Evidence map›Paper›PMID 28552971›Full record

ArticlePloS one2017

Qualitative analysis of how patients decide that they want risk-reducing mastectomy, and the implications for surgeons in responding to emotionally-motivated patient requests.

Stephen L Brown, Demian Whiting, Hannah G Fielden, Pooja Saini, Helen Beesley, Christopher Holcombe, Susan Holcombe, Lyn Greenhalgh, Louise Fairburn, Peter Salmon

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
–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

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Peace of Mind: A Role in Unnecessary Care?Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Article
  6. Surgical decision making in premenopausalJournal of medical genetics · 2022
    Observational
  7. Article
  8. Article
  9. Article
  10. Reconciling the theory and reality of shared decision-making: A "matching" approach to practitioner leadership.Health expectations : an international journal of public participation in health care and health policy · 2019
    Review
  11. 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

10 authors.

Stephen L BrownDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.ORCID http://orcid.org/0000-0002-6142-0995
Demian WhitingHull York Medical School, Hull, United Kingdom.
Hannah G FieldenDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.
Pooja SainiDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.
Helen BeesleyDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.
Christopher HolcombeRoyal Liverpool and Broadgreen University Hospitals NHS Trust, Liverpool, United Kingdom.
Susan HolcombeRoyal Liverpool and Broadgreen University Hospitals NHS Trust, Liverpool, United Kingdom.
Lyn GreenhalghRoyal Liverpool Women's Hospital NHS Trust, Liverpool, United Kingdom.
Louise FairburnDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.
Peter SalmonDepartment of Psychological Sciences, University of Liverpool, Liverpool, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveContemporary approaches to medical decision-making advise that clinicians should respect patients' decisions. However, patients' decisions are often shaped by heuristics, such as being guided by emotion, rather than by objective risk and benefit. Risk-reducing mastectomy (RRM) decisions focus this dilemma sharply. RRM reduces breast cancer (BC) risk, but is invasive and can have iatrogenic consequences. Previous evidence suggests that emotion guides patients' decision-making about RRM. We interviewed patients to better understand how they made decisions about RRM, using findings to consider how clinicians could ethically respond to their decisions.

methodsQualitative face-to-face interviews with 34 patients listed for RRM surgery and two who had decided against RRM.

resultsPatients generally did not use objective risk estimates or, indeed, consider risks and benefits of RRM. Instead emotions guided their decisions: they chose RRM because they feared BC and wanted to do 'all they could' to prevent it. Most therefore perceived RRM to be the 'obvious' option and made the decision easily. However, many recounted extensive post-decisional deliberation, generally directed towards justifying the original decision. A few patients deliberated before the decision because fears of surgery counterbalanced those of BC.

conclusionPatients seeking RRM were motivated by fear of BC, and the need to avoid potential regret for not doing all they could to prevent it. We suggest that choices such as that for RRM, which are made emotionally, can be respected as autonomous decisions, provided patients have considered risks and benefits. Drawing on psychological theory about how people do make decisions, as well as normative views of how they should, we propose that practitioners can guide consideration of risks and benefits even, where necessary, after patients have opted for surgery. This model of practice could be extended to other medical decisions that are influenced by patients' emotions.

Indexed as

Decision MakingEmotionsMastectomyPatient ParticipationBreast NeoplasmsGenetic Predisposition to DiseaseHumans

Identifiers

PMID28552971
PMCPMC5446175

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.