Ecologically Valid Tablet-based Cognitive Training: A Case Report of a Bilateral Thalamic Stroke Patient
Notice bibliographique
Résumé
Bilateral thalamic infarcts are associated with severe and long-term impairments, leading to a poor functional prognosis. As a result, patients can exhibit a wide range of cognitive and behavioral deficits, including difficulties with attention, learning and memory, language, emotional processing, time perception, and loss of self-activation, manifested through apathy and indifference. Information and Communication Technology-based Cognitive Training (ICT-based CT) with more ecologically valid content may be valuable in intervening with these patients. Beyond enhancing motivation and engagement, such technologies can be equipped with several features, such as cue systems and errorless learning techniques, that assist patients with severe declarative memory deficits by minimizing errors and engaging alternative non-declarative memory routes to facilitate encoding and retrieval of new information. Herein, we present a case report of LT, a 41-yearold female patient, with 10 years of formal education, diagnosed with bilateral thalamic stroke who enrolled in a one-month tablet-based CT intervention with the prototype version of the NeuroAIreh@b platform. Prior to the intervention, LT was submitted to a neuropsychological assessment to characterize her cognitive abilities, emotional state (i.e., presence and severity of depressive symptomatology), quality of life, and functional abilities. The tablet-based CT intervention encompassed eight 45-minute sessions and involved performing four types of Reh@Apps incorporating CT tasks (i.e., cancelation, categorization, action sequencing and calculation) within daily life scenarios (i.e., the kitchen and the supermarket). After the CT intervention, LT was reassessed and demonstrated reliable increases in the Montreal Cognitive Assessment, Digit Symbol-Coding, and the Phonemic Verbal Fluency test, suggesting improvements in global cognitive functioning, processing speed and phonemic verbal fluency, respectively. Moreover, quantitative improvements in both immediate and delayed recall trials of the Free and Cued Selective Reminding Test indicated a slight improvement in verbal episodic memory. Concerning the emotional status domain, LT also reported less depressive symptomatology. Throughout the rehabilitation program, LT became progressively more autonomous when performing tasks, requiring fewer cues and verbal instructions from the therapist, which enhanced her engagement, emotional stability, and self-efficacy. A three-month follow-up reassessment revealed that her cognitive and emotional status reverted to baseline values. This case report highlights the potential of a personalized tablet-based CT, not only to improve learning and compensate for memory deficits but also to foster self-efficacy and well-being in patients with severe acquired brain injuries and poor functional prognosis. Future studies should focus on optimizing patient outcomes by exploring extended ICT-based CT within a comprehensive and multicomponent rehabilitation program delivered in community settings. These programs can be implemented life-long and can incorporate both compensatory strategies training that capitalizes on implicit learning and memory, and psychosocial interventions for caregivers (e.g., emotional support, psychoeducation) to further increase the patient’s adherence and generalization of gains to everyday life.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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) | 0,001 | 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 tête enseignante, 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 ».