Knowledge and practices of malaysian healthy plate (quarter quarter half program) among adult community in cybercity, Kepayan, Sabah
Bibliographic record
Abstract
The Malaysian Healthy Plate, known as the Quarter Quarter Half Program, is a dietary guideline aimed at promoting balanced nutrition among Malaysians. This study investigates the knowledge and practice of this program among the adult community in Cybercity Kepayan, Sabah. Using a cross-sectional design, data were collected through surveys with a representative sample of adults. In this study, majority of the participants are female, working with the government. Most of the participants are a variety of races as in Sabah (n=157, 53,7%), a single individual (n=178, 62.8%), a degree holder in education (n=147, 51.9%) and have monthly income of RM2000-RM3999 (n=84, 29.7%). Most of the participants (n=131, 46.7%) have high level of knowledge about MHP QQHP. Most of the participants (n=209, 73.9%) have a moderate level of practices about MHP QQHP. There was no significant association between socio- demographic data and level of practice of Malaysian Healthy Plate as well as level of QOL (p > 0.05). The findings reveal that while there is a general awareness of the Quarter Quarter Half Program, practical adherence is limited due to various factors such as lack of detailed understanding and accessibility to healthy food options The study underscores the need for enhanced educational efforts and community-based initiatives to bridge the gap between knowledge and practice. These findings have significant implications for public health strategies aiming to improve dietary habits and overall health in the region.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".