Investigation into Grief Experiences of the Bereaved During the Covid-19 Pandemic
Bibliographic record
Abstract
The objective of the current study was to investigate the grief experiences of people affected by COVID-19. The study adopted a qualitative design of descriptive phenomenology. Fifteen adults who had lost a family member during the COVID-19 pandemic were selected as the sample through the purposive sampling method until theoretical saturation was achieved. Data was collected using semi-structured interviews and the Colaizzi analysis method. Six main themes (i.e., unexpressed grief, psychosomatic reactions, negative emotions, family problems, and social and occupational problems) were extracted. Data analysis showed that complex disenfranchised grief is the pervasive consequence of the COVID-19 experience. According to the findings, participants experienced disenfranchised grief during the loss of their loved ones due to the COVID-19 disease, which was a complex, painful experience accompanied by negative emotions and family, work, and social tensions. This grief is accompanied by more severe and prolonged symptoms, making it difficult for the bereaved to return to normal life. In unexpressed grieving, there are intense feelings of grief, pain, separation, despair, emptiness, low self-esteem, bitterness, or longing for the presence of the deceased. This grief originated from the conditions of quarantine and physical distance on the one hand, which required the control of the outbreak of the COVID-19 disease, and on the other hand, the cultural-religious context of the Iranian people.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".