A Software Tool Aimed at Automating the Generation, Distribution, and Assessment of Social Media Messages for Health Promotion and Education Research

Reuter, Katja; MacLennan, Alicia; Le, NamQuyen; Unger, Jennifer B.; Kaiser, Elsi; Angyan, Praveen

doi:10.2196/11263

Cited by 6 publications

(11 citation statements)

References 34 publications

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“…This study included the dissemination and analysis of a total of 1275 antismoking health messages posted across three social media platforms (Twitter, Facebook, and Instagram) between April 19 and July 12, 2017, as previously described [ 36 ]. The messages were focused on the risks of using combustible tobacco products.…”

Section: Methodsmentioning

confidence: 99%

“…For this experiment, we developed parameterized text message templates (n=102) and extracted images (n=315) from two government-sponsored health education campaigns [ 36 ]. Copy-protected images from these campaigns were replaced with similar images from a public photo repository, Stocksnap, and topic-related hashtags (n=4) from Twitter (eg, #cigs, #cigarettes, #smoking, #tobaccofree) .…”

Section: Methodsmentioning

confidence: 99%

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

Reuter¹,

Wilson²,

Moran³

et al. 2021

JMIR Public Health Surveill

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Background Public health organizations have begun to use social media to increase awareness of health harm and positively improve health behavior. Little is known about effective strategies to disseminate health education messages digitally and ultimately achieve optimal audience engagement. Objective This study aims to assess the difference in audience engagement with identical antismoking 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 that health messages might not receive 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 on the risk of smoking among users of three social media sites (Twitter, Facebook, and Instagram) and disseminated 1275 health messages between April 19 and July 12, 2017 (85 days). The identical messages were distributed at the same time and as organic (unpaid) and advertised (paid) messages, each including a link to an educational website with more information about the topic. Outcome measures included message engagement (ie, the click-through rate [CTR] of the social media messages) and educational website engagement (ie, the CTR 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 antitobacco health messages differed significantly across social media (P<.001 for all). Instagram showed the statistically significant highest overall mean message engagement (CTR=0.0037; 95% CI 0.0032-0.0042), followed by Facebook (CTR=0.0026; 95% CI 0.0022-0.0030) and Twitter (CTR=0.0015; 95% CI 0.0013-0.0017). Facebook showed the highest as well as the lowest CTR for any individual message. However, the message CTR is not indicative of 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 (wCTR=0.6308; 95% CI 0.5640-0.6975), followed by Facebook (wCTR=0.2213; 95% CI 0.1932-0.2495) and Instagram (wCTR=0.0334; 95% CI 0.0230-0.0438). We found a statistically significant higher CTR for organic (unpaid) messages (CTR=0.0074; 95% CI 0.0047-0.0100) compared with paid advertisements (CTR=0.0022; 95% CI 0.0017-0.0027; P<.001 and P<.001, respectively). Conclusions Our study provides evidence-based insights to guide the design of health promotion efforts on social media. Future studies should examine the platform-specific impact of psycholinguistic message variations on user engagement, include newer sites such as Snapchat and TikTok, and study the correlation between web-based behavior and real-world health behavior change. The need is urgent in light of increased health-related marketing and misinformation on social media.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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

Reuter¹,

Wilson²,

Moran³

et al. 2021

JMIR Public Health Surveill

Self Cite

View full text Add to dashboard Cite

show abstract

“…As such, it is crucial to incorporate comment moderation protocols into tobacco prevention campaigns on social media. This could include automated moderation tools that detect toxic comments to support fast response and moderation [ 26 , 31 - 34 ], educating the public about conversational techniques that sustain the productivity of online discourses, or deletion of toxic comments and suspension of associated accounts.…”

Section: Discussionmentioning

confidence: 99%

“…A total of 1275 campaign message posts were posted during the study period (Twitter: n=510; Facebook: n=510; Instagram: n=255) as specified in the technical implementation paper published previously [ 26 ]. Each campaign message was posted at the most once each month over 85 days.…”

Section: Methodsmentioning

confidence: 99%

Public Response to a Social Media Tobacco Prevention Campaign: Content Analysis

Majmundar¹,

Le²,

Moran³

et al. 2020

JMIR Public Health Surveill

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Background Prior research suggests that social media–based public health campaigns are often targeted by countercampaigns. Objective Using reactance theory as the theoretical framework, this research characterizes the nature of public response to tobacco prevention messages disseminated via a social media–based campaign. We also examine whether agreement with the prevention messages is associated with comment tone and nature of the contribution to the overall discussion. Methods User comments to tobacco prevention messages, posted between April 19, 2017 and July 12, 2017, were extracted from Twitter, Facebook, and Instagram. Two coders categorized comments in terms of tone, agreement with message, nature of contribution, mentions of government agency and regulation, promotional or spam comments, and format of comment. Chi-square analyses tested associations between agreement with the message and tone of the public response and the nature of contributions to the discussions. Results Of the 1242 comments received (Twitter: n=1004; Facebook: n=176; Instagram: n=62), many comments used a negative tone (42.75%) and disagreed with the health messages (39.77%), while the majority made healthy contributions to the discussions (84.38%). Only 0.56% of messages mentioned government agencies, and only 0.48% of the comments were antiregulation. Comments employing a positive tone (84.13%) or making healthy contributions (69.11%) were more likely to agree with the campaign messages (P=0.01). Comments employing a negative tone (71.25%) or making toxic contributions (36.26%) generally disagreed with the messages (P=0.01). Conclusions The majority of user comments in response to a tobacco prevention campaign made healthy contributions. Our findings encourage the use of social media to promote dialogue about controversial health topics such as smoking. However, toxicity was characteristic of comments that disagreed with the health messages. Managing negative and toxic comments on social media is a crucial issue for social media–based tobacco prevention campaigns to consider.

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“…Las herramientas que se encargan de difundir contenido diverso al público general y tienen como objetivo satisfacer las necesidades de los espectadores, ya sea con un fin económico o social, son los mass media (Insituto Internacional Español de Marketing digital s. f.) y es el concepto llamado media advocacy el que pretende utilizar los mass media para prevenir problemas de salud mediante la promo ción de hábitos saludables (Wallack 1993;Reuter et al 2019).…”

Section: Introducción!unclassified