Exploring the Relational Intervention of Storytelling: A Qualitative Study of the Patient Stories Project in a Single ICU
Bibliographic record
Abstract
OBJECTIVES: Our study objective was to explore nurses' experiences of how the Patient Stories Project, an intervention consisting of garnering and sharing ICU survivor stories with the ICU team, influenced their perceptions of the value of their work and their nurse-patient relationships. DESIGN: This was a qualitative descriptive case study that used thematic analysis. SETTING: This study was conducted in a single, 34-bed adult ICU in a Canadian tertiary care teaching hospital, serving a mixed medical and surgical patient population and employing over 200 nurses. SUBJECTS: Semistructured focus groups with 12 ICU nurses were conducted between June 2019 and July 2019. INTERVENTION: The Patient Stories Project is a systematic process for collecting and sharing former patients' stories. On a regular basis, former ICU patients return to the ICU to say, "thank you," share their experiences, and tell their stories to staff. MEASUREMENTS AND MAIN RESULTS: Storytelling through the Patient Stories Project gives meaning to nurses' work and provides avenues for nurses to think about their work more positively. Key themes were as follows: 1) perspective taking, 2) emphasizing the value in caring, 3) providing positive closure, 4) engendering team belonging, and 5) building a sense of hope. CONCLUSIONS: This study addresses the Critical Care Societies Collaboratives "call to action" to create a healthy work environment. Nurse focus group participants articulated how an initiative such as the Patient Stories Project may augment the relational aspects of work that are important to nurses, as well as their patients and families. Our study results have implications for the importance of using storytelling as a relational strategy to protect against depersonalization and cynicism, elements of burnout.
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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 | 0.027 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".