Views of Indian Migrants on Adaptation of Child Oral Health Leaflets: A Qualitative Study
Bibliographic record
Abstract
The aim of this study was to gain insight on the views of Hindi-speaking mothers on readily available English language oral health education materials and to evaluate the acceptability of Hindi language adapted versions of these materials. This qualitative study is nested within an ongoing multi-centre birth cohort study in Greater Western Sydney, Australia. Following purposive selection of Hindi-speaking mothers (n = 19), a semi-structured interview was conducted. Two English leaflets were mailed to participants prior to the interview. The simplified English and translated Hindi versions of the leaflets were provided at the interview, and the participants were asked to compare and evaluate all three versions. Interviews were audio recorded, and thematic analysis was used to analyse data from interview transcripts. A majority of the participants reported a certain degree of difficulty in reading and comprehending oral health messages in Hindi. Although Hindi translations were accurate, mothers preferred the simplified English as opposed to the Hindi version. Visual illustrations and a simple layout facilitated the understanding of oral health messages. Developers of oral health education leaflets should thoroughly research their prospective user groups, particularly migrant populations, and identify the need for simplified or translated oral health education leaflets.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".