Evidence map›Paper›PMID 28778216›Full record

ArticleSystematic reviews2017

Increasing value and reducing waste in data extraction for systematic reviews: tracking data in data extraction forms.

Farhad Shokraneh, Clive E Adams

Abstract readLetter
PubMed Full text at PMC Publisher
In one paragraph

Article in Systematic reviews, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Farhad ShokranehCochrane Schizophrenia Group, The Institute of Mental Health, A Partnership Between The University of Nottingham and Nottinghamshire Healthcare NHS Trust, Nottingham, UK. Farhad.Shokraneh@nottingham.ac.uk.ORCID 0000-0001-9687-8560
Clive E AdamsCochrane Schizophrenia Group, The Institute of Mental Health, A Partnership Between The University of Nottingham and Nottinghamshire Healthcare NHS Trust, Nottingham, UK.

Funding

Department of Health HTA/14/27/02
6 · The paper itself

Abstract

Data extraction is one of the most time-consuming tasks in performing a systematic review. Extraction is often onto some sort of form. Sharing completed forms can be used to check quality and accuracy of extraction or for re-cycling data to other researchers for updating. However, validating each piece of extracted data is time-consuming and linking to source problematic.In this methodology paper, we summarize three methods for reporting the location of data in original full-text reports, comparing their advantages and disadvantages.

Indexed as

Information Storage and RetrievalReview Literature as TopicData MiningHumansSurveys and QuestionnairesData extractionData locationIncreasing valuePortable Document Format (PDF)Reducing wasteSystematic reviewsTraceable data

Identifiers

PMID28778216
PMCPMC5544999

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.