The Relationship of Psychological and Somatic Well-Being in Patients
Bibliographic record
Abstract
Background. Understanding of emotional aspects of painful experiences can significantly expand the therapeutic tools for both doctors and psychologists. Objective. The focus is placed on the study of the relationship between psychological and somatic well-being of patients with pain syndrome. Study Participants. Sample included 119 people: 57 men (average age 47.9 years) and 62 women (average age 46.5 years) from the number of outpatients of the treatment and prevention institution “City Health Center #12” (Minsk). Methods. The study used: the Subjective Well-being Scale, the Numeric Pain Rating Scale (NPRS), the McGill Pain Questionnaire (MPQ), the Differential Emotion Scale, the Toronto Alexithymia Scale, and the Giessen Subjective Complaints List, GBB. Results. The analysis of the correlations of emotional state and somatic complaints has revealed similarities and specificity of subjective experiences of patients in different conditions. The correlation analysis showed a certain relationship between emotional state and well-being, which is closely related to subjective well-being. Conclusion. Subjective well-being of patients is related to psychoemotional state, health and somatic complaints, as well as, to some extent, to the level of alexithymia. Patients' well-being is related to their emotional state and negative emotions. Practical application of the results. Understanding the psychological state of the patient can be useful for developing a personalized approach to treatment and successful rehabilitation through intrapersonal resources.
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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 | 0.001 | 0.003 |
| 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".