Correlation analysis of alexithymia level and social support of patients with depression
Bibliographic record
Abstract
Objective To find out the level of alexithymia and the relationship between alexithymia and social support of patients with depression. Methods 86 patients with alexithymia were investigated by Toronto Alexithymia Scale(TAS) and Social Support Rating Scale(SSRS). Results The scores of depression patients(75.22 ± 13.93 ) in TAS were significant higher than the controls group ( 60. 19 ± 9.27 ) ( P ＜ 0.01 ).Scores in factor 1-ability of describing feelings and factor 2-ability of identifyings of depression patients were highest, devating the median. Except subjective social support wash't related to all factors of TAS, ability of describing feelings was negatively correlated with the total scores and all factors of SSRS( P ＜ 0. 01 ) , and fancy was positively correlated with the total scores and all factors of SSRS( P ＜ 0.01 ). Conclusion Level of alexithymia was significant correlated with social support for patients with depression, and doctors can improve the situation of social support of depression patients by solving the difficulties in expressing feelings. Key words: Depression; Alexithymia; Social support
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".