Exploring the Viability of Neurobic Exercises as an Intervention for Cognitive Impairment: A Literature Review
Bibliographic record
Abstract
Aim: To investigate the viability of implementing neurobic exercise interventions among adults diagnosed with Mild Cognitive Impairment (MCI). Materials and Methods: A comprehensive search of electronic databases PubMed, Google Scholar, Medline, was done for relevant studies, including randomised controlled trials, observational studies. Inclusion criteria were both male and female with cognitive impairment, implementation of neurobic programme and their follow ups. A total of four articles were synthesised out of 12, for the review based on the inclusion criteria. Results: All the four studies yielded positive results. Firstly, use of neurobic exercises exhibited a significant decrease in Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) relative change scores, indicating cognitive decline improvement, and significantly higher Catechol-O-methyltransferase (COMT) relative change scores, reflecting enhanced cognitive performance at 3rd and 6th weeks. Secondly, serum Brain-derived Neurotrophic Factor (BDNF) level in the neurobic group was slightly higher than pretest. There was change in Montreal Cognitive Assessment (MoCA) scale in post treatment experimental group as compared to conventional group. Participants expressed high satisfaction with the activities and perceived the intervention as helpful. Conclusion: The implementation of neurobic exercise interventions proved to be both feasible and was well-received by people with cognitive impairment. It also proved to improve quality of life. Neurobic exercises suggest future research avenues demonstrating a forward looking approach to address existing research gaps.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".