Known, lost, and recovered: Efficacy of formal‐semantic therapy and spaced retrieval method in a case of semantic dementia
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Bibliographic record
Abstract
Background: Few studies have addressed rehabilitation in semantic dementia. A potentially promising method is formal-semantic therapy, which consists of tasks in which the names of concepts and their semantic characteristics are presented. It could also be enhanced by spaced retrieval, a learning method improving retention through recalling information after increasing recall intervals. \nAims: This study explores the efficacy of both a formal-semantic therapy and the spaced retrieval method to restore lost concepts in TBo, a woman with semantic dementia. \nMethods & Procedures: The formal-semantic therapy consisted of giving TBo semantic feedback followed by a cueing technique to facilitate naming. Formal-semantic therapy with simple repetition was compared to formal-semantic therapy with spaced retrieval. TBo’s performance was measured throughout the study with picture naming and generation of verbal attributes. Two untrained lists were also measured for generalisation effects. \nOutcomes & Results: Results indicate that, after therapy, TBo could name 3/8 of the trained items, compared to no items on the untrained lists. She also showed an increase in performance for the evocation of specific semantic attributes of concepts, reaching 6/ 8 of correct responses. Moreover, she maintained her performance up to 5 weeks after the end of the study. Finally, when compared to simple repeated practice, spaced retrieval did not enhance learning and no generalisation was observed between trained and non-trained categories. \nConclusions: Along with recent results reported in the literature, TBo’s results confirm that people with semantic dementia can improve their naming performance with training but that this is limited. However, formal-semantic therapy seems very promising for retraining specific semantic attributes. Instead of focusing on naming, we suggest that therapies used in semantic dementia should aim at restoring specific and functionally relevant concepts to enable the individuals to be more autonomous in daily living.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it