Evidence map›Paper›PMID 42888620›Full record

ArticleMedicine2026

Mapping the symptom management journey across the treatment cycle for breast cancer patients: A qualitative study.

WenQian Shao, JingPing Qian, WeiMin Xu, Xiao Chen

Abstract read
In one paragraph

Article in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

WenQian ShaoDepartment of Thyroid and Breast Surgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
JingPing QianHealth Education and Health Promotion Office, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
WeiMin XuDepartment of Thyroid and Breast Surgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.ORCID 0009-0005-3543-6431
Xiao ChenDepartment of Thyroid and Breast Surgery, The Second Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.

Funding

Anhui Provincial Health Commission Scientific Research Project AHWJ2023BAC20034
6 · The paper itself

Abstract

The aim of this study is to identify the multidimensional needs of breast cancer patients in symptom management using a patient journey map, providing an evidence-based foundation for optimizing nursing interventions. This descriptive qualitative study recruited 15 breast cancer patients from a tertiary hospital in Hefei for semi-structured interviews between January and August 2024. Data were analyzed using Colaizzi's 7-step method to construct a comprehensive journey map. The symptom management journey comprised 3 phases: screening and diagnosis, the perioperative period, and the ongoing treatment phase. Twenty-two themes were categorized into tasks, emotions, and pain points. Tasks included symptom detection and rehabilitation; emotions encompassed generalized anxiety and stigma; and pain points highlighted barriers like symptom misinterpretation and the risk of loss to follow-up. The map visually illustrated the dynamic evolution of patient needs. The findings highlight distinct stage-specific patterns in patients' needs and barriers during symptom management. The patient journey map serves as a structured framework for identifying key intervention nodes and supporting more targeted, stage-oriented nursing care.

Indexed as

Breast NeoplasmsAdultAgedFemaleHumansMiddle AgedQualitative ResearchSymptom Burdenbreast cancernursing carepatient journey mapsymptom management

Identifiers

PMID42888620
PMCPMC13680948

What OpenQuestion holds

Textmetadata
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.