Effectiveness of Nursing Intervention Program Based on Emotional Awareness and Emotion Regulation on the Social Functioning of Patients with schizophrenia
Bibliographic record
Abstract
Background: Patients with schizophrenia have poorer social and vocational functioning, emotional dysregulation, cognitive and executive function deficits, which place a heavy strain on the person and the community. Aim: explore the effectiveness of the nursing intervention program based on emotional awareness and emotion regulation on the social functioning of patients with schizophrenia. Design: A quasi-experimental design, one group (pre and post-test) was utilized. Subjects: A purposive sample of 60 patients with schizophrenia. Study setting: Inpatient psychiatric wards at El-Azazi Hospital for Mental Health and Addiction Management in Abo Hamad City, Sharqia Governorate, Egypt. Tools: Demographic and clinical data questionnaire of schizophrenic patients, Toronto Alexithymia scale, emotion regulation questionnaire, and social function questionnaire. Results: The nursing intervention program based on emotional awareness and regulation had a statistically significant effect (P = 0.0001) on social functioning among studied patients with schizophrenia. Conclusion: The nursing intervention program based on emotional awareness and regulation has a great effect in enhancing social functioning, raising emotional awareness and regulation as well as lowering alexithymia levels in studied schizophrenic patients. Recommendation: Emotional awareness and regulation intervention nursing program should be given to all schizophrenic patients to improve their social functioning, enhance emotional awareness, regulation and reduce their levels of alexithymia.
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 | 0.001 |
| 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) | 0.002 | 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".