Quality of life of children and their caregivers during an AOM episode: development and use of a telephone questionnaire
Bibliographic record
Abstract
BACKGROUND: The negative consequences of acute otitis media (AOM) on the quality of life (QOL) of children and their families need to be measured to assess benefits of preventive interventions. METHODS: A new questionnaire was specifically designed for use in telephone surveys. A random sample of Canadian families was selected using random-digit dialling. Caregivers of children 6-59 months of age who experienced at least one AOM episode during the last 12 months were interviewed. Multidimensional severity and global QOL scores were measured both for affected children and their caregivers. Internal consistency of scores was assessed using standard tests. RESULTS: Of the 502 eligible caregivers who completed the survey, 161 (32%) reported at least one AOM episode during the last 12 months and these cases were included in the analysis. Average severity was 2.6 for children and 2.4 for caregivers on a 1 to 4 scale (maximum severity). Cronbach alpha values were 0.78 and 0.81 for the severity score of children and caregivers respectively. Average QOL was 3.4 for children and 3.5 for caregivers on a 1 to 5 scale (best QOL). There was moderate to high correlation between severity and QOL scores, and between these scores and duration of AOM episodes. CONCLUSIONS: The questionnaire was easy to use during telephone interviews and results suggest good reliability and validity of the different scores to measure AOM severity and QOL of children and their caregivers during an AOM episode.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".