The storied mind: A meta-narrative review exploring the capacity of stories to foster humanism in health care
Bibliographic record
Abstract
Objective: Healthcare organizations are increasingly engaging the voice of patients and families through storytelling initiatives in hopes that this will yield compassionate and humanistic outcomes. To date, very little research is available that directly guides and justifies storytelling initiatives as a mechanism for promoting humanistic culture shifts in healthcare. This review aimed to uncover diverse research and evidence on how storytelling can be utilized to promote humanistic shifts in healthcare organizations.Methods: A meta-narrative review and analysis was undertaken including qualitative, quantitative, theoretical, and conceptual papers. Searches were restricted to English Language journals, and no time frame restrictions were made. A literature assessment form was created to guide the review using a consistent taxonomy to appraise each paper. Analysis was done in two-stages: firstly, identifying emergent themes within each research discipline; secondly, comparing and contrasting themes from the different disciplines.Results: A total of 115 papers were identified for review resulting from the literature review protocol. Eighty-three papers were included in the final review: 48 papers from Healthcare/Medicine combined, 28 from Business, 14 from Education, 5 from Organizational Development and 19 from Humanities (inclusive of Psychology and Communications). There were three key findings: 1) Storytelling promotes sense-making while also perpetuating bias; 2) Stories are uniquely primed to elicit empathy and compassion; 3) Story listening and how stories are interacted with by the listener are key considerations for organizations aiming to shift culture.Conclusions: This review solidifies storytelling as a mechanism suited to furthering humanistic practices in healthcare while contributing new knowledge in support of developing policies, strategies and research initiatives that account for how stories are understood and the processes that encourage reflection and interaction by listeners.
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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 | 0.016 | 0.073 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".