Evidence map›Paper›PMID 28163857›Full record

ArticleElectronic physician2016

Perceived needs in women with gestational diabetes: A qualitative study.

Taraneh Emamgoli Khooshehchin, Zohre Keshavarz, Maryam Afrakhteh, Elham Shakibazadeh, Soghrat Faghihzadeh

Abstract read
In one paragraph

Article in Electronic physician, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 3 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

9 citing papers in PubMed, 3 syntheses or guidelines 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

5 authors.

Taraneh Emamgoli KhooshehchinStudent Research Office, Ph.D. Candidate, Department of Reproductive Health, School of Nursing and Midwifery, International Branch, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Zohre KeshavarzAssistant Professor, Department of Reproductive Health, School of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Maryam AfrakhtehDepartment of Obstetrics and Gynecology of Shohada Tajresh Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Elham ShakibazadehAssistant Professor, Department of Health Education and Promotion, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
Soghrat FaghihzadehDepartment of Biostatistics, Zanjan University of Medical Sciences, Zanjan, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDiabetes is the most common medical complication of pregnancy. It can be associated with many complications for mother and fetus. Gestational diabetes is also one of the main health issues in Iran. Therefore, the present study is aimed at a deeper understanding of women's experiences of gestational diabetes and their perceived needs to inform future lifestyle interventions.

methodsThis qualitative content analysis study was carried out in 2015. Participants were pregnant women diagnosed with gestational diabetes in the 24

resultsContent analysis highlighted two themes; educational needs and need to support. The former was featured with five main categories: information sources, education process, unknown and known, weaknesses of public information system, and eagerness to learn. The latter was featured with two main categories: family support and social support.

conclusionClarifying the needs of the mothers with gestational diabetes, leads to better and proper education planning and a program toward the improvement of health, self-care, and prevention of diabetes.

Indexed as

Content analysisDiabetesNeedsPregnancyWomen

Identifiers

PMID28163857
PMCPMC5279975

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LicenceCC BY-NC-ND
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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.