Experiences of partners of professional nurses venting traumatic information
Bibliographic record
Abstract
BACKGROUND: Professional nurses employed in trauma units encounter numerous stressors in their practice environment. They use different strategies to cope with this stress, including venting traumatic information to their partners and other family members. AIMS: To describe how partners of professional nurses cope with traumatic information being vented to them. METHODS: A qualitative research method with an interpretive descriptive inquiry design was used to explore, interpret and describe the coping experiences of the nurses' partners. Purposive sampling was used to select a total of 14 partners, but only ten participated in semi-structured interviews. Tesch's eight steps of open coding were used for data analysis. RESULTS: Four main themes were identified indicating adaptive and maladaptive coping skills, namely partners' experiences of traumatic information vented to them; partners' coping activities; reciprocal communication and relationship support between partners and nurses; and resilience of partners to deal with the nursing profession. CONCLUSION: Partners employed different ways to cope with traumatic information. It was essential for partners and nurses to be supported by nurses' practice environments and to develop resilience to fulfil reciprocal supportive roles in their relationships.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| 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".