Human Factors Multi-technique Approach to Teenage Engagement in Digital Technologies Health Research

  • Alexandra R. Lang
  • Michael P. Craven
  • Sarah Atkinson
  • Lucy Simons
  • Sue Cobb
  • Marco Mazzola
Chapter
Part of the Human–Computer Interaction Series book series (HCIS)

Abstract

This chapter explores the use of multi-techniques for teenage HCI health research. Through four case studies we present information about adolescents as users of healthcare services and technologies, adolescent personal development and the human factors approaches through which teenagers have been involved in healthcare research projects. In each case study comprising of the design or evaluation of a new digital technology for supporting health or well-being, the techniques used by researchers to involve teenagers are explored and analysed. The case studies examine various aspects of technology design and use including but not limited to usability, acceptability and learnability. The penultimate section of the chapter presents a ‘Schema for Multi-technique HCI Health Research with Teenagers’ and provides the supporting case for a multi-method approach. The conclusions of the chapter reinforce the benefits that are specific to the implementation of multi-technique research with teenage participants. Consideration of the eight factors outlined in the ‘Schema’ within study designs should serve to unlock the potential of teenagers, ensuring reliable elicitation of their views and needs.

References

  1. Arnab S, Dunwell I, Debattista K (2013). Serious games for healthcare: applications and implications. Serious Games for Healthcare: Applications and Implications, 1–295. doi:10.4018/978-1-4666-1903-6
  2. Bircher J (2005) Towards a dynamic definition of health and disease. Med Health Care Philos 8(3):335–341. doi:10.1007/s11019-005-0538-y CrossRefGoogle Scholar
  3. Blakemore SJ (2010) The developing social brain: implications for education. Neuron 65(6):744–747. doi:10.1016/j.neuron.2010.03.004 CrossRefGoogle Scholar
  4. Boardwell J, Roberson J (2014) Learning from the Labs How to fund and deliver social tech for charities and social enterprises. Retrieved from http://www.innovationlabs.org.uk/wp-content/uploads/2014/11/Learning-from-the-Labs-Social-Tech-Ebook.pdf
  5. Bos L, Marsh A, Carroll D, Gupta SMR (2008) Patient 2.0 empowerment. In: Paper presented at the proceedings of the 2008 International Conference on Semantic Web & Web Services (SWWS08). http://members.media-effect.be/P4F/_images/20100408patientempowermenthealth20.pdf
  6. Burnett S, Bault N, Coricelli G, Blakemore SJ (2010) Adolescents’ heightened risk-seeking in a probabilistic gambling task. Cogn Dev 25(2):183–196. doi:10.1016/j.cogdev.2009.11.003 CrossRefGoogle Scholar
  7. Clark A, Moss P (2005) Listening to young children. The mosaic approach. National Children’s Bureau, LondonGoogle Scholar
  8. Clough BA, Casey LM (2011) Technological adjuncts to enhance current psychotherapy practices: A review. Clin Psychol Rev 31(3):279–292. doi:10.1016/j.cpr.2010.12.008 CrossRefGoogle Scholar
  9. Cotton R, Irwin J, Wilkins A, Young C (2014). The future’s digital Mental health and technology, p 50. Retrieved from http://www.nhsconfed.org/resources/2014/09/the-future-s-digital-mental-health-and-technology
  10. Creswell JW (1999) Mixed-method research: introduction and application. In: Cizek GJ (ed) Handbook of educational policy. Academic, San Diego, pp 455–472CrossRefGoogle Scholar
  11. Elkind D (1967) Egocentrism in adolescence. Child Dev 38(4):1025–1034. doi:10.1111/j.1467-8624.1967.tb04378.x CrossRefGoogle Scholar
  12. Elliott GR, Feldman SS (2010) At the threshold: the developing adolescent. Harvard University Press, Cambridge MAGoogle Scholar
  13. EXPO (2015) Giovani Ambasciartori del Cibo. EXPO Milan 2015. European Union Pavillion, Milan. 1st September 2015. Milan, ItalyGoogle Scholar
  14. Fitton D, Read JC, Horton M (2013) The challenge of working with teens as participants in interaction design. In: Paper presented at the In CHI’13 extended abstracts on human factors in computing systemsGoogle Scholar
  15. Fogg BJ (2009). A behavior model for persuasive design. In: Paper presented at the proceedings of the 4th international conference on persuasive technology, Claremont, California, USAGoogle Scholar
  16. Fryar CD, Carroll MD, Odgen CL (2014) Prevalence of overweight and obesity among children and adolescents: United States, 1963–1965 through 2011–2012. http://www.cdc.gov/nchs/data/hestat/obesity_child_11_12/obesity_child_11_12.pdf
  17. Hagell A, Coleman J, Brookes F (2013) Key data on adolescence 2013. The Association for Young People’s Health (AYPH), LondonGoogle Scholar
  18. Hart R (1992) Children’s participation. From tokenism to citizenship. UNICEF International Child Development Centre, FlorenceGoogle Scholar
  19. Ho TC, Yang G, Wu J, Cassey P, Brown SD, Hoang N, … Duncan LG (2014) Functional connectivity of negative emotional processing in adolescent depression. J Affect Disord 155:65–74Google Scholar
  20. Hollis C, Martin J, Amani S, Cotton R, Denis M, Lewis S (2014) Technological innovations in mental healthcare. Annual report of the Chief Medical Officer 2013. Public Mental Health Priorities: Investing in the Evidence. Department of Health, LondonGoogle Scholar
  21. Kazdin AE, Blase SL (2011) Rebooting psychotherapy research and practice to reduce the burden of mental illness. Perspect Psychol Sci 6(1):21–37. doi:10.1177/1745691610393527 CrossRefGoogle Scholar
  22. Kroemer KHE (2005). Design for children and adolescents. ‘Extra-Ordinary’ ergonomics: how to accommodate small and big persons, the disabled and elderly, expectant mothers, and children. CRC Press, pp 175–198Google Scholar
  23. Lang AR (2012). Medical device design for adolescents. PhD, University of Nottingham, UKGoogle Scholar
  24. Lang AR, Martin JL, Sharples S, Crowe JA (2009). Enabling adolescents to participate in the design and improvement of medical devices. In: Paper presented at the International Ergonomics Association, 17th World Congress on Ergonomics., Beijing, ChinaGoogle Scholar
  25. Lang AR, Martin JL, Sharples S, Crowe JA (2013) The effect of design on the usability and real world effectiveness of medical devices: a case study with adolescent users. Appl Ergon 44(5):799–810CrossRefGoogle Scholar
  26. Lang AR, Martin JL, Sharples S, Crowe JA (2014) Medical device design for adolescent adherence and developmental goals: a case study of a cystic fibrosis physiotherapy device. Patient Preference Adherence 8:301–309. doi:10.2147/Ppa.S59423 CrossRefGoogle Scholar
  27. Luxton DD, McCann RA, Bush NE, Mishkind MC, Reger GM (2011) mHealth for mental health: integrating smartphone technology in behavioral healthcare. Prof Psychol Res Pract 42(6):505–512. doi:10.1037/a0024485 CrossRefGoogle Scholar
  28. Macvean A, Robertson J (2012). iFitQuest: a school based study of a mobile location-aware exergame for adolescents. In: Paper presented at the proceedings of the 14th international conference on Human-computer interaction with mobile devices and services, San Francisco, California, USAGoogle Scholar
  29. Matthews M, Doherty G, Sharry J, Fitzpatrick C (2008) Mobile phone mood charting for adolescents. Br J Guid Couns 36(2):113–129. doi:10.1080/03069880801926400 CrossRefGoogle Scholar
  30. McDonagh JE (2000) The adolescent challenge. Nephrol Dial Transplant 15(11):1761–1765. doi:10.1093/ndt/15.11.1761 CrossRefGoogle Scholar
  31. Michaud PA, Suris JC, Viner R (2004) The adolescent with a chronic condition. Part II: healthcare provision. Arch Dis Child 89(10):943–949. doi:10.1136/adc.2003.045377 CrossRefGoogle Scholar
  32. Nasi G, Cucciniello M, Guerrazzi C (2015) The role of mobile technologies in health care processes: the case of cancer supportive care. J Med Internet Res 17(2), e26. doi:10.2196/jmir.3757 CrossRefGoogle Scholar
  33. NICE (2008) Attention deficit hyperactivity disorder: diagnosis and management. NICE Guidelines. Retrieved October, 29, 2015, from https://www.nice.org.uk/guidance/cg72
  34. NIMH (1999) Multimodal Treatment of Attention Deficit Hyperactivity Disorder (MTA) Study. Retrieved October 29, 2015, from http://www.nimh.nih.gov/funding/clinical-research/practical/mta/multimodal-treatment-of-attention-deficit-hyperactivity-disorder-mta-study.shtml
  35. OFCOM (2015) The communications market report 2015. August 6th 2015. Office of Communications, London.Google Scholar
  36. PEGASO (2015) Pegaso fit for future. Retrieved December 4, 2015, from http://pegasof4f.eu/home
  37. PEW (2013) Teens and technology 2013. Retrieved June 5, 2015, from http://www.pewinternet.org/files/old-media//Files/Reports/2013/PIP_TeensandTechnology2013.pdf
  38. Punch S (2002) Research with children – the same or different from research with adults? Childhood 9(3):321–341CrossRefGoogle Scholar
  39. Simons L, Craven M, Martin J (2015). Learning from the labs volume 2: evaluating effectiveness, lessons and reflections. Retrieved from http://www.innovationlabs.org.uk/wp-content/uploads/2015/04/Learning-from-the-Labs-Volume-2-Exec-Summary-of-Evaluating-Effectiveness.pdf
  40. Simons L, Valentine AZ, Falconer C, Groom M, Daley D, Craven MP, Young Z, Hall C, Hollis C (2016) Developing mhealth remote monitoring technology for attention deficit hyperactivity disorder: a qualitative study eliciting user priorities and needs. JMIR mHealth uHealth 4(1):e31.Google Scholar
  41. Steinberg L (2008) A social neuroscience perspective on adolescent risk-taking. Dev Rev 28(1):78–106. doi:10.1016/j.dr.2007.08.002 CrossRefGoogle Scholar
  42. Stewart-Brown S, Tennant A, Tennant R, Platt S, Parkinson J, Weich S (2009) Internal construct validity of the Warwick-Edinburgh Mental Well-being Scale (WEMWBS): a Rasch analysis using data from the Scottish Health Education Population Survey. Health Qual Life Outcom 7. doi:Artn 1510.1186/1477-7525-7-15Google Scholar
  43. Thomas N, O’Kane C (1998) The ethics of participatory research with children. Child Soc 12(5):336–348CrossRefGoogle Scholar
  44. Ulicsak M (2010). You can learn your parents are immature: an analysis of what learning can result from family video gaming.In: Proceedings of the 4th European conference on games based learning, pp 403–411Google Scholar
  45. USCB (2012) Age and sex composition in the United States: 2012. Retrieved October 29, 2015, 2015, from https://www.census.gov/population/age/data/2012comp.html
  46. Viner R, Macfarlane A (2005) Health promotion. BMJ 330(7490):527–529. doi:10.1136/bmj.330.7490.527 CrossRefGoogle Scholar
  47. YM (2015) Mental health statistics. Retrieved October 29, 2015, from http://www.youngminds.org.uk/training_services/policy/mental_health_statistics

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Alexandra R. Lang
    • 1
  • Michael P. Craven
    • 2
  • Sarah Atkinson
    • 1
  • Lucy Simons
    • 2
  • Sue Cobb
    • 1
  • Marco Mazzola
    • 3
    • 4
  1. 1.Human Factors Research GroupUniversity of NottinghamNottinghamUK
  2. 2.NIHR MindTech Healthcare Technology Co-operative, Institute of Mental HealthUniversity of NottinghamNottinghamUK
  3. 3.Politecnico di Milano, Design DepartmentMilanItaly
  4. 4.Neosperience SpaMilanItaly

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