Principles and philosophies for speech and language therapists working with people with primary progressive aphasia: an international expert consensus
Bibliographic record
Abstract
PURPOSE: Primary progressive aphasia (PPA) is a language-led dementia associated with Alzheimer's pathology and fronto-temporal lobar degeneration. Multiple tailored speech and language interventions have been developed for people with PPA. Speech and language therapists/speech-language pathologists (SLT/Ps) report lacking confidence in identifying the most pertinent interventions options relevant to their clients living with PPA during their illness trajectory. MATERIALS AND METHODS: The aim of this study was to establish a consensus amongst 15 clinical-academic SLT/Ps on best practice in selection and delivery of speech and language therapy interventions for people with PPA. An online nominal group technique (NGT) and consequent focus group session were held. NGT rankings were aggregated and focus groups video recorded, transcribed, and reflexive thematic analysis undertaken. RESULTS: The results of the NGT identified 17 items. Two main themes and seven further subthemes were identified in the focus groups. The main themes comprised (1) philosophy of person-centredness and (2) complexity. The seven subthemes were knowing people deeply, preventing disasters, practical issues, professional development, connectedness, barriers and limitations, and peer support and mentoring towards a shared understanding. CONCLUSIONS: This study describes the philosophy of expert practice and outlines a set of best practice principles when working with people with PPA.Implications for rehabilitationPrimary progressive aphasia (PPA) describes a group of language led dementias which deteriorate inexorably over time.Providing speech and language therapy for people with PPA is complex and must be person centred and bespoke.This study describes the philosophy of expert practice and outlines a set of best practice principles for speech and language therapists/pathologists working with people with people with PPA.
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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 | 0.217 | 0.138 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.012 | 0.019 |
| Research integrity | 0.012 | 0.020 |
| Insufficient payload (model declined to judge) | 0.002 | 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".