Evidence map›Paper›PMID 34794116›Full record

ArticleJMIR public health and surveillance2021

Learning From a Massive Open Online COVID-19 Vaccination Training Experience: Survey Study.

Shoshanna Goldin, So Yeon Joyce Kong, Anna Tokar, Heini Utunen, Ngouille Ndiaye, Jhilmil Bahl, Ranil Appuhamy, Ann Moen

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.4field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 16 citations in OpenAlex.

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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

8 authors at 2 institutions in 2 countries.

Shoshanna GoldinInfluenza Preparedness and Response, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0001-8116-7010
So Yeon Joyce KongStrategic Research, Laerdal Medical, Stavanger, Norway.ORCID 0000-0001-5106-7342
Anna TokarLearning and Capacity Development Unit, WHO Health Emergencies Program, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0003-4992-6819
Heini UtunenLearning and Capacity Development Unit, WHO Health Emergencies Program, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0002-0509-5067
Ngouille NdiayeLearning and Capacity Development Unit, WHO Health Emergencies Program, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0002-6051-9483
Jhilmil BahlDepartment of Immunization, Vaccines and Biologicals, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0003-4681-8206
Ranil AppuhamyLearning and Capacity Development Unit, WHO Health Emergencies Program, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0002-3329-7504
Ann MoenInfluenza Preparedness and Response, Organisation Mondiale de la Santé, Genève, Switzerland.ORCID 0000-0003-0863-0405
World Health Organization · CHLaerdal (Norway) · NO

Funding

World Health Organization 001
6 · The paper itself

Abstract

backgroundTo prepare key stakeholders for the global COVID-19 vaccination rollout, the World Health Organization and partners developed online vaccination training packages. The online course was launched in December 2020 on the OpenWHO learning platform. This paper presents the findings of an evaluation of this course.

objectiveThe aim of this evaluation was to provide insights into user experiences and challenges, measure the impact of the course in terms of knowledge gained, and anticipate potential interest in future online vaccination courses.

methodsThe primary source of data was the anonymized information on course participants, enrollment, completion, and scores from the OpenWHO platform's statistical data and metric reporting system. Data from the OpenWHO platform were analyzed from the opening of the courses in mid-December 2020 to mid-April 2021. In addition, a learner feedback survey was sent by email to all course participants to complete within a 3-week period (March 19 to April 9, 2021). The survey was designed to determine the perceived strengths and weaknesses of the training packages and to understand barriers to access.

resultsDuring the study period, 53,593 learners enrolled in the course. Of them, 30,034 (56.0%) completed the course, which is substantially higher than the industry benchmark of 5%-10% for a massive open online course (MOOC). Overall, learners averaged 76.5% on the prequiz compared to 85% on the postquiz, resulting in an increase in average score of 9%. A total of 2019 learners from the course participated in the survey. Nearly 98% (n=1647 fully agree, n=308 somewhat agree; N=1986 survey respondents excluding missing values) of respondents fully or somewhat agreed that they had more confidence in their ability to support COVID-19 vaccination following completion of this course.

conclusionsThe online vaccine training was well received by the target audience, with a measurable impact on knowledge gained. The key benefits of online training were the convenience, self-paced nature, access to downloadable material, and ability to replay material, as well as an increased ability to concentrate. Online training was identified as a timely, cost-effective way of delivering essential training to a large number of people to prepare for the COVID-19 vaccination rollout.

Indexed as

COVID-19Education, DistanceCOVID-19 VaccinesHumansSARS-CoV-2Surveys and QuestionnairesVaccinationCOVID-19 VaccineschallengeCOVID-19educationevaluationimpactinterestknowledgemassive open online courseonline educationpandemicpreparationtraininguser experiencevaccinationvaccine

Identifiers

PMID34794116
PMCPMC8647976
OpenAlexW3211560007

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.