The effectiveness of Mindfulness-Based Stress Reduction on Intolerance of Uncertainty and Anxiety Sensitivity among Individuals with Generalized Anxiety Disorder
Bibliographic record
Abstract
The Generalized Anxiety Disorder (GAD) is one of the most chronic and detrimental disorders and it is considered a common disorder in childhood and adolescence. Furthermore, this disorder is associated with many problems in the health domain. As such, this study attempted to gauge the impact of mindfulness-based stress reduction on intolerance of uncertainty and anxiety sensitivity among students with generalized anxiety disorder. Therefore, it was attempted to run a quasi-experimental research, including a pre-test, a post-test and a control group, among high schools of Robat Karim in Tehran province. Having used the purposive sampling method, 30 students diagnosed with generalized anxiety disorder, intolerance of uncertainty and high anxiety sensitivity were selected. Then, they were randomly assigned to experimental (15 students) and control groups (15 students). Consequently, the mindfulness program was introduced to the experimental group in 8 sessions and the control group received no treatment. It should be noted that groups were assessed before and after treatment with generalized anxiety scale, anxiety sensitivity and intolerance of uncertainty. The results of analysis of covariance showed that mindfulness-based stress reduction programs significantly reduced the symptoms of generalized anxiety disorder, anxiety sensitivity and intolerance of uncertainty. Since mindfulness reduces the levels of two key components of generalized anxiety disorder, namely intolerance of uncertainty and anxiety sensitivity, it seems appropriate to make use of this program in the treatment of generalized anxiety disorder.
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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".