The Effect of Cognitive-Behavioral Therapy (CBT) on Anxiety Reduction in Critical Care Unit (CCU) Patients During Hospitalization
Bibliographic record
Abstract
Patients admitted to Critical Care Units (CCU) face multiple stressors, and these stressors cause anxiety in patients. Anxiety increases heart function in heart patients. High levels of anxiety in cardiac patients increase in association with hospital complications. The purpose of this study was to determine the effect of Cognitive-Behavioral Therapy (CBT) on reducing the anxiety of patients in CCU during their hospitalization. The study design was quasi-experimental (pre-test and post-test). This study was performed on patients in CCU of Shahid Mostafa Khomeini hospital in 2019; for this purpose, 30 patients in CCU were randomly divided into intervention (n=15) and control (n=15) groups. Before the intervention, the demographic variables questionnaire and DASS-21 anxiety questionnaire were completed by both groups. Then, the intervention group received CBT for eight sessions according to the average number of hospital days (eight days) by the therapist (researcher). The control group did not receive any intervention. After the intervention, the demographic variables questionnaire and DASS-21 questionnaire were completed by the intervention and control groups again. Data analysis was done by SPSS-21 software and descriptive tests, ANOVA, and independent and pairwise t-test. There was no significant difference between the two groups in the mean score of anxiety before treatment, but the mean score of anxiety significantly decreased after treatment in the intervention group (9.63±2.773) compared to the control group (13.23±2.115; p<0.001). CBT can reduce the level of anxiety in patients admitted to CCU, and this method can be used as a simple and low-cost complementary non-pharmacological practice in these patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.010 |
| 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) | 0.000 | 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 teacher head, 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".