Adapting the Multiple Sclerosis Functional Composite for Telehealth Administration Using Videoconference Delivery: Methodological Considerations and Interrater Reliability
Bibliographic record
Abstract
Objective: To describe the adaptations made and to examine interrater reliability and feasibility of administering a telehealth version of the Multiple Sclerosis Functional Composite (tele-MSFC). Design: The Multiple Sclerosis Functional Composite (MSFC) is a commonly used, in-person clinical outcome assessment. It is composed of the timed 25-Foot Walk Test (T25FWT), Nine-Hole Peg Test (NHPT), and Paced Auditory Serial Addition Test (PASAT). The MSFC was adapted for videoconference administration as part of a larger clinical trial. One of the adaptations included administering a timed 12.5-Foot Walk Test (T12.5FWT) for participants who did not have adequate space in their homes for the T25FWT. Participants, examiners, and raters completed surveys online about their satisfaction and experience with tele-MSFC. Setting: Participants underwent the tele-MSFC in their homes using a laptop or smartphone while examiners scored the tele-MSFC in real-time at a remote location. Participants: Community-dwelling adults (n=61) with mild-to-moderate multiple sclerosis (MS) symptoms. Interventions: Not applicable. Main Outcome Measure: Tele-MSFC. Results: Intraclass correlation coefficients (ICC) assessed interrater reliability between the examiner and 2 independent raters who later scored a recording of the tele-MSFC. Interrater reliability was excellent (ICC>0.90) for all tests, including the T12.5FWT. Participants were highly satisfied with tele-MSFC. However, challenges included adequate space for T25FWT, technical difficulties, and safety and privacy considerations of individuals with moderate impairments who were requested to have their caregivers present during testing. Conclusion: The tele-MSFC is reliable and feasible to administer with adaptations for community-dwelling adults with mild to moderate MS symptoms. Further validation of T12.5FWT is needed.
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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 | 0.212 | 0.270 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".