Associative memory and memory complaints in people with first episode of depression: use of the Face-Name Associative Memory Exam (FNAME)
Bibliographic record
Abstract
The aim of the study is to assesses associative memory and memory complaints in daily life in people with a First Episode of Depression (FED). This is a preliminary pilot study with observational design. Thirty participants were recruited and assessed: fifteen patients (FED) and 15 healthy (HCtrl) participants. The recruitment was from Mental Health Units between 2021 to 2022. DSM-5 diagnostic criteria and the International Neuropsychiatric Interview (MINI) were used to diagnose depression. The cognitive tests used were face-Name Associative Memory Exam (FNAME), daily life memory questionnaire (MFE-30), and Montreal Cognitive Assessment Test (MoCA). FED patients showed mean score compared to the HCtrl significantly higher on the MFE-30, but there were no significant differences in the FNAME. Furthermore, the results no significant correlations were observed between subjective (MFE-30) and objective (FNAME) memory performance. We observed a dissociation between FED patients’ perception of memory difficulties and their objectively measured memory.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".