ArticleHealth communication2021
A Content Analysis of Social Support Messages about Environmental Breast Cancer Risk within Blogs for Mothers.
Article in Health communication, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 17 citations in OpenAlex.
- Health messages that engage audiences after the COVID-19 pandemic: content analysis of Chinese posts on social media.Frontiers in public health · 2025Article
- Using a Social Network Approach to Characterize Oral Health Behavior Social Support Among Mexican-Origin Young Adults.Journal of health communication · 2025Article
- The Use of Social Media to Express and Manage Medical Uncertainty in Dyskeratosis Congenita: Content Analysis.JMIR infodemiology · 2024Article
- Use of Social Media for Health Advocacy for Digital Communities: Descriptive Study.JMIR formative research · 2023Article
- Support-Seeking Strategies and Social Support Provided in Chinese Online Health Communities Related to COVID-19.Frontiers in psychology · 2021Article
- Supportive communication patterns among informal caregivers of older adults on Reddit: A content analysis.Digital healthArticle
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
Bloggers can help stimulate online conversations among their readers about a variety of health topics, including breast cancer. However, in previous studies, researchers have not specifically examined supportive messages within an online blogger community that stem from an intervention where bloggers were provided with evidence-based information about breast cancer risk that they could tailor and disseminate to their readers. In the current study, we content analyzed 282 supportive messages within online conversations from participants in blogger communities over a 2-month period immediately following an intervention where the authors provided 74 bloggers who write about motherhood issues with an infographic based on evidence-based information from the Breast Cancer and the Environment Research Program (BCERP) about environmental breast cancer risk/prevention. Bloggers who shared information about their personal breast cancer risk generated a significantly higher number of blog reader comments than bloggers who did not share information about their personal breast cancer risk. Bloggers who cited breast cancer statistics in posts were more likely to draw esteem and emotional support from their readers. Bloggers' repetition of information from blog intervention messages was more likely to elicit esteem, informational, and emotional support from readers. Disclosure of a personal breast cancer diagnosis was associated with mixed types of social support messages. The theoretical and practical implications are discussed along with key limitations of the study and future directions for research in this area.
Indexed as
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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.