Community Vitality: A Healthy Life for Everyone - Part 2: Resource Website Development
Bibliographic record
Abstract
Objective: A group of faculty from nursing, exercise science, nutrition, psychology, and occupational safety and health has been working on a four-part research project that investigates healthy lifestyles of centenarians in the world's Blue Zones. The project's aim is to educate people about concepts of centenarian lifestyles and compare and contrast with habits of Americans.Methods: This four-part study includes resource website development, interviews with elderly people in the local community about lifestyles and habits, administration to local adults of a survey about barriers to healthy lifestyles, and education on findings in local elementary schools. The goal of this portion of the four-part study was to develop a website that provides easily accessible information for community members to learn about the Community Vitality project. In addition, community members can access resources related to movement (physical activity), rest (reducing stress, sleeping, and identifying life objectives), nutrition (eating a plant-based diet, intuitive eating, and drinking red wine), and connection (time with family and social groups). The website was created using multiple areas of expertise and includes resources in and around the local community that relate to these four major concepts. Ultimately, the researchers’ goal is for community members to access and utilize the resources to learn about and practice healthy living.Results: The website went live in January, 2022. The website URL has recently been shared with people of all ages in the community via social media and other outlets so that they have access to one location with recommendations for healthy living related to movement, rest, nutrition, and connections. The researchers plan to utilize student research involvement to keep the website and links current on a monthly basis as well as monitor number of views.Conclusions: Blue Zones are areas of the world where there are more centenarians per capita than the rest of the world. In addition, they tend to be healthier than the elderly in the United States. This project aims to identify habits of local people and barriers to healthy living, and then educate people about healthy living and potential changes that can be made.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.009 |
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".