International Practices of Speech‐Language Pathologists Working with Bilingual Speakers with Primary Progressive Aphasia
Bibliographic record
Abstract
Abstract Background Although primary progressive aphasia (PPA) is considered a rarer form of dementia, individuals living with PPA are increasingly identified by healthcare professionals. Research investigating speech‐language assessment and intervention in PPA has been conducted primarily in monolingual speakers and little is known about clinical decision‐making of speech‐language pathologists (SLPs) working with bilinguals with PPA. Methods A comprehensive survey containing questions regarding clinician confidence, prioritization, and ratings of basic competency for Volkmer, Cartwright, Ruggero et al.’s (2023) best practice principles was constructed with questions that also queried practices pertaining to working with bilingual populations. Data was collected anonymously, via the Qualtrics survey platform and the survey was disseminated via social media and through social networks of study team members. Results A total of 185 participants responded with representation from 27 countries. In total, bilingual participants spoke a total of 39 different languages. The average number of languages spoken by respondents was 1.86 (SD = 1.08). Twenty‐three percent of respondents reported that they provided clinical services bilingually and 28% identified as bicultural. Respondents indicated that coursework in their training to become SLPs related to bilingual neurogenic communication disorders was covered for less than two hours (39%), less than five hours (33%), or more than five hours (28%). The majority of respondents indicated that they sometimes or typically worked with an interpreter or translator for conducting bilingual assessments (43%) or performed them independently (18%). When asked which language respondents typically assess participants in, 5% indicated the maternal language, 39% indicated the dominant/most functional language(s), and 54% indicated the language(s) the clinician felt comfortable speaking. Conclusion This study reports, for the first time, the practices of speech‐language pathologists working with bilingual speakers with PPA. Results indicate that SLPs are likely to receive some exposure to bilingual adult neurogenic communication disorders in their training. SLPs are more likely to assess bilingual individuals with PPA in the languages clinicians speak, or in the participant’s most functional/dominant language(s). Additional international forums are needed to extend core principles and philosophies of SLP practices, particularly when individuals living with PPA speak more than one language.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".