ArticleFrontiers in public health2022
Health education
Article in Frontiers in public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Graph-Based Modeling of Behavioral Transitions for Digital Health Applications: Trajectory Analysis Framework.Journal of medical Internet research · 2026Article
- Home Environment as a Therapeutic Target for Prevention and Treatment of Chronic Diseases: Delivering Restorative Living Spaces, Patient Education and Self-Care by Bridging Biophilic Design, E-Commerce and Digital Health Technologies.International journal of environmental research and public health · 2025Article
- French Version of the User Mobile Application Rating Scale: Adaptation and Validation Study.JMIR mHealth and uHealth · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Increasing health care costs and high economic burden exemplify the impact of chronic diseases on public health. Multifaceted approaches to treating chronic diseases include pharmaceutical drugs, digital therapeutics, and lifestyle medicine. Chronic diseases are largely preventable, and health promotion yields positive outcomes. However, despite positive return on investment (ROI) and cost-to-benefit ratio (CBR) for health promotion (median ROI 2.2, median CBR 14.4), commercial marketing of healthy lifestyles and self-care is limited. The objective of this perspective article is to discuss how digital marketing of consumer goods and services that support therapeutic self-care can also bridge public health and for-profit interests. We describe how "empowerment" marketing campaigns can provide evidence-based associations between products/services and self-care benefits for people living with chronic pain and depression. Such a "health education as marketing" strategy is illustrated by educational ads describing how contact with nature, music, and yoga can improve chronic pain and reduce depressive symptoms. Creating associations between health-related benefits of these activities with products (outdoor and yoga apparel, audio equipment) and services (music streaming services, music mobile apps, eco-tourism, yoga studios) that support them expand their value proposition, thus incentivizing profit-driven companies to engage in public health campaigns. Long-term success of companies that incorporate evidence-based health education as marketing and branding strategies will depend on following ethical considerations and advertising guidelines defined by consumer protection regulatory agencies, such as the Federal Trade Commission (FTC). In conclusion, integration of health education about self-care and commercial marketing can support health care outcomes and disease prevention.
Indexed as
Identifiers
What OpenQuestion holds
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.