Toward a better assessment of coping with bereavement: Applicability to diverse experiences and conceptual structure of the <i>coping with bereavement questionnaire</i>
Bibliographic record
Abstract
Coping strategies are key adjustable elements mediating the relationship between risk factors and grief outcomes. It is essential to assess coping correctly. Scales based on the Dual Process Model of Coping with Bereavement have tended to confuse coping strategies and symptoms. The Coping with Bereavement Questionnaire was created to address such shortcomings. This article uses two datasets from Belgian studies to assess the applicability of the items as well as the factor structure of the scale. Logistic regressions revealed nine items as less applicable to a more diverse bereaved sample than people who lost their intimate partner, leading to their exclusion. Factor analyses revealed and confirmed a three-factor structure of coping strategies describing the bereaved’s efforts to (1) accept the death and look to the future, (2) avoid thoughts and feelings, and (3) maintain the bond with the deceased. Theoretical issues related to the DPM are discussed.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| 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 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".