Revised Self-Monitoring Scale
Bibliographic record
Abstract
Objective To investigate whether the Revised Self-Monitoring Scale (RSMS), an informant measure of socioemotional sensitivity, is a potential clinical endpoint for treatment trials for patients with behavioral variant frontotemporal dementia (bvFTD). Methods We investigated whether RSMS informant ratings reflected disease severity in 475 participants (71 bvFTD mutation+, 154 bvFTD mutation−, 12 behavioral mild cognitive impairment [MCI] mutation+, 98 asymptomatic mutation+, 140 asymptomatic mutation−). In a subset of 62 patients (20 bvFTD mutation+, 35 bvFTD mutation−, 7 MCI mutation+) who had at least 2 time points of T1-weighted images available on the same 3T scanner, we examined longitudinal changes in RSMS score over time and its correspondence to progressive gray matter atrophy. Results RSMS score showed a similar pattern in mutation carriers and noncarriers, with significant drops at each stage of progression from asymptomatic to very mild, mild, moderate, and severe disease (F4,48 = 140.10, p < 0.001) and a significant slope of decline over time in patients with bvFTD (p = 0.004, 95% confidence interval [CI] −1.90 to −0.23). More rapid declines on the RSMS corresponded to faster gray matter atrophy predominantly in the salience network (SN), and RSMS score progression best predicted thalamic volume in very mild and mild disease stages of bvFTD. Higher RSMS score predicted more caregiver burden (p < 0.001, 95% CI −0.30 to −0.11). Conclusions The RSMS is sensitive to progression of both socioemotional symptoms and SN atrophy in patients with bvFTD and corresponds directly to caregiver burden. The RSMS may be useful in both neurologic practice and clinical trials aiming to treat behavioral symptoms of patients with bvFTD.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".