Evidence map›Paper›PMID 31424457›Full record

ArticleOncology nursing forum2019

Evaluating an Online Training Course to Develop and Sustain Cancer Navigation and Survivorship Programs.

Serena Phillips, Aubrey V K Villalobos, Mandi Pratt-Chapman

Abstract read
In one paragraph

Article in Oncology nursing forum, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Serena PhillipsGeorge Washington University Cancer Center.ORCID 0000-0002-7100-9710
Aubrey V K VillalobosGeorge Washington University Cancer Center.ORCID 0000-0002-3588-2678
Mandi Pratt-ChapmanGeorge Washington University Cancer Center.

Funding

ENHANCE NATL COMPREHENSIVE CANCER CONTROL U38DP004972 · DP · GEORGE WASHINGTON UNIVERSITY · PI CHAPMAN, MANDI PRATT · 2013 to 2014
$849k
NCCDPHP CDC HHS U38 DP004972
6 · The paper itself

Abstract

objectivesTo evaluate the impact of the Executive Training on Navigation and Survivorship (Executive Training) online training course, designed by the George Washington University Cancer Center, on nurses and other healthcare professionals. SAMPLE &

settingA volunteer sample of 499 healthcare professionals, including nurses and patient navigators, were recruited through multiple Internet-based channels. METHODS & VARIABLES: Participants completed questionnaires before and after each module and at the end of the training. Descriptive statistics were calculated, and paired t tests were used to assess pre- and post-test learning confidence gains for each module. Qualitative feedback from participants was also summarized.

resultsFrom pre- to post-test, each group demonstrated statistically significant improvements in confidence (p < 0.05) for all seven training modules. Confidence gains were statistically significant for 19 of 20 learning objectives (p < 0.05). Overall rating scores and qualitative feedback were positive. IMPLICATIONS FOR NURSING: The Executive Training course prepares healthcare professionals from diverse backgrounds to establish navigation and survivorship programs. In addition, the training content addresses gaps in nursing education on planning and budgeting that can improve success.

Indexed as

Cancer SurvivorsSurvivorshipAdultBudgetsConsumer BehaviorEducation, DistanceEducation, Nursing, ContinuingFemaleHealth PersonnelHumansMaleMiddle AgedOncology NursingPatient Education as TopicPatient NavigationProgram Evaluationcancer program planningnursing educationpatient navigationsurvivorship

Identifiers

PMID31424457
PMCPMC6937197

What OpenQuestion holds

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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.