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Thomson, W.M.; Foster Page, L A; Robinson, P G; Do, L G; Traebert, J; Mohamed, A R; Turton, B J; McGrath, C; Bekes, K; Hirsch, C; Del Carmen Aguilar-Diaz, F; Marshman, Z; Benson, P E; Baker, S R (2016)
Publisher: Wiley
Languages: English
Types: Article
Subjects: /dk/atira/pure/researchoutput/pubmedpublicationtype/D016428, Journal Article

OBJECTIVE: To examine the factor structure and other psychometric characteristics of the most commonly used child oral-health-related quality-of-life (OHRQoL) measure (the 16-item short-form CPQ11-14 ) in a large number of children (N = 5804) from different settings and who had a range of caries experience and associated impacts.

METHODS: Secondary data analyses used subnational epidemiological samples of 11- to 14-year-olds in Australia (N = 372), New Zealand (three samples: 352, 202, 429), Brunei (423), Cambodia (244), Hong Kong (542), Malaysia (439), Thailand (220, 325), England (88, 374), Germany (1055), Mexico (335) and Brazil (404). Confirmatory factor analysis (CFA) was used to examine the factor structure of the CPQ11-14 across the combined sample and within four regions (Australia/NZ, Asia, UK/Europe and Latin America). Item impact and internal reliability analysis were also conducted.

RESULTS: Caries experience varied, with mean DMFT scores ranging from 0.5 in the Malaysian sample to 3.4 in one New Zealand sample. Even more variation was noted in the proportion reporting only fair or poor oral health; this was highest in the Cambodian and Mexican samples and lowest in the German sample and one New Zealand sample. One in 10 reported that their oral health had a marked impact on their life overall. The CFA across all samples revealed two factors with eigenvalues greater than 1. The first involved all items in the oral symptoms and functional limitations subscales; the second involved all emotional well-being and social well-being items. The first was designated the 'symptoms/function' subscale, and the second was designated the 'well-being' subscale. Cronbach's alpha scores were 0.72 and 0.84, respectively. The symptoms/function subscale contained more of the items with greater impact, with the item 'Food stuck in between your teeth' having greatest impact; in the well-being subscale, the 'Felt shy or embarrassed' item had the greatest impact. Repeating the analyses by world region gave similar findings.

CONCLUSION: The CPQ11-14 performed well cross-sectionally in the largest analysis of the scale in the literature to date, with robust and mostly consistent psychometric characteristics, albeit with two underlying factors (rather than the originally hypothesized four-factor structure). It appears to be a sound, robust measure which should be useful for research, practice and policy.

  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • 3. Traebert J, Telino de Lacerda J, Foster Page LA, Thomson WM, Bortolluzzi M. Impact of traumatic dental injuries on the quality of life of school children. J Dent Traumatol 2011;28:423-8.
    • 4. Mohamed AR, Thomson WM, Foster Page LA. Epidemiological validation of a Malay version of the Child Perceptions Questionnaire (CPQ11-14) in Brunei. Brunei Darussalam J Health 2013;5:56-69.
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    • 15. Marshman Z, Rodd H, Stern M, Mitchell C, Locker D, Jokovic A, Robinson PG. An evaluation of the Child Perceptions Questionnaire in the UK. Community Dent Health. 2005;22:151-5.
    • 16. Pine CM, Pitts NB, Nugent ZJ. British Association for the Study of Community Dentistry (BASCD) guidance on the statistical aspects of training and calibration of examiners for surveys of child dental health. A BASCD coordinated dental epidemiology programme quality standard. Community Dent Health. 1997;14(Suppl 1):18-29.
    • 17. Benson PE, Da'as T, Johal A, Mandall NA, Williams AC, Baker SR, Marshman Z. Relationships between dental appearance, self-esteem, socio-economic status, and oral health-related quality of life in UK schoolchildren: A 3-year cohort study. Eur J Orthod 2015;37:481-90.
  • No related research data.
  • Discovered through pilot similarity algorithms. Send us your feedback.

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