Trends and gaps in precision health research: A scoping review

dc.contributor.authorViana, John Noel
dc.contributor.authorEdney, Sarah
dc.contributor.authorGondalia, Shakuntla
dc.contributor.authorMauch, Chelsea
dc.contributor.authorSellak, Hamza
dc.contributor.authorO'Callaghan, Nathan
dc.contributor.authorRyan, Jillian C
dc.date.accessioned2024-09-25T01:48:22Z
dc.date.available2024-09-25T01:48:22Z
dc.date.issued2021
dc.date.updated2024-03-10T07:15:31Z
dc.description.abstractObjective To determine progress and gaps in global precision health research, examining whether precision health studies integrate multiple types of information for health promotion or restoration. Design Scoping 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. Results After 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. Conclusions Although 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.
dc.description.sponsorshipThe researchers involved in this study are funded by the Australian National University, Commonwealth Scientific and Industrial Research Organisation, and/or the National University of Singapore. JNV acknowledges the ANU- CSIRO (Australian National University- Commonwealth Scientific and Industrial Research Organisation) Responsible Innovation collaboration for funding and support. There are no relevant grant numbers to mention.
dc.format.mimetypeapplication/pdfen_AU
dc.identifier.issn2044-6055
dc.identifier.urihttps://hdl.handle.net/1885/733720871
dc.language.isoen_AUen_AU
dc.provenanceThis is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
dc.publisherBMJ Publishing Group
dc.rights© 2021 The authors
dc.rights.licenseCreative Commons Attribution licence
dc.rights.urihttp://creativecommons.org/licenses/ by-nc-nd/4.0/
dc.sourceBMJ Open
dc.titleTrends and gaps in precision health research: A scoping review
dc.typeJournal article
dcterms.accessRightsOpen Access
local.bibliographicCitation.issue10
local.bibliographicCitation.lastpage11
local.bibliographicCitation.startpage1
local.contributor.affiliationViana, John Noel, College of Science, ANU
local.contributor.affiliationEdney, Sarah, National University of Singapore
local.contributor.affiliationGondalia, Shakuntla, Commonwealth Scientific and Industrial Research Organisation
local.contributor.affiliationMauch, Chelsea, Commonwealth Scientific and Industrial Research Organisation
local.contributor.affiliationSellak, Hamza, Commonwealth Scientific and Industrial Research Organisation
local.contributor.affiliationO'Callaghan, Nathan, Commonwealth Scientific and Industrial Research Organisation
local.contributor.affiliationRyan, Jillian C, Commonwealth Scientific and Industrial Research Organisation
local.contributor.authoruidViana, John Noel, u1095987
local.description.notesImported from ARIES
local.identifier.absfor420602 - Health equity
local.identifier.absfor420603 - Health promotion
local.identifier.absfor420302 - Digital health
local.identifier.ariespublicationa383154xPUB22644
local.identifier.citationvolume11
local.identifier.doi10.1136/bmjopen-2021-056938
local.identifier.scopusID2-s2.0-85118731789
local.identifier.thomsonIDWOS:000711992300028
local.publisher.urlhttps://bmjopen.bmj.com/
local.type.statusPublished Version

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