The Progressive Aphasia Communication Toolkit (PACT): A Strengths-Based Approach to Multidomain Evaluation for Intervention
Bibliographic record
Abstract
INTRODUCTION: Assessments of communication for people living with primary progressive aphasia (PwPPA) remain limited. This work describes the development of a strengths-based, ecologically valid instrument - the Progressive Aphasia Communication Toolkit (PACT). METHODS: This work consisted of five experiments: two to develop (Experiments 1 and 2) and three to pilot (Experiments 3 to 5) a novel instrument for PPA. Ninety-five individuals worldwide contributed to this work: 80 researchers and clinicians, nine PwPPA, and six care partners. RESULTS: Experiments 1 and 2 yielded a four-scale instrument comprising quantitative and qualitative feedback. Experiments 3 to 5 resulted in structural refinement and digitization of the tool, revealed strong PwPPA and care partner acceptance of the PACT, and demonstrated high inter-rater agreement for general observability (91%) and perceived communication strength (85%). DISCUSSION: Current findings indicate that the PACT provides a holistic profile of communication strengths for PwPPA and can guide clinicians in developing functional therapeutic targets. Highlights: Instruments to evaluate communicative competence in PwPPA are centered on diagnosis and impairment.Documentation of communication strengths has direct implications for person-centered care and behavioral intervention.The PACT was developed in partnership with expert clinicians, researchers, PwPPA, and care partners.The PACT captures functional, real-world communication ability through a structured conversation and provides a shared framework to describe communicative competence across disciplines.Preliminary findings support that the PACT is ecologically valid, minimally burdensome, preferred by PwPPA and care partners, and clinically feasible for clinicians and researchers.Future work will serve to develop cultural-linguistic adaptations of the PACT and investigate the instrument's validity, reliability, and feasibility as an assessment procedure for PwPPA in a larger sample.
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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 | 0.070 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".