Evidence map›Paper›PMID 34697128›Full record

ArticleBMJ open2021

Trends and gaps in precision health research: a scoping review.

John Noel Viana, Sarah Edney, Shakuntla Gondalia, Chelsea Mauch, Hamza Sellak, Nathan O'Callaghan, Jillian C Ryan

Abstract readScoping Review
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Article
  2. Closing the Implementation Gap in Precision Nursing Care.The journal of nursing research : JNR · 2026
    Article
  3. Article
  4. Article
  5. Article
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  7. Article
  8. Article
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  12. Article
  13. Exploring human biology with N-of-1 clinical trials.Cambridge prisms. Precision medicine · 2023
    Article
  14. Article
  15. Article
  16. Review
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

7 authors.

John Noel VianaResponsible Innovation Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Brisbane, Queensland, Australia john.viana@anu.edu.au.ORCID 0000-0002-4004-7546
Sarah EdneyPhysical Activity and Nutrition Determinants in Asia (PANDA) programme, Saw Swee Hock School of Public Health, National University of Singapore, Singapore.ORCID 0000-0002-3925-517X
Shakuntla GondaliaPrecision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia.ORCID 0000-0002-9658-0307
Chelsea MauchHealth and Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia.
Hamza SellakPrecision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia.ORCID 0000-0003-3666-8136
Nathan O'CallaghanPrecision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia.
Jillian C RyanPrecision Health Future Science Platform, Commonwealth Scientific and Industrial Research Organisation, Adelaide, South Australia, Australia.ORCID 0000-0003-0655-3047

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo determine progress and gaps in global precision health research, examining whether precision health studies integrate multiple types of information for health promotion or restoration.

designScoping review. DATA SOURCES: Searches in Medline (OVID), PsycINFO (OVID), Embase, Scopus, Web of Science and grey literature (Google Scholar) were carried out in June 2020. ELIGIBILITY CRITERIA: Studies should describe original precision health research; involve human participants, datasets or samples; and collect health-related information. Reviews, editorial articles, conference abstracts or posters, dissertations and articles not published in English were excluded. DATA EXTRACTION AND SYNTHESIS: The following data were extracted in independent duplicate: author details, study objectives, technology developed, study design, health conditions addressed, precision health focus, data collected for personalisation, participant characteristics and sentence defining 'precision health'. Quantitative and qualitative data were summarised narratively in text and presented in tables and graphs.

resultsAfter screening 8053 articles, 225 studies were reviewed. Almost half (105/225, 46.7%) of the studies focused on developing an intervention, primarily digital health promotion tools (80/225, 35.6%). Only 28.9% (65/225) of the studies used at least four types of participant data for tailoring, with personalisation usually based on behavioural (108/225, 48%), sociodemographic (100/225, 44.4%) and/or clinical (98/225, 43.6%) information. Participant median age was 48 years old (IQR 28-61), and the top three health conditions addressed were metabolic disorders (35/225, 15.6%), cardiovascular disease (29/225, 12.9%) and cancer (26/225, 11.6%). Only 68% of the studies (153/225) reported participants' gender, 38.7% (87/225) provided participants' race/ethnicity, and 20.4% (46/225) included people from socioeconomically disadvantaged backgrounds. More than 57% of the articles (130/225) have authors from only one discipline.

conclusionsAlthough there is a growing number of precision health studies that test or develop interventions, there is a significant gap in the integration of multiple data types, systematic intervention assessment using randomised controlled trials and reporting of participant gender and ethnicity. Greater interdisciplinary collaboration is needed to gather multiple data types; collectively analyse big and complex data; and provide interventions that restore, maintain and/or promote good health for all, from birth to old age.

Indexed as

Health PromotionPrecision MedicineHumansMiddle AgedResearch Designgeneral medicine (see internal medicine)nutrition & dieteticsoccupational & industrial medicinepreventive medicinepublic healthsocial medicine

Identifiers

PMID34697128
PMCPMC8547511

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.