Evidence map›Paper›PMID 36204454›Full record

ArticleFrontiers in research metrics and analytics2022

Impact of supervisors' research style on young biomedical scientists' capacity development as measured by REDi, a novel index of crossdisciplinarity.

Akiko Hashiguchi, Hiroka Hamada, Satoru Takahashi, Keisuke Honda

Abstract read
In one paragraph

Article in Frontiers in research metrics and analytics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

4 authors.

Akiko HashiguchiFaculty of Medicine, University of Tsukuba, Tsukuba, Japan.
Hiroka HamadaPlanning Unit, Administration Planning and Coordination Section, The Institute of Statistical Mathematics, Tachikawa, Japan.
Satoru TakahashiFaculty of Medicine, University of Tsukuba, Tsukuba, Japan.
Keisuke HondaPlanning Unit, Administration Planning and Coordination Section, The Institute of Statistical Mathematics, Tachikawa, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The challenge for medical schools in Japan is to develop research activities for innovation. This study aimed at analyzing the connection between the research output of "promising researchers" (next-generation leaders in terms of research activity) and their supervisors' past research activities to identify those factors that impact researchers' performance. Activity was analyzed from the viewpoints of productivity, coauthorship networks, and research impact using a novel index called the Research Diversity Index (REDi) that quantifies crossdisciplinarity. Research funding, which has not yet been fully utilized in correlation studies of the characteristics of authors, was also considered in this study. For the promising researchers extracted using betweenness centrality scores within coauthorship networks, there were diachronic correlations between the records of the promising researchers and those of their supervisors. Supervisor leadership as measured by the number of last-authored publications and extent of networking had a positive effect on the promising researchers productivity. Supervisors' research style of integrating knowledge from multiple fields, as measured by REDi, was negatively correlated with the publication impact of promising researchers, suggesting that REDi is useful as a novel indicator of research quality not being captured by existing indices. It was also noted that establishing an academic presence through extensive collaborations could be advantageous for obtaining research funding, especially from top-down government programs. The possible implications of this study for promoting research activities are the importance of incorporating new doctorates into research groups at an early stage and that of promoting interinstitutional, crossdisciplinary collaborations. Classification code: MSC: 62P10 Applications of statistics to biology and medical sciences; meta-analysis.JEL: Z1Z10 Cultural Economics • Economic Sociology • Economic Anthropology- General.

Indexed as

collaborative networkscorrelation analysisdiachronic effectfundingresearch activitiesResearch Diversity Index (REDi)

Identifiers

PMID36204454
PMCPMC9531751

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Registered trials

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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.