The relationship between social acknowledgment and prolonged grief symptoms: a multiple mediation effect of beliefs about the goodness and controllability of grief-related emotions
Bibliographic record
Abstract
Background: Social acknowledgment is a protective factor for survivors of trauma. However, the role of social acknowledgment in association with prolonged grief symptoms has not yet been established.Objectives: The current study aims to explore the relationship between social acknowledgment and prolonged grief via two beliefs foundational to how people think about grief-related emotions (1) goodness (i.e. whether emotions are desirable, useful, or unwanted and harmful), and (2) controllability (i.e. whether emotions are regulated according to our will or involuntary, arising of their own accord). These effects were explored in two different cultural samples of bereaved people.Methods: One hundred and fifty-four German-speaking and two hundred and sixty-two Chinese bereaved people who lost their loved ones completed questionnaires assessing social acknowledgment, beliefs about the goodness and controllability of grief-related emotions, and prolonged grief symptoms.Results: Correlation analyses showed that social acknowledgment was positively linked with stronger beliefs about the goodness and controllability of grief-related emotions and negatively related to prolonged grief symptoms. Beliefs about the goodness and controllability of grief-related emotions correlated negatively with prolonged grief symptoms. Multiple mediation analyses suggested that beliefs about the controllability and goodness of grief-related emotions mediated the link between social acknowledgment and prolonged grief symptoms. Cultural groups did not moderate the above model.Conclusion: Social acknowledgment may be related to bereavement adjustment consequences via the roles of beliefs about the goodness and controllability of grief-related emotions. These effects seem to be consistent cross-culturally.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.006 | 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".