Reliability of the ICD-10 International Personality Disorder Examination (Urdu Translation): A preliminary study
Bibliographic record
Abstract
OBJECTIVE: To test the reliability and applicability of Urdu translation of the International personality disorder examination (IPDE) in a psychiatric outpatient population in Pakistan. METHODS: This study was conducted at the outpatient department of Fatima Memorial Hospital Lahore from April 2012 to March 2013. Patients considered to have a personality disorder by a psychiatrist were initially screened by the IPDE screening questionnaire. Those who scored positive on screening were evaluated in a detailed interview using IPDE. Two interviewers conducted the interviews simultaneously, to ensure inter-rater reliability. For translation, permission was taken from World Health Organization. Linguistic equivalence was assessed through back- translation and conceptual equivalence through opinion of mental health experts. The final Urdu draft was obtained after incorporating modifications suggested by experts following a feasibility study. The analysis was carried out using SPSS v.20. RESULTS: Out of 30 enrolled patients, 25(83.3%) were females. The mean age of the sample was 28.5+6.08 years. Majority of patients had more than one personality disorder. Most prevalent personality disorder was emotionally unstable borderline type with a phi correlation of 0.831, followed by emotionally unstable impulsive type and anankastic personality disorder with phi correlations of 0.930 and 0.867, respectively, for definite cases. Correlation coefficient for dimensional scores between the two raters was 0.392 for paranoid personality disorder, 0.842 for anankastic and around 0.9 for the rest of the personality disorders, each. CONCLUSION: Urdu translation of IPDE is a reliable tool to screen and diagnose personality disorders in population of Pakistan.
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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 | 0.013 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".