Skip to main content

“Not Just Little Adults”: Qualitative Methods to Support the Development of Pediatric Patient-Reported Outcomes

Abstract

The US FDA and the European Medicines Agency (EMA) have issued incentives and laws mandating clinical research in pediatrics. While guidances for the development and validation of patient-reported outcomes (PROs) or health-related quality of life (HRQL) measures have been issued by these agencies, little attention has focused on pediatric PRO development methods. With reference to the literature, this article provides an overview of specific considerations that should be made with regard to the development of pediatric PRO measures, with a focus on performing qualitative research to ensure content validity. Throughout the questionnaire development process it is critical to use developmentally appropriate language and techniques to ensure outcomes have content validity, and will be reliable and valid within narrow age bands (0–2, 3–5, 6–8, 9–11, 12–14, 15–17 years). For qualitative research, sample sizes within those age bands must be adequate to demonstrate saturation while taking into account children’s rapid growth and development. Interview methods, interview guides, and length of interview must all take developmental stage into account. Drawings, play-doh, or props can be used to engage the child. Care needs to be taken during cognitive debriefing, where repeated questioning can lead a child to change their answers, due to thinking their answer is incorrect. For the PROs themselves, the greatest challenge is in measuring outcomes in children aged 5–8 years. In this age range, while self-report is generally more valid, parent reports of observable behaviors are generally more reliable. As such, ‘team completion’ or a parent-administered child report is often the best option for children aged 5–8 years. For infants and very young children (aged 0–4 years), patient rating of observable behaviors is necessary, and, for adolescents and children aged 9 years and older, self-reported outcomes are generally valid and reliable. In conclusion, the development of PRO measures for use in children requires careful tailoring of qualitative methods, and performing research within narrow age bands. The best reporter should be carefully considered dependent on the child’s age, developmental ability, and the concept being measured, and team completion should be considered alongside self-completion and observer measures.

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

Fig. 1
Fig. 2
Fig. 3

References

  1. 1.

    Bevans KB, Riley AW, Moon J, Forrest CB. Conceptual and methodological advances in child-reported outcomes measurement. Expert Rev Pharmacoecon Outcomes Res. 2010;10(4):385–96.

    PubMed  Article  Google Scholar 

  2. 2.

    Forrest CB, Simpson L, Clancy C. Child health services research: challenges and opportunities. JAMA. 1997;277(22):1787–93.

    PubMed  Article  CAS  Google Scholar 

  3. 3.

    Maldonado S. United States perspective. In: Mulberg A, Silber S, van den Anker J, editors. Pediatric drug development: concepts and applications. New Jersey: Wiley; 2009. p. 133–6.

    Google Scholar 

  4. 4.

    The Best Pharmaceuticals for Children Act of 2002. Public Law 107-109, 115 Stat.1408-1424. 2002. http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DevelopmentResources/UCM049874.pdf.

  5. 5.

    The Pedatric Research Equity Act of 2003. Public Law 108-155, 117 Stat.1936-1943. 2003. http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DevelopmentResources/UCM077853.pdf.

  6. 6.

    The Pediatric Research Equity Act of 2007. Public Law 110-85, 121 STAT.823 (Food and Drug Administration Amendments Act (FDAAA) of 2007—Title IV). 2007. http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DevelopmentResources/UCM049870.pdf.

  7. 7.

    The Best Pharmaceuticals for Children Act of 2007. Public Law 110-85, 121 STAT.823 (Food and Drug Administration Amendments Act (FDAA) of 2007—Title V). 22007. http://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/DevelopmentResources/UCM049870.pdf.

  8. 8.

    Regulation (EC) no 1901/2006 of the european parliament and of the council of 12 December 2006 on medicinal products for paediatric use and amending Regulation (EEC) No 1768/92, Directive2001/20/EC, Directive 2001/83/EC and Regulation (EC) No 726/2004. Official Journal of the European Union. 2006. http://ec.europa.eu/health/files/eudralex/vol-1/reg_2006_1901/reg_2006_1901_en.pdf.

  9. 9.

    Regulation (EC) no 1902/2006 of the european parliament and of the council of 20 December 2006 amending Regulation 1901/2006 on medicinal products for paediatric use. Official Journal of European Union. 2006. http://ec.europa.eu/health/files/eudralex/vol-1/reg_2006_1902/reg_2006_1902_en.pdf.

  10. 10.

    Landgraf J, Abetz L. Measuring health outcomes in pediatric populations: issue in psychometrics and application. In: Spilker B, editor. Quality of life and pharmacoeconomics in clinical trials. Philadelphia: Lippincott-Raven Publishers; 1996. p. 793–802.

    Google Scholar 

  11. 11.

    Pasquali SK, Burstein DS, Benjamin DK, Smith PB, Li JS. Globalization of pediatric research: analysis of clinical trials completed for pediatric exclusivity. Pediatrics. 2010;126(3):e687–92.

    PubMed  Article  Google Scholar 

  12. 12.

    Pharmaceutical Research and Manufacturers of America’s (PhRMA). PhRMA Statement on Tremendous Success of BPCA and PREA. 2011. http://www.phrma.org/media/releases/phrma-statement-tremendous-success-bpca-prea.

  13. 13.

    European Medicines Agency. Reflection Paper on the Regulatory Guidance for the Use of Health-Related Quality of Life (HRQL) Measures in the Evaluation of Medicinal Products. 2005. http://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003637.pdf.

  14. 14.

    US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER), Center for Biologics Evaluation and Research (CBER), Center for Devices and Radiological Health (CDRH). Guidance for Industry—Patient-Reported Outcome Measures: Use in Medical Product Development to support Labeling Claims. 2009. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM193282.pdf.

  15. 15.

    Leidy NK, Vernon M. Perspectives on patient-reported outcomes: content validity and qualitative research in a changing clinical trial environment. Pharmacoeconomics. 2008;26(5):363–70.

    PubMed  Article  Google Scholar 

  16. 16.

    Patrick DL, Burke LB, Powers JH, Scott JA, Rock EP, Dawisha S, et al. Patient-reported outcomes to support medical product labeling claims: FDA perspective. Value Health. 2007;10(Suppl 2):S125–37.

    PubMed  Article  Google Scholar 

  17. 17.

    Lasch KE, Marquis P, Vigneux M, Abetz L, Arnould B, Bayliss M, et al. PRO development: rigorous qualitative research as the crucial foundation. Qual Life Res. 2010;19(8):1087–96.

    PubMed  Article  Google Scholar 

  18. 18.

    Matza L, Swensen A, Flood E, Secnik K, Kline Leidy N. Assessment of health-related quality of life in children: a review of conceptual, methodological, and regulatory issues. Value Health. 2004;7(Number 1):79–90.

    PubMed  Article  Google Scholar 

  19. 19.

    Rothman M, Kleinman L. Patient-reported outcomes in pediatric drug development. In: Mulberg A, Silber S, van den Anker J, editors. Pediatric drug development: concepts and applications. New Jersey: Wiley; 2009. p. 513–24.

    Google Scholar 

  20. 20.

    Arbuckle R, Abetz L, Durmer J, Ivenenko A, Owens J, Croenlin J, et al. Development of the Pediatric Restless Legs Syndrome Severity Scale (R-RLS-SS): a patient reported outcome measure of pediatric RLS symptoms and impact. Sleep Med. 2010;11(9):897–906.

    PubMed  Article  Google Scholar 

  21. 21.

    Solans M, Pane S, Estrada MD, Serra-Sutton V, Berra S, Herdman M, et al. Health-related quality of life measurement in children and adolescents: a systematic review of generic and disease-specific instruments. Value Health. 2008;11(4):742–64.

    PubMed  Article  Google Scholar 

  22. 22.

    Woolley ME, Bowen GL, Bowen NK. Cognitive pretesting and the developmental validity of child self-report instruments: theory and applications. Res Soc Work Pract. 2004;14(3):191–200.

    PubMed  Article  Google Scholar 

  23. 23.

    Fuchs M. The reliability of children’s survey responses: the impact of cognitive functioning on respondent behavior. In: Proceedings of Statistics Canada Symposium 2008: Data Collection: Challenges, Achievements and New Directions; 2009.

  24. 24.

    de Leeuw ED. Improving data quality when surveying children and adolescents: cognitive and social development and its role in questionnaire construction and pretesting. Report prepared for the Annual Meeting of the Academy of Finland: Research Programs Public Health Challenges and Health and Welfare of Children and Young People, May 10-12. Naantali, Finland; 2011.

  25. 25.

    Ravens-Sieberer U, Erhart M, Wille N, Wetzel R, Nickel J, Bullinger M. Generic health-related quality-of-life assessment in children and adolescents: methodological considerations. Pharmacoeconomics. 2006;24(12):1199–220.

    PubMed  Article  Google Scholar 

  26. 26.

    Inhelder B, Piaget J. The growth of logical thinking from childhood to adolescence. London: Routledge; 1958.

    Book  Google Scholar 

  27. 27.

    Inhelder B, Piaget J. The early growth of logic in the child. London: Routledge; 1964.

    Google Scholar 

  28. 28.

    Vygotsky LS. Mind in society: the development of higher psychological processes. Cambridge: Harvard University Press; 1978.

    Google Scholar 

  29. 29.

    Bronfenbrenner U. The ecology of human development: experiments by nature and design. Cambridge: Harvard University Press; 1981.

    Google Scholar 

  30. 30.

    Kail RE. Children and their development. 5th ed. Englewood Cliffs: Prentice Hall; 2006.

    Google Scholar 

  31. 31.

    Borgers N, de Leeuw E, Hox J. Children as respondents in survey research: cognitive development and response quality. Bulletin de Methodologie Sociologique. 2000;66:60–75.

    Article  Google Scholar 

  32. 32.

    Siegler RS, Richards DD. The development of intelligence. In: Sternberg RJ, editor. Handbook of human intelligence. Cambridge: Cambridge University Press; 1982. p. 897–971.

    Google Scholar 

  33. 33.

    Scarr S. Understanding development. New York: Harcourt Publications; 1986.

    Google Scholar 

  34. 34.

    Sodian B, Kristen S. Theory of mind. Towards a theory of thinking. Berlin: Springer; 2010. p. 189–201.

    Book  Google Scholar 

  35. 35.

    Perner J. Understanding the representational mind. Cambridge: MIT Press; 1991.

    Google Scholar 

  36. 36.

    White SH. Evidence for a hierarchical arrangement of learning processes. In: Lewis PL, editor. Advances in child development and behavior, vol 2. JAI; 1965. p. 187–220.

  37. 37.

    White SH. The child’s entry into the “age of reason”. In: Sameroff AJ, Haith MM, editors. The five to seven year shift: the age of reason and responsibility. Chicago: University of Chicago Press; 1996. p. 17–30.

    Google Scholar 

  38. 38.

    Manificat S, Dazord A. Children’s Quality of Life Assessment: preliminary results obtained with the AUQUEI Questionnaire. Qual Life Newsletter 1998;2–3.

  39. 39.

    Ross DM, Ross SA. Childhood pain: the school-aged child’s viewpoint. Pain. 1984;20(2):179–91.

    PubMed  Article  CAS  Google Scholar 

  40. 40.

    Punch S. Research with children: the same or different from research with adults? Childhood. 2002;9(3):321–41.

    Google Scholar 

  41. 41.

    Walsh TR, Irwin DE, Meier A, Varni JW, DeWalt DA. The use of focus groups in the development of the PROMIS pediatrics item bank. Qual Life Res. 2008;17(5):725–35.

    PubMed  Article  Google Scholar 

  42. 42.

    Ravens-Sieberer U, Gosch A, Rajmil L, Erhart M, Bruil J, Duer W, et al. The KIDSCREEN-52 Quality of Life measure for children and adolescents: development and first results from a European survey. Expert Rev Pharmacoecon Outcomes Res. 2005;5(3):353–64.

    PubMed  Article  Google Scholar 

  43. 43.

    Heary CM, Hennessy E. The use of focus group interviews in pediatric health care research. J Pediatr Psychol. 2002;27(1):47–57.

    PubMed  Article  Google Scholar 

  44. 44.

    Lewis A. Group child interviews as a research tool. Br Edu Res J. 1992;18(4):413–21.

    Article  Google Scholar 

  45. 45.

    Levine IS, Zimmerman JD. Using qualitative data to inform public policy: evaluating “choose to de-fuse”. Am J Orthopsychiatry. 1996;66(3):363–77.

    PubMed  Article  CAS  Google Scholar 

  46. 46.

    McColl E. Developing Questionnaires. Assessing Quality of Life in Clinical Trials. New York: Oxford University Press; 2013. p. 9–23.

    Google Scholar 

  47. 47.

    Tajfel H, Turner JC. An integrative theory of intergroup conflict. In: Worchel S, Austin W, editors. The Social Psychology of Intergroup Relations. Belmont: Brooks/Cole; 1979. p. 33–48.

    Google Scholar 

  48. 48.

    Tajfel H, Turner JC. The social identity theory of intergroup behavior Psychology of Intergroup Relations. Chicago: Nelson-Hall; 1986. p. 7–24.

    Google Scholar 

  49. 49.

    van Hattum MJC, de Leeuw ED. A disk by mail survey of pupils in primary schools; data quality and logistics. J Off Stat. 1999;15:413–30.

    Google Scholar 

  50. 50.

    Hoppe MJ, Wells EA, Wilsdon A, Gillmore MR, Morrison DM. Children’s knowledge and beliefs about AIDS: qualitative data from focus group interviews. Health Educ Q. 1994;21(1):117–26.

    PubMed  Article  CAS  Google Scholar 

  51. 51.

    Donaldson MC. Children;s minds. London: Fontana Press; 1978.

    Google Scholar 

  52. 52.

    Vaughn SS, Sinagub J. Focus group interviews in education and psychology. London: Sage; 1996.

    Google Scholar 

  53. 53.

    Eiser C, Morse R. Can parents rate their child’s health-related quality of life? Results of a systematic review. Qual Life Res. 2001;10(4):347–57.

    PubMed  Article  CAS  Google Scholar 

  54. 54.

    Petrou S. Methodological issues raised by preference-based approaches to measuring the health status of children. Health Econ. 2003;12(8):697–702.

    PubMed  Article  Google Scholar 

  55. 55.

    Pal DK. Quality of life assessment in children: a review of conceptual and methodological issues in multidimensional health status measures. J Epidemiol Community Health. 1996;50(4):391–6.

    PubMed  Article  CAS  Google Scholar 

  56. 56.

    US FDA, CDER, CBER, CDRH. Guidance for industry: patient-reported outcome measures: use in medical product development to support labelling claims. FDA 2009. http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM193282.pdf.

  57. 57.

    Glaser B, Strauss A. The discovery of grounded theory: strategies for qualitative research. Chicago: Aldine; 1967.

    Google Scholar 

  58. 58.

    Bowen G. Grounded theory and sensitizing concepts. Int J Qual Methods. 2006;5(No 3):1–9.

    Google Scholar 

  59. 59.

    Picchietti DL, Arbuckle RA, Abetz L, Durmer JS, Ivanenko A, Owens JA, et al. Pediatric restless legs syndrome: analysis of symptom descriptions and drawings. J Child Neurol. 2011;26(11):1365–76.

    PubMed  Article  Google Scholar 

  60. 60.

    Abetz LN, Arbuckle RA, Carson RT, Lewis BE, Hunter LJ, Shiff SJ, et al. Development of a pediatric chronic constipation symptom measure: results of qualitative interviews with children and their parents. 2010. In: 17th Annual Conference of the International Society for Quality of Life Research October 27–30 2010.

  61. 61.

    Carson R, Arbuckle R, Abetz L, Lewis B, Hunter L, Johnston J, et al. The symptoms of irritable bowel syndrome with constipation (IBS-C): results of qualitative interviews with children and their parents. 27-10-2010. In: ISOQOL 17th Annual Conference, London, UK, 27–30 October 2010.

  62. 62.

    van Laerhoven H, van der Zaag-Loonen H, Derkx BHF. A comparison of Likert scale and visual analogue scales as response options in children’s questionnaires. Acta Paediatr. 2004;93(6):830–5.

    PubMed  Article  Google Scholar 

  63. 63.

    Shields BJ, Palermo TM, Powers JD, Grewe SD, Smith GA. Predictors of a child’s ability to use a visual analogue scale. Child Care Health Dev. 2003;29(4):281–90.

    PubMed  Article  CAS  Google Scholar 

  64. 64.

    Rebok G, Riley A, Forrest C, Starfield B, Green B, Robertson J, et al. Elementary school-aged children’s reports of their health: a cognitive interviewing study. Qual Life Res. 2001;10(1):59–70.

    PubMed  Article  CAS  Google Scholar 

  65. 65.

    Juniper EF. Quality of life in adults and children with asthma and rhinitis. Allergy. 1997;52(10):971–7.

    PubMed  Article  CAS  Google Scholar 

  66. 66.

    Wong D, Wilson D, Whaley L. Whaley and wong’s nursing care of infants and children. St Louis: Mosby; 1995.

    Google Scholar 

  67. 67.

    Wong DL, Baker CM. Pain in children: comparison of assessment scales. Pediatr Nurs. 1988;14(1):9–17.

    PubMed  CAS  Google Scholar 

  68. 68.

    Hockenberry MJ, Wilson D, Winkelstein ML. Wong’s essential of pediatric nursing. 7th ed. St. Louis: Mosby; 2005.

    Google Scholar 

  69. 69.

    Cremeens J, Eiser C, Blades M. Brief report: assessing the impact of rating scale type, types of items, and age on the measurement of school-age children’s self-reported quality of life. J Pediatr Psychol. 2007;32(2):132–8.

    PubMed  Article  Google Scholar 

  70. 70.

    Willis GB. Cognitive interviewing and questionnaire design: a training manual. Cognitive methods staff working paper series, no. 7. Office of Research and Methodology, National Center for Health Statistics. 1994. Hyattsville (MD).

  71. 71.

    Farrar MJ, Goodman GS. Developmental changes in event memory. Child Dev. 1992;63(1):173–87.

    PubMed  Article  CAS  Google Scholar 

  72. 72.

    Brainerd C, Ornstein PA. Children’s memory for witnessed events: the developmental backdrop. In: Doris J, editor. The suggestibility of children’s recollections: implications for eyewitness testimony. Washington, DC: American Psychological Association; 1991. p. 10–20.

    Chapter  Google Scholar 

  73. 73.

    Feikin DR, Audi A, Olack B, Bigogo GM, Polyak C, Burke H, et al. Evaluation of the optimal recall period for disease symptoms in home-based morbidity surveillance in rural and urban Kenya. Int J Epidemiol. 2010;39(2):450–8.

    PubMed  Article  Google Scholar 

  74. 74.

    Gill LJ, Shand PAX, Fuggle P, Dugan B, Davies SC. Pain assessment for children with sickle cell disease: Improved validity of diary keeping versus interview ratings. Br J Health Psychol. 1997;2(2):131–40.

    Article  Google Scholar 

  75. 75.

    van der Plas RN, Benninga MA, Redekop WK, Taminiau JA, Buller HA. How accurate is the recall of bowel habits in children with defaecation disorders? Eur J Pediatr. 1997;156(3):178–81.

    PubMed  Article  Google Scholar 

  76. 76.

    Scarr S, Weinberg R, Levine A. The intellectual revolution of middle childhood. Underst Dev. 1986. p. 343-81.

  77. 77.

    Siegal M. Knowing children: experiments in conversation and cognition. Hove: Lawrence Erlbaum Associates; 1991.

    Google Scholar 

  78. 78.

    Piaget J. The child’s conception of physical causality. Boston: Adams & Co; 1960.

    Google Scholar 

  79. 79.

    Bullock M, Gelman R. Preschool children’s assumptions about cause and effect: temporal ordering. Child Dev. 1979;50:89–96.

    Article  Google Scholar 

  80. 80.

    Bullock M. Preschool children’s understanding of causal connections. Br J Dev Psychol. 1984;2(2):139–48.

    Article  Google Scholar 

  81. 81.

    Goodman G, Rudy L, Bottoms BL, Aman C. Children’s concerns and memory: issues of ecological validity in the study of children’s eyewitness testimony. In: Fivush R, Hudson JA, editors. Knowing and remembering in young children. London: Cambridge University Press; 1990. p. 249–84.

    Google Scholar 

  82. 82.

    Nelson K. How children represent knowledge of their world in and out of language. Children’s thinking: What develops?. New Jersey: Lawrence Erlbaum Associates Inc; 1978. p. 225–73.

    Google Scholar 

  83. 83.

    Nelson K. Event knowledge: structure and function in development. London: Psychology Press; 1986.

    Google Scholar 

  84. 84.

    Willis G. Cognitive interviewing—a tool for improving questionnaire design. New York: Sage Publications; 2005.

    Google Scholar 

  85. 85.

    Herdman M, Fox-Rushby J, Badia X. A model of equivalence in the cultural adaptation of HRQoL instruments: the universalist approach. Qual Life Res. 1998;7(4):323–35.

    PubMed  Article  CAS  Google Scholar 

  86. 86.

    Landgraf JM, Abetz LN, DeNardo BA, Tucker LB. Clinical validity of the Child Health Questionnaire-Parent Form in children with rheumatoid arthritis. In: Poster presented at the 1995 National Scientific Meeting of the American College of Rheumatology, San Francisco, CA, October 21, 1995. 21-10-1995.

  87. 87.

    Starfield B, Bergner M, Ensminger M, Riley A, Ryan S, Green B, et al. Adolescent health status measurement: development of the Child Health and Illness Profile. Pediatrics. 1993;91(2):430–5.

    PubMed  CAS  Google Scholar 

  88. 88.

    Riley AW, Forrest CB, Rebok GW, Starfield B, Green BF, Robertson JA, et al. The Child Report Form of the CHIP-Child Edition: reliability and validity. Med Care. 2004;42(3):221–31.

    PubMed  Article  Google Scholar 

  89. 89.

    Riley AW, Forrest CB, Starfield B, Rebok GW, Robertson JA, Green BF. The Parent Report Form of the CHIP-Child Edition: reliability and validity. Med Care. 2004;42(3):210–20.

    PubMed  Article  Google Scholar 

  90. 90.

    Ravens-Sieberer U. The revised KINDL-R: Final results on reliability, validity and responsiveness of a modular HRQOL instrument for children and adolescents. 8. Jahrestagung der International Society for Quality of Life Research (ISOQOL). Qual Life Res. 2001;3:199.

    Google Scholar 

  91. 91.

    Ravens-Sieberer U, Gosch A, Abel T, Auquier P, Bellach BM, Bruil J, et al. Quality of life in children and adolescents: a European public health perspective. Soz Praventivmed. 2001;46(5):294–302.

    PubMed  Article  CAS  Google Scholar 

  92. 92.

    Theunissen NC, Vogel T, Koopman HM, Verrips GH, Zwinderman KA, Verloove-Vanhorick SP, et al. The proxy problem: child report versus parent report in health related quality of life research. Qual Life Res. 1998;7:387–97.

    PubMed  Article  CAS  Google Scholar 

  93. 93.

    Verrips GHW, Vogels AGC, Ouden AL, Paneth N, Verloove-Vanhorick SP. Measuring health-related quality of life in adolescents: agreement between raters and between methods of administration. Child Care Health Dev. 2000;26(6):457–69.

    PubMed  Article  CAS  Google Scholar 

  94. 94.

    Ennett ST, DeVellis BM, Anne Earp J, Kredich D, Warren RW, Wilhelm CL. Disease experience and psychosocial adjustment in children with juvenile rheumatoid arthritis: children’s versus mothers’ reports. J Pediatr Psychol. 1991;16(5):557–68.

    PubMed  Article  CAS  Google Scholar 

  95. 95.

    Vogel T, Verrips GH, Verloove-Vanhorick SP, Fekkes M, Kamphuis RP, Koopman HM, et al. Measuring health related quality of life in children: the development of the TACQOL parent form. Qual Life Res. 1998;7:457–65.

    Article  Google Scholar 

  96. 96.

    Cremeens J, Eiser C, Blades M. Factors influencing agreement between child self-report and parent proxy-reports on the Pediatric Quality of Life Inventory TM 4.0 (PedsQLTM) generic core scales. Health Qual Life Outcomes. 2006;4(1):58.

    PubMed  Article  Google Scholar 

  97. 97.

    Carona CP, Morais TF, Leitão S, Marques D, Silva N, Nazare B, et al. Assessing health-related quality of life in children and adolescents with asthma and epilepsy: results from the pilot validation study of the Portuguese versions of DISABKIDS-37. In: 16th Annual Conference of the International Society for Quality of Life Research (ISOQOL) [New Orleans, Louisiana, USA]. 31-10-2009.

  98. 98.

    Vetter TR, Bridgewater CL, McGwin G. An observational study of patient versus parental perceptions of health-related quality of life in children and adolescents with a chronic pain condition: who should the clinician believe? Health Qual Life Outcomes. 2012;10(1):85.

    PubMed  Article  Google Scholar 

  99. 99.

    Youssef NN, Murphy TG, Langseder AL, Rosh JR. Quality of life for children with functional abdominal pain: a comparison study of patients’ and parents’ perceptions. Pediatrics. 2006;117(1):54–9.

    PubMed  Article  Google Scholar 

  100. 100.

    Johnson SB, Wang C. Why do adolescents say they are less healthy than their parents think they are? The importance of mental health varies by social class in a nationally representative sample. Pediatrics. 2008;121(2):e307–13.

    PubMed  Article  Google Scholar 

  101. 101.

    Waters E, Stewart-Brown S, Fitzpatrick R. Agreement between adolescent self-report and parent reports of health and well-being: results of an epidemiological study. Child Care Health Dev. 2003;29(6):501–9.

    PubMed  Article  CAS  Google Scholar 

  102. 102.

    Annett RD, Bender BG, DuHamel TR, Lapidus J. Factors influencing parent reports on quality of life for children with asthma. J Asthma. 2003;40(5):577–87.

    PubMed  Article  Google Scholar 

  103. 103.

    Ronen G-M, Streiner D-L, Rosenbaum P. Canadian pediatric EN. Health-related quality of life in children with epilepsy: development and validation of self-report and parent proxy measures. Epilepsia. 2003;44(4):598–612.

    PubMed  Article  Google Scholar 

  104. 104.

    Atherton JS. Learning and teaching; Piaget’s developmental theory. 2010. http://www.learningandteaching.info/learning/piaget.htm.

Download references

Acknowledgments

We would like to acknowledge the support provided by Kate Bolton in preparing one draft of the manuscript, and the support of Nicola Moss in helping with formatting and quality checking. In addition, we are grateful for the helpful comments of two anonymous reviewers.

Disclosure of interests

Both Rob Arbuckle and Linda Abetz-Webb are employees of Adelphi Values, a health outcomes consultancy that specialises in working with healthcare companies on the development, validation, and use of PRO instruments. As such, both authors have been contracted to perform research for numerous pharmaceutical companies. Neither author owns stocks in any pharmaceutical company, nor have they been a direct employee of a pharmaceutical company.

Author contributions

Both authors contributed to the conception and writing of all parts of the manuscript and both authors read and approved the final version.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Rob Arbuckle.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Arbuckle, R., Abetz-Webb, L. “Not Just Little Adults”: Qualitative Methods to Support the Development of Pediatric Patient-Reported Outcomes. Patient 6, 143–159 (2013). https://doi.org/10.1007/s40271-013-0022-3

Download citation

Keywords

  • Focus Group
  • Recall Period
  • Cognitive Debriefing
  • Child Rating
  • Information Processing Theory