Evidence map›Paper›PMID 34225687›Full record

ArticleBMC public health2021

Patterns of use and perceived value of social media for population health among population health stakeholders: a cross-sectional web-based survey.

Sungwon Yoon, Sharon Wee, Vivian S Y Lee, Jing Lin, Julian Thumboo

Abstract read
In one paragraph

Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. From Engagement to Concerns: Social Media Use Among a Sample of Australian Public Health Professionals.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Social Media Influencers, Health Literacy, and Food Literacy: A Correlational Study Among Adolescents.International journal of environmental research and public health · 2024
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Kidney Nutrition in the Era of Social Media: Bridging the Gap of Nutrition Education and Kidney Health Literacy by Leveraging Resources of Social Networking.Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation · 2022
    Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sungwon YoonRegional Health System, Singapore Health Services, Singapore, Singapore.
Sharon WeeRegional Health System, Singapore Health Services, Singapore, Singapore.
Vivian S Y LeeRegional Health System, Singapore Health Services, Singapore, Singapore.
Jing LinRegional Health System, Singapore Health Services, Singapore, Singapore.
Julian ThumbooRegional Health System, Singapore Health Services, Singapore, Singapore. julian.thumboo@singhealth.com.sg.

Funding

National Medical Research Council NMRC/CG/027/2017
6 · The paper itself

Abstract

backgroundAlthough existing studies have described patterns of social media use in healthcare, most are focused on health professionals in one discipline. Population health requires a multi-disciplinary approach to ensure diversity and to include diverse stakeholders. To date, what is known about using social media in population health is focused on its potential as a communication tool. This study aims to investigate patterns of use and perceived value of social media usage among stakeholders in population health practice, policy, or research.

methodsWe conducted a web-based survey of delegates attending the Singapore Population Health Conversations and Workshop. We designed a 24-item questionnaire to assess 1) social media use in terms of type of platform and frequency of use; 2) perceptions of social media relevance and impact on population health; and 3) top three areas in population health that would benefit from social media. We used descriptive and logistic regression analyses to assess the relationships between variables.

resultsOf the 308 survey respondents, 97.7% reported that they use social media in some form. Messaging (96.8%) was the most dominant activity when using social media. Challenges in implementing social media for population health were time investment by health care professionals (56.2%) and patient adoption (52.9%). The top three population health areas that would benefit most from using social media were the promotion of healthy behaviors (60.7%), community engagement (47.7%), and preventive care (40.6%). Older respondents (> = 40 years) were less likely to view social media as useful for the promotion of healthy behaviors (OR = 0.34; 95% CI: 0.19-0.60). Non-social/healthcare professionals were more likely to consider social media to be useful for community engagement (OR = 1.74; 95% CI: 1.10-2.76). For preventive care, older respondents (OR = 0.51; 95% CI: 0.32-0.82) and non-social/healthcare professionals were less likely to view social media as useful (OR = 0.61; 95% CI: 0.38-0.97).

conclusionsOur findings suggest that it may be important to select the specific care areas that would benefit most from using social media. The time investment needed by population health professionals should be fully addressed in planning to maximize the application and potential value of social media.

Indexed as

Population HealthSocial MediaCross-Sectional StudiesHealth PersonnelHumansSingaporeSurveys and QuestionnairesCross-sectional surveyHealthcare professionalsPopulation healthSocial care professionalsSocial media

Identifiers

PMID34225687
PMCPMC8256205

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.