Evidence map›Paper›PMID 26327964›Full record

ArticleThe Pan African medical journal2015

Use of mobile learning technology among final year medical students in Kenya.

Moses Muia Masika, Gregory Barnabas Omondi, Dennis Simiyu Natembeya, Ephraim Mwatha Mugane, Kefa Ogonyo Bosire, Isaac Ongubo Kibwage

Abstract read
In one paragraph

Article in The Pan African medical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Smartphone and medical application use among dentists in China.BMC medical informatics and decision making · 2020
    Article
  9. Article
  10. Article
  11. Mobile Learning in Medical Education.Journal of medical systems · 2018
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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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

6 authors.

Moses Muia MasikaDepartment of Medical Microbiology, School of Medicine, University of Nairobi, Kenya.
Gregory Barnabas OmondiPartnership for Health and Development Africa, Kenya.
Dennis Simiyu NatembeyaPartnership for Health and Development Africa, Kenya.
Ephraim Mwatha MuganeSchool of Pharmacy, Department of Pharmaceutics, University of Nairobi, Kenya.
Kefa Ogonyo BosireDepartment of Pharmacology and Pharmacognosy, School of Pharmacy, University of Nairobi, Kenya.
Isaac Ongubo KibwageCollege of Health Sciences, University of Nairobi, Kenya.

Funding

Programatic-Strengthening Medical Education for Improved Health Outcomes in KenyaR24TW008889 · FIC · UNIVERSITY OF NAIROBI · PI KIBWAGE, ISAAC ONGUBO · 2010 to 2014
$10.4M
FIC NIH HHS 1R24TW008889FIC NIH HHS R24 TW008889
6 · The paper itself

Abstract

introductionMobile phone penetration has increased exponentially over the last decade as has its application in nearly all spheres of life including health and medical education. This study aimed at assessing the use of mobile learning technology and its challenges among final year undergraduate students in the College of Health sciences, University of Nairobi.

methodsThis was a cross-sectional descriptive study conducted among final year undergraduate students at the University of Nairobi, College of Health Sciences. Self-administered, anonymous questionnaires were issued to all final year students in their lecture rooms after obtaining informed consent. Data on demographics, mobile device ownership and mobile learning technology use and its challenges was collected. Data entry and analysis was done using SPSS(®). Chi-square and t-test were used for bivariate analysis.

resultsWe had 292 respondents; 62% were medical students, 16% were nursing students, 13% were pharmacy students and 9% were dental surgery students. The majority were female (59%) and the average age was 24 years. Eighty eight percent (88%) of the respondents owned a smart device and nearly all of them used it for learning. 64% of the respondents used medical mobile applications. The main challenges were lack of a smart device, lack of technical know-how in accessing or using apps, sub-optimal internet access, cost of acquiring apps and limited device memory.

conclusionMobile learning is increasingly popular among medical students and should be leveraged in promoting access and quality of medical education.

Indexed as

AdultCell PhoneCross-Sectional StudiesEducational TechnologyEducation, ProfessionalFemaleHealth OccupationsHumansInternetKenyaMaleMobile ApplicationsStudents, Health OccupationsSurveys and QuestionnairesYoung Adultmedical educationmobile applicationmobile-devicemobile learningSmartphone

Identifiers

PMID26327964
PMCPMC4546722

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.