Maternal and paternal contribution to intergenerational psychosocial transmission of paan chewing
Bibliographic record
Abstract
OBJECTIVES: Paan chewing is a recognized risk factor for oral cancer in the Asian population. However, there is currently little evidence about the intergenerational psychosocial transmission of paan chewing in South Indian families. We investigated the association between parental and participant's paan chewing in a South Indian population. METHODS: A subset of data was drawn from a hospital-based case-control study on oral cancer, the HeNCe Life study, conducted at Government Dental and Medical Colleges of Kozhikode, South India. Analyses were based on 371 noncancer control participants having diseases unrelated to known risk factors for oral cancer. Demographics, behavioral habits (e.g., paan chewing, smoking), and indicators of socioeconomic position (SEP) of both participants and their parents were collected with the use of a questionnaire-based interview and a life grid technique. Unconditional logistic regression assessed odds ratios (OR) and 95% confidence intervals (95% CI) for the associations between parental and participant's paan chewing, adjusted for confounders. RESULTS: Over half of the participants were males (55.2%), and the mean age of participants was 59 (SD = 12) years. After adjusting for age, religion, parents' SEP, parents' education, smoking and alcohol consumption, and perceived parenting behavior, we observed that maternal paan chewing and paternal paan chewing were significantly associated with the participant's paan chewing ([OR = 2.40, 95% CI = 1.11-5.21] and [OR = 3.05, 95% CI = 1.48-6.27], respectively). CONCLUSIONS: Intergenerational psychosocial transmission of the habit of paan chewing could occur through shared sociocultural or environmental factors.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".