Consumption and Purchasing Intent of Omega-3 Enriched Food Products by Lebanese Consumers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the modern nutrition patterns of many populations, consumers' intake of omega-3 oils does not reach the required levels. Eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) of the most potent omega-3 health benefits and commonly referred to as marine fatty acids, are not sufficiently consumed. This has led to numerous studies and attempts to produce foods enriched with omega-3 fatty acids. While applying fortification techniques, the most important challenge faced is to prevent the degradation of these fatty acids since both EPA and DHA are prone to oxidation. This study aims to predict the intention of Lebanese consumers towards the purchase of omega-3 enriched foods by applying the Theory of Planned Behavior Model. An online self-administered questionnaire was designed and conducted among Lebanese population. Results were collected throughout the month of August, 2021. Descriptive statistics, correlation and regression analyses were carried out using IBM SPSS Statistics 25. One hundred and eight (108) responses were received, 88% of which showed positive results on the intention of purchase of omega-3 enriched foods. Multiple linear regression analysis explained 30.4% of the variance in intention (p<0.001), and attitude and behavioral beliefs were the significant determinants of intention. One limitation though is faced within the Lebanese consumers is their economic status; but in general, respondents show willingness to spend money and time to purchase such fortified food provided that promoters should emphasize on the multiple health benefits of such products.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it