An investigation of the effectiveness of written emotional disclosure on defense mechanisms of alexithymic individuals
Bibliographic record
Abstract
The aim of the present study was to investigate the effects of written emotional disclosure on the defense mechanisms of alexithymic people. A qausi-experimental pretest-posttest control group design was used to determine the effectiveness of written emotional disclosure. For this purpose, 130 male and female master's and PhD students at University of Tehran were selected by convenience sampling method. A total of 35 participants having high scortes on Toronto Alexithymia Scale (TAS-20) were screened and randomly assigned to two experimental and control groups. The Defensive Style Questionnaire (DSQ) was performed to evaluate the participant's defense mechanisms. Then, a two-week program of written emotional disclosure (6 sessions, 20 minutes for each), was used to measure changes in post-test. Research data were analysed using non-parametric tests (Wilcoxon and Mann Whitney-U) with SPSS version 23. The results showed that written emotional disclosure reduced the use of immature defense mechanisms and increased the mature defenses; with no significant change on neurotic defenses. It is concluded that written emotional discloure can be used as a complementary and effective therapy in psychotherapy.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".