Advances in Technology Promote Patient-Centered Care in Cardiac Rehabilitation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patient-centered health care (PCC) is a framework of clinical care focused on the patient's individual health care needs. In particular, it emphasizes the development of a partnership between the patient, physician, and healthcare workers to actively involve and empower the patient in their health care decisions. Additionally, PCC goals include ensuring access to care, emotional support, engaging patient support systems, physical comfort, and continuity of care. Technology also provides a platform to engage patients and their families in their care and can be a useful tool to gauge their level of interest, knowledge, and motivations to adequately educate them on the many factors that contribute to their disease, including diet, exercise, medication adherence, psychological support, and early symptom detection. In this article, we summarize the importance of technology in promoting PCC in cardiac rehabilitation and the impact technology may have on the different aspects of patient and physician relationships. Modern technological devices including smartphones, tablets, wearables, and other internet-enabled devices have been shown to help patient-staff communication, cater to patients' individual needs, increase access to health care, and implement aspects of PCC domains.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it