Feasibility of a School-based Study of Health Risk Behaviors in Ethnic Fijian Female Adolescents in Fiji: The HEALTHY Fiji Study.
Bibliographic record
Abstract
OBJECTIVE: Behavioral risk assessment is critical to developing intervention strategies to promote adolescent health, but also presents logistical, ethical, and scientific challenges. This paper reports on feasibility of a school-based study of health-risk behaviors in ethnic Fijian adolescent girls. METHODS: We assessed feasibility of school-based participation and implementation of assessment in the local vernacular language by examining observational data and by calculating response rates and as well as language selection and item completion rates. RESULTS: All invited study area schools participated (n=12). Response rates were >70% for study participation among eligible study participants in the overall sample as well as the peri-urban and rural sub-samples. The majority of respondents (71.9%) selected the local Fijian vernacular language version rather than the English version (28.1%). Although 43.6% of respondents completed a questionnaire in a language not spoken as the primary language at home, only ten respondents (1.9%) were assessed as having difficulty with the language of the self-report questionnaire. Item completion rates for the primary outcomes were >90% for both study phases and in both language versions. Study participant response rate for further assessment of concerning symptoms was also very high and teachers were successfully recruited for participation in training and accepting referrals to support these students at each participating school. CONCLUSION: School-based behavioral risk data collection in the vernacular language was feasible. Evaluation and referral of individual study participants with concerning symptoms to educators for further assistance and support also appeared feasible. We suggest that close collaboration among Fiji-based and specialty consultants to address scientific, linguistic, logistical, and ethical challenges were contributing factors to study feasibility.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".