Effectiveness of Korean medicine treatments in improving cognitive function and prefrontal cortex activity in older individuals with mild cognitive impairment: retrospective observational study
Bibliographic record
Abstract
Background: Mild cognitive impairment (MCI) is a growing concern among older adults, with limited effective pharmacological treatments available. Despite the potential of herbal medicine and acupuncture in managing MCI, there is a lack of research on their long-term effects on cognitive function and brain activity in clinical practice settings. This study aimed to address this gap by exploring the effects of a community-based program integrating herbal medicine and acupuncture on cognitive function and neural responses in older individuals with MCI. Methods: Nineteen individuals were enrolled from a pool of 250 individuals registered in the 2021 Busan Dementia Prevention & Care Program. Participants with MCI received herbal medicine, acupuncture, and pharmacopuncture treatments over a 6-month period. The Montreal Cognitive Assessment (MoCA) was administered at baseline and after 3 and 6 months to evaluate cognitive function. Functional near-infrared spectroscopy (fNIRS) was used to measure prefrontal cortex activity during cognitive task performance, including verbal fluency, Stroop color and word, and digit span backward tests. Results: < 0.0001]. Additionally, the deoxygenated hemoglobin beta coefficient in the left frontopolar prefrontal cortex significantly decreased during the Stroop task after the intervention. Conclusion: The Dementia Prevention & Care Program, which integrates herbal medicine and acupuncture, may enhance cognitive function in individuals with MCI. Moreover, the observed changes in prefrontal cortex activity after completion of the program suggest a need for further investigation of the underlying mechanisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".