Resistance training reduces depressive and anxiety symptoms in older women: a pilot study
Bibliographic record
Abstract
OBJECTIVES: Forty-one older women (68 ± 8 years) composed a training group (TG) or a control group (CG). The TG was submitted to a supervised, progressive RT program over 12 weeks, involving eight whole-body exercises performed with three sets of 8-12 repetitions, three days per week, whereas CG remains with no intervention for the same period. Muscular strength (one-repetition maximum tests), cognitive function (Montreal Cognitive Assessment - MoCA; Verbal Fluency Tests), depression (15-item eriatric Depression Scale - GDS-15), and anxiety (Beck Anxiety Inventory - BAI) were assessed before and after the intervention period. RESULTS: There were observed significant (P < 0.001) RT-induced improvements on total muscular strength (TG: pre = 122.4 ± 24.1/post = 134.3 ± 36.7; CG: pre = 105.4 ± 15.4/post = 99.2 ± 17.1) and MoCA (TG: pre =21.7 ± 4.5/post = 22.5 ± 4.7; CG: pre = 20.3 ± 3.7/post = 19.3 ± 4.1). Depressive and anxiety symptoms (even when adjusted by chronological age and changes in muscular strength or cognitive function) were reduced with RT according to GDS-15 (TG: pre = 2.26 ± 1.53/post = 1.92 ± 1.68; CG: pre =2.68 ± 1.13/post = 2.25 ± 1.18) and BAI (TG: pre = 4.07 ± 5.68/post = 2.33 ± 3.71; CG: pre = 5.18 ± 7.70/post = 9.81 ± 7.10). The time x group interactions were significant for depressive and anxiety symptoms. CONCLUSIONS: Our results suggest that a 12-week RT program reduces depressive and anxiety symptoms, regardless of age, muscular strength, and cognition function in older women.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".