The working alliance with people experiencing suicidal ideation: A qualitative study of nurses’ perspectives
Bibliographic record
Abstract
AIMS: This study aimed to enhance the conceptual understanding of the working alliance in the context of nursing care for people experiencing suicidal ideation. DESIGN: A qualitative study based on grounded theory was conducted. METHODS: Two authors conducted individual semi-structured interviews from September 2017-January 2019. Twenty-eight nurses in 13 wards of four psychiatric hospitals participated. The Qualitative Analysis Guide of Leuven was used to support constant data comparisons and the cyclic processes of data collection and data analysis. FINDINGS: The nurses' perspectives revealed that the working alliance can be understood as an interpersonal and collaborative relational process. This relational process highlighted the core variable 'seeking connectedness and attunement with the person at risk of suicide'. The core variable underpinned three clusters: investing in the foundations of the working alliance, nourishing the clinical dimension of the working alliance and realizing an impact with the working alliance. CONCLUSION: This study highlights the importance for nurses to assess, evaluate and respond to persons' suicidal ideation in harmony with a commitment to connect with them and attune to their perspective. IMPACT: The relational process uncovered through this study offers valuable insights to support advanced nursing practice, where nurses meaningfully integrate relational elements of care with their contributions to suicide prevention and treatment.
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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 | 0.021 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.011 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".