Retrospective Analysis of Outcomes from Two Intensive Comprehensive Aphasia Programs
Bibliographic record
Abstract
Positive outcomes from intensive therapy for individuals with aphasia have been reported in the literature. Little is known about the characteristics of individuals who attend intensive comprehensive aphasia programs (ICAPs) and what factors may predict who makes clinically significant changes when attending such programs. Demographic data on participants from 6 ICAPs showed that individuals who attend these programs spanned the entire age range (from adolescence to late adulthood), but they generally tended to be middle-aged and predominantly male. Analysis of outcome data from 2 of these ICAPs found that age and gender were not significant predictors of improved outcome on measures of language ability or functional communication. However, time post onset was related to clinical improvement in functional communication as measured by the Communication Activities of Daily Living, second edition (CADL-2). In addition, for one sample, initial severity of aphasia was related to outcome on the Western Aphasia Battery-Revised, such that individuals with more severe aphasia tended to show greater recovery compared to those with mild aphasia. Initial severity of aphasia also was highly correlated with changes in CADL-2 scores. These results suggest that adults of all ages with aphasia in either the acute or chronic phase of recovery can continue to show positive improvements in language ability and functional communication with intensive treatment.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".