Engaging Hope: The Experiences of Male Spouses of Women With Breast Cancer
Bibliographic record
Abstract
PURPOSE/OBJECTIVES: To explore the hope experience of male spouses of women with breast cancer. DESIGN: Thorne's qualitative interpretive descriptive approach was used. SETTING: Homes of participants in two western Canadian provinces. SAMPLE: 11 male spouses of women with breast cancer. METHODS: 24 open-ended tape-recorded telephone interviews were completed. Data were transcribed and then analyzed used Thorne's approach. MAIN RESEARCH VARIABLES: Hope. FINDINGS: The participants described their hope as tangible and important to them. Hope was influenced by their partners' hope and courage and gave participants the courage to support their partners. The overarching theme was engaging hope. The participants described their hope as always being there, but with the diagnoses of their partners' breast cancer, they needed to engage their hope. Other themes were finding balance, discovering what works, and focusing on the positives. CONCLUSIONS: The participants emphasized the importance and the positive outcomes associated with hope, such as being able to continue caring for their partner. IMPLICATIONS FOR NURSING: The importance of hope in the participants' lives underscores the need to find ways to foster hope in this population. The findings also suggest that the hope experience of men may differ from the experience of women; therefore, strategies to foster hope in this population should be tailored to the male experience.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".