Comprehensive intervention combining group and personalized language therapy in primary progressive aphasia: Quantitative and qualitative findings
Bibliographic record
Abstract
INTRODUCTION: Increasingly, studies are demonstrating language and communication improvement after behavioral interventions for primary progressive aphasia (PPA), and the caregiver perspective has been highlighted as critically important to determining treatment success in this population. This is an exploratory study investigating a comprehensive, person-centered intervention promoting everyday communication, functional independence, and quality of life for people with PPA (PwPPA) and their caregivers. METHODS: Four intervention programs were run separately in 6 to 8 week blocks with a total of 14 dyads (PwPPA and caregiver) enrolled. Group sessions lasted 2 hours and included communication strategy training, PPA education from multidisciplinary experts, speech therapy for PwPPA, and a support group for caregivers (blocks 1 and 2). Personalized language exercises were assigned for home practice, using apps or paper-and-pencil tasks. Quantitative and qualitative outcomes were measured before and after each treatment block and included: the Revised Western Aphasia Battery (WAB-R) Aphasia Quotient (AQ) and subtest scores, content information units (CIUs) on the WAB-R picture description task, and qualitative content analysis of semi-structured interviews, gathered from both PwPPA and caregivers. RESULTS: = 0.09). Qualitative findings from PwPPA and caregivers were very positive, and underscored the sense of community, improved language, communication, and well-being, and access to multidisciplinary expertise and resources afforded by the program. DISCUSSION: Further investigation into the most appropriate assessment tools and intervention approaches for PPA is warranted and has the potential to make a significant positive impact on PwPPA and their families. Highlights: We combined quantitative and qualitative measures of efficacy in treating primary progressive aphasia.Language skills were maintained and communication improvement approached significance.Participants noted the benefits of peer support, education, and communication practice.
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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".