Intensive Comprehensive Aphasia Programs: An International Survey of Practice
Bibliographic record
Abstract
BACKGROUND: In response to the need to simultaneously address multiple domains of the International Classification of Functioning, Disability and Health (ICF) in aphasia therapy and to incorporate intensive treatment doses consistent with principles of neuroplasticity, a potentially potent treatment option termed intensive comprehensive aphasia programs (ICAPs) has been developed. OBJECTIVE: To conduct an international survey of ICAPs to determine the extent of their use and to explore current ICAP practices. METHODS: A 32-item online survey was distributed internationally through Survey Monkey between May and August 2012. The survey addressed ICAP staffing, philosophy, values, funding, admission criteria, activities, family involvement, outcome measures, and factors considered important to success. RESULTS: Twelve ICAPs responded: 8 from the United States, 2 from Canada, and 1 each from Australia and the United Kingdom. The majority of ICAPs are affiliated with university programs and are funded through participant self-pay. ICAPs emphasize individualized treatment goals and evidence-based practices, with a focus on applying the principles of neuroplasticity related to repetition and intensity of treatment. On average, 6 people with aphasia attend each ICAP, for 4 days per week for 4 weeks, receiving about 100 hours of individual, group, and computer-based treatment. Speech-language pathologists, students, and volunteers staff the majority of ICAPs. CONCLUSIONS: ICAPs are increasing in number but remain a rare service delivery option. They address the needs of individuals who want access to intensive treatment and are interested in making significant changes to their communication skills and psychosocial well-being in a short period of time. Their efficacy and cost-effectiveness require future investigation.
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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".