Initial Reliability of the Diagnostic Interview for Narcissism Adapted for Preadolescents: Parent Version (P-DIN).
Bibliographic record
Abstract
INTRODUCTION: the Diagnostic Interview for Narcissism, an instrument developed by Gunderson and associates to assess pathological narcissistic traits in adults, has been adapted for use with parents of preadolescents as a semi-structured interview. A sixth section has been added to assess the parental narcissistic investment of the child. METHODS: the sample consists of 21 parents of children (aged 8-13 years) at risk for narcissistic personality disorder. An interviewer-observer design, with independent interview evaluation, was used to assess inter-rater reliabilities. Both raters were blind to diagnostic information. RESULTS: Very good inter-rater reliabilities (ranging from .85 to 1.00) were obtained for all 35 statements of this Parent version of the DIN (P-DIN). Good internal consistencies a=0.82, a=0.88, a=0.69, respectively) were obtained for the first three Sections of the P-DIN, which include all the DSM-IV criteria for Narcissistic Personality Disorder. Section V, Social/Moral Adaptation (a=0.54), and Section VI, Parental Narcissistic Investment of the Child (a=0.62), had weaker internal consistencies. Section IV, Mood States, had the lowest internal consistency (a=0.50). Finally, a high reliability coefficient was obtained for the total scale (a=0.92, 32 statements for Sections I to V). CONCLUSION: present results of this pilot study justify further research into the P-DIN psychometric properties.
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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".