Evidence map›Paper›PMID 41591926›Full record

ArticleJMIR cancer2026

Development of a Web-Based Experiential Learning Intervention for the Public to Reduce Cancer Stigma: Tutorial on the Application of Intervention Mapping.

Miyako Tsuchiya, Keiichiro Adachi, Akiko Kimata, Kaori Kumagai

Abstract read
In one paragraph

Article in JMIR cancer, 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.

Miyako Tsuchiya *Research Institute of Nursing, Musashino University, 3-3-3, Ariake, Koto-ku, Tokyo, 135-8181, Japan, 81 3-5530-7730.ORCID 0000-0003-4670-1702
Keiichiro Adachi *Faculty of Health Sciences, Yamaguchi University Graduate School of Medicine, Ube, Japan.ORCID 0000-0001-6343-4525
Akiko Kimata *Former Division of Health Care Delivery, Survivorship and Policy Research, Institute of Cancer Control, National Cancer Center, Tokyo, Japan.ORCID 0000-0001-9629-1604
Kaori Kumagai *School of Nursing and Social Services, Health Sciences University of Hokkaido, Ishikari, Japan.ORCID 0009-0002-4014-3172

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Stigma may negatively impact individuals throughout the continuum of cancer care and survivorship. Multitheory and multilevel intervention programs are necessary to reduce stigma but remain globally limited. Objective: This tutorial aims to illustrate the development of a web-based experiential learning intervention, "Friend Supporter," designed for the public, which simulates scenarios to foster empathy and helping intentions. We applied the intervention mapping (IM) approach, which is rooted in the socioecological model, using the first four steps. Methods: In step 1, key issues faced by cancer survivors and influential factors were identified through empirical evidence and literature reviews on cancer stigmas and psychological theories. A multidisciplinary planning team assessed issue-related logic. In step 2, a logic model of change was created based on step 1 findings. In step 3, we designed program themes and a structure using systematic reviews and needs surveys among the public (n=1076) and cancer survivors (n=473), while applying theoretical change methods and practical strategies. Step 4 integrated prior findings. Inputs from an expert panel (n=5) and the public (n=13) using the think-aloud approach were used to refine the materials and functions, with educational resources for program providers also developed. Results: Step 1 revealed that public misconceptions and attitudes worsened the quality of life of cancer survivors. Step 2 identified 3 long-term outcomes: reduced public bias, improved responses to disclosure via acquired skills, and support aligned with survivors' aspirations. The short-term primary outcome was helping intention. Personal factors (knowledge, skills, and self-efficacy) were also expected to improve helping intention as mediators. In step 3, the literature review showed that multicomponent online interventions effectively reduced stigma. The survey indicated the public most needed information on "how to interact with friends diagnosed with cancer" (317/1076, 29.5%), regardless of whether they had a friend diagnosed with cancer (χ21=0.98; P=.32). Participants with no friends diagnosed with cancer were more likely to require information concerning "survival rates of all types of cancer" (χ21=7.3; P=.007). Preferred delivery modes were booklets or leaflets (529/1076, 49.2%) and the internet (texts and figures: 460/1076, 42.8%). Cancer survivors wanted their friends to understand "the possibility of a cure as a result of early detection and treatment" (193/473, 40.8%). To produce program materials, we applied stigma and discrimination, protection motivation, social cognitive, and learning theories. The 5-module program included self-learning, role-plays, worksheets, and written feedback from clinical psychologists. Step 4 confirmed the feasibility of the program with minor refinement. We then developed a practical guide for program providers' future implementation. Conclusions: IM is useful for systematically developing web-based multitheory and multilevel interventions. "Friend Supporter" offers a promising approach to enhance supportive behaviors and reduce cancer stigma. Quantitative evaluation is underway using the final 2 IM steps (implementation and evaluation) to determine real-world effectiveness.

Indexed as

Cancer SurvivorsInternet-Based InterventionNeoplasmsProblem-Based LearningSocial StigmaAdultFemaleHumansInternetMaleMiddle Agedcancerdigital intervention developmentintervention mappingstigmasurvivorship

Identifiers

PMID41591926
PMCPMC12840868

What OpenQuestion holds

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LicenceCC BY
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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.