Physical activity, screen time and sleep among children and adolescents: findings from the 2022 active healthy kids Ethiopia
Bibliographic record
Abstract
BACKGROUND: Few studies have been conducted on movement behaviours in low-income countries, indicating a need for further surveillance. This study aimed to track changes since the release of Ethiopia's 2018 Report Card indicators and explore further gaps in physical activity, sedentary screen time and sleep among Ethiopian children and adolescents (5-17 years). METHODS: We reviewed studies examining physical activity, sedentary screen time and sleep among Ethiopian children and adolescents. Relevant data were systematically searched from digital databases including PubMed, Medline, Scopus, Web of Science, WHO Hinari and Google Scholar, in alignment with the study objective. Policy or program documents were obtained from Ethiopian government official websites. Records were screened by two independent reviewers and extracted by the first author and verified by a co-author. Data were synthesised according to the harmonised Active Healthy Kids Global Alliance standards (A ≥ 80%, B 60-79%, C 40-59%, D 20-39%, F < 20%, INC = incomplete data). RESULTS: We found eight studies (n = 8) with relevant information; all were based on parent- or self-reported data. Only a small proportion of them met the guidelines for physical activity (16%) and sedentary screen time (55%). There were no data available for sleep. Since the release of the 2018 Report Card, there have been improvements in the grades for School, Active Transportation, Sedentary Behaviour, Community and Environment, and Government indicators from D to A-, C to B-, F to C+, F to C-, and D to C, respectively. However, grades for Overall Physical Activity, and Organised Sport and Physical Activity decreased from D to F and from C to C-, respectively, while the rest of the indicators remained unchanged. The Sleep indicator was introduced for the first time. CONCLUSION: Some indicators highlighted positive changes but limitations with data representativeness and quality underscore the need for improved surveillance to understand and promote healthy levels of movement behaviours in Ethiopian children and adolescents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".