Evidence map›Paper›PMID 36575493›Full record

ArticleHuman resources for health2022

Pre-service medical education course completion and drop-out rates.

Osahon Enabulele, Joan Emien Enabulele

Abstract read
In one paragraph

Article in Human resources for health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

2 authors.

Osahon EnabuleleDepartment of Family Medicine, University of Benin Teaching Hospital, Ugbowo, P.O. Box 10427, Benin City, Edo, Nigeria. osahoncmavp@gmail.com.ORCID 0000-0003-0786-2001
Joan Emien EnabuleleDepartment of Restorative Dentistry, University of Benin, P.M.B. 1154, Benin City, Edo, Nigeria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe "Global strategy on human resources for health: Workforce 2030" was adopted by the 69th World Health Assembly. Among its objectives is the strengthening of data on human resources for health, to inform evidence-based policy decisions. These data include the course completion and drop-out rates, to inform mechanisms that support recruitment and retention.

objectiveThis paper sought to evaluate trends in course completion and drop-out rates of health workforce students. However, original data were only obtained for pre-service medical students, but no other health worker occupational groups.

methodsA mixed method approach was employed to obtain data presented in this paper. A structured questionnaire was sent out to targeted medical training institutions, regulatory bodies, and National Medical Associations, supplemented by a web and literature search for existing studies or data reports. Data were analyzed using IBM SPSS Statistics version 21.0 (Chicago, IL, USA) and Microsoft Excel 2010.

resultsEight previously published studies were identified originating from six countries, with course completion rates ranging from 84% in Pakistan to 98.6% in the United States of America, while the drop-out rates ranged from 1.4% in the United States of America to 16% in Pakistan. An analysis of pre-service medical students in Australia and New Zealand, revealed average course completion rates of 93.3% and 96.9%, respectively, and average drop-out rates of 6.7% and 3.1%, respectively. An analysis of pre-service medical students from Nigeria, revealed an average course completion rate of 88.3%, and an average drop-out rate of 11.7%. Data were not readily available for most countries targeted during the research, either because of lack of existing mechanisms for collation of required data or restrictions making such data publicly unavailable and inaccessible.

conclusionsDrop-out rate for pre-service medical students varies across countries with some countries recording higher drop-out rates, which raise significant concerns about the capacity of such countries to scale up production of human resources for health. Data that monitor both course completion and drop-out rates, and seek to provide insight into reasons for observed numbers, can inform mechanisms to address the causes of course drop-out and support student retention.

Indexed as

Education, MedicalStudents, MedicalAustraliaHealth WorkforceHumansUnited StatesWorkforceCourse completion rateCourse drop-out rateEducationMedical studentsRetentionTraining

Identifiers

PMID36575493
PMCPMC9793383

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.