Functional food awareness and perceptions in relation to information sources in older adults
Bibliographic record
Abstract
BACKGROUND: The functional food industry has experienced innovative and economic expansion, yet research into consumer perceptions of functional foods and their associated health claims is limited. Among consumers, older adults could benefit from functional foods due to age-related issues pertaining to food and health. The purpose of this research was to identify the need for information related to functional foods among older adults (≥60 years old) and to assess awareness and perceptions of health claims on functional food packages. METHODS: Community-dwelling older adults (n = 200) completed a researcher administered questionnaire designed to collect information about functional foods including current consumption, motivating factors for consumption, perceived need for information, sources of information for functional foods and awareness of health claims. RESULTS: Prevalence of functional food consumption among participants was 93.0%. Increased awareness and knowledge was the most commonly reported factor that would promote functional food consumption (85.5%) and 63.5% of participants wanted more information about functional foods with preferred sources being newspapers/magazines/books (68.5%) and food labels (66.1%). Participants were predominately (93.5%) aware of health claims on functional foods and those with more education were more likely to report being aware of health claims (p = 0.045). CONCLUSIONS: Although functional food consumption among older adults in this sample is high, there is a need for further information regarding functional foods. These results inform stakeholders regarding the potential for information to influence functional food acceptance among older adult consumers.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".