Tangram Puzzles in Patients with Neurocognitive Disorders: A Pilot Study
Bibliographic record
Abstract
Objective: The tangram puzzle is a serious math puzzle game used to promote mathematic development in children, which improves visuospatial function and creativity. A game to improve cognitive functions is useful for patients with neurocognitive disorders. This pilot study aimed to determine whether this game could improve cognitive function in patients with neurocognitive disorders. Materials: This study recruited patients with mild Alzheimer’s disease or mild cognitive impairment who were followed longitudinally by the Department of Psychiatry, Juntendo University Hospital, or Juntendo Tokyo Koto Geriatric Medical Center (Tokyo, Japan). Methods: Participants were asked to solve Tangram puzzles 2–3 times weekly, spending 30–40 min/session at home with or without family members for approximately 90 (Study 1) or 180 (Study 2) days. Mini-Mental State Examination (MMSE) in Study 1 as well as a Japanese version of the Montreal Cognitive Assessment and Trail Making Test in Study 2 were performed on the initial and final days. Results: Study 1 comprised eight participants and Study 2 comprised nine participants. Statistically significant improvement was observed in MMSE total score (p = 0.016) and orientation segment (p = 0.026) in Study 1. No statistically significant difference was noted in MMSE total score, orientation segment, or MoCA-J (Japanese version of Montreal Cognitive Assessment) score between the initial and final days in Study 2 (p = 0.764, p = 0.583, and p = 0.401, respectively). Conclusions: Study 1 revealed that Tangram puzzles may ameliorate the progression of cognitive functions in patients with neurocognitive disorders within a short time (3 months); however, Study 2 did not show a consistent result. Thus, randomized controlled trials are warranted to draw a conclusion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".