Bibliographic record
Abstract
Geography limits the referral and participation of rural patients in cardiac rehabilitation programs (CRP). The extensive applications of the Internet and telecommunications technology may be the solution to provide rural cardiac patients with access to CRP. To our knowledge, no studies have investigated the application of teleconferencing via Internet Protocol (IP) network to a cardiac rehabilitation (CR) exercise class setting. PURPOSE To identify the basic procedures, technology, interactions and limitations that result when a CR exercise program is transmitted over the Internet via teleconferencing software to another location, in real-time, with interactive capabilities. METHODS Nine volunteers from a local CRP were placed into one of two groups: host or remote. Participants then took part in three teleconferenced CR exercise classes to examine their ability to interact and be monitored from a distance. After each session, participants, the exercise leader and medical/health professional staff completed questionnaires relating their satisfaction with the exercise class as provided by the specific technology. RESULTS 100% of participants (n=9) in both the host and remote groups indicated satisfaction with the quality of the technology, the degree of social interaction and the quality of the exercises provided via a teleconferenced CR exercise class. No statistically significant differences were noted (p > .05) between host and remote sites. However, even with video transmission rates of 15 frames per second, an on-site health professional was essential to detect subtle physical/facial distress. CONCLUSION This study suggests that teleconferencing is a meaningful and worthwhile application of CR to target rural patients. Data transmission challenges would be alleviated with one megabit per second guaranteed bandwidth and 1.2GHz processor, or better, at the host and remote sites for smooth, synchronized streamed data. Supported by Bell Canada University Labs
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".