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Factors Associated With Increased Dissemination of Positive Mental Health Messaging On Social Media.


ABSTRACT: Background: The dissemination of positive messages about mental health is a key goal of organizations and individuals. Aims: Our aim was to examine factors that predict increased dissemination of such messages. Method: We analyzed 10,998 positive messages authored on Twitter and studied factors associated with messages that are shared (re-tweeted) using logistic regression. Characteristics of the account, message, linguistic style, sentiment, and topic were examined. Results: Less than one third of positive messages (31.7%) were shared at least once. In adjusted models, accounts that posted a greater number of messages were less likely to have any single message shared. Messages about military-related topics were 60% more likely to be shared (adjusted odds ratio [AOR] = 1.6, 95% CI [1.1, 2.1]) as well as messages containing achievement-related keywords (AOR = 1.6, 95% CI [1.3, 1.9]). Conversely, positive messages explicitly addressing eating/food, appearance, and sad affective states were less likely to be shared. Multiple other message characteristics influenced sharing. Limitations: Only messages on a single platform and over a focused period of time were analyzed. Conclusion: A knowledge of factors affecting dissemination of positive mental health messages may aid organizations and individuals seeking to promote such messages online.

SUBMITTER: Sumner SA 

PROVIDER: S-EPMC7217348 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Factors Associated With Increased Dissemination of Positive Mental Health Messaging On Social Media.

Sumner Steven A SA   Bowen Daniel A DA   Bartholow Brad B  

Crisis 20190508 2


<i>Background:</i> The dissemination of positive messages about mental health is a key goal of organizations and individuals. <i>Aims:</i> Our aim was to examine factors that predict increased dissemination of such messages. <i>Method:</i> We analyzed 10,998 positive messages authored on Twitter and studied factors associated with messages that are shared (re-tweeted) using logistic regression. Characteristics of the account, message, linguistic style, sentiment, and topic were examined. <i>Resu  ...[more]

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