ArticlemHealth2019
Pregnancy posting: exploring characteristics of social media posts around pregnancy and user engagement.
Article in mHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Which educational messengers do medical students prefer for receiving healthinformation? Development and psychometrics of using health messengers questionnaire.BMC public health · 2024Article
- Article
- Article
- Automated classification of lay health articles using natural language processing: a case study on pregnancy health and postpartum depression.Frontiers in psychiatry · 2023Article
- Feedback on Instagram posts for a gestational weight gain intervention.Translational behavioral medicine · 2022Article
- The Use of Social Media for Preconception Information and Pregnancy Planning among Young Women.Journal of clinical medicine · 2021Article
- Using content analysis to inform health communication efforts on social media: Is popularity the goal?mHealth · 2021Article
- #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses.International journal of environmental research and public health · 2020Article
- Article
Corrections and comments
- Commented on by
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPregnant women use the Internet and social networking sites to meet a variety of pregnancy-related needs as well as to help make decisions regarding their pregnancy and/or parenting. Knowing more about the current landscape of social networking sites as it relates to pregnancy can inform future work that wants to leverage social media for education or support.
methodsAcross a 7-day period, we conducted a content analysis of 4 Facebook pregnancy-related groups and 4 Instagram pregnancy-related channels. The posts were coded based on the nature, content, and purpose of each post as well as the number of likes, shares, and comments for each. After establishing inter-rater reliability, univariate statistics were used to describe the nature, characteristics, and popularity of the posts for each group or channel. We then used logistic regressions to predict which characteristics were associated with being popular or unpopular with users.
resultsThere were 288 eligible posts within the 7-day window. Only a small proportion of the large (182,000 to 2,527,712) amount of followers responded with likes or comments (comments: mean =0.02%, SD =0.04%; likes: mean =0.36%, SD =0.89%). Facebook posts tended to give more general pregnancy-related information or opportunities for personal sharing while Instagram posts often had emotional support themes or posts meant to make pregnancy relatable. Popular posts tended to try to make pregnancy more relatable (OR =4.21, P<0.01) or offer emotional support (OR =4.62, P<0.01), while unpopular posts tended to provide general pregnancy-related information (OR= 2.17, P<0.05).
conclusionsIn general, there were clear characteristics that differentiated the two social networking site posts that garner user attention or not. This can inform how to provide health information and social support via social media to maximize its influence. This work suggests which features are desirable for followers and can help those interested in leveraging Instagram and Facebook to provide pregnancy-related health information.
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.