Impact of reminder calls on the attendance of geriatric patients in general fitness classes
Bibliographic record
Abstract
Background.One of the most important recommendations for senior citizens is to do moderate physical activity regularly.Physical exercises improve body coordination and prevent injuries.According to Statistics Poland, more than 75% of Polish senior citizens are physically inactive.Objectives.The aim of the study was to assess whether the organisation of general fitness classes by a GP and physiotherapists can improve the physical condition of senior citizens and whether reminder calls can reduce senior patients' absence from these classes. Material and methods.The size of the study group was established on the basis of a study conducted by Statistics Poland, according to which more than 80% of Polish people above 60 years of age declare no physical activity.It was assumed that during an appointment, a GP can motivate a senior patient to participate in general fitness classes.In addition to the above intervention, participants to the study group received reminder calls once a week.40 groups of 6 individuals each were created.50 female senior patients were selected in order to assess patients' physical condition right before and after and 15 weeks after the fitness programme using the Senior Fitness Test (SFT).Results.224 persons divided into 39 groups participated in the study.19 groups made up a control group (108 persons), and 20 constituted a study group (116 persons).A statistically significant difference (p < 0.05) was observed for attendance in the general fitness classes in the group addressed with reminder calls.A statistically significant improvement of Senior Fitness Test results was observed for 4 out of 6 tests performed among 50 women before and after the fitness programme.Conclusions.Organisation of general fitness classes for senior patients by a GP can improve the physical condition in this group of patients.Reminder calls can reduce patients' absence from general fitness classes.
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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 | 0.007 | 0.067 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".