A Schema Therapy–Based eHealth Program for Patients with Borderline Personality Disorder (priovi): Naturalistic Single-Arm Observational Study
Bibliographic record
Abstract
BACKGROUND: Electronic health (eHealth) programs have been found to be effective in treating many psychological conditions. However, regarding borderline personality disorder (BPD), only a few eHealth programs have been tested, involving small interventions based on the dialectical behavior therapy treatment approach. We investigated priovi, a program based on the schema therapy (ST) approach. priovi is considerably more comprehensive than prior programs, offering broad psychoeducation content and many therapeutic exercises. OBJECTIVE: We tested the acceptability and feasibility of priovi in 14 patients with BPD as an add-on to individual face-to-face ST. METHODS: Patients received weekly individual ST and used priovi over a period of 12 months. We assessed BPD symptom severity using self-reported and interview-based measures. Qualitative interviews were conducted with both patients and therapists to assess their experiences with priovi. RESULTS: BPD symptoms improved significantly (Cohen d=1.0). Overall, qualitative data showed that priovi was positively received by both patients and therapists. Some exercises provoked mild anxiety; however, no serious threat to safety was detected. CONCLUSIONS: priovi is a potentially helpful and safe tool that could support individual ST. It needs to be further tested in a randomized controlled study. TRIAL REGISTRATION: German Clinical Trials Register DRKS00011538; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00011538 (Archived by WebCite at http://www.webcitation.org/74jb0AgV8).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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 teacher head, 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".