A naturalistic pilot study exploring the differences between fragile and resistant patients in ISTDP
Bibliographic record
Abstract
Intensive Short-Term Dynamic Psychotherapy (ISTDP) defines two spectra of patients based on the patients’ capacity to tolerate anxiety and complex emotions. Resistant patients have a better capacity to tolerate affective stimulus compared to fragile patients. There is, however, little empirical evidence that supports this categorization. This exploratory study seeks to identify reliable differences between 330 resistant and 88 fragile patients. To assess which category patients belong to, therapists conducted a specific psychodiagnostic assessment of patients when entering psychotherapy. Patients selfreported on the Brief Symptom Inventory (BSI) and the Inventory of Interpersonal Problems (IIP). Independent samples t-tests estimated differences between psychodiagnostic categories on self-reported measurements. Fragile patients scored significantly higher on five IIP subscales and all BSI subscales, barring “Paranoid Ideation”. As symptom distress might mask underlying pathological processes, we used a matching procedure to compare resistant and fragile patients with the same level of symptom distress, before repeating estimation of differences between the categories. Fragile patients scored significantly higher only on the BSI somatization subscale as well as on three items from the BSI somatization subscale, and one item from each of three other BSI subscales (i.e., “Phobic anxiety”, “Anxiety”, “Psychoticism”). The study used generic psychometric instruments. A specific psychometric instrument developed according to ISTDP theory would likely be more suited to capture group differences. The results provide support for the notion that fragile patients in general experience more psychological distress and specifically suffer from more somatization and additionally anxiety, phobic anxiety and psychoticism symptoms.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".