The experiences of male sudden cardiac arrest survivors and their partners: a gender analysis
Bibliographic record
Abstract
AIM: To explore how masculinities shape the experiences of men and their partners after survival from out-of-hospital cardiac arrest. BACKGROUND: Survivors of out-of-hospital cardiac arrest report depression, dependence on others for daily functioning, decreased participation in society and significant decreases in quality of life. There is growing evidence that masculine gender identities play a central role in the recovery experiences of men and their families following other major cardiac events. However, to date, there has been no examination of how masculinities shape men's experiences of recovery following out-of-hospital cardiac arrest. DESIGN: Interview study guided by an interpretive description approach. Data were subjected to thematic analysis. METHOD: A purposive sample of seven male sudden cardiac arrest survivors and 6 female partners was recruited in 2010 from a secondary care centre in British Columbia, Canada. RESULTS: Three themes were prominent in the experiences of the participants: (1) Support and self-reliance; (2) Dealing with emotional (in) vulnerability; and (3) No longer a 'He-man'. CONCLUSION: Masculinities played a role in men's experiences of recovery and adaptation following out-of-hospital cardiac arrest. Hegemonic masculinity partly explained men's experiences, notably their reluctance to seek professional support and reactions to changes in lifestyle. However, the study also suggests that the popular stereotype of men being 'strong and silent' in the face of ill-health may only be a part of a more complex story. Nurses would benefit from taking into consideration the potential influence of male gender identities on men's recovery postcardiac arrest.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".