Role of Alexithymia, Anxiety, and Depression in Predicting Self-Efficacy in Academic Students
Why this work is in the frame
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Bibliographic record
Abstract
Objective . Little research is available on the predictive factors of self-efficacy in college students. The aim of the present study is to examine the role of alexithymia, anxiety, and depression in predicting self-efficacy in academic students. Design . In a cross-sectional study, a total of 133 students at Babol University of Medical Sciences (Medicine, Dentistry, and Paramedicine) participated in the study between 2014 and 2015. All participants completed the Toronto Alexithymia Scale (TAS-20), College Academic Self-Efficacy Scale (CASES), and 14 items on anxiety and depression derived from the 28 items of the General Health Questionnaire (28-GHQ). Results . Pearson correlation coefficients revealed negative significant relationships between alexithymia and the three subscales with student self-efficacy. There was no significant correlation between anxiety/depression symptoms and student self-efficacy. A backward multiple regression analysis revealed that alexithymia was a negative significant predictor of self-efficacy in academic students (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mi>B</mml:mi><mml:mo>=</mml:mo><mml:mo>-</mml:mo><mml:mn fontstyle="italic">0.512</mml:mn></mml:math>, <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mi>P</mml:mi><mml:mo><</mml:mo><mml:mn fontstyle="italic">0</mml:mn><mml:mo>.</mml:mo><mml:mn fontstyle="italic">001</mml:mn></mml:math>). The prevalence of alexithymia was 21.8% in students. Multiple backward logistic analysis regression revealed that number of passed semesters, gender, mother’s education, father’s education, and doctoral level did not accurately predict alexithymia in college students. Conclusion . As alexithymia is prevalent in college students and affects self-efficacy and academic functioning, we suggest it should be routinely evaluated by mental physicians at universities.
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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 | 0.001 | 0.000 |
| 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 it