Alexitimia\ty\tdepresión\ten\tmayores\tque\tpractican\t actividad\tfísica\tdirigida
Bibliographic record
Abstract
Associations between alexithymia and depression and sociodemographic \nfactors have been investigated in elderly population. Whether exercise plays a \nrole as a protective factor against these conditions has yet to be \ndetermined. Thus, the aim of this study was to investigate alexithymia and \ndepression and its association with physical activity in elderly people. Twentyseven \nparticipants, 9 men and 18 women (aged 64±5.1). Subjects were \nassigned to either a sedentary group or a physically active group. All \nparticipants filled in Yesavage Scale, Toronto Alexithymia Scale (TAS)-20 and \nSF-12. Data were analyzed using Student’s t-test and multiple linear regression \nanalyses. Results showed that physically active elderly people scored lower for alexithymia and depression than sedentary subjects. These findings suggest \nthat physical activity may have a role in benefiting mental disorders.
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 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 | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".