International Prolonged Grief Disorder Scale Addendum for Refugees and Displaced people (IPGDS-ARD): A study of Arabic-speaking bereaved refugees
Bibliographic record
Abstract
Background: Prolonged grief disorder (PGD) is a new and significant addition to the ICD-11 WHO disease classification system and the DSM 5-TR. As a new disorder, it stands to improve diagnostic precision, enhance communication among health professionals and patients, provide better access to care and lead to effective treatments and intervention. However, it remains to be determined if the new diagnostic criteria for PGD are applicable to different cultural groups. Method: Here we sought to adapt the International Prolonged Grief Disorder Scale for refugees and displaced people. We conducted two focus groups with clinicians and health care workers and six cognitive interviews with bereaved Arabic-speaking refugees. Results: This formative research resulted in an addendum (comprised of three new scales) to the IPGDS aimed to aid with treatment planning: the 42 item Addendum for Refugees and Displaced people (IPGDS-ARD). Here we present the steps for scale augmentation based on cultural considerations, a detailed description of clinical utility, feasibility and content validity established at each step, and an analysis of the percent of change in content at each step. Conclusion: We conclude that the presented method of scale augmentation is a feasible and efficient approach that led to a culturally relevant, clinically useful addendum to an existing PGD questionnaire.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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 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".