Eliciting Information on Differential Sensation of Heat in Those With and Without Poststroke Aphasia Using a Visual Analogue Scale
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Aphasia can result in an inability to communicate the presence, location, or intensity of pain. Although visual analogue scales (VASs) exist, it is unknown whether they are useful in assessing pain in individuals with aphasia. The objective was to determine whether those with poststroke aphasia could respond differentially to thermal stimuli of varying intensities using a standardized VAS. METHODS: Five groups of participants were assessed: those without stroke, those with stroke but without aphasia, and 3 groups with varying degrees of aphasia. A 10-cm vertical VAS was used to measure responses to varying thermal intensities delivered on the participant's forearm. RESULTS: Across all 5 groups, a similar proportion demonstrated ability to discriminate between 2 temperatures (chi2=1.899; P=0.75). When presented with 4 temperatures, all groups performed more poorly, yet with similar success rates across groups (chi2=0.1267; P=0.88). The repeated-measures ANOVA revealed no effect of group but a significant effect of temperature (P<0.0001). CONCLUSIONS: A VAS may be useful in clinical identification of differing intensities of stimuli in a substantial proportion of those with aphasia.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.005 | 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".