INVESTIGATION AND ANALYSIS OF THE STRESS COPING CHARACTERISTICS OF PATIENTS SUFFERING PERSISTENT SOMATOFORM PAIN DISORDER
Bibliographic record
Abstract
Objective: To study the stress coping characteristics of the patients who suffered persistent somatoform pain disorders(PSPD),and explore the pathological psychological mechanism of PSPD.Methods: Totally 53 patients were selected in the experimental group according to the diagnosis criteria inCCMD-3,and 53 normal people were selected as the control group by stratifed sampling.The two groups were measured using Defensive Style Questionnaire(DSQ),Perceived Social Support Scale(PSSS),and Toronto Alexithymia Scale(TAS).Results: The frequency of using unmatured defensive mechanism and the alexithymia of the experimental group were significantly higher than that of the control group,and the frequency of using matured defensive mechanism and the ability of perceiving social support of the experimental group were signifcantly lower than that of the control group.Conclusion: Patients suffering PSPD are incapable to relieve their mood in time and can't cope the problem effectively.They are used to using unmatured defensive mechanisms such as somatization,complaints,fantasy and so on.They cannot perceive and utilize the social support system fully.Thus the inner confict gets worse,and the patients are apt to go into the vicious circle of bad mood-worse pain-invalid coping,and the somatization symptoms will persist for a long time.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".