Dietary Habits among Adolescent Girls 9–13 Years of Age that have Accessed Nutritional Information in Last 12 Months in the Upper Manya Krobo District, Ghana
Bibliographic record
Abstract
A desire to acquire health information is present among Ghanaian youth. About half (53%) of adolescent Internet users, 15–18 years of age residing in Accra, Ghana, have searched for health information online. Access to adequate nutritional information may positively influence dietary habits among adolescent girls. This analysis examined the association between the acquisition of nutritional information and dietary habits among adolescent girls. We carried out a cross‐sectional survey among adolescent girls 9–13 years of age (n=1420) living in 3 subdistricts of the rural Upper Manya Krobo district in the Eastern Region of Ghana in 2014. Data were recorded concerning the access to nutritional information during the past 12 months as well as dietary intake during the previous week. Ten percent of adolescent female participants reported receiving nutritional information during the previous 12 months. Among those who did receive nutritional information, the majority of participants (62%) received it in school, followed by access from home (21%), local community activities (9%), local clinic (6%), and other sources (1%). Receiving nutritional information was significantly associated with consumption of organ meats (p < 0.0001) whereas there was no significant association with diet diversity (p=0.14), intake of animal source foods (p=0.35), or vitamin A‐rich food products (p=0.87). Research shows that nutritional information is not yet accessible to the majority of adolescent girls in this district. Further research is needed to identify best nutrition education practices that increase the accessibility and quality of health messages tailored to adolescent girls. These data are part of Clinical Trials # NCT01985243. Support or Funding Information Global Affairs Canada, Government of Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".