Evidence map›Paper›PMID 35182377›Full record

ReviewJournal of community genetics2022

Patient-facing genetic and genomic mobile apps in the UK: a systematic review of content, functionality, and quality.

Norina Gasteiger, Amy Vercell, Alan Davies, Dawn Dowding, Naz Khan, Angela Davies

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of community genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 pooled it
1.8field-weighted citation impact, top 16% of its field
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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 2 institutions in 1 country.

Norina GasteigerDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0001-7801-7417
Amy VercellDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, UK.
Alan DaviesDivision of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0001-5737-5629
Dawn DowdingDivision of Nursing, Midwifery and Social Work, School of Health Sciences, University of Manchester, Manchester, UK.ORCID http://orcid.org/0000-0001-5672-8605
Naz KhanManchester Centre for Genomic Medicine, St. Mary's Hospital, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.
Angela DaviesDivision of Informatics, Imaging & Data Sciences, School of Health Sciences, The University of Manchester, Manchester, UK. angela.davies@manchester.ac.uk.ORCID http://orcid.org/0000-0002-3365-7231
Manchester Academic Health Science Centre · GBUniversity of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Close relative (consanguineous) marriage is widely practised globally, and it increases the risk of genetic disorders. Mobile apps may increase awareness and education regarding the associated risks in a sensitive, engaging, and accessible manner. This systematic review of patient-facing genetic/genomic mobile apps explores content, function, and quality. We searched the NHS Apps Library and the UK Google Play and Apple App stores for patient-facing genomic/genetic smartphone apps. Descriptive information and information on content was extracted and summarized. Readability was examined using the Flesch-Kincaid metrics. Two raters assessed each app, using the Mobile App Rating Scale (MARS) and the IMS Institute for Healthcare Informatics functionality score. A total of 754 apps were identified, of which 22 met the eligibility criteria. All apps intended to inform/educate users, while 32% analyzed genetic data, and 18% helped to diagnose genetic conditions. Most (68%) were clearly about genetics, but only 14% were affiliated with a medical/health body or charity, and only 36% had a privacy strategy. Mean reading scores were 35 (of 100), with the average reading age being equivalent to US grade 12 (UK year 13). On average, apps had 3.3 of the 11 IMS functionality criteria. The mean MARS quality score was 3.2 ± 0.7. Half met the minimum acceptability score (3 of 5). None had been formally evaluated. It was evident that there are few high-quality genomic/genetic patient-facing apps available in the UK. This demonstrates a need for an accessible, culturally sensitive, evidence-based app to improve genetic literacy within patient populations and specific communities.

Indexed as

App reviewGenesGeneticsGenomicsSmartphone app

Identifiers

PMID35182377
PMCPMC8941009
OpenAlexW4212824807

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.