Goals Set After Completing a Teleconference-Delivered Program for Managing Multiple Sclerosis Fatigue
Bibliographic record
Abstract
Setting goals can be a valuable skill to self-manage multiple sclerosis (MS) fatigue. A better understanding of the goals set by people with MS after completing a fatigue management program can assist health care professionals with tailoring interventions for clients. This study aimed to describe the focus of goals set by people with MS after a teleconference-delivered fatigue management program and to evaluate the extent to which participants were able to achieve their goals over time. In total, 485 goals were set by 81 participants. Over a follow-up period, 64 participants rated 284 goals regarding progress made toward goal achievement. Approximately 50% of the rated goals were considered achieved. The most common type of goal achieved was that of instrumental activities of daily living. Short-term goals were more likely to be achieved. This study highlights the need for and importance of promoting and teaching goal-setting skills to people with MS.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".