Hopelessness Ratings in Relapsing-Remitting and Secondary Progressive Multiple Sclerosis
Bibliographic record
Abstract
OBJECTIVE: Two recent randomized double-blind placebo controlled clinical trials of interferon beta-1a in multiple sclerosis have obtained hopelessness ratings using the Beck Hopelessness Scale (BHS). One of these studies, the PRISMS trial, evaluated interferon beta-1a in relapsing remitting multiple sclerosis (RRMS). Another, the SPECTRIMS trial, evaluated the same medication in secondary progressive (SP) MS. The objective of this analysis was to compare levels of hopelessness in persons with RRMS and SPMS, and to describe changes over time in the clinical trial participants. METHOD: Raw data from each clinical trial was obtained from the sponsor of the trials (Serono). Median BHS ratings, and the proportions at or above the BHS cut-point of 10 were calculated over a two (PRISMS) or three (SPECTRIMS) year period. RESULTS: The analysis included n = 532 clinical trial participants. Ratings of hopelessness were higher in SPMS clinical trial participants (SPECTRIMS) than in the RRMS group (PRISMS) at baseline (Fisher's exact test, p = 0.0035). Furthermore, ratings of hopelessness were higher during follow-up than at baseline, in the SPMS group (McNemar's exact probability,p = 0.0015), but not in the RRMS group (McNemar's exact probability,p = 0.65). Depression was strongly associated with hopelessness in both RRMS (z = 4.13, p < 0.001) and SPMS (z = 5.24, p < 0.001). CONCLUSIONS: Hopelessness is associated with SPMS, and may increase over time in this group. Hopelessness may influence suicide risk in people with MS and may potentially have an impact on coping and quality of life. Additional research is necessary to define the clinical implications of hopelessness in persons with this condition.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".