Breaking Through the Glass Ceiling—Having <i>That</i> Conversation: A Constructivist Grounded Theory Study Exploring the Experiences of Nephrology Nurses’ Practice in Kidney Supportive Care in Canada
Bibliographic record
Abstract
Background Dialysis as treatment for kidney failure can result in significant physical and psychosocial symptom burden. Kidney supportive care (KSC), encompassing advance care planning (ACP), is an approach to care involving early identification and treatment of symptoms that improves the quality of life of people receiving dialysis. However, ACP is underused and often initiated late in the illness. The delay or lack of engagement in KSC by nephrology nurses until near the end of life may result in people receiving care that is discordant with their values, wishes, and preferences. Purpose The purpose of our study was to construct a substantive theory about the process of engagement in KSC by nurses in Canadian dialysis settings. Methods Using Charmaz's constructivist grounded theory method, 23 registered nurses working in hemodialysis and peritoneal dialysis were recruited to participate in two intensive interviews. Concurrent data collection and analysis were undertaken, with constant comparative analysis of codes until the attainment of theoretical saturation, as well as memo-writing and researcher reflexivity, to aid the emergence of categories and concepts. Findings In the substantive theory “Breaking Through the Glass Ceiling of Engagement—Having That Conversation,” three stages of engagement (Transactional, Intentional, Actional) are identified that describe nurses’ practice patterns of engagement in communication about goals of care with patients. This engagement is modulated by a boundary of professionalism and familiarity with patients, amid multi-dimensional contextual barriers. Conclusion Nephrology nurses have a vital role in discussions about goals of care and require training to enhance their communication skills.
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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 | 0.025 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.035 | 0.028 |
| Scholarly communication | 0.013 | 0.005 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.002 | 0.006 |
| 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".