Network analysis of emotional symptoms and cognitive function changes in primary insomnia
Bibliographic record
Abstract
Background Primary insomnia is a common and complex disorder characterized by a range of symptoms and consequences of varying severity. Long-term sleep disturbances can lead to anxiety, depression and cognitive dysfunctions. This study aimed to investigate the relationship between emotional changes and cognitive dysfunction in patients with primary insomnia and to explore the factors influencing the disorder. Methods The study participants included 40 patients with primary insomnia diagnosed by the International Classification of Sleep Disorders-3 and 48 healthy controls from the Seventh People’s Hospital of Wenzhou. The Pittsburgh Sleep Quality Index, Montreal Cognitive Assessment, Hamilton Anxiety Scale and Hamilton Depression Scale were used to assess clinical symptoms. T-tests, chi-square tests, Pearson correlation and network analysis were used to examine the mutual relationship between emotional symptoms and cognitive function in participants with primary insomnia. Results Both immediate and delayed memory of the primary insomnia group was significantly worse than that of the healthy controls group, whereas there was no significant difference in long-term delayed recognition between the two groups. The naming and language scores of the primary insomnia group were significantly lower than those of the healthy controls group. The total Pittsburgh Sleep Quality Index score was positively correlated with anxiety and depression symptoms. Conclusion This study emphasized the correlation between emotional symptoms and cognitive dysfunction in patients with primary insomnia. Simultaneously, their levels of anxiety and depression were both positively correlated with the degree of cognitive dysfunction.
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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 | 0.002 | 0.001 |
| 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".