Evidence map›Paper›PMID 36176348›Full record

ArticlePatient preference and adherence2022

The Development of Schematics to Illustrate Women's Experiences with Adjuvant Hormone Therapy in the Treatment of Breast Cancer.

Othman AlOmeir, Nilesh Patel, Parastou Donyai

Abstract read
In one paragraph

Article in Patient preference and adherence, 2022. 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
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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

3 authors.

Othman AlOmeirDepartment of Pharmacy, University of Reading, Reading, Berkshire, UK.ORCID 0000-0002-3800-6825
Nilesh PatelDepartment of Pharmacy, University of Reading, Reading, Berkshire, UK.ORCID 0000-0002-8600-0663
Parastou DonyaiDepartment of Pharmacy, University of Reading, Reading, Berkshire, UK.ORCID 0000-0001-5403-6170

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Non-adherence to adjuvant hormone therapy prescribed orally in the treatment of breast cancer is complex as the literature has shown. Many women find it hard to adhere to the hormonal medicines they are prescribed and expected to take for at least 5 years following the initial management of their breast cancer. Arguably, communicating other women's 'trials, tribulations, and triumphs' with medication-taking could help newly-diagnosed patients to better prepare for the journey ahead. Our objective was to visually represent women's experiences with these medicines using data synthesized in the literature. Methods: Three schematics were drawn for each phase of medication-taking, namely, starting out, adherence, and cessation. The schematics were validated by interviewing a panel of healthcare professionals (n=10) and calculating a Content Validity Index (CVI). The edited drawings were discussed with a separate panel of breast cancer survivors (n=14) whose responses were elicited qualitatively in one-to-one interviews. Results: A total of 76 individual pictograms were drawn across the three schematics. The 13 pictograms that had an item-level CVI<0.8 were modified according to feedback resulting in three final schematics with an overall CVI of 87%, 87% and 80%, respectively. Conclusion: Synthesised summaries of women's experiences with oral hormone therapy for breast cancer were visualised via three validated schematics. The schematics could aid patient-professional communication to help anticipate and tackle negative experiences and support decisions to take hormone medication in breast cancer.

Indexed as

adherencebreast cancerhormone therapymedicationpictogramqualitative research

Identifiers

PMID36176348
PMCPMC9514301

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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.