Psychotherapeutic case formulation: Plan analysis for narcissistic personality disorder
Bibliographic record
Abstract
BACKGROUND: One of the relevant case formulation methods for personality difficulties is plan analysis. The present study aimed at delivering a prototypical plan analysis for clients presenting with a diagnosis of narcissistic personality disorder (NPD). The sample consisted of 14 participants diagnosed with an NPD. Based on audio clinical material, we developed 14 individual plan analyses that we then merged into a single prototypical plan analysis. For explorative purposes, we ran an ordinary least squares regression model to predict the narcissistic symptoms severity (NAR) measured on a scale of 1-7 of the 14 clients by the presence (respectively absence) of certain plans in their individual plan analysis. The synthesis revealed that clients with pathological narcissism share common basic motives. Results of the regression model reveal that the presence of the plan 'be strong' reduces the NAR scale by 1.52 points (p = 0.011). DISCUSSION: In the treatment of psychological disorders, precise case formulations allow therapists for making clinically appropriate decision, personalizing the intervention and gaining insight into the client's subjective experience. In the prototypical plan structure we developed for NPD, clients strive to strengthen their self-esteem and avoid loss of control, criticism and confrontation as well as to get support, understanding and solidarity. When beginning psychotherapy with a client presenting with NPD, the therapist can use these plans as valuable information to help writing tailored, and therefore more efficient, case formulations for their patients presenting with an NPD.
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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 | 0.001 |
| 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) | 0.002 | 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 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".