Using Normalization Process Theory to Evaluate an End-of-Life Pediatric Palliative Care Web-Based Training Program for Nurses: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Palliative care (PC) is a new concept in Iraq, and there is no training for health care specialists or the public. The lack of education and training programs is the most important barrier for PC. Intermediate training is needed for nurses who regularly manage patients with life-threatening diseases. The End-of-Life Nursing Education Consortium for pediatric palliative care (PPC) program is intended for nurses who are interested in providing care to children with life-limiting diseases or providing support in the event of an accident or unexpected death. OBJECTIVE: Our trial aims to evaluate the effect of a web-based training course, using the Normalization Process Theory. It focuses on how complex interventions become routinely embedded in practice and on training of a sample of academic nurses in the application of PPC in routine daily practice. It hypothesizes that nurses will be able to provide PC for the pediatric population after completing the training. METHODS: This is a multicenter, parallel, pragmatic trial in 5 health care settings spread across a single city in Babylon Province, Iraq. Participants will be recruited and stratified into 2 categories (critical care units and noncritical care units). In the experimental condition, 86 nurses will be trained in the application of PPC for 2 weeks through a web-based training course powered by the Relais Platform. The nurses will be invited to participate via email or instant messaging (WhatsApp, Telegram, or Viber). They will provide end-of-life care in addition to usual care to children and adolescents with life-limiting conditions. In the control condition, 86 nurses will continue usual care. The program's effectiveness will be assessed at the level of nurses only. We will compare baseline findings (before the intervention) with postintervention findings (after completing the training course). A further assessment will be performed 3 months after the course. As numerous unidentified factors can influence the effect of the training, we will perform a progressive evaluation to assess sample selection, application, and intervention value, as well as implementation difficulties. The nursing staff will not be blinded to the intervention, but will be blinded to the results. RESULTS: The study trial recruitment opened in July 2020. The first outcomes became available in December 2020. CONCLUSIONS: The trial attempts to clarify the delivery of PC at the end of life through the implementation of a web-based training course among Iraqi nurses in the pediatric field. The study strengths include the usual practice setting, staff training, readiness of staff to participate in the study, and random allocation to the intervention. However, participants may drop out after being transferred to another department during the study period. TRIAL REGISTRATION: ClinicalTrials.gov NCT04461561; https://clinicaltrials.gov/ct2/show/NCT04461561. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/23783.
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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 | 0.065 | 0.060 |
| Meta-epidemiology (narrow) | 0.009 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.054 | 0.009 |
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".