Bibliographic record
Abstract
Research from several domains indicates that genetic factors, childhood environment, and later interpersonal experiences are important sources of how patients relate to their therapists (transference). Transference work, a core specific technique in psychodynamic psychotherapy, focuses on exploring the patient-therapist relationship, with the idea that this may lead to improvement of the patients' relationships outside therapy. Many psychotherapy researchers hold the position that specific techniques do not contribute much to the outcome of psychotherapy. However, more than 30 studies have reported significant associations between transference work and outcome. These findings indicate that transference work interventions are indeed active ingredients (for better or worse). Naturalistic studies suggest that a high frequency of transference interventions may have negative effects. Randomized clinical trials indicate that transference-based treatments and alternative treatments work equally well with regard to symptom improvement. However, transference-based treatments appear to be much more effective with regard to interpersonal relations and other measures of personality functioning. The average between-groups effect size for the experimental studies listed in this article was large. Contrary to common clinical wisdom, transference interventions seem to be most important for (mainly female) patients with difficult interpersonal relationships and more severe personality pathology. Gain of insight may be a specific mechanism of change in dynamic psychotherapy, but only one treatment component study has linked transference work directly to gains in insight and subsequent improvement in interpersonal functioning. Research that examines how transference phenomena may be responded to in nondynamic therapies is scarce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".