Deciphering the mechanisms of phonological therapy in jargon aphasia
Bibliographic record
Abstract
BACKGROUND: Severe word production difficulties remain one of the most challenging clinical symptoms to treat in individuals with jargon aphasia. Clinically, it is important to determine why some individuals with jargon aphasia improve following therapy when others do not. We report a therapy study with AM, an individual with severe neologistic jargon aphasia, and provide a subsequent comparison with previous cases, with the purpose of informing both our theoretical and clinical understanding of jargon aphasia. AIMS: To investigate AM's locus of word production deficit and determine the effectiveness of phonological component analysis (PCA) therapy, a phonological cueing therapy, in the re-learning and generalization of naming responses for words. In addition, AM's performance in therapy, linguistic profile and ability to engage with therapy/cues were compared in a retrospective analysis with the background linguistic and therapy data of two other individuals with jargon aphasia (P9 and FF), who responded differentially to PCA. This was undertake to explore possible prognostic indicators of phonological therapy for jargon aphasia. METHODS & PROCEDURES: A battery of linguistic and neuropsychological tests was used to identify AM's word production deficit. A single-subject multiple probe design across behaviours was employed to evaluate the effects of PCA therapy on the re-learning and generalization of naming responses. In the retrospective analysis of AM, P9 and FF, we compared differences and similarities in performance on various linguistic tasks, the ability to engage in therapy (i.e., ability to generate and use the cues), as well as to retain and maintain cues. OUTCOMES & RESULTS: AM's locus of deficit was identified in the mapping between semantics and phonology. PCA was found to be effective in improving naming in two of the three treated word lists during the treatment phase; however, these gains were not maintained. Generalization to untreated picture names was not observed. Findings from the retrospective analysis illustrated that oral reading skills, the ability to segment phonological information from words and active engagement with provided cues are likely prerequisites for obtaining robust and long-term gains. CONCLUSIONS & IMPLICATIONS: We demonstrated that phonological therapy could be beneficial for the remediation of naming abilities at least in the re-learning phase; however, maintenance and generalization of these gains were limited. This research helps to elucidate the considerations and evaluations necessary for the appropriateness of phonological therapy and candidacy of individuals with jargon aphasia for this treatment approach.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".