Known, lost, and recovered: Efficacy of formal‐semantic therapy and spaced retrieval method in a case of semantic dementia
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. Aims: 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. Methods & 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. Outcomes & 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. Conclusions: 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. The first author was supported by PhD awards from the Quebec Rehabilitation Research Network, the Canadian Institutes of Health Research, the Interdisciplinary Training in Research on Health and Aging, and the Ordre des ergothérapeutes du Québec. The authors also wish to thank TBo for her enthusiastic participation in this study, as well as Lindsey Nickels, Karen Croot, Kim S. Graham and two anonymous reviewers for their invaluable comments on earlier drafts of this paper.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".