Evidence map›Paper›PMID 38200069›Full record

ArticleScientific reports2024

BrainSwarming, blockchain, and bioethics: applying Innovation Enhancing Techniques to healthcare and research.

Anuraag A Vazirani, Tony McCaffrey, Julian Savulescu, Sebastian Porsdam Mann

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Anuraag A Vazirani *Medical Sciences Division, University of Oxford, Oxford, UK. aav@doctors.org.uk.
Tony McCaffreyHead, Computer Science Department, Eagle Hill School, Hardwick, MA, USA.
Julian SavulescuDirector & Chen Su Lan Centennial Professor in Medical Ethics, Centre for Biomedical Ethics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Sebastian Porsdam Mann *Faculty of Law, University of Oxford, Oxford, UK. sebastian.porsdammann@law.ox.ac.uk.

Funding

Wellcome Trust
6 · The paper itself

Abstract

Innovation in healthcare and biomedicine is in decline, yet there exist no widely-known alternatives to traditional brainstorming that can be employed for innovative idea generation. McCaffrey's Innovation Enhancing Techniques (IETs) were developed to enhance creative problem-solving by helping the solver to overcome common psychological obstacles to generating innovative ideas. These techniques were devised for engineering and design problems, which involve solving practical goals using physical materials. Healthcare and science problems however often involve solving abstract goals using intangible resources. Here we adapt two of McCaffrey's IETs, BrainSwarming and the Generic Parts Technique, to effectively enhance idea generation for such problems. To demonstrate their potential, we apply these techniques to a case study involving the use of blockchain technologies to facilitate ethical goals in biomedicine, and successfully identify 100 potential solutions to this problem. Being simple to understand and easy to implement, these and other IETs have significant potential to improve innovation and idea generation in healthcare, scientific, and technological contexts. By catalysing idea generation in problem-solving, these techniques may be used to target the innovative stagnation currently facing the scientific world.

Indexed as

BlockchainCatalysisDelivery of Health CareDrugs, GenericHealth FacilitiesDrugs, Generic

Identifiers

PMID38200069
PMCPMC10781689

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.