Feasibility and Acceptability of Remotely Accessed Compensatory Cognitive Training for Japanese People With Schizophrenia: Pilot Study
Bibliographic record
Abstract
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.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".