Development of an oral health outcome measure for children aged 6 to 14 years
Bibliographic record
Abstract
The impact that oral and orofacial conditions have on the well-being of children has not been studied as no adequate measure is available. The research was undertaken to design the Child Oral Health Quality of Life Questionnaire (COHQoL) to assess the oral-health-related quality of life (OHRQoL) of 6–14-year-old children and their families. It was planned to consist of a Parental Perceptions Questionnaire (PPQ), a Family Impact Scale (FIS), and Child Perceptions Questionnaires for 6–7- (CPQ6–7); 8–10- (CPQ8–10), and 11–14-year-olds (CPQ 11–14). This thesis reports on the development of the PPQ and the CPQ11–14 and testing of their discriminative properties. It also explores the adequacy of parents as information providers in paediatric health outcome research by examining the relationship between the PPQ and the CPQ11–14 reports and the extent, nature and predictors of “Don't know” responses given by parents. The PPQ and the CPQ11–14 were constructed according to the process derived from the theory of measurement and scale development. Preliminary item pools were developed through reviews of relevant literature and interviews with health professionals (n = 17), parents (n = 33) and children (n = 11). The items rated the most frequent and bothersome by parents (n = 208) and children (n = 83) were selected for the questionnaires. Construct validity testing involved 231 parents and 123 children, of whom 79 and 65 provided data for the assessment of test-retest reliability of the respective questionnaires. Both questionnaires demonstrated satisfactory validity and reliability. There were no systematic differences between mothers and their children at the group level. However, there was a substantial disagreement at the individual level and some parents exhibited limited knowledge, particularly with respect to emotional and social consequences. Therefore, the studies indicated that data should be obtained from children whenever this is possible and that parents should be used as classic ‘proxies’ only when children are unable to report on their OHRQoL. As the PPQ and the CPQ11–14 have been tested on clinical child populations, their validity and reliability have to be demonstrated in non-clinical settings for their use in surveys of general child populations. Their application in intervention studies requires that their evaluative properties (longitudinal construct validity and responsiveness) are established.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".