The role of the mental health nurse in pediatric hematology-oncology – Part 1: Developing an innovative practice
Bibliographic record
Abstract
Introduction: Pediatric hematological and oncological illnesses present many coping challenges. Mental health issues can arise during and after treatment, in both patients and their families. The current model of care does not always seem to meet the needs identified by some young patients. In Quebec, nurses are allowed to assess and care for patients experiencing physical and mental health difficulties (Ordre des infirmières et infirmiers du Québec, 2016). Therefore, a mental health nurse clinician (MHNC) with experience in pediatric hematology/oncology could provide care that is complementary to that offered by psychologists, social workers, and other psychosocial professionals in the pediatric hematology/oncology unit in order to meet any needs that remain unmet. The MHNC project has three stages: (1) role development, (2) role implementation, and (3) role assessment one year after implementation. In this first article, we explain how the MHNC role was developed. Methodology: We used the participatory, evidence-based, patient-focused process for advanced practice nursing (APN) role development, implementation, and evaluation (PEPPA Framework; Bryant-Lukosius & Dicenso, 2004) to develop this model. The first five steps in the PEPPA Framework were applied in the creation of the MHNC role to (1) select the target population, (2) identify the stakeholders to be involved, (3) ascertain needs, (4) determine and prioritize problems and set goals, and (5) define a new model of care. Results: After multiple meetings involving numerous health professionals and managers, the MHNC role was developed with a versatile, transdisciplinary perspective to address better the needs of young cancer patients (especially those in their teens) and their families. The role was developed around four main areas of practice: (1) interventions offered to patient-family, (2) interventions offered to health professionals, (3) psychiatric consultation-liaison, and (4) education and research. Conclusion: The next steps are to use a strategic plan to implement the role and then to evaluate the impact of the role one year after implementation.
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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 | 0.017 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".