Evidence map›Paper›PMID 34878993›Full record

ArticleJournal of medical Internet research2021

Expectations of Health Researchers From Academic Social Network Sites: Qualitative Study.

Mohammad Dehghani, Mehdi Kahouei, Shahin Akhondzadeh, Bita Mesgarpour, Reza Ferdousi

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mohammad DehghaniDepartment of Health Information Technology, Khomein University of Medical Sciences, Khomein, Iran.ORCID 0000-0002-5309-0703
Mehdi KahoueiSocial Determinants of Health Research Center, School of Allied Medical Sciences, Semnan University of Medical Sciences, Semnan, Iran.ORCID 0000-0003-0720-4519
Shahin AkhondzadehPsychiatric Research Center, Roozbeh Hospital, Tehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-2277-5101
Bita MesgarpourNational Institute for Medical Research Development (NIMAD), Tehran, Iran.ORCID 0000-0002-4004-8493
Reza FerdousiDepartment of Health Information Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID 0000-0001-5511-5452

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundToday, academic social network sites' role in improving the quality of education and how investigators conduct their research has become more critical.

objectiveThis study aimed to investigate Iranian health researchers' requirements for academic social network sites from a low-income country perspective.

methodsThis qualitative study with a phenomenological approach was done in 2020. In this study, 23 researchers in the health system were selected by purposive sampling. Semistructured interviews were used to collect data. Data were analyzed by MaxQDA-10 software and the content analysis method.

resultsWe identified 2 categories of functional and technical characteristics in the study participants' expectations. Functional characteristics included facilitating communication and team activities, managing scientific publications, enhancing the process of conducting research, being informative, and sharing and trading laboratory materials and equipment. Technical characteristics of an academic social network include user management capabilities, high security and privacy, being user-friendly, and other technical features.

conclusionsHealth researchers emphasized 2 functional and technical characteristics required to meet academic social network sites' expectations.

Indexed as

MotivationPrivacyHumansIranQualitative ResearchSocial Networkingacademicacademic social networkcontent analysisliteraturequalitativeresearchresearcherresearch networksocial network

Identifiers

PMID34878993
PMCPMC8693187

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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.