<p>Experience of patients and practitioners with a team and technology approach to chronic back disorder management</p>
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
PURPOSE: Although rural and remote residents face general challenges accessing health care in comparison to urban dwellers, care for musculoskeletal conditions like chronic back disorders (CBD) is particularly challenging for rural and remote residents due to lack of access to physical yherapists. Telerehabilitation such as secure videoconferencing offers one solution to this disparity in rural care delivery, but incorporating the perspectives of health practitioners and patients is important when developing new sustainable care models. PATIENTS AND METHODS: This study investigated the experiences of practitioners and patients during a novel interprofessional model of assessment where an urban-based physical therapist used videoconferencing to virtually join a rural nurse practitioner and a rural patient with CBD. Patient surveys and semi-structured interviews of practitioners and patients were analyzed quantitatively and qualitatively. RESULTS: Most patients were "very satisfied" (62.1%) or "satisfied" (31.6%) with the overall experience, and "very" (63.1%) or "somewhat (36.9%) confident" with the assessment. Thematic analysis of interviews revealed that this novel assessment method identified: access to care for CBD, effective interprofessional practice, enhanced clinical care for CBD, and technology considerations. CONCLUSION: Patient satisfaction with the telerehabilitation model of care was high. Patients and practitioners reported their experiences were impacted by access to care, interprofessional practice, enhanced care for CBD and technology. These findings will be useful in the development of patient-centered models of care utilizing telehealth strategies.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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