Evidence map›Paper›PMID 29273050›Full record

ArticleBMC public health2017

Responses to provision of personalised cancer risk information: a qualitative interview study with members of the public.

Juliet A Usher-Smith, Barbora Silarova, Artitaya Lophatananon, Robbie Duschinsky, Jackie Campbell, Joanne Warcaba, Kenneth Muir

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.7field-weighted citation impact, top 23% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Trial
  2. Review
  3. Article
  4. Development and Validation of Lifestyle-Based Models to Predict Incidence of the Most Common Potentially Preventable Cancers.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2019
    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

7 authors at 4 institutions in 1 country.

Juliet A Usher-SmithThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Box 113 Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK. jau20@medschl.cam.ac.uk.ORCID 0000-0002-8501-2531
Barbora SilarovaMRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK.
Artitaya LophatananonInstitute of Population Health, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
Robbie DuschinskyThe Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Box 113 Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.
Jackie CampbellInstitute of Health and Wellbeing, University of Northampton, Park Campus, Boughton Green Road, Northampton, NN2 7AL, UK.
Joanne WarcabaMoulton Surgery, 120 Northampton Lane North, Moulton, NN3 7QP, UK.
Kenneth MuirInstitute of Population Health, University of Manchester, Oxford Road, Manchester, M13 9PL, UK.
University of Cambridge · GBUniversity of Manchester · GBMoulton College · GBUniversity of Northampton · GB

Funding

Cancer Research UK 20818Cancer Research UK C18281/A19169Cancer Research UK C55650/A20818Medical Research Council MC_UU_12015/4
6 · The paper itself

Abstract

backgroundIt is estimated that nearly 600,000 cancer cases in the UK could have been avoided in the past five years if people had healthier lifestyles. A number of theories of behaviour change suggest that before people will change health behaviours, they must accept that a risk applies to them. This study aimed to explore the views of the public on receiving personalised cancer risk information and the potential for that information to motivate behaviour change.

methodsWe conducted 27 interviews with members of the public (mean age 49 ± 23 years). Each participant completed a questionnaire to allow calculation of their risk of developing the most common cancers (10 for women, 8 for men). During the interviews we presented their risk using a web-based tool developed for the study and discussions covered their views on receiving that information. Each interview was audio-recorded and then analysed using thematic analysis.

resultsParticipants generally viewed the concept of personalised cancer risk positively. The first reaction of almost all when presented with their 10-year risk of an individual cancer without any further context was that it was low and not concerning. Views on what constituted a high risk ranged widely, from 0.5 to 60%. All felt seeing the impact of changes in lifestyle was helpful. For some this led to intentions to change behaviour, but reductions in risk were not always motivating as the risks were considered low and differences small.

conclusionsProvision of personalised cancer risk was well received and may be a useful addition to other cancer prevention initiatives. Further work is needed in particular to develop ways to present cancer risk that reflect the general perception of what constitutes a risk high enough to motivate behaviour change and help patients contextualise a less well known health risk by providing a frame of reference.

Indexed as

Attitude to HealthNeoplasmsPrecision MedicineRiskAdultFemaleHealth BehaviorHealth CommunicationHumansIntentionLife StyleMaleMiddle AgedMotivationQualitative ResearchRisk Reduction BehaviorCancerCommunicationPreventionQualitative researchRisk

Identifiers

PMID29273050
PMCPMC5741964
OpenAlexW2776523386

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.