Evidence map›Paper›PMID 27340306›Full record

ArticleScientometrics

Tracing the indirect societal impacts of biomedical research: development and piloting of a technique based on citations.

Teresa H Jones, Steve Hanney

Abstract read
In one paragraph

Article in Scientometrics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Tracing Long-Term Outcomes of Basic Research Using Citation Networks.Frontiers in research metrics and analytics · 2020
    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

2 authors.

Teresa H JonesHealth Economics Research Group, Brunel University London, Uxbridge, Middlesex UB8 3PH UK.
Steve HanneyHealth Economics Research Group, Brunel University London, Uxbridge, Middlesex UB8 3PH UK.

Funding

Medical Research Council G0802314
6 · The paper itself

Abstract

There is growing interest in assessing the societal impacts of research such as informing health policies and clinical practice, and contributing to improved health. Bibliometric approaches have long been used to assess knowledge outputs, but can they also help evaluate societal impacts? We aimed to see how far the societal impacts could be traced by identifying key research articles in the psychiatry/neuroscience area and exploring their societal impact through analysing several generations of citing papers. Informed by a literature review of citation categorisation, we developed a prototype template to qualitatively assess a reference's importance to the citing paper and tested it on 96 papers. We refined the template for a pilot study to assess the importance of citations, including self-cites, to four key research articles. We then similarly assessed citations to those citing papers for which the key article was Central i.e. it was very important to the message of the citing article. We applied a filter of three or more citation occasions in order to focus on the citing articles where the reference was most likely to be Central. We found the reference was Central for 4.4 % of citing research articles overall and ten times more frequently if the article contained three or more citation occasions. We created a citation stream of influence for each key paper across up to five generations of citations. We searched the Web of Science for citations to all Central papers and identified societal impacts, including international clinical guidelines citing papers across the generations.

Indexed as

Citation categorisationCitation generationsQualitative analysisResearch assessmentSocietal impacts of research

Identifiers

PMID27340306
PMCPMC4869749

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.