Feasibility and Acceptability of Remotely Accessed Compensatory Cognitive Training for Japanese People With Schizophrenia: Pilot Study
Notice bibliographique
Résumé
Background: Compensatory cognitive training (CCT) is an evidence-based treatment for improving cognitive function in patients with schizophrenia. However, the need for patients to commute to treatment sites hinders its widespread use. Using a remote device to conduct CCT could improve its accessibility, making it easier for participants to adjust their schedules and reducing their burden. Objective: The objective of this study was to (1) investigate the creation and participant acceptability of CCT using a remote compensatory cognitive training (r-CCT) device, (2) determine the feasibility of implementing the developed intervention, and (3) collect preliminary data for future studies of the effectiveness of r-CCT in Japan. Methods: To reduce participant movement during training, CCT was conducted remotely in real time, using borrowed iPads. The training was conducted in a group format through video conferencing once a week for 2 h, for a total of 12 sessions. In total, 4 patients with schizophrenia who underwent r-CCT were recruited to determine participation or dropout rates across 12 training sessions. In addition, their diagnostic assessment (the Scale of Positive Symptoms and the Scale of Negative Symptoms), cognitive function (eg, the Japanese version of the Trail Making Test Part A [TMT-A] and Trail Making Test Part B [TMT-B], digit span, and digit symbol), social functioning (Social Functioning Scale Japanese version [SFS-J]), and quality of life (Japanese Schizophrenia Quality of Life Scale [JSQLS]) were assessed before, immediately after, and 3 months after implementation. Results: The average participation rate of the 3 participants (a male in his 30s was excluded) was high at 92%. Immediately after the r-CCT, positive trends were observed in cognitive function-excluding prospective memory. For example, the TMT-A scores improved for all 3 participants: Participant A (from 58 s to 56 s), Participant B (from 52 s to 49 s), and Participant C (from 65 s to 49 s). The Japanese Verbal Learning Test (JVLT) immediate scores also increased: Participant A (from 16 to 19), Participant B (from 13 to 14), and Participant C (from 14 to 21). Functional outcomes, assessed using the SFS-J, showed limited improvement immediately postintervention but tended to return to or fall below preintervention levels at the 3-month follow-up. Quality of life (QOL) scores, measured using the JSQLS, remained relatively stable or improved immediately following the r-CCT and at the 3-month follow-up. Conclusions: Despite this study's small number of participants and lack of randomization, it suggests that the accessibility and implementation potential of r-CCT may be high. The ability to participate in training from any location could be expected to increase participation rates or reduce dropout rates. In the future, the authors will develop the implementation method further and increase the sample size to demonstrate the training's effectiveness.
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 | 0,004 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».