Effectiveness of Mindfulness-Based Education on Alexithymia, Test Anxiety and Adjustment to College in Students
Bibliographic record
Abstract
Objective: Student periods are always accompanied by various challenges, including increased alexithymia and test anxiety, and decreased adjustment to college. Consequently, the aim of the present study was to determine the effectiveness of mindfulness-based education on alexithymia, test anxiety, and adjustment to college in students. Methods and Materials: This research was a quasi-experimental with a pre-test and post-test design with a control group. The population of this study was girl students of Payam Noor University of South Tehran Branch in the 2023-2024 academic years. The sample of this study was 30 students who were selected by purposive sampling method and randomly with the help of a lottery assigned into two equal groups. The experimental group received 8 sessions of 120 minute with the mindfulness-based education protocol of Baer et al. (2006), and the control group did not receive any education. The data of the present research were collected with Toronto alexithymia scale (Bagby et al., 1994), test anxiety questionnaire (Sarason, 1957), and adjustment to college questionnaire (Baker and Siryk, 1984) and were analyzed by multivariate analysis of covariance in SPSS-23 software. Findings: The findings of this study showed that there were significant differences between the groups in terms of all three variables of alexithymia, test anxiety, and adjustment to college. In other words, mindfulness-based education decreasing alexithymia and test anxiety, and increasing adjustment to college in students (P<0.001). Conclusion: According to the results of the present research, university counselors and psychologists can use mindfulness-based education to decrease alexithymia and test anxiety, and increase adjustment to college in students.
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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".