Short‐Term Psychodynamic Psychotherapy with Mentalization‐Based Techniques in Major Depressive Disorder patients: Relationship among alexithymia, reflective functioning, and outcome variables – A Pilot study
Bibliographic record
Abstract
OBJECTIVES: In depressed patients, recent advances have highlighted impairment in mentalizing: identifying and interpreting one's own or other's mental states. Short-Term Psychodynamic Psychotherapy (STPP) has proven to be effective in reducing symptoms and improving relational/functional abilities in these subjects. Therefore, the first aim of our study was to evaluate effectiveness of STPP with Mentalization-Based Techniques (STMBP) on their clinical outcomes and the second, to investigate Reflective Functioning and alexithymia concerning treatment outcomes in depressed subjects. DESIGN: A baseline evaluation of reflective functioning, alexithymia and depression was conducted before an STMBP treatment. Patients were re-tested successively after 40 weeks (T1) and in a follow-up after 1 year at the end of the treatment (T2). METHODS: A total of 24 patients principally diagnosed with Major Depressive Disorder (MDD) underwent a STMBP conducted by two expert therapists. Global Assessment Functioning (GAF), Toronto Alexithymia Scale-20 (TAS-20) and Hamilton Depression Rating Scale (HAM-D) data were collected at the baseline (T0) by two clinical therapists, along with RF scores rated by two trained raters. HAM-D, TAS-20 and GAF follow-ups were conducted at the end of the treatment after 40 weeks (T1) and after 1-year follow-up (T2). RESULTS: Results highlighted an improvement of both HAM-D and TAS-20 scores in our sample. Moreover, a negative correlation between RF and TAS-20 was found. Both HAM-D and RF at T0 influenced depressive outcomes at the end of the treatment. CONCLUSIONS: Results confirmed the effectiveness of STMBP in MDD, suggesting also an inverse association between RF and alexithymia. PRACTITIONER POINTS: Our study demonstrates how STMBP could be effective in MDD even after 40 sessions, maintaining its effect in a 1-year follow-up. STMBP improves subjective capability of reflecting on the mental states of oneself and others. Our intervention allows patients to orientate thoughts from inside to outside, reducing negative beliefs also in absence of a pharmacological therapy (during the follow-up).
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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 | 0.001 |
| 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".