Development and pilot testing of an oral hygiene self-care photonovel for Punjabi immigrants: a qualitative study.
Bibliographic record
Abstract
Introduction: The purpose of this research study was to develop and pilot test a culturally and linguistically appropriate oral hygiene self-care photonovel for Punjabi immigrants. Methods: Purposeful sampling technique was used to recruit 5 members of a Punjabi community organization (the Sikh Women's Association of Montreal) for participation in 3 focus group sessions in August 2015. A thematic content analysis approach was used to sort the data, enabling identification of the storyline and photonovel contents from the themes that emerged. Comic Life 3 version 3.1.1 software was used to create a "Safeguard Your Smile" (SYS) photonovel, which was printed for pilot testing. Ten additional participants were recruited for this pilot testing, enabling further revision of the photonovel based on their suggestions. Results: Four major themes emerged from the focus group discussions: 1) lack of understanding of oral hygiene self-care and risk factors; 2) lack of oral hygiene self-care-related awareness and routine; 3) lack of emphasis on prevention by oral health care providers; and 4) perceived barriers to accessing dental health care. Thematic content analysis revealed a lack of knowledge of oral hygiene self-care skills and routine. Guided by these overarching themes, a final version of the photonovel script was created including photographs of key characters. The photonovel was subsequently printed for pilot testing. Pilot test results revealed close to 80% of participants agreed that the SYS photonovel was culturally and linguistically appropriate and easy to understand. Conclusions: A culturally and linguistically appropriate photonovel may be a useful tool for enhancing oral hygiene self-care knowledge among ethnic communities. Further studies are required to test the effectiveness of such a tool.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| 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".