Relearning lost vocabulary in nonfluent progressive aphasia with MossTalk Words®
Notice bibliographique
Résumé
Background: The literature on aphasia has been growing rapidly, with reports of different therapeutic approaches for a post‐stroke anomia. While individuals with post‐stroke anomia frequently recover to some extent, the other end of the aphasia recovery continuum is occupied by those who experience relentless language dissolution as a result of progressive disorders such as primary progressive aphasia. One of the most recent additions to the field of aphasia rehabilitation is therapy whereby either part of or the entire therapy is administered via computer‐based programmes. There have been few treatment studies investigating the rehabilitation of language abilities in people with primary progressive aphasia (PPA). Aims: The objectives of this investigation were to examine the ability of PPA individuals to relearn lost words and to determine the extent of benefits derived from MossTalk Words®, a computer‐based treatment for anomia. Methods and Procedures: Using a multiple baseline across behaviours design, we explored treatment‐specific effects, maintenance, and generalisation of improvements derived from this therapy programme. Two participants with nonfluent PPA were treated, each on three lists of words for which low and stable baselines were first established. Sessions occurred two to three times a week. Treatment involved the presentation of a picture on the computer screen, with the participants being required to name it. Success in treatment was measured by probing list naming every second session. Once a participant attained 80% accuracy over two consecutive probes, or participated in 12 sessions (whichever occurred first), treatment of a list was terminated and the next list was started. Each participant was tested on all items immediately after therapy, and again 1 month later. Outcomes and Results: Both participants improved their naming skills with the MossTalk Words®. P1 required only four sessions to reach the proposed criterion of 80% (up to 100%) correct on each list. The effects of treatment were maintained immediately and, to a lesser degree, 4 weeks later. P2 required all 12 sessions for each of the three lists. Results were variable immediately after testing, but seemingly maintained 4 weeks later. Conclusions: The results demonstrate that both participants with primary progressive aphasia benefited (although to a different extent) from a computer‐based treatment for anomia. These results are encouraging and suggest that such a treatment may be a viable therapy approach for patients who suffer from PPA in the absence of a generalised cognitive impairment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».