Screening of Chronic Alcoholics for Cognitive Impairment Using Montreal Cognitive Assessment—Occupational Therapy Perspective
Bibliographic record
Abstract
Rationale: Chronic alcoholics suffer from cognitive impairment, thereby affecting their ADL and work performance. Objectives: The objective was to screen chronic alcoholics for cognitive impairment and assessing affectations in various components of MoCA. Early screening to help them from further deterioration in ADL and work. Materials and Methodology: In this case control study, 50 chronic alcoholics, males, age group 30–50 years, abstaining for more than two months, referred to outpatient De-addiction Occupational Therapy department of K. E. M. Hospital, Mumbai were screened using MoCA (Hindi) and compared with their age matched control group. Results: All patients showed mild cognitive impairment (MCI) on MoCA, irrespective of pattern and frequency of drinking. Their average mean score in MoCA test and control group was 21.02 and 26.03, respectively. The domains more affected were language, abstraction and memory, thus affecting their performance in ADL and work. Results were analyzed using unpaired ‘ t’-test and were statistically significant at the level of p < 0.05 and 95 per cent confidence level. Conclusion: Screening of chronic alcoholics using MoCA showed MCI with varying degree of affectations in the sub-components of the test.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".