The functional communication scale for patients with neurodegenerative disease: development and validation of a French test evaluating residual communication skills
Bibliographic record
Abstract
Verbal and nonverbal communication impairments are often observed in the context of neurodegenerative diseases. Identifying the most appropriate communication strategies for each patient, by a better understanding of his communicational difficulties, would help to maintain his autonomy and to improve his quality of life. OBJECTIVE: To propose a rapid and ecological tool specifically adapted for people with cognitive disorders in advanced stages of the diseases. METHODS: Two major steps were necessary, the development of the tool itself (A) and the evaluation of some of its psychometric properties (B). The first step (A) allowed the development of a tool aimed at the observation of communication skills during a situation of natural interaction and the analysis of communication according to various activities (production, recognition and comprehension of oral language acts, written and gestural, as well as figures, in different degrees of complexity). The second step (B) consisted to measure the validity of the content and the criterion of the test, as well as its fidelity between judges. The final version of the tool is composed of two grids, an examiner's guide and a patient's test sheet. The use of the tool has been standardized. RESULTS: At the end of the validation process, psychometric properties demonstrated good content validity and good criterion validity for the scale. Fidelity was subsequently measured and also judged to be good. After that, a pre-test with patients with neurodegenerative diseases has been carried out. CONCLUSION: This tool should address a significant clinical need to enable clinicians to rapidly describe communication skills in a patient with neurodegenerative disease and to recommend communication strategies for formal and informal caregivers.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".