Evidence map›Paper›PMID 32735228›Full record

ArticleJMIR mHealth and uHealth2020

A Tool for Rating the Value of Health Education Mobile Apps to Enhance Student Learning (MARuL): Development and Usability Study.

Tehmina Gladman, Grace Tylee, Steve Gallagher, Jonathan Mair, Sarah C Rennie, Rebecca Grainger

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Tehmina GladmanEducation Unit, University of Otago Wellington, Wellington, New Zealand.ORCID 0000-0002-5112-3460
Grace TyleeUniversity of Otago Wellington, Wellington, New Zealand.ORCID 0000-0002-1964-6958
Steve GallagherEducation Unit, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.ORCID 0000-0003-1108-4388
Jonathan MairHutt Valley District Health Board, Lower Hutt, New Zealand.ORCID 0000-0002-2512-2421
Sarah C RennieEducation Unit, University of Otago Wellington, Wellington, New Zealand.ORCID 0000-0001-8638-8955
Rebecca GraingerEducation Unit, University of Otago Wellington, Wellington, New Zealand.ORCID 0000-0001-9201-8678

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo realize the potential for mobile learning in clinical skills acquisition, medical students and their teachers should be able to evaluate the value of an app to support student learning of clinical skills. To our knowledge, there is currently no rubric for evaluation of quality or value that is specific for apps to support medical student learning. Such a rubric might assist students to be more confident in using apps to support their learning.

objectiveThe objective of this study was to develop an instrument that can be used by health professional educators to rate the value of a mobile app to support health professional student learning.

methodsUsing the literature, we developed a list of potential criteria for the evaluation of educational app value, which were then refined with a student group using a modified nominal group technique. The refined list was organized into themes, and the initial rubric, Mobile App Rubric for Learning (MARuL, version 1), was developed. iOS and Android app stores were searched for clinical skills apps that met our inclusion criteria. After the 2 reviewers were trained and the item descriptions were refined (version 2), a random sample of 10 included apps, 5 for each mobile operating system, was reviewed. Interitem and interrater analyses and discussions with the reviewers resulted in refinement of MARuL to version 3. The reviewers completed a review of 41 clinical skills mobile apps, and a second round of interitem and interrater reliability testing was performed, leading to version 4 of the MARuL.

resultsStudents identified 28 items (from an initial set of 144 possible items) during the nominal group phase, and these were then grouped into 4 themes: teaching and learning, user centered, professional, and usability. Testing and refinement with reviewers reduced the list to 26 items. Internal consistency for MARuL was excellent (α=.96), and the interrater reliability as measured by the intraclass correlation coefficient (ICC) was good (ICC=0.66).

conclusionsMARuL offers a fast and user-friendly method for teachers to select valuable apps to enhance student learning.

Indexed as

Mobile ApplicationsStudents, MedicalHealth EducationHumansLearningReproducibility of Resultsdigital learninghealth occupations studentsjust-in-time learningmedical educationmhealthmobile appsmobile learningmobile phonequestionnaire designrubricself-directed learning

Identifiers

PMID32735228
PMCPMC7428912

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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.