Evidence map›Paper›PMID 37456568›Full record

ArticleFrontiers in pediatrics2023

Evaluation of learning transfer after a perinatal/neonatal palliative care virtual training course.

Sinead Brady, Elvira Parravicini, Charlotte Wool

Abstract read
In one paragraph

Article in Frontiers in pediatrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sinead BradyDepartment of Pediatrics, Division of Neonatology, Columbia University Irving Medical Center, New York, NY, United States.
Elvira ParraviciniDepartment of Pediatrics, Division of Neonatology, Columbia University Irving Medical Center, New York, NY, United States.
Charlotte WoolCollege of Nursing and Health Professions, York College of Pennsylvania, York, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The success of a training can be determined by the degree of learning transfer. To address a gap in educational offerings during the pandemic, an interdisciplinary team developed and offered a 3-day virtual course, called Next Level Perinatal Palliative Care Training. Objective: This study aimed to evaluate the transfer of learning and practice from a virtual training course on perinatal/neonatal palliative care (PNPC) by a range of clinicians. Study design: A descriptive prospective survey design was used to collect data at two time points, immediately following the training course and 6 months later. Frequency and descriptive statistics were used to measure the implementation of PNPC quality indicators, self-reported competence, and clinical facilitators and barriers. A Results: At course completion, participants anticipated opportunities to implement PNPC strategies with means of 84-87, and at the 6-month mark, the reported implementation had means ranging from 71 to 77. At 6 months post training, participants reported feeling competent/highly competent in each variable with frequency scores of 89%-98%. The opportunity to learn key concepts of PNPC and refresh skill sets ranked as the top facilitators, while the top barriers were the lack of opportunity to use PNPC principles and the lack of funding. Conclusion: Learning transfer after a virtual training course of PNPC proved to be successful, with a high rate of self-reported actual implementation and competence at 6 months after the training.

Indexed as

learning transferneonatal comfort careperinatal palliative caretrainingvirtual training

Identifiers

PMID37456568
PMCPMC10347523

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.