Micro and macro‐linguistic analysis of narrative discourse in Moroccan patients with Alzheimer’s Disease
Bibliographic record
Abstract
Abstract Background The production of narrative discourse or connected speech implies dynamic and complex functions at different levels of neuro‐cognitive, micro (parts of speech) and macro‐linguistic processing (cohesion and coherence). Such functions are classically impaired in Alzheimer’s disease (AD). Several studies have described these impairments in European languages; however, no study has characterized them in terms of neuro‐psycholinguistic patterns in Arabic. Method We studied the speech sample of six patients with moderate Alzheimer’s disease from the Alzheimer’s Center in Rabat. They described orally the picture of cookies theft subtest (BDAE). They meet the clinical criteria for AD (McKhann, 2011). The average age is 69 years (SD: 5.9; 61‐77) and of education is 13.6 years (SD: 2.3; 9‐15), duration of the disease is 5 years (SD 2.09; 3‐8). The neuropsychological assessment has been carried out with MoCA (Montréal Cognitive Assessment), MIS (Memory Impairment screen), Fluency tasks and Clock drawing test. Regarding discourse analysis and psycholinguistic variables, we used the method which has been described by Croisile (1996) and Boschi et al (2017). Result The neurolinguistic assessment showed an impairment of macro‐linguistic variables. The effectiveness of speech was clearly one of the most impaired variables as well as the syntactic complexity in the majority of patients. Cohesion has been lower than local and global coherence. These macro‐linguistic performances revealed a pragmatic dysfunction as part of the neuropsycho‐linguistic profile of our patients depending on their disease duration. However, at a micro‐linguistic level, functional words and verbs were the most produced in oral description compared to nouns, adjectives and adverbs. Such results might evoke the hypothesis of an impairment of explicit linguistic knowledge which involved different intra and inter‐linguistic systems in AD. Conclusion The wide range of cognitive‐linguistic impairments which has been highlighted during the cookie theft picture description, showed the importance of assessing micro and macro‐linguistic impairments in narrative speech in Moroccan patients with AD. Such linguistic task is an added‐value to formal assessments and follow‐up of cognitive decline in AD.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".