The Relationship Between Subjective Memory Complaints and Objective Memory Performance, Depression and Anxiety Levels in Patients Under 55 Years of Age
Bibliographic record
Abstract
OBJECTIVE: Psychiatric differential diagnosis is often ignored in young patients with memory complaints, even if no neurological or physical illnesses were evident. In this study, we aimed to determine the relationship between subjective memory complaints and objective memory impairment, depression and anxiety levels in young patients with memory complaints. METHOD: The study was carried out with 56 patients under the age of 55 who applied to the psychiatry, neurology and internal medicine outpatient clinics with memory complaints and 55 healthy volunteers. All participants completed the Subjective Memory Complaints Questionnaire (SMCQ), the Montreal Cognitive Assessment (MoCA), the Auditory Verbal Learning Test (AVLT), the Benton Visual Memory Test (BVMT), the Digit Span Test (DST), the Verbal Fluency Test (VFT), the Beck Depression Inventory (BDI) and the Beck Anxiety Inventory (BAI). RESULTS: Significant differences were observed in the scores of SMCQ, MoCA, AVLT, BVMT, DST, VFT, BDI and BAI in individuals with memory complaints compared to the controls, which could not be ascribed to any neurological or physical disease. Depression and anxiety levels were significantly higher than those of the control group. CONCLUSION: Differential diagnosis of memory complaints has to be made in young patients. Subjective memory complaints may be indicative of depression and anxiety disorders. It is necessary to evaluate the cognitive impairment that may develop over time in young patients with subjective memory disturbances via longitudinal studies.
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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) | 0.002 | 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".