Coping strategies in relation to negative work events and accommodations in employed multiple sclerosis patients
Bibliographic record
Abstract
BACKGROUND: Job loss is common in multiple sclerosis (MS) and is known to exert a negative effect on quality of life. The process leading up to job loss typically includes negative work events, productivity losses and a need for accommodations. By using active coping strategies job loss may be prevented or delayed. OBJECTIVE: Our goal was to examine negative work events and accommodations in relation to coping strategies in employed relapsing-remitting MS patients. METHODS: Ninety-seven MS patients (77% females; 21-59 years old) completed questionnaires concerning the patient's work situation, coping strategies, demographics, physical, psychological and cognitive functioning. Forward binary logistic regression analyses were conducted to examine coping strategies and other (disease) characteristics predictive of reported negative work events and accommodations. RESULTS: Nineteen per cent of the employed MS patients reported one or more negative work events, associated with a higher use of emotion-oriented coping and more absenteeism. Seventy-three per cent reported using one or more work accommodations, associated with a higher educational level and more presenteeism. MS patients reporting physical changes to the workplace employed more emotion-oriented coping, while flexible scheduling was associated with task-oriented coping. CONCLUSION: Emotion-oriented and task-oriented coping strategies are associated with negative work events and the use of accommodations.
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 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".