Comparing Active and Inactive Former Experienced Athletes Regarding Physical and Mental Health Indices
Bibliographic record
Abstract
Background: Psychophysiological health status impairs during old age, and exercise is one of the factors that has a significant impact on the mental and physical health of the elderly. However, the impact of exercise on these indicators as well as the effects of exercise continuation or cessation have not been clearly identified. Objectives: This study aimed to evaluate and compare the effects of doing regular exercise and cessation of exercise on physical and mental health indicators of the old people. Methods: A total of 395 old individuals with a history of at least five years of regular exercise who had either stopped exercising for two years or been engaged in regular exercise volunteered to participate in this study. Two questionnaires including Beck Depression Inventory questionnaire (by Aaron Beck) and McGill Pain Questionnaire were used to measure the depression and the pain perception, respectively. Cardiorespiratory fitness, body mass index (BMI), waist to hip ratio (WHR), and balance were measured using relevant tests. T-test and Pearson correlation coefficient test were used to analyze the data. Results: The results showed that the indicators of physical health (i.e., cardiovascular fitness, disability, muscle pain, BMI, and WHR) in active old individuals were significantly different from those in inactive old ones; however, blood pressure and balance indicators were not different in active and inactive old individuals. Furthermore, psychological health indicators (i.e., life expectancy and depression) were significantly higher in active old individuals than inactive ones. Conclusions: In sum, continuation of physical activities during old age was found necessary to maintain some health indices. It was also found that the effects of previous physical activities on some health indices were not permanent.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".