Moving Together While Staying Apart: Practical Recommendations for 24-Hour Home-Based Movement Behaviours for Those With Cardiovascular Disease
Bibliographic record
Abstract
The novel coronavirus disease 2019 is a global public health crisis that disproportionately affects those with preexisting conditions. Cardiovascular disease (CVD) is the leading cause of death worldwide and many key CVD risk factors are modifiable (e.g., physical inactivity, sedentary behaviour, obesity). To limit the spread of coronavirus 2019, most governments have implemented restrictions and recommended staying at home, reducing social contact to a select and exclusive few, and limiting large gatherings. Such public health constraints may have unintended, negative health consequences on 24-hour movement behaviours. The primary purpose of this review is to provide practical at-home recommendations for sedentary time, sleep, and physical activity in those living with CVD. Adults with CVD will benefit from practical recommendations to reduce sedentary time, increase purposeful exercise, and maintain optimal sleep patterns while being at home and adhering to public health restrictions. Our recommendations include the following: (i) self-monitoring sitting time; (ii) engaging in 2-3 days per week of purposeful exercise for those with low exercise capacity and > 3 days per week for those with moderate-to-high exercise capacity; (iii) self-monitoring exercise intensity through the use of scales or wearable devices; (iv) maintaining a regular sleep schedule; and (v) moving daily. Clinicians should be aware that clear communication of the importance of limiting prolonged sedentary time, engaging in regular physical activity and exercise, and ensuring optimal sleep in association with the provision of clear, comprehensible, and practical advice is fundamental to ensuring that those living with CVD respond optimally to the challenges posed by the pandemic.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.006 |
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".