Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Network interventions for changing physical activity behaviour in preadolescents

Nature Human Behaviour volume 2, pages 778–787 (2018)Cite this article

Subjects

Abstract

Network interventions can help to achieve behavioural change by inducing peer-pressure in the network. However, inducing peer-pressure without considering the structure of the existing social network may render the intervention ineffective or weaker. In a seven-week school-based field experiment using preadolescents’ physical activity as a proxy for estimating behavioural change, we test the hypothesis that boys’ and girls’ distinct networks are susceptible to different social incentives. We run three different social-rewards schemes, in which classmates’ rewards depend on the physical activity of two friends either reciprocally (directly or indirectly) or collectively. Compared with a random-rewards control, social-rewards schemes have an overall significantly positive effect on physical activity (51.8% increase), with females being more receptive to the direct reciprocity scheme (76.4%) and males to team (collective) rewards (131.5%). Differences in the sex-specific sub-networks can explain these findings. Network interventions adapted to the network-specific characteristics may constitute a powerful tool for behavioural change.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Rewarding, interactions and allocation of points in the social-rewards schemes.
Fig. 2
Fig. 3: Average daily minutes of MVPA.
Fig. 4: Average daily minutes of MVPA by experimental condition and sex.

Data availability

The datasets generated and analysed during this study are available from the corresponding author upon request.

References

  1. Sinan, A. & Walker, D. Identifying influential and susceptible members of social networks. Science 337, 337–341 (2012).

    Article  CAS  Google Scholar 

  2. Centola, D. & Macy, M. Complex contagions and the weakness of long ties. Am. J. Sociol. 113, 702–734 (2007).

    Article  Google Scholar 

  3. Valente, T. W. Network interventions. Science 337, 49–53 (2012).

    Article  CAS  PubMed  Google Scholar 

  4. Eckles, D., Karrer, B. & Ugander, J. Design and analysis of experiments in networks: reducing bias from interference. J. Causal Inference 5, 20150021 (2017).

    Google Scholar 

  5. Benenson, J., Apostoleris, N. & Parnass, J. The organization of children’s same‐sex peer relationships. New Dir. Child Adolesc. Dev. 1998, 5–23 (1998).

    Article  Google Scholar 

  6. Mehta, M. C. & Strough, J. N. Sex segregation in friendships and normative contexts across the life span. Dev. Rev. 29, 201–220 (2009).

    Article  Google Scholar 

  7. Rose, A. J. & Rudolph, K. D. A review of sex differences in peer relationship processes: potential trade-offs for the emotional and behavioral development of girls and boys. Psychol. Bull. 132, 98 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  8. Carrell, S. E., Hoekstra, M. & West, J. E. Is poor fitness contagious? Evidence from randomly assigned friends. J. Public Econ. 95, 657–663 (2011).

    Article  Google Scholar 

  9. Cohen-Cole, E. & Fletcher, J. M. Is obesity contagious? Social networks vs. environmental factors in the obesity epidemic. J. Health Econ. 27, 1382–1387 (2008).

    Article  PubMed  Google Scholar 

  10. Christakis, N. A. & Fowler, J. H. The spread of obesity in a large social network over 32 years. New Engl. J. Med. 357, 370–379 (2007).

    Article  CAS  PubMed  Google Scholar 

  11. De La Haye, K., Robins, G., Mohr, P. & Wilson, C. How physical activity shapes, and is shaped by, adolescent friendships. Soc. Sci. Med. 73, 719–728 (2011).

    Article  PubMed  Google Scholar 

  12. Cialdini, R. B., Kallgren, C. A. & Reno, R. R. A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Adv. Exp. Soc. Psychol. 24, 201–234 (1991).

    Article  Google Scholar 

  13. Schultz, P. W., Nolan, J. M., Cialdini, R. B., Goldstein, N. J. & Griskevicius, V. The constructive, destructive, and reconstructive power of social norms. Psychol. Sci. 18, 429–434 (2007).

    Article  PubMed  Google Scholar 

  14. Morris, S. Contagion. Rev. Econ. Stud. 67, 57–78 (2000).

    Article  Google Scholar 

  15. Calvó‐Armengol, A. & M. O. Jackson, M. O. Peer pressure. J. Eur. Econ. Assoc. 8, 62–89 (2010).

    Article  Google Scholar 

  16. Deci, E. L. Effects of externally mediated rewards on intrinsic motivation. J. Pers. Soc. Psychol. 18, 105 (1971).

    Article  Google Scholar 

  17. Gneezy, U., Meier, S. & Rey-Biel, P. When and why incentives (don’t) work to modify behavior. J. Econ. Perspect. 25, 191–210 (2011).

    Article  Google Scholar 

  18. Valente, T. W. Social Networks and Health: Models, Methods, and Applications (Oxford Univ. Press, New York, 2010).

  19. Pickard, G. et al. Time-critical social mobilization. Science 334, 509–512 (2011).

    Article  CAS  PubMed  Google Scholar 

  20. Centola, D. An experimental study of homophily in the adoption of health behavior. Science 334, 1269–1272 (2011).

    Article  CAS  PubMed  Google Scholar 

  21. Leider, S., Möbius, M., Rosenblat, T. & Do, A. Q. Directed altruism and enforced reciprocity in social networks. Q. J. Econ. 124, 1815–1851 (2009).

    Article  Google Scholar 

  22. Rand, D., Dreber, A., Ellingsen, T., Fudenberg, D. & Nowak, M. A. Positive interactions promote public cooperation. Science 325, 1272–1275 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Nowak, M. A. Five rules for the evolution of cooperation. Science 314, 1560–1563 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Mani, A., Rahwan, I., & Pentland, A. Inducing peer pressure to promote cooperation. Sci. Rep. 3, 1735 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Aharony, N., Pan, W., Ip, C., Khayal, I. & Pentland, A. Social fMRI: investigating and shaping social mechanisms in the real world. Pervasive Mobile Comput. 7, 643–659 (2011).

    Article  Google Scholar 

  26. Bandiera, O., Barankay, I. & Rasul, I. Team incentives: evidence from a firm level experiment. J. Eur. Econ. Assoc. 11, 1079–1114 (2013).

    Article  Google Scholar 

  27. Nowak, M. A., Tarnita, C. E. & Antal, T. Evolutionary dynamics in structured populations. Philos. Trans. R. Soc. Lond. B 365, 19–30 (2010).

    Article  Google Scholar 

  28. Rand, D. G., Arbesman, S. & Christakis, N. A. Dynamic social networks promote cooperation in experiments with humans. Proc. Natl Acad. Sci. USA 108, 19193–19198 (2011).

    Article  CAS  PubMed  Google Scholar 

  29. Mountjoy, M. et al. International Olympic Committee consensus statement on the health and fitness of young people through physical activity and sport. Br. J. Sports Med. 45, 839–848 (2011).

    Article  PubMed  Google Scholar 

  30. Metcalf, B., William, H., & Wilkin, T. Effectiveness of intervention on physical activity of children: systematic review and meta-analysis of controlled trials with objectively measured outcomes (EarlyBird 54). BMJ 345, e5888 (2012).

    Article  PubMed  Google Scholar 

  31. Babcock, P., Bedard, K., Charness, G., Hartman, J. & Royer, H. Letting down the team? Social effects of team incentives. J. Eur. Econ. Assoc. 13, 841–870 (2015).

    Article  Google Scholar 

  32. Yoeli, E., Hoffman, M., Rand, D. G. & Nowak, M. A. Powering up with indirect reciprocity in a large-scale field experiment. Proc. Natl Acad. Sci. USA 110(Suppl. 2), 10424–10429 (2013).

    Article  CAS  PubMed  Google Scholar 

  33. Greiner, B. & Levati, M. V. Indirect reciprocity in cyclical networks: an experimental study. J. Econ. Psychol. 26, 711–731 (2005).

    Article  Google Scholar 

  34. Charness, G. & Gneezy, U. Incentives to exercise. Econometrica. 77, 909–931 (2009).

    Article  Google Scholar 

  35. Acland, D. & Levy, M. R. Naiveté, projection bias, and habit formation in gym attendance. Manage. Sci. 61, 146–160 (2015).

    Article  Google Scholar 

  36. Troiano, R. P. et al. Physical activity in the United States measured by accelerometer. Med. Sci. Sports Exerc. 40, 181–188 (2007).

    Article  Google Scholar 

  37. Krackhardt, D., & Stern, R. N. Informal networks and organizational crises: an experimental simulation. Soc. Psychol. Q 51, 123–140 (1988).

    Article  Google Scholar 

  38. Evenson, K. R., Catellier, D. J., Gill, K., Ondrak, K. S. & McMurray, R. G. Calibration of two objective measures of physical activity for children. J. Sport Sci. 26, 1557–1565 (2008).

    Article  Google Scholar 

  39. Ledyard, J. O. in Handbook of Experimental Economics (eds Kagel, J. & Roth, A.) 111–194 (Princeton Univ. Press, Princeton, 1995).

  40. Winkler, E. A. H. et al. Identifying sedentary time using automated estimates of accelerometer wear time. Br. J. Sports Med. 46, 436–442 (2012).

    Article  PubMed  Google Scholar 

  41. Choi, L., Liu, Z., Matthews, C. E., & Buchowski, M. S. Validation of accelerometer wear and nonwear time classification algorithm. Med. Sci. Sports Exerc. 43, 357–364 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Kruskal, W. H. & Wallis, W. A. Use of ranks in one-criterion variance analysis. J. Am. Stat. Assoc. 47, 583–621 (1952).

    Article  Google Scholar 

  43. Mann, H. B., & Whitney, D. R. On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947).

    Article  Google Scholar 

  44. French, J. in Research Methods in the Behavioral Sciences (eds Festinger, L. & Katz, D.) Ch. 3 (Holt, Rinehart & Winston, New York, 1953).

  45. Zizzo, D. J. Experimenter demand effects in economic experiments. Exp. Econ. 13, 75–98 (2010).

    Article  Google Scholar 

  46. Wedekind, C. & Milinski, M. Cooperation through image scoring in humans. Science 288, 850–852 (2000).

    Article  CAS  PubMed  Google Scholar 

  47. Baines, E. & Blatchford, P. Sex differences in the structure and stability of children’s playground social networks and their overlap with friendship relations. Br. J. Dev. Psychol. 27, 743–760 (2009).

    Article  PubMed  Google Scholar 

  48. Howes, C., Chamberlain, B. & Lee, L. Ethnic heterogeneity of social networks and cross-ethnic friendships of elementary school boys and girls. Merrill. Palmer. Q. 53, 325–346 (2007).

    Article  Google Scholar 

  49. Freedson, P. S., Pober, D., & Janz, K. F. Calibration of accelerometer output for children. Med. Sci. Sports Exerc. 37, S523–S530 (2005).

    Article  PubMed  Google Scholar 

  50. Trost, S. G., Loprinzi, P. D., Moore, R., & Pfeiffer, K. A. Comparison of accelerometer cut points for predicting activity intensity in youth. Med. Sci. Sports Exerc. 43, 1360–1368 (2011).

    Article  PubMed  Google Scholar 

  51. Dössegger, A. et al. Reactivity to accelerometer measurement of children and adolescents. Med. Sci. Sports. Exerc. 46, 1140 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  52. Frey, E. & Rogers, T. Persistence: how treatment effects persist after interventions stop. Policy Insights Behav. Brain Sci. 1, 172–179 (2014).

    Article  Google Scholar 

  53. van der Linden, S. The nature of viral altruism and how to make it stick. Nat. Hum. Behav. 1, 0041 (2017).

    Article  Google Scholar 

  54. Torgerson, W. S. Multidimensional scaling: I. Theory and method. Psychometrika 17, 401–409 (1952).

    Article  Google Scholar 

  55. Camerer, C., & Hogarth, R. M. The effects of financial incentives in experiments: a review and capital-labor-production framework. J. Risk Uncertain. 19, 7–42 (1999).

    Article  Google Scholar 

Download references

Acknowledgements

We thank S. Gächter, A. M. Espin, S. Kriemler, F. Exadaktylos, E. Yoeli, E. Woelbert, S. Stoffel and J. Fooken for discussions and feedback. We also thank C. Merletti representing the Ufficio Scolastico Territoriale per la Lombardia for his authorization and ethical approval for this study in schools under his responsibility. We thank P. Benetti from the same office for coordinating communication with all school directors, teachers, parental associations and students’ parents. We finally thank all the school directors and teachers involved, and all the parents and the children who agreed voluntarily to participate in this study (Scuola Primaria “G. Galilei”, Ispra; Scuola Primaria “S. Pellico”, Ranco; Scuola Primaria “G. Pascoli”, Taino; Scuola Primaria “D. Alighieri”, Angera; Scuole Primarie “G. Ungaretti” and “G. Matteotti”, Sesto Calende; Scuola Primaria “D. Alighieri” Golasecca; Scuola Primaria “A. Manzoni” Mercallo; Scuola Primaria “L. Scotti” Laveno; Scuola Primaria” G. de Amicis” Vergiate; Scuola Primaria “G. Wojtyla” Cimbro; Scuola Primaria “S. Tamborini” Varano Borghi; Scuola Primaria “A. Liborio” Comabbio, Scuola Primaria “A. Manzoni” Malgesso). This research was exclusively funded by the European Commission. The supply of the technical equipment (accelerometers) and the contributions of H.B. and E.v.S. were supported by the Medical Research Council (MC_UU_12015/7), and the Centre for Diet and Activity Research (CEDAR), a UKCRC Public Health Research Centre of Excellence (RES-590-28-0002). Funding from the British Heart Foundation, Department of Health, Economic and Social Research Council, Medical Research Council and the Wellcome Trust, under the auspices of the UK Clinical Research Collaboration is acknowledged. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Any opinions expressed in this article are those of the authors and not of the European Commission or any other involved institute affiliated by the authors. Data on physical activity and bilateral friendships are provided by the authors upon request.

Author information

Authors and Affiliations

  1. Joint Research Centre, European Commission, Ispra, Italy

    Antonios Proestakis, Eugenia Polizzi di Sorrentino, Sandra Caldeira & Benedikt Herrmann

  2. Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy

    Eugenia Polizzi di Sorrentino

  3. UKCRC Centre for Diet and Activity Research (CEDAR) and MRC Epidemiology Unit, University of Cambridge, Cambridge, UK

    Helen Elizabeth Brown & Esther van Sluijs

  4. Industrial and Systems Engineering, University of Minnesota, Minneapolis, MN, USA

    Ankur Mani

Authors
  1. Antonios Proestakis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eugenia Polizzi di Sorrentino
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Helen Elizabeth Brown
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Esther van Sluijs
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ankur Mani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sandra Caldeira
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Benedikt Herrmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

A.P., B.H., A.M. and S.C. developed the concept. A.P., E.P.d.S. and B.H. designed the experiments. A.P., B.H., E.P.d.S. and S.C. obtained the ethical approval and the authorization from the data protection officer. E.P.d.S., S.C. and A.P. recruited the students and took permissions from the schools’ directors/teachers. E.P.d.S. and A.P. performed the experiments. H.E.B and E.v.S. led on physical activity measurement and processing. A.P., E.P.d.S. and A.M. analysed the data. B.H. supervised the study. A.P., S.C., E.v.S., H.E.B, E.P.d.S, B.H. and A.M. wrote the paper.

Corresponding author

Correspondence to Antonios Proestakis.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figures 1–18, Supplementary Tables 1–7, Supplementary Note, Supplementary Methods

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Proestakis, A., di Sorrentino, E.P., Brown, H.E. et al. Network interventions for changing physical activity behaviour in preadolescents. Nat Hum Behav 2, 778–787 (2018). https://doi.org/10.1038/s41562-018-0436-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-018-0436-y

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing