118 Can we reasonably recommend strength training twice weekly for the general adult population aged 18-64 years to secure optimal body functionality?
Bibliographic record
Abstract
Abstract Purpose The objective of the study was to conduct a quality assessment of the scientific literature underlying the Danish Health Authorities (DHA) revised recommendations on physical activity (PA), with focus on the new advice on strength training twice a week to secure optimal body functionality in the adult population aged 18-64 years. Methods The study was a scoping review. Reviews conducted by the World Health Organization (WHO), the American and Canadian Health Authorities, and evidence referenced in earlier reports from DHA were included for initial review, as DHA refer to these as base for their PA-guideline revision. Studies included in the reviews were title- and abstract screened to assess whether they investigated PA and/or strength training in a population of adults aged 18-64 years. Studies identified through this screening, were furthermore full text screened, and finally included in a quality assessment, if they investigated a strength training intervention in relation to a measure of body functionality. The quality assessment was inspired by STROBE and the Jadad Scale (for observational studies and RCTs respectively) and extended with an assessment of the study’s research goal compliance (causal or predictive) to evaluate the study’s ability to detect eventual effects of the intervention on body functionality. Results A total of 25 out of 879 studies identified in the reviews were selected for quality assessment. Great variations in quality were identified, and many studies (13 out of 25) did not achieve 2/3 of potential quality points. The studies generally support strength training as an effective intervention on body functionality. However, 15 of the 16 RCTs investigated a study population with functional limitations, e.g. populations with musculoskeletal disorders, and most studies were based on a study population in the higher end of the age spectrum 18-64 years. Conclusions The literature does not clearly support a recommendation on strength training twice weekly for the general adult population to secure optimal body functionality. The formulation of PA-guidelines should be based on evidence that 1) aims to draw causal conclusions on the effect of the recommended intervention and 2) investigates a population comparable to the target audience. Funding None
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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 | 0.033 | 0.171 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".