ArticleJMIR cancer2020
Cancer Patients' and Survivors' Perceptions of the Calm App: Cross-Sectional Descriptive Study.
Article in JMIR cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 11 papers, 2 of them syntheses that pooled it.
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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.
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.
Effects of a Mobile Meditation App on Stress During COVID-19 Pandemic in Outpatient Obstetrics and Gynecology Patients; a Randomized Controlled Trial
Effects of a Mobile App on Health and Well-being During COVID-19 Pandemic in House Staff at Banner University Medical Center Phoenix
Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Just-in-Time Adaptive Mechanisms of Popular Mobile Apps for Individuals With Depression: Systematic App Search and Literature Review.Journal of medical Internet research · 2021Pooled it
- Article
- Digital Guardian Angel Supported by an Artificial Intelligence System to Improve Quality of Life, Well-being, and Health Outcomes of Patients With Cancer (ONCORELIEF): Protocol for a Single Arm Prospective Multicenter Pilot Study.JMIR research protocols · 2023Article
- Artificial intelligence empowered digital health technologies in cancer survivorship care: A scoping review.Asia-Pacific journal of oncology nursing · 2022Article
- Meditation Mobile App Developed for Patients With and Survivors of Cancer: Feasibility Randomized Controlled Trial.JMIR cancer · 2022Article
- Insomnia as an Unmet Need in Patients With Chronic Hematological Cancer: Protocol for a Randomized Controlled Trial Evaluating a Consumer-Based Meditation App for Treatment of Sleep Disturbance.JMIR research protocols · 2022Article
- Utilizing Social Media Advertisements and Participant Social Networks to Recruit African American Breast Cancer Survivors: Design and Rationale.Frontiers in public health · 2022Article
- Marketplace and Literature Review of Spanish Language Mental Health Apps.Frontiers in digital health · 2021Review
- Article
- Compas-Y: A mixed methods pilot evaluation of a mobile self-compassion training for people with newly diagnosed cancer.Digital healthArticle
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a need for tools to decrease cancer patients' and survivors' long-term symptom burden. Complementary strategies, such as meditation, can accompany pharmacologic therapy to improve symptoms. Although support programs with targeted content have wider reach, higher adherence, and greater impact, there are no consumer-based meditation apps designed specifically for cancer.
objectiveThis study aimed to gather information to advise the development of a cancer-specific meditation app in a small convenience sample of cancer patients and survivors who currently use the Calm app.
methodsAdult cancer patients and survivors who are Calm users (N=82) were recruited through the Daily Calm Facebook page. Participants completed a Web-based survey related to Calm app use and satisfaction, interest in and ideas for a cancer-specific Calm app, and demographic characteristics. Open-ended responses were inductively coded.
resultsParticipants were aged between 18 and 72 years (mean 48.60 years, SD 15.20), mostly female (77/82, 94%), white (65/79, 82%), and non-Hispanic (70/75, 93%), and reported using Calm at least 5 times per week (49/82, 60%). Although rates of satisfaction with current Calm components were high (65/82, 79%; and 51/81, 63%), only 49% (40/82) of participants used guided meditations that they felt specifically helped with their cancer-related symptoms and survivorship, and 40% (33/82) would prefer more cancer-related content, with guided meditations for cancer-specific anxieties (eg, fear of recurrence; n=15) and coping with strong emotions (n=12) being the most common suggestions. A majority of participants (51/82, 62%) reported that they would be interested in becoming a member of a Calm cancer community (eg, in-app discussion boards: 41/46, 89%; and social media communities: 35/42, 83%). Almost half of the participants (37/82, 45%) reported that they would benefit from features that tracked symptoms in concurrence with app usage, but respondents were divided on whether this information should be shared with health care providers through the app (49/82, 60% would share).
conclusionsResponses suggest ways in which the current Calm app could be adapted to better fit cancer patients' and survivors' needs and preferences, including adding more cancer-specific content, increasing the amount of content focusing on coping with strong emotions, developing communities for Calm users who are cancer patients and survivors, and including features that track cancer-related symptoms. Given differences in opinions about which features were desirable or would be useful, there is a clear need for future cancer-specific apps to be customizable (eg, ability to turn different features on or off). Although future research should address these topics in larger, more diverse samples, these data will serve as a starting point for the development of cancer-specific meditation app and provide a framework for evaluating their effects.
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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.