Home-based cognitive remediation and transcranial direct current stimulation to enhance cognition in older adults with major depressive disorder or mild cognitive impairment: An open label study
Bibliographic record
Abstract
OBJECTIVES: Interventions to prevent dementia among older adults with high-risk conditions such as Mild Cognitive Impairment (MCI) or Major Depressive Disorder (MDD) are highly needed. This study assessed the feasibility, adherence, safety, and clinical effects of home-based Cognitive Remediation (CR) with transcranial Direct Current Stimulation (tDCS) delivered by study partners in these populations. DESIGN: Open-label study. PARTICIPANTS: Patients with a diagnosis of MCI, MDD in remission (rMDD), or both, were enrolled as a couple with their study partners. INTERVENTION: Home-based CR+tDCS, five days/week for eight weeks and then CR online with one week of CR+tDCS boosters every six months for up to two years. METHODS: Nineteen couples were enrolled. Cognitive testing was administered at baseline, after the 8-week phase, and then yearly from baseline for up to two years. Measures of feasibility, adherence and safety and clinical and cognitive outcomes were collected. RESULTS: Study partners experienced increased perceived competence in delivering the intervention [F (1, 164) = 18.87, p < 0.001]. Eighty percent of the 8-week sessions were completed by 84 % of the patients; 56 % of the patients completed the 2-year intervention. Improvement in global cognition was observed in patients [F (3, 15.1) = 4.04, p = 0.027], and in quality of life in study partners [F (3, 30.6) = 6.18, p = 0.002]. CONCLUSIONS: This study demonstrates that home-based CR+tDCS is feasible and safe in patients with MCI or rMDD, and could improve cognition in patients and quality of life in study partners. Randomized controlled trials are needed to confirm these findings.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".