“Continuing the Connection” or “Carrying On”? A Qualitative Evidence Synthesis of How Widows Explain the Physical Health Outcomes After Spousal Loss
Bibliographic record
Abstract
The experience of losing a loved one can have profound effects on physical and psychological well-being, and previous research has reported an increased risk of mortality after spousal loss. This qualitative evidence synthesis reviewed 16 studies on the perspectives of widows who experienced adverse physical health outcomes after spousal loss. This review examines how widows described or explained the physical health outcomes after losing their spouse. We found that widows implicitly associated the physical health outcomes they experienced with losing their spouse. They described that losing their spouse exacerbated preexisting illness and led to new disease conditions such as heart failure, rheumatoid arthritis, infections, acute urinary retention, shingles, and impaired mobility. While these physical health outcomes limited widows’ ability to come to terms with their loss, widows in multiple studies prioritized the emotional and mental consequences associated with grief over any physical health outcomes they experienced. Furthermore, since the deceased spouse performed caregiving responsibilities, the surviving spouse experienced a shift from caregiving to self-management of their preexisting medical condition. In situations where widows were unable to meet their own health needs, they experienced an intensification of their own illness. Given these findings, we consider the relationship between widows’ meaning-making and physical and clinical outcomes. We discuss how meaning-making can contribute to severe emotional, mental, and physical health outcomes after a traumatic event such as spousal loss.
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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 | 0.046 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".