Impact of personal experiences on career path, clinical practice, and professional endurance among hospice nurses caring for dying children
Bibliographic record
Abstract
Context and objective: The multifaceted demands of pediatric hospice work often discourage nurses from pursuing the career route and may overwhelm nurses who choose to do the work, risking burnout. The relationship between nurses’ personal experiences and their decisions to pursue this difficult work, as well as their ability to sustain it, has not been studied previously. The study objective was to explore the influences of pediatric hospice nurses’ personal experiences on their career trajectories, their clinical approaches to caring for dying children, and their endurance in doing so.Methods: From the 551 community hospice nurses in Tennessee, Mississppi, and Arkansas who completed a survey as part of a previous study, purposive sampling was used to select a cohort of 41 nurses. Semi-structured interviews were conducted, recorded, and transcribed. Content analysis of interview transcripts was performed.Results: Nurses described three types of personal experiences that shaped their professional practice: 1) personal illness, 2) personal loss, and 3) parenthood. We identified two major themes characterizing how personal experiences influence their work: 1) leading them into the hospice field (“career trajectory”) and 2) strengthening their clinical practice (“clinical approach”) through four mechanisms: a) identifying tools for patient care, b) connecting with pediatric patients, c) connecting with bereaved families, and d) finding balance between competing priorities.Conclusions: Personal experiences of illness, loss, and parenthood influence hospice nurses’ career trajectories and how they care for dying children. Normalizing these influences and integrating reflection on them into hospice training may empower nurses to pursue pediatric hospice nursing, find meaning in the work, and build professional endurance.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".