Validity of the TGI-SR+ in Francophone populations: Insights from Quebec and Belgium
Bibliographic record
Abstract
The loss of a significant person can lead to a broad spectrum of responses. While most individuals gradually recover within a year, a minority develop Prolonged Grief Disorder (PGD). The Traumatic Grief Inventory Self-Report Plus (TGI-SR+) was recently developed to ensure that the original scale (TGI-SR) still accurately assesses PGD in line with the latest diagnostic standards of the DSM-5-TR and ICD-11. This study aimed to validate the TGI-SR+ within two French-speaking cohorts: 276 French-Canadian and 469 Belgian participants. Data were collected through an online survey in 2022. Confirmatory factor analysis resulted in a 4-factor model for the TGI-SR+ total scale, but high inter-item correlations favored a 1-factor solution. A 1-factor model was found for the DSM-5-TR and ICD-11 PGD scores. Convergent validity with mental health disorder, depression, and post-traumatic growth, and known-group validity were confirmed. The findings endorse the TGI-SR+ as a valid tool for detecting potential PGD.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".