Evidence map›Paper›PMID 40234010›Full record

ArticleBJGP open2025

Primary care online training on multifactorial breast cancer risk: pre-post evaluation study.

Francisca Stutzin Donoso, Juliet A Usher-Smith, Lorenzo Ficorella, Antonis C Antoniou, Jon Emery, Marc Tischkowitz, Tim Carver, Douglas F Easton, Fiona M Walter, Stephanie Archer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BJGP open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

10 authors.

Francisca Stutzin DonosoPrimary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK fsd26@cam.ac.uk.ORCID https://orcid.org/0000-0003-1590-1226
Juliet A Usher-SmithPrimary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-8501-2531
Lorenzo FicorellaCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-0577-1571
Antonis C AntoniouCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0001-9223-3116
Jon EmeryCentre for Cancer Research and Department of General Practice and Primary Care, University of Melbourne, Melbourne, Australia.ORCID https://orcid.org/0000-0002-5274-6336
Marc TischkowitzDepartment of Genomic Medicine, National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0002-7880-0628
Tim CarverCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0003-1508-3091
Douglas F EastonCentre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0003-2444-3247
Fiona M WalterWolfson Institute of Population Health, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.ORCID https://orcid.org/0000-0002-7191-6476
Stephanie ArcherDepartment of Psychology, University of Cambridge, Cambridge, UK.ORCID https://orcid.org/0000-0003-1349-7178

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is estimated that more than 250 000 women in the UK are at increased risk of breast cancer, but only a small fraction are identified. Digital tools, such as CanRisk, enable multifactorial breast cancer risk assessment. Implementation of such tools within primary care would allow primary care professionals (PCPs) to reassure women at population-level risk and identify those at increased risk who will benefit most from targeted prevention or early detection. Previous studies suggest that PCPs will require educational resources to support the delivery of multifactorial breast cancer risk assessments.

aimTo develop and evaluate a new 'Multifactorial breast cancer risk assessment in primary care' online training for UK PCPs. DESIGN &

settingA mixed-methods pre-post evaluation study was undertaken. Thirty-five PCPs from across the UK participated in the evaluation and data collection was completed online between May and July 2024.

methodThe online training was developed following a scoping review of the literature. The Kirkpatrick model of training evaluation was used as a framework and participants were given pre-training and post-training evaluation questionnaires. Statistical analysis for the evaluation focused on the primary outcome of objective knowledge and mean changes were analysed with a paired sample

resultsObjective knowledge showed a significant mean increase (0.771, 95% confidence interval [CI] = 0.187 to 1.355,

conclusionThe 'Multifactorial breast cancer risk assessment in primary care' online training significantly increases PCPs' knowledge and confidence to conduct multifactorial breast cancer risk assessments, and it was well received by PCPs.

Indexed as

breast cancerbreast neoplasmse-learningprimary health carerisk assessment

Identifiers

PMID40234010
PMCPMC12728842

What Socratic 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 Socratic graph.