Evidence map›Paper›PMID 39996861›Full record

ArticleCurrent oncology (Toronto, Ont.)2025

Language of the Heart: Creating Digital Stories and Found Poetry to Understand Patients' Experiences Living with Advanced Cancer.

Kathleen C Sitter, Jessame Gamboa, Janet Margaret de Groot

Abstract read
In one paragraph

Article in Current oncology (Toronto, Ont.), 2025. 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

3 authors.

Kathleen C SitterFaculty of Social Work, University of Calgary, Calgary, AB T2N 1N4, Canada.ORCID 0000-0002-2479-279X
Jessame GamboaDepartment of Psychiatry, Oncology, and Community Health Sciences, Cuming School of Medicine, University of Calgary, Calgary, AB T2N 2T9, Canada.
Janet Margaret de GrootDepartment of Psychiatry, Oncology, and Community Health Sciences, Cuming School of Medicine, University of Calgary, Calgary, AB T2N 2T9, Canada.ORCID 0000-0003-4684-4586

Funding

Alberta Cancer Foundation 27420
6 · The paper itself

Abstract

In this article, we share our findings on patients' experiences creating digital stories about living with advanced cancer, represented through found poetry. Over a period of 12 months, patients from the program "Managing Cancer and Living Meaningfully" (CALM) completed digital stories about their experiences living with cancer. Digital stories are short, personalized videos that combine photographs, imagery, narration, and music to communicate a personal experience about a topic of inquiry. Patient interviews were conducted about the digital storytelling process. Found poetry guided the analysis technique. It is a form of arts-based research that involves using words and phrases found in interview transcripts to create poems that represent research themes. This article begins with a brief overview of the psychosocial intervention CALM, arts in healthcare, and found poetry, followed by the project background. The found poems represent themes of emotional impact, legacy making, and support and collaboration. Findings also indicate the inherently relational aspect of digital storytelling as participants emphasized the integral role of the digital storytelling facilitator. What follows is a discussion on digital storytelling, which considers the role of found poetry in representing patient voices in the research process.

Indexed as

NeoplasmsPoetry as TopicFemaleHumansLanguageMaleNarrationadvanced cancerdigital storytellingfound poetryhealthcarepatient experiencespoetic inquiry

Identifiers

PMID39996861
PMCPMC11854169

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.