Evidence map›Paper›PMID 29678133›Full record

ArticleBMC public health2018

Popularity and impact of using smart devices in medicine: experiences in Saudi Arabia.

Sameer Al-Ghamdi

Abstract read
In one paragraph

Article in BMC public health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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

  1. Pooled it
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  13. Smartphone and medical application use among dentists in China.BMC medical informatics and decision making · 2020
    Article
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  15. Smart Devices and Better Health: Positive Associations Between Smart Devices and Health Among Older Adults.Inquiry : a journal of medical care organization, provision and financing
    Article
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

1 author.

Sameer Al-GhamdiDepartment of Family Medicine, College of Medicine, Prince Sattam bin Abdulaziz University, Al Kharj, Saudi Arabia. Sam3443@gmail.com.ORCID 0000-0003-0506-0574

Funding

The Deanship of Scientific Research at Prince Sattam bin Abdulaziz University no- 2017/03/3361
6 · The paper itself

Abstract

backgroundThe present study aimed to investigate smart device medical apps currently preferred by physicians in Saudi Arabia and the perceived impact of the apps on patient care.

methodsQuestionnaires for this cross-sectional study on smart device medical apps were randomly emailed to 384 physicians registered in the Saudi Commission of Health Specialists database. A total of 300 physicians returned completed questionnaires, with a response rate of 78.5%. Physician demographics and their perceptions of medical apps were assessed, including questions on the purpose, impact, and types of medical apps used. Questions were answered using a Likert scale (1 = strongly disagree, 2 = disagree, 3 = not sure, 4 = agree, and 5 = strongly agree).

resultsStudy subjects had a median age of 39 years (57.7% male). Most respondents (88.3%) had smart devices, and 86.3% had at least one medical app installed. Just over half used an app at least once a day (53.0%). Medical apps were positively perceived, with physicians reporting increased dependency on the apps (Likert score: 4.7 ± 0.5).

conclusionMedical apps were perceived to positively impact education, physician efficiency, and patient care.

Indexed as

Attitude of Health PersonnelAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedMobile ApplicationsPhysiciansPractice Patterns, Physicians'Saudi ArabiaSmartphoneSurveys and QuestionnairesMedicineSaudi ArabiaSmart deviceSmartphone

Identifiers

PMID29678133
PMCPMC5910597

What OpenQuestion holds

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LicenceCC BY
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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.