The Effectiveness of Emotion Focused Therapy on Alexithymia and Internalized Self-Criticism in Neurotic Perfectionist Girls
Bibliographic record
Abstract
Aim and Background: The aim of the current study was to investigate the effectiveness of Emotion Focused Therapy on Alexithymia and Internalized Self-Criticism in Neurotic Perfectionist girls. Methods and Materials: The statistical population consisted of all Neurotic Perfectionist girls in Ahvaz. The research sample consisted of 5 girls that were selected according to the results of the neurotic perfectionism questionnaires (NPQ), using purposeful sampling method. In this research, a single-case experimental design, type of concurrent multiple baseline designs was used. Instruments were Toronto ʼs Alexithymia Scale (1994), Thompson and Zuroff ʼs The Levels of Self-Criticism Scale (LSCS) (2004). The data was collected in three phases of baseline, during intervention, and three month follow-up. Findings: The findings indicate that the subjects in the treatment phase experienced improvement in Alexithymia (10.58) and Internalized Self-Criticism (21.32), and in the follow-up in regards to Alexithymia (19.41) and Internalized Self-Criticism (51.76). The change index was indicative of meaningful changes (z=1.96 α=0.05). Conclusions: Therefore, the research findings illustrated that Emotion Focused Therapy reduces Alexithymia and Internalized Self-Criticism in Neurotic Perfectionist girls.
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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) | 0.002 | 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".