GRADE ADOLOPMENT Process to Develop 24-Hour Movement Behavior Recommendations and Physical Activity Guidelines for the Under 5s in the UK, 2019
Bibliographic record
Abstract
Background: Physical activity guideline developers are faced with demands to produce guidelines quickly and at low cost. This paper summarises a new, efficient, approach taken to develop UK Chief Medical Officers’ (CMOs) Guidelines for the Under 5s, 2019. Methods: The Grading of Recommendations Assessment, Development and Evaluation (GRADE) Adaptation, Adoption, De Novo Development (ADOLOPMENT) approach was used, based on 24-hour movement behavior guidelines from Canada and Australia in 2017, with a systematic review update in 2018. Draft recommendations were based on (a) the influence of time spent asleep, sedentary, and in physically activity on 10 health outcomes and (b) the influence of PA and sedentary behaviour (including screen time) on sleep outcomes (e.g. duration, latency). Results: There was consistent evidence of links between the 24-hour movement behaviors and all outcomes, and a high degree of UK stakeholder support for all draft recommendations. UK Guidelines for the Under 5s will be published in 2019 with new guidance on infant tummy time and moderate-to-vigorous-intensity physical activity in pre-schoolers, but draft recommendations on sleep and screen time were not accepted by the CMOs. Conclusions: This was the first time that the GRADE ADOLOPMENT process has been used in Europe to develop physical activity guidelines. It permitted a rapid and inexpensive production of the UK Physical Activity Guidelines for the Under 5s.
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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 | 0.064 | 0.156 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.008 |
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".