Addressing rural and remote access disparities for patients with inflammatory arthritis through video‐conferencing and innovative inter‐professional care models
Bibliographic record
Abstract
OBJECTIVE: The aim of the present study was to evaluate whether rheumatoid arthritis (RA) patients followed longitudinally using video-conferencing and inter-professional care support have comparable disease control to those followed in traditional in-person rheumatology clinics. METHODS: This was a randomized controlled trial for 85 RA patients allocated to either traditional in-person rheumatology follow-up or video-conferenced follow-up with urban-based rheumatologists and rural in-person physical therapist examiners. Follow-up was every 3 months for 9 months. Outcome measures included disease activity metrics (disease activity in 28 joints with CRP measure score [DAS28-CRP], and RA disease activity index [RADAI]), modified health assessment questionnaire (mHAQ), quality of life (EuroQOL five dimensions questionnaire [EQ5D]) and patient satisfaction (nine-item visit-specific satisfaction questionnaire [VSQ9]). RESULTS: Of 85 participants, 54 were randomized to the video-conferencing team model and 31 to the traditional clinic (control group). Dropout rates were high, with only 31 (57%) from the video-conferencing and 23 (74%) from the control group completing the study. The mean age for study participants was 56 years; 20% were male. Mean RA disease duration was 13.9 years. There were no significant between-group differences in DAS28-CRP, RADAI, mHAQ or EQ5D scores at baseline or over the study period. Satisfaction rates were high in both groups. CONCLUSIONS: We found no evidence of a difference in effectiveness between inter-professional video-conferencing and traditional rheumatology clinic for both the provision of effective follow-up care and patient satisfaction for established RA patients. High dropout rates reinforce the need for consultation with patients' needs and preferences in developing models of care. While use of video-conferencing/telehealth technologies may be a distinct advantage for some patients, there may be loss of travel-related auxiliary benefits for others.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".