Mini-SEA: Validity and Normative Data for the French-Quebec Population Aged 50 Years and Above
Bibliographic record
Abstract
OBJECTIVE: The mini Social cognition & Emotional Assessment (mini-SEA) is a social cognition battery which assesses theory of mind and emotion recognition. Currently, no psychometrically validated measure of social cognition with adapted normative data exists for the middle-aged and elderly French-Quebec population. This project aims to determine the known-group discriminant validity of a cultural and linguistic adaptation of the mini-SEA between cognitively healthy people, those with mild cognitive impairment (MCI) or living with Alzheimer's Disease (AD). This study also aims to examine the stability of mini-SEA's performance over a 3-4-month time period, as well as to produce normative data for French-Quebec people aged 50 years. Normative data are derived for the full and an abbreviated version of the Faux Pas subtest. METHOD: The sample included 211 French-speaking participants from Quebec (Canada) aged 50 to 89 years. Mini-SEA's performance between a sub-sample of cognitively healthy people (n = 20), those with MCI (n = 20) or with AD (n = 20) was compared. A sub-sample of cognitively healthy people (n = 30) performed the task twice to estimate test-retest reliability. Socio-demographic variables' effects on scores were examined to produce normative data in the form of regression equations or percentile ranks. RESULTS: Significant differences emerged between cognitively healthy people and those with MCI or AD. Moreover, scores were relatively stable over a period of 3 to 4 months. Finally, for the normative data, age, gender, and education were associated with performance on the mini-SEA or its subtests. CONCLUSIONS: This study improves and standardizes social cognition's assessment among French-Quebec individuals, which will help characterize their cognitive profile.
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 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 | 0.001 | 0.001 |
| 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".