacke L. From game design elements to gamefulness: defining gamification. In: Proceedings of the 15th international academic MindTrek conference: envisioning future media environments: ACM; 2011. p. 9–15.
    1. Dobbins M, Husson H, DeCorby K, LaRocca RL. School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18. Cochrane Database Syst Rev. 2013:CD007651.
    1. DoE. School enrolments - school level data: Department of Education; 2015.
    1. Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG. Calibration of two objective measures of physical activity for children. J Sports Sci. 2008;26:1557–1565. doi: 10.1080/02640410802334196.
    1. Fitzgerald A, Fitzgerald N, Aherne C. Do peers matter? A review of peer and/or friends' influence on physical activity among American adolescents. J Adolesc. 2012;35:941–958. doi: 10.1016/j.adolescence.2012.01.002.
    1. Goodman R. The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry. 1997;38:581–586. doi: 10.1111/j.1469-7610.1997.tb01545.x.
    1. Hanneman RA, Riddle M. Introduction to social network methods. Riverside: University of California, Riverside; 2005.
    1. Harrington DM, Murphy M, Carlin A, Coppinger T, Donnelly A, Dowd KP, Keating T, Murphy N, Murtagh E, et al. Results from Ireland north and South’s 2016 report card on physical activity for children and youth. J Phys Act Health. 2016;13:S183–SS88. doi: 10.1123/jpah.2016-0334.
    1. He J, McClish D. The application of last observation carried forward in the persistent binary case. Austin Biom Biostat. 2015;2:1018.
    1. Humphreys BR, Ruseski JE, Zhou L. Physical activity, present bias, and habit formation: theory and evidence from longitudinal data. Working Paper No. 2015-06. 2015.
    1. Hunter RF, de Silva D, Reynolds V, Bird W, Fox KR. International inter-school competition to encourage children to walk to school: a mixed methods feasibility study. BMC Res Notes. 2015;8:19. doi: 10.1186/s13104-014-0959-x.
    1. Hunter RF, McAneney H, Davis M, Tully MA, Valente TW, Kee F. “Hidden” social networks in behavior change interventions. Am J Public Health. 2015;105:513–516. doi: 10.2105/AJPH.2014.302399.
    1. Hynynen ST, van Stralen MM, Sniehotta FF, Araujo-Soares V, Hardeman W, Chinapaw MJ, Vasankari T, Hankonen N. A systematic review of school-based interventions targeting physical activity and sedentary behaviour among older adolescents. Int Rev Sport Exerc Psychol. 2016;9:22–44. doi: 10.1080/1750984X.2015.1081706.
    1. Isensee B, Hanewinkel R. Meta-analysis on the effects of the smoke-free class competition on smoking prevention in adolescents. Eur Addict Res. 2012;18:110–115. doi: 10.1159/000335085.
    1. Jago R, Edwards MJ, Sebire SJ, Tomkinson K, Bird EL, Banfield K, May T, Kesten JM, Cooper AR, et al. Effect and cost of an after-school dance programme on the physical activity of 11-12 year old girls: the Bristol Girls Dance Project, a school-based cluster randomised controlled trial. Int J Behav Nutr Phys Act. 2015;12:128. doi: 10.1186/s12966-015-0289-y.
    1. Johnson D, Deterding S, Kuhn K-A, Staneva A, Stoyanov S, Hides L. Gamification for health and wellbeing: a systematic review of the literature. Internet Interv. 2016;6:89–106. doi: 10.1016/j.invent.2016.10.002.
    1. Lancaster GA. Pilot and feasibility studies come of age! Pilot Feasibility Stud. 2015;1:1. doi: 10.1186/2055-5784-1-1.
    1. Lister C, West JH, Cannon B, Sax T, Brodegard D. Just a fad? Gamification in health and fitness apps. JMIR Serious Games. 2014;2:e9. doi: 10.2196/games.3413.
    1. 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;20:859–870. doi: 10.1111/obr.12823.
    1. Lubans DR, Plotnikoff RC, Miller A, Scott JJ, Thompson D, Tudor-Locke C. Using pedometers for measuring and increasing physical activity in children and adolescents. Am J Lifestyle Med. 2014;9:418–427. doi: 10.1177/1559827614537774.
    1. Lührmann, M., Serra-Garcia, M., Winter, J., 2013. Measuring teenagers’ time preferences using convex time budgets. CESifo Area Conference on Behavioral Economics.
    1. Luoto J, Carman KG. Behavioral economics guidelines with applications for health interventions: Inter-American Development Bank; 2014.
    1. Macdonald-Wallis K, Jago R, Sterne JA. Social network analysis of childhood and youth physical activity: a systematic review. Am J Prev Med. 2012;43:636–642. doi: 10.1016/j.amepre.2012.08.021.
    1. Maturo CC, Cunningham SA. Influence of friends on children's physical activity: a review. Am J Public Health. 2013;103:e23–e38. doi: 10.2105/AJPH.2013.301366.
    1. McCartney M. Game on for Pokemon Go. BMJ. 2016;354:i4306. doi: 10.1136/bmj.i4306.
    1. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, Eccles MP, Cane J, Wood CE. 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;46:81–95. doi: 10.1007/s12160-013-9486-6.
    1. Moore GF, Audrey S, Barker M, Bond L, Bonell C, Hardeman W, Moore L, O'Cathain A, Tinati T, et al. Process evaluation of complex interventions: Medical Research Council guidance. BMJ. 2015;350:h1258. doi: 10.1136/bmj.h1258.
    1. Ommundsen Y, Page A, Ku PW, 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.
    1. Pearson M, Chilton R, Wyatt K, Abraham C, Ford T, Woods HB, Anderson R. Implementing health promotion programmes in schools: a realist systematic review of research and experience in the United Kingdom. Implement Sci. 2015;10:149. doi: 10.1186/s13012-015-0338-6.
    1. Peretti-Watel P, L'Haridon O, Seror V. Time preferences, socioeconomic status and smokers' behaviour, attitudes and risk awareness. Eur J Pub Health. 2013;23:783–788. doi: 10.1093/eurpub/cks189.
    1. Perry CL, Sellers DE, Johnson C, Pedersen S, Bachman KJ, Parcel GS, Stone EJ, Luepker RV, Wu M, et al. The Child and Adolescent Trial for Cardiovascular Health (CATCH): intervention, implementation, and feasibility for elementary schools in the United States. Health Educ Behav. 1997;24:716–735. doi: 10.1177/109019819702400607.
    1. Roberto CA, Kawachi I. Behavioral economics and public health. New York: Oxford University Press; 2015.
    1. Routen AC, Upton D, Edwards MG, Peters DM. The effect of pedometer step goal, feedback and self-monitoring interventions on accelerometer-measured physical activity in children. Grad J Sport Exerc Phys Educ Res. 2014;2:37–53.
    1. Ryan RM, Deci EL. Self-determination theory: basic psychological needs in motivation, development, and wellness. New York: Guilford Publications; 2017.
    1. Ryan RM, Rigby CS, Przybylski A. The motivational pull of video games: a self-determination theory approach. Motiv Emot. 2006;30:344–360. doi: 10.1007/s11031-006-9051-8.
    1. Sallis JF, Bull F, Guthold R, Heath GW, Inoue S, Kelly P, Oyeyemi AL, Perez LG, Richards J, et al. Progress in physical activity over the Olympic quadrennium. Lancet. 2016;388:1325–1336. doi: 10.1016/S0140-6736(16)30581-5.
    1. Sallis JF, Prochaska JJ, Taylor WC, Hill JO, Geraci JC. Correlates of physical activity in a national sample of girls and boys in grades 4 through 12. Health Psychol. 1999;18:410–415. doi: 10.1037/0278-6133.18.4.410.
    1. Sardi L, Idri A, Fernandez-Aleman JL. A systematic review of gamification in e-health. J Biomed Inform. 2017;71:31–48. doi: 10.1016/j.jbi.2017.05.011.
    1. Sawka KJ, McCormack GR, Nettel-Aguirre A, Swanson K. Associations between aspects of friendship networks and dietary behavior in youth: findings from a systematized review. Eat Behav. 2015;18:7–15. doi: 10.1016/j.eatbeh.2015.03.002.
    1. Seaborn K, Fels DI. Gamification in theory and action: a survey. Int J Hum Comput Stud. 2015;74:14–31. doi: 10.1016/j.ijhcs.2014.09.006.
    1. Sebire SJ, Jago R, Banfield K, Edwards MJ, Campbell R, Kipping R, Blair PS, Kadir B, Garfield K, et al. Results of a feasibility cluster randomised controlled trial of a peer-led school-based intervention to increase the physical activity of adolescent girls (PLAN-A) Int J Behav Nutr Phys Act. 2018;15:50. doi: 10.1186/s12966-018-0682-4.
    1. Skinner BF. Science and human behavior. New York: Simon and Schuster; 1953.
    1. Stewart-Brown S, Janmohamed K. User guide. Version 1. 2008. Warwick-Edinburgh mental well-being scale.
    1. Strohacker K, Galarraga O, Williams DM. The impact of incentives on exercise behavior: a systematic review of randomized controlled trials. Ann Behav Med. 2014;48:92–99. doi: 10.1007/s12160-013-9577-4.
    1. Sutter M, Kocher MG, Glätzle-Rützler D, Trautmann ST. Impatience and uncertainty: experimental decisions predict adolescents’ field behavior. Am Econ Rev. 2013;103:510–531. doi: 10.1257/aer.103.1.510.
    1. Telama R, Yang X, Leskinen E, Kankaanpaa A, Hirvensalo M, Tammelin T, Viikari JS, Raitakari OT. Tracking of physical activity from early childhood through youth into adulthood. Med Sci Sports Exerc. 2014;46:955–962. doi: 10.1249/MSS.0000000000000181.
    1. Tennant R, Hiller L, Fishwick R, Platt S, Joseph S, Weich S, Parkinson J, Secker J, Stewart-Brown S. The Warwick-Edinburgh Mental Well-being Scale (WEMWBS): development and UK validation. Health Qual Life Outcomes. 2007;5:63. doi: 10.1186/1477-7525-5-63.
    1. Thorgeirsson T, Kawachi I. Behavioral economics: merging psychology and economics for lifestyle interventions. Am J Prev Med. 2013;44:185–189. doi: 10.1016/j.amepre.2012.10.008.
    1. Tigges BB. Parental consent and adolescent risk behavior research. J Nurs Scholarsh. 2003;35:283–289. doi: 10.1111/j.1547-5069.2003.00283.x.
    1. Wise J. Pokémon Go's health benefits seem short lived. BMJ. 2016;355:i6684. doi: 10.1136/bmj.i6684.
    1. Wong FY. Erratum to: influence of Pokemon Go on physical activity levels of university players: a cross-sectional study. Int J Health Geogr. 2017;16:17. doi: 10.1186/s12942-017-0089-5.
    1. Zimmerman FJ. Using behavioral economics to promote physical activity. Prev Med. 2009;49:289–291. doi: 10.1016/j.ypmed.2009.07.008.

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