scholarly journals Comparative analysis of general audience engagement with anti-smoking public health messages across multiple social media sites: Evidence-based recommendations for health communicators (Preprint)

10.2196/24429 ◽  
2020 ◽  
Author(s):  
Katja Reuter ◽  
Melissa L. Wilson ◽  
Meghan Moran ◽  
NamQuyen Le ◽  
Praveen Angyan ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Comparative Analysis ◽  
Health Messages ◽  
Evidence Based ◽  
Audience Engagement ◽  
General Audience ◽  
Public Health Messages

scholarly journals Correction: General Audience Engagement With Antismoking Public Health Messages Across Multiple Social Media Sites: Comparative Analysis

10.2196/28131 ◽  
2021 ◽  
Vol 7 (2) ◽  
pp. e28131
Author(s):  
Katja Reuter ◽  
Melissa L Wilson ◽  
Meghan Moran ◽  
NamQuyen Le ◽  
Praveen Angyan ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Comparative Analysis ◽  
Health Messages ◽  
Audience Engagement ◽  
General Audience ◽  
Public Health Messages

scholarly journals Leveraging Evidence-Based Messaging to Prevent the Spread of COVID-19

2021 ◽  
Author(s):  
Anastasia Browning ◽  
Melissa E Moss ◽  
Elliot Berkman
Keyword(s):  
Public Health ◽  
At Risk ◽  
Goal Orientation ◽  
Message Framing ◽  
Goal Orientations ◽  
Health Messages ◽  
Evidence Based ◽  
Public Health Messages ◽  
At Risk Populations

With cases of COVID-19 still spreading in America, and vaccines still inaccessible or undesired by many, individual mitigation behaviors, such as mask-wearing, remain critical defenses against this deadly virus. This study assessed whether approach-versus-avoidance message framing and goal-orientation affect people's intentions to follow COVID-19 preventative procedures. N = 832 subjects were randomly assigned to view mitigation messaging with either approach or avoidance framing, and either self-protective or altruistic goal-orientation. We observed a significant effect of goal-orientation, such that altruistic (versus self-protective) goal-orientations in messaging lead to stronger intentions to follow mitigation procedures. No significant effect of approach or avoidance framing was found on intentions to follow mitigation procedures. These results suggest an immediate need to address the wording of our public health messages. Adjusting the framing of COVID-19 preventative communications to reflect altruistic goals might increase the effectiveness of communications to protect at-risk populations.

Youth get a D+ grade in physical activity: How can we change public health messages to help reverse this trend?

2019 ◽  
Vol 44 (5) ◽  
pp. 567-570 ◽  
Author(s):  
Angela S. Alberga ◽  
Michelle Fortier ◽  
Corliss Bean ◽  
Yoni Freedhoff
Keyword(s):  
Public Health ◽  
Physical Activity ◽  
Physical Appearance ◽  
Sport Performance ◽  
Health Messages ◽  
Evidence Based ◽  
Public Health Perspective ◽  
Public Health Messages ◽  
Promotion Of Physical Activity ◽  
Policies And Programs

The purpose of this paper is to critique how the promotion of physical activity (PA) is communicated and offer evidence-based alternative framings to encourage PA in youth. We argue that PA promotion messaging should not be tied to outcomes that focus on changing physical appearance, preventing or treating diseases, or sport performance or competition. From a public health perspective, we suggest that PA should instead focus on campaigns, policies, and programs that tie PA to enjoyment, wellbeing, and play.

scholarly journals Comparative analysis of audience engagement with public health messages across multiple social media sites: Evidence-based recommendations for health communicators (Preprint)

2020 ◽  
Author(s):  
Katja Reuter ◽  
Melissa L. Wilson ◽  
Meghan Moran ◽  
NamQuyen Le ◽  
Praveen Angyan ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Health Promotion ◽  
Health Education ◽  
Health Messages ◽  
User Engagement ◽  
Goodness Of Fit Test ◽  
Audience Engagement ◽  
The Social ◽  
Click Through Rate

BACKGROUND Public health organizations have begun to use social media to increase awareness of health harms and positively improve health behavior. However, little is known about effective strategies for the digital dissemination of health education messages that ultimately result in optimal audience engagement with the health messages and with links to educational resource(s) specified in those messages. OBJECTIVE The objective of this study was to assess the difference in audience engagement with identical anti-smoking health messages on three social media sites: Twitter, Facebook, and Instagram, and with a referring link to a tobacco prevention website cited in these messages. We hypothesized health messages might not get the same user engagement on these media, although these messages were identical and distributed at the same time. METHODS We measured the effect of health promotion messages about the risk of smoking on users of three social media sites (Twitter, Facebook, and Instagram). We disseminated 1,275 health messages between April 19 to July 12, 2017 (85 days). The messages were distributed in identical form, at the same time, as organic (non-paid) and advertised (paid) messages, each including a link to an educational website with more information about the topic. Outcome measures included (i) message engagement, ie, the click-through rate (CTR) of the social media messages, and (ii) educational website engagement: the click-through rate on the educational website (wCTR). To analyze the data and model relationships, we used mixed effects negative binomial regression, z-statistic, and the Hosmer-Lemeshow goodness of fit test. RESULTS Comparisons between social media sites showed that CTRs for identical anti-tobacco health messages differed significantly across social media (P<.001 for all). Instagram showed the statistically significant highest overall mean message engagement, followed by Facebook, and Twitter. Facebook showed the highest CTR for any individual message as well some of the lowest. However, the message CTR is not indicative of the user engagement with the educational website content. Pairwise comparisons of the social media sites differed with respect to the wCTR (P<.001 for all). Messages on Twitter showed the lowest CTR, but they resulted in the highest level of website engagement, followed by Facebook, and Instagram. We found a statistically significant higher CTR for organic (unpaid) messages compared with paid ads (P<.001). CONCLUSIONS This work contributes to developing a scientific approach to select social media platform(s) for health promotion and increasing transparency of the processes and mechanisms that make digital health education effective. CLINICALTRIAL N/A

The advent of social media influencer tourism: Travel health risks and opportunities

2021 ◽  
Author(s):  
Ryan M Mangan ◽  
Gerard T Flaherty
Keyword(s):  
Public Health ◽  
Social Media ◽  
Health Risks ◽  
Travel Medicine ◽  
Health Messages ◽  
Vulnerable Group ◽  
Travel Health ◽  
Public Health Messages

Abstract The authors assert that social media influencer tourism should be recognised as a novel entity in travel medicine, in order to protect this vulnerable group of travellers from harm to themselves and their host destinations, and to harness their potential as communicators of positive public health messages.

scholarly journals Tweet for Behavior Change: Using Social Media for the Dissemination of Public Health Messages

2017 ◽  
Vol 3 (1) ◽  
pp. e14 ◽  
Author(s):  
Aisling Gough ◽  
Ruth F Hunter ◽  
Oluwaseun Ajao ◽  
Anna Jurek ◽  
Gary McKeown ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Behavior Change ◽  
Health Messages ◽  
Public Health Messages

scholarly journals Social Media Use, Disbelief and (Mis)information During a Pandemic: An Examination of Young Adult Nigerians’ Interactions with COVID-19 Public Health Messaging

2021 ◽  
pp. 1-18
Author(s):  
Olutobi Akingbade
Keyword(s):  
Public Health ◽  
Social Media ◽  
Young Adult ◽  
Low Income ◽  
Meaning Making ◽  
Health Messages ◽  
Media Messages ◽  
Public Health Messages ◽  
Social Media Platforms ◽  
The Government

This study contributes to transdisciplinary understanding of the COVID-19 pandemic through an examination of perceptions of public health messages as consumed primarily through social media by a purposively enlisted set of young adult Nigerians. The research used focus group discussions and in-depth interviews to elicit the views of 11 young adults, aged 21 to 24, resident in Ajegunle, a low-income community in Lagos, Nigeria’s commercial capital. The study identifies the centrality of social media platforms to the respondents’ processes of meaning-making, and draws on Hall’s (1980) encoding/decoding model in order to bring to the fore their oppositional interpretations of public health messages. The study also identifies respondents’ varying levels of disbelief about the realities of COVID-19, their mistrust of the government officials conveying and enforcing decisions to combat the pandemic, and the propensity for the social media messages they consume and propagate to serve as channels of misinformation.

Dynamic transactional model: a framework for communicating public health messages via social media

2020 ◽  
pp. 175791392093591 ◽  
Author(s):  
M Parackal ◽  
S Parackal ◽  
D Mather ◽  
S Eusebius
Keyword(s):  
Public Health ◽  
Social Media ◽  
Theoretical Framework ◽  
Health Messages ◽  
Transactional Model ◽  
Childbearing Age ◽  
Public Health Messages ◽  
Attractive Option ◽  
Use Of Social Media ◽  
Holding Back

Aims: Social media, because of its broad coverage, is an attractive option for communicating public health messages. However, the lack of a theoretical framework, supporting the two-way communication of social media, is holding back its development and use. This study investigated the suitability of a dynamic transactional model (DTM) of communication for explaining the use of social media for communicating public health messages. Methods: The study was carried out on ‘Don’t know? Don’t drink’, a Facebook campaign against drinking alcohol during pregnancy that targeted women of childbearing age in New Zealand. The comments generated were analysed for two features of DTM, namely inter- and intra-transaction, by examining the plurality of topics and polarity of sentiments, using text-mining techniques. Results: The analysis of the textual data revealed nine independent topics, confirming the plurality of topics. The conversation contained both positive and negative terms, establishing the polarity of sentiment. Conclusions: This study verified the two DTM features (inter- and intra-transaction) in the comments produced by the ‘Don’t know? Don’t drink’ campaign implemented on Facebook. DTM exhibited the potential to be a theoretical framework for recommending and evaluating social media sites like Facebook for communicating public health messages.

scholarly journals Social Network Analysis of COVID-19 Public Discourse on Twitter: Implications for Risk Communication

2020 ◽  
pp. 1-9
Author(s):  
Paola Pascual-Ferrá ◽  
Neil Alperstein ◽  
Daniel J. Barnett
Keyword(s):  
Public Health ◽  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Risk Communication ◽  
Public Discourse ◽  
Health Messages ◽  
Public Health Messages ◽  
Public Health Officials

ABSTRACT Objectives: The purpose of this study was to demonstrate the use of social network analysis to understand public discourse on Twitter around the novel coronavirus disease 2019 (COVID-19) pandemic. We examined different network properties that might affect the successful dissemination by and adoption of public health messages from public health officials and health agencies. Methods: We focused on conversations on Twitter during 3 key communication events from late January to early June of 2020. We used Netlytic, a Web-based software that collects publicly available data from social media sites such as Twitter. Results: We found that the network of conversations around COVID-19 is highly decentralized, fragmented, and loosely connected; these characteristics can hinder the successful dissemination of public health messages in a network. Competing conversations and misinformation can hamper risk communication efforts in a way that imperil public health. Conclusions: Looking at basic metrics might create a misleading picture of the effectiveness of risk communication efforts on social media if not analyzed within the context of the larger network. Social network analysis of conversations on social media should be an integral part of how public health officials and agencies plan, monitor, and evaluate risk communication efforts.

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