Factors contributing to wellness of the aging population in Thunder Bay
Bibliographic record
Abstract
The purpose of this three year sequential study was to examine factors \ncontributing to the wellness of 32 self-professed healthy seniors aged 65-74, 75-84, and \n85 years of age and older, living in Thunder Bay based on their; patterns of physical \nactivity; factors contributing to health and well-being; and lifestyle habits. In an attempt to \nbetter understand wellness over time, these respondents were visited each year from \n1993 to 1995. Since the number of participants in the oldest group declined from 11 to \nthree by the third year of the investigation, their responses are not included where they \nwould violate rules of statistical inference. Walking and gardening were the most popular \nactivities. Participants in the youngest age group were consistently active in the largest \nnumber of activities of the most vigorous nature over the three year period. The middle \nand oldest age groups reported a change by doing less vigorous physical activity over \nthe three year study. However, further analysis indicated that the middle and oldest age \ngroups engaged in compensatory behaviour. They replaced vigorous physical activity \nwith less intense activity and practiced over a longer duration. Participants uniformly \nperceived themselves as more active than their peers during adolescence, and also In \neach year of the study. Each age group identified regular physical activity, diet, and rest \nas the most important factors contributing to health and well-being. Despite their positive \nperception of personal health status, all three age groups indicated functional difficulty \nwith: standing, bending, and hearing. Participants also indicated that they were coping \nwith chronic conditions such as: arthritis, heart disease, and high blood pressure. The \nseniors In this study shared similar lifestyles. Each age group acknowledged the \nimportance of reaching specific goals such as: Independence, fitness, having fun, and \nrelaxation. Each group reported doing various leisure activities such as reading, visiting \nwith friends, and family. Even though the choices that the seniors made in the three age \ngroups demonstrated some variability, their responses indicate positive aging, and give \nus an understanding of wellness. The behaviour of these seniors indicates that they \nexhibit the components of successful aging as illustrated by Rowe and Kahn (1998): low \nrisk of disease, high mental and physical function, and active engagement with life.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".