Emotion recognition deficit and cognition in schizophrenia
Bibliographic record
Abstract
Psychomotor symptoms of depression are understudied despite having a severe impact on patient outcomes. This review aims to summarize the evidence on motor features of depression assessed with instrumental procedures, and examine age-related differences. We included studies investigating posture, balance and gait ascertained with instrumental measurements among individuals with depressive symptoms or disorders. Studies on subjects with specific physical illnesses were excluded. Methodological quality was assessed with the Newcastle - Ottawa Scale (NOS) and PRISMA guidelines were followed. 33 studies (13 case-control, five cross-sectional, nine longitudinal and six intervention) with overall low-medium quality were included. Different instruments were employed to assess posture (e.g. digital cameras), balance (balance, stepping platform) or gait (e.g. Six-Minute-Walking Test, instrumented walkways). Results suggest that depression in adults is associated with significant impairments of posture, balance and gait. Motor abnormalities among depressed older adults may depend on the interplay of physical diseases, cognitive impairment and mood. Very few intervention studies measured motor symptoms as outcome. Available evidence suggests, however, that antidepressant drugs and physical exercise may be beneficial for motor abnormalities. Despite the lack of high-quality studies, instrumental assessments confirm the presence and importance of motor abnormalities in depression, with potential age-related differences in their pathophysiology.
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 | 0.001 | 0.001 |
| 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".