Evidence map›Paper›PMID 31993110›Full record

ArticleOnline journal of public health informatics2019

Citizen Science Models in Health Research: an Australian Commentary.

Ann Borda, Kathleen Gray, Laura Downie

Abstract read
In one paragraph

Article in Online journal of public health informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Machine learning in healthcare citizen science: A scoping review.International journal of medical informatics · 2025
    Article
  3. Review
  4. Article
  5. Citizen Science Studies in Nursing: A Systematic Review.Nursing reports (Pavia, Italy) · 2024
    Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Combining the Digital, Social and Physical Layer to Create Age-Friendly Cities and Communities.International journal of environmental research and public health · 2021
    Article
  15. 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

3 authors.

Ann BordaHealth and Biomedical Informatics Centre Faculty of Medicine, Dentistry and Health Sciences The University of Melbourne Melbourne, VIC 3010, Australia.
Kathleen GrayHealth and Biomedical Informatics Centre Faculty of Medicine, Dentistry and Health Sciences The University of Melbourne Melbourne, VIC 3010, Australia.
Laura DownieDepartment of Optometry and Vision Sciences Faculty of Medicine, Dentistry and Health Sciences The University of Melbourne Melbourne, VIC 3010, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This qualitative review explores how established citizen science models can inform and support meaningful engagement of public in health research in Australia. In particular, with the growth in participatory health research approaches and increasing consumer participation in contributing to this research through digital technologies, there are gaps in our understanding of best practice in health and biomedical citizen science research to address these paradigm shifts. Notable gaps are how we might more clearly define the parameters of such research and which citizen science models might best support digitally-enabled participation falling within these. Further work in this area is expected to lead to how established citizen science methods may help improve the quality of and the translation of public engagement in health research.

Indexed as

citizen sciencecommunity based participatory researchcrowdsourcingpublic health

Identifiers

PMID31993110
PMCPMC6975539

What OpenQuestion holds

Textmetadata
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.