ArticleBMC medical informatics and decision making2021
Digi-Do: a digital information tool to support patients with breast cancer before, during, and after start of radiotherapy treatment: an RCT study protocol.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04394325 (Digi-Do - a Digital Information Tool to Help Patients Diagnosed With Breast Cancer to be Involved and Prepared Before, During, and After Start of Radiotherapy Treatment), which is not on this map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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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.
Digi-Do - a Digital Information Tool to Help Patients Diagnosed With Breast Cancer to be Involved and Prepared Before, During, and After Start of Radiotherapy Treatment
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Mobile applications in radiation oncology-current choices and future potentials.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2023Pooled it
- Benefit of adding Cureety Techcare telemonitoring to usual care during injectable anticancer treatment: the OPTIMACURE multicentric French prospective randomized study.BMC health services research · 2025Trial
- Personalized surgical informed consent with stereoscopic visualization in neurosurgery-real benefit for the patient or unnecessary gimmick?Acta neurochirurgica · 2023Trial
- Evaluation of the ALIBIRD mHealth Platform for Care of Patients With Lung Cancer: Prospective Pilot Study.JMIR cancer · 2026Article
- Acute skin toxicity and self-management ability among Chinese breast cancer radiotherapy patients: a qualitative study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Exploring the Role of Complexity in Health Care Technology Bottom-Up Innovations: Multiple-Case Study Using the Nonadoption, Abandonment, Scale-Up, Spread, and Sustainability Complexity Assessment Tool.JMIR human factors · 2024Article
- Women's experience of the health information process involving a digital information tool before commencing radiation therapy for breast cancer: a deductive interview study.BMC health services research · 2023Article
- Using virtual reality to prepare patients for radiotherapy: A systematic review of interventional studies with educational sessions.Technical innovations & patient support in radiation oncology · 2023Review
- Digital Transformation in Healthcare: Technology Acceptance and Its Applications.International journal of environmental research and public health · 2023Article
- Beyond effectiveness evaluation: Contributing to the discussion on complexity of digital health interventions with examples from cancer care.Frontiers in public health · 2022Article
- Article
- Breamy: An augmented reality mHealth prototype for surgical decision-making in breast cancer.Healthcare technology lettersArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRadiation Therapy (RT) is a common treatment after breast cancer surgery and a complex process using high energy X-rays to eradicate cancer cells, important in reducing the risk of local recurrence. The high-tech environment and unfamiliar nature of RT can affect the patient's experience of the treatment. Misconceptions or lack of knowledge about RT processes can increase levels of anxiety and enhance feelings of being unprepared at the beginning of treatment. Moreover, the waiting time is often quite long. The primary aim of this study will be to evaluate whether a digital information tool with VR-technology and preparatory information can decrease distress as well as enhance the self-efficacy and health literacy of patients affected by breast cancer before, during, and after RT. A secondary aim will be to explore whether the digital information tool increase patient flow while maintaining or increasing the quality of care.
methodThe study is a prospective and longitudinal RCT study with an Action Research participatory design approach including mixed-methods data collection, i.e., standardised instruments, qualitative interviews (face-to-face and telephone) with a phenomenological hermeneutical approach, diaries, observations, and time measurements, and scheduled to take place from autumn 2020 to spring 2022. The intervention group (n = 80), will receive standard care and information (oral and written) and the digital information tool; and the control group (n = 80), will receive standard care and information (oral and written). Study recruitment and randomisation will be completed at two centres in the west of Sweden. DISCUSSION: Research in this area is scarce and, to our knowledge, only few previous studies examine VR as a tool for increasing preparedness for patients with breast cancer about to undergo RT that also includes follow-ups six months after completed treatment. The participatory approach and design will safeguard the possibilities to capture the patient perspective throughout the development process, and the RCT design supports high research quality. Digitalisation brings new possibilities to provide safe, person-centred information that also displays a realistic picture of RT treatment and its contexts. The planned study will generate generalisable knowledge of relevance in similar health care contexts.
trial registrationClinicalTrials.gov Identifier: NCT04394325. Registered May 19, 2020. Prospectively registered.
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Registered trials
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.