Comparative analysis of irrational beliefs and alexithymia to predict anxiety, neuroticism, and depression
Bibliographic record
Abstract
Anxiety, neuroticism and depression are highly studied human disturbances in the field of psychology. There are many theories as to the cause of these distresses. Followers of Albert Ellis' Rational Emotive Behavior Therapy have hypothesized that the maintaining of irrational beliefs causes emotional distress. Others have theorized that a condition known as alexithymia is responsible for emotional distresses. Literally "no words for feelings," alexithymia is a condition where individuals are unable to describe their feelings, they are unable to distinguish between their feelings and bodily sensations, and they have a tendency to overemphasize the concrete details of external events. This project was conducted to compare the two theories and to determine whether they worked together to best predict the emotional distresses, or if one theory was superior to the other. Several self-report questionnaires were administered to college students. These questionnaires included the Survey of Personal Beliefs, the MalouffSchutte Belief Scale, the Toronto Alexithymia Scale-20 (TAS - 20), the Beck Depression Inventory, the neuroticism subscale of the Eysenck Personality Questionnaire-Revised, and the Hospital Anxiety and Depression Scale. Multiple regression analysis demonstrated that an TAS - 20 subscale, Difficulty Identifying Feelings, was an especially important predictor of all emotional dysfunction measures. The irrational belief constructs were not as important in explaining variance in anxiety, depression, and neuroticism. These data had a number of implications about attempts to relate irrational beliefs to emotional disturbance, about the scales used to measure irrational beliefs, and about the use of alexithymia to predict emotional disturbance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".