How to Avoid Lower Priority for Smoking Cessation Support Content on Facebook: An Analysis of Engagement Bait.
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SUBMITTER: Watti J
PROVIDER: S-EPMC9859185 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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How to Avoid Lower Priority for Smoking Cessation Support Content on Facebook: An Analysis of Engagement Bait.
Watti Jezdancher J Millner Máté M Siklósi Kata K Hamvai Csaba C Kelemen Oguz O Pócs Dávid D
International journal of environmental research and public health 20230105 2
Facebook demotes "engagement bait" content that makes people interact. As a result of this sanctioning, public health content can reach fewer Facebook users. This study aims to determine the negative effect of engagement bait and find alternative techniques. In a three-year period, 791 smoking cessation support content was included (<i>n</i> = 791). The Facebook posts were classified into "engagement bait", "alternative techniques" and control groups. Facebook metrics were compared between the s ...[more]
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Project description:BackgroundSocial media offer a great opportunity to deliver smoking cessation treatment to young adults, but previous online and social media interventions targeting health behavior change have struggled with low participant engagement. We examined engagement generated by content based on the Transtheoretical Model of Behavior Change (TTM) in a motivationally tailored smoking cessation intervention on Facebook.ObjectiveThis study aimed to identify which intervention content based on the TTM (Decisional Balance and 10 processes of change) generated the highest engagement among participants in pre-action stages of change (Precontemplation, Contemplation, and Preparation).MethodsParticipants (N=79, 20% female, mean age 20.8) were assessed for readiness to quit smoking and assigned to one of 7 secret Facebook groups tailored to their stage of change. Daily postings to the groups based on TTM Decisional Balance and the 10 processes of change were made by research staff over 3 months. Engagement was operationalized as the number of participant comments to each post. TTM content-based predictors of number of comments were analyzed and stratified by baseline stage of change, using negative binomial regression analyses with and without zero inflation.ResultsA total of 512 TTM-based posts generated 630 individual comments. In Precontemplation and Contemplation groups, Decisional Balance posts generated above average engagement (P=.01 and P<.001). In Contemplation groups, posts based on the TTM processes Dramatic Relief and Self-Liberation resulted in below average engagement (P=.01 and P=.005). In Preparation groups, posts based on Consciousness Raising generated above average engagement (P=.009). Participant engagement decreased over time and differed between groups within Precontemplation and Contemplation stages, but was independent of day of the week and time of day the content was posted to the groups. No participant baseline characteristics significantly predicted engagement.ConclusionsParticipants not ready to quit in the next 30 days (in Precontemplation or Contemplation) engaged most when prompted to think about the pros and cons of behavior change, while those in the Preparation stage engaged most when posts increased awareness about smoking and smoking cessation. Findings support tailoring intervention content to readiness to quit and suggest intervention components that may be most effective in generating high participant engagement on social media.
| S-EPMC4704894 | biostudies-literature
Project description:BackgroundFacebook can be a suitable platform for public health interventions. Facebook users can express their reaction to the given social media content in many ways using interaction buttons. The analysis of these interactions can be advantageous in increasing reach and engagement of public health interventions.ObjectiveThis research aimed at understanding how Facebook users' interactions correlate with organic reach and engagement regarding the same smoking cessation support contents.MethodsThe study population consisted of Facebook users who were reached by a public smoking cessation support page without advertising. We included 1025 nonpaid Facebook posts (N=1025) which used smoking cessation strategies based on a motivational interviewing counseling style. The following data were collected from the "Post Details": the number of people who saw the given nonpaid content (organic reach) which consisted of fan and nonfan reach according to previous "page like" activity; each rate of "engagement indicators" (such as the symbols of "like," "love," "haha," "wow," "sad," "angry"; or other interactions: "shares," "comments," "clicks"); and the rate of negative Facebook interactions (eg, "post hides" or "unlike of page"). Overall, these data were analyzed with the Spearman correlation method.ResultsSurprisingly, we found a significant negative correlation between organic reach and the "like" reaction (rs=-0.418; P<.001). The strongest significant positive correlations of organic reach were observed with the "haha" reaction (rs=0.396; P<.001), comments (rs=0.368; P<.001), and the "love" reaction (rs=0.264; P<.001). Furthermore, nonfan reach correlated positively with "shares" (rs=0.388; P<.001) and clicks (rs=0.135; P<.001), while fan reach correlated positively with the "haha" reaction (rs=0.457; P<.001), comments (rs=0.393; P<.001), and the "love" reaction (rs=0.310; P<.001). Contrary to expectations, the "like" reaction was sharply separated by significant negative correlations from "wow" (rs=-0.077; P=.013), "sad" (rs=-0.120; P<.001), "angry" reactions (rs=-0.136; P<.001), and comments (rs=-0.130; P<.001). Additionally, a high rate of negative Facebook interactions was significantly associated with "wow" (rs=0.076; P=.016) and "sad" reactions (rs=0.091; P=.003).ConclusionsThis study has shown that it is possible to hypothesize a disadvantage of the "like" reaction and advantages of other interactions (eg, the "haha" reaction or "comments") in content algorithmic ranking on Facebook. In addition, the correlational analysis revealed a need of a further categorization to fan-specific interactions (eg, "haha" or "love" reactions) and nonfan-specific interactions (eg, "shares" and "clicks"). Regarding the direction of the correlations, these findings suggest that some interactions (eg, negative Facebook interactions, "wow," "sad," and "angry" reactions) may decrease the engagement, while other interactions ("like," "love," "haha" reactions, "shares," and "clicks") may increase the engagement during Facebook-based smoking cessation interventions. This hypothesis-generating research offers an important insight into the relationship between organic reach, engagement, and Facebook users' interactions for public health professionals who design Facebook-based interventions.
| S-EPMC8277334 | biostudies-literature
Project description:The "processes of change" and "motivational language" are common in smoker Facebook users' comments under smoking cessation support contents. Smokers can combine this verbalization of the smoking cessation process with visual expression when they use comments and Facebook reactions at the same time. The aim of this study was to understand the relationship between processes of change, motivational language, and the Facebook reaction buttons. A total of 821 smokers' comments were analyzed in the current study (n = 821), which responded to image-based smoking cessation support contents. The processes of change and the motivational language used in the investigated comments were identified. These linguistic categories were compared with the usage of reaction buttons. The Facebook users who used the "Haha" reaction button wrote a significantly higher proportion of sustain talk than those who used the "Like" or "Love" reaction buttons. The Facebook users who combined the comment and "Love" reaction wrote significantly more change talk than those who did not utilize these buttons. We suggest that the "Haha" reaction may be a negative indicator, the "Like" reaction may be a neutral indicator, and the "Love" reaction may be a positive engagement indicator in terms of the smoking cessation process during Facebook-based interventions. These results may highlight how to evaluate Facebook reactions relating to smoking cessation support contents.
| S-EPMC9408543 | biostudies-literature
Project description:IntroductionUsing WebQuit as a case study, a smoking cessation website grounded in Acceptance and Commitment Therapy, we aimed to identify sequence clusters of content usage and examine their associations with baseline characteristics, change to a key mechanism of action, and smoking cessation.MethodsParticipants were adult smokers allocated to the WebQuit arm in a randomized controlled trial (n = 1,313). WebQuit contains theory-informed content including goal setting, self-monitoring and feedback, and values- and acceptance-based exercises. Sequence analysis was used to temporally order 30-s website usage segments for each participant. Similarities between sequences were assessed with the optimal matching distance algorithm and used as input in an agglomerative hierarchical clustering analysis. Associations between sequence clusters and baseline characteristics, acceptance of cravings at 3 months and self-reported 30-day point prevalence abstinence at 12 months were examined with linear and logistic regression.ResultsThree qualitatively different sequence clusters were identified. "Disengagers" (576/1,313) almost exclusively used the goal-setting feature. "Tryers" (375/1,313) used goal setting and two of the values- and acceptance-based components ("Be Aware," "Be Willing"). "Committers" (362/1,313) primarily used two of the values- and acceptance-based components ("Be Willing," "Be Inspired"), goal setting, and self-monitoring and feedback. Compared with Disengagers, Committers demonstrated greater increases in acceptance of cravings (p = .01) and 64% greater odds of quit success (ORadj = 1.64, 95% CI = 1.18, 2.29, p = .003).DiscussionWebQuit users were categorized into Disengagers, Tryers, and Committers based on their qualitatively different content usage patterns. Committers saw increases in a key mechanism of action and greater odds of quit success.ImplicationsThis case study demonstrates how employing sequence and cluster analysis of usage data can help researchers and practitioners gain a better understanding of how users engage with a given eHealth intervention over time and use findings to test theory and/or to improve future iterations to the intervention. Future WebQuit users may benefit from being directed to the values- and acceptance-based and the self-monitoring and feedback components via reminders over the course of the program.
| S-EPMC8186423 | biostudies-literature
Project description:People living with HIV (PLWH) are more likely to smoke compared to HIV-uninfected counterparts, but little is known about smoking behaviors in sub-Saharan Africa. To address this gap in knowledge, we characterized smoking cessation patterns among people living with HIV (PLWH) compared to HIV-uninfected individuals in rural Uganda. PLWH were at least 40 years of age and on antiretroviral therapy for at least three years, and HIV-uninfected individuals were recruited from the clinical catchment area. Our primary outcome of interest was smoking cessation, which was assessed using an adapted WHO STEPS smoking questionnaire. We fit Cox proportional hazards models to compare time to smoking cessation between PLWH pre-care, PLWH in care, and HIV-uninfected individuals. We found that, compared to HIV-uninfected individuals, PLWH in care were less likely to have ever smoked (40% vs. 49%, p = 0.04). The combined sample of 267 ever-smokers had a median age of 56 (IQR 49-68), 56% (n = 150) were male, and 26% (n = 70) were current smokers. In time-to-event analyses, HIV-uninfected individuals and PLWH prior to clinic enrollment ceased smoking at similar rates (HR 0.8, 95% CI 0.5-1.2). However, after enrolling in HIV care, PLWH had a hazard of smoking cessation over twice that of HIV-uninfected individuals and three times that of PLWH prior to enrollment (HR 2.4, 95% CI 1.3-4.6, p = 0.005 and HR 3.0, 95% CI 1.6-5.5, p = 0.001, respectively). In summary, we observed high rates of smoking cessation among PLWH after engagement in HIV care in rural Uganda. While we hypothesize that greater access to primary care services and health counseling might contribute, future studies should better investigate the mechanism of this association.
| S-EPMC6258063 | biostudies-literature
Project description:IntroductionThe electronic cigarette (e-cigarette) market has evolved rapidly in recent years, with exploding growth in brands and product types; however, e-cigarette use among priority (sexual minority and low-income) populations and its relationship with smoking-cessation and tobacco control policies have yet to be fully characterized.MethodsThe authors conducted a nationally representative online survey of 17,522 U.S. adults in 2013. Participants were drawn from GfK's KnowledgePanel. Logistic regression models were used to analyze relationships between e-cigarettes (awareness, ever use, current use) and cigarette smoking and cessation behaviors, tobacco control policies, and demographics. Analyses were conducted in 2014.ResultsApproximately 15% of participants reported ever use of e-cigarettes, 5.1% reported current use, and 34.5% of ever users reported current use. E-cigarette awareness was lower among women, minorities, and those with low education. Ever and current use of e-cigarettes was higher among current cigarette smokers, young adults, and those with low SES; both ever use and current use were correlated with current cigarette smoking status, particularly when combined with quit intentions or attempts. Lesbian/gay/bisexual/transgender respondents had higher rates of ever use and current use. Ever use was lower in states with comprehensive smoking bans. No significant relationship between cigarette price and e-cigarette use was detected.ConclusionsOngoing surveillance of e-cigarette use among subpopulation groups and monitoring their use for combustible cigarette cessation are needed. Important variations in the patterns and correlates of e-cigarette awareness and use exist among priority populations. These findings have implications for future e-cigarette policy decisions.
| S-EPMC4718827 | biostudies-literature
Project description:IntroductionSocial media, including Facebook outreach, is increasingly being used as a participant recruitment tool, and may be particularly useful in tobacco and smoking cessation studies. The Recruitment Innovation Center at Vanderbilt University Medical Center partnered with Project LUNA, a smoking cessation study, to conduct a pilot social media campaign aimed at increasing study recruitment.MethodsTwo posts encouraging study participation were developed and promoted on Facebook to users with an interest in smoking-related topics, with a link to a study-specific webpage. Facebook and website analytics were collected, including impressions, clicks, click-through rates, website traffic, and clicks to the study screening form. Study screening and enrollment data were also collected.ResultsThe Facebook campaign ran in June 2019 in the greater Houston area. In total, the Facebook posts logged 1,179,844 impressions, 6490 clicks, and an overall click-through rate of 0.55%. There were no differences in response to the two different promotional posts. Approximately 3812 unique individuals visited an intermediary study page, with 473 expressing interest in the study. Forty-three potential participants contacted the study team, resulting in study enrollment and randomization of 23 participants, with an estimated cost per enrolled participant of $441.ConclusionsThe social media campaign was successful at increasing outreach and interest in the LUNA study. However, the price-per-participant enrolled was higher than in comparable tobacco cessation studies. These results and lessons learned may be beneficial to others considering social media as a recruitment method for their clinical research trial.
| S-EPMC8429250 | biostudies-literature
Project description:Hospital-based interventions promote smoking cessation after discharge. Strategies to deliver these interventions are needed, especially now that providing smoking cessation advice or treatment, or both, to inpatient smokers is a publicly reported quality-of-care measure for US hospitals.To assess the effect of adding a tobacco order set to an existing computerized order-entry system used to admit Medicine patients to 1 hospital.Pre-post study.Proportion of admitted patients who had smoking status identified, a smoking counselor consulted, or nicotine replacement therapy (NRT) ordered during 4 months before and after the change. In 4 months after implementation, the order set was used with 76% of Medicine admissions, and a known smoking status was recorded for 81% of these patients. The intervention increased the proportion of admitted patients who were referred for smoking counseling (0.8 to 2.1%) and had NRT ordered (1.6 to 2.5%) (p < .0001 for both). Concomitantly, the hospital's performance on the smoking cessation quality measure improved.Adding a brief tobacco order set to an existing computerized order-entry system increased a hospital's provision of evidence-based tobacco treatment and helped to improve its performance on a publicly reported quality measure. It provides a model for US hospitals seeking to improve their quality of care for inpatients.
| S-EPMC2517966 | biostudies-other
Project description:Adolescent cigarette smokers have an increased risk of sustained smoking into adulthood. Smartphone applications (apps) for smoking cessation are a promising treatment resource. However, research on apps for adolescent smoking cessation is limited. This study compared smoking cessation mobile apps targeting an adolescent audience with popular cessation apps for a general audience. Adolescent and general-audience apps were identified by searching the Google Play and Apple App Stores (November 2016). Two coders assessed each app for adherence to clinical practice guidelines for tobacco and adolescent-specific content (2016-2017) and developed a summary score that summed all adherence and adolescent content criteria. Eight adolescent apps were identified and compared with the top 38 general apps (as ranked by Apple and Google). Both general and adolescent apps commonly had adherence content related to developing a quit plan (general: 73.68 per cent; adolescent: 87.50 per cent) and enhancing motivation by describing the rewards of not smoking (general: 76.32 per cent; adolescent: 62.50 per cent). Adolescent-specific content such as peer influence on smoking was common in adolescent apps but not in general apps (general: 5.26 per cent; adolescent: 62.50 per cent). Adolescent apps had a higher general adherence content summary score [t (44) = 2.55, p = .01] and a higher adolescent content summary score [t (7.81) = 2.47, p = .04] than the general apps. On average, adolescent cessation apps included more adherence content and adolescent-specific content than general apps. Future research is needed to determine the extent to which adolescents engage with the adherence content available in these apps.
| S-EPMC7295698 | biostudies-literature
Project description:BackgroundMany people use apps for smoking cessation, and the effectiveness of these apps has been proven in several studies. However, no study has classified these apps and only few studies have analyzed the characteristics of these apps that influence their quality.ObjectiveThe purpose of this study was to analyze the content and the quality of smoking cessation apps by type and identify the characteristics that affect their overall quality.MethodsTwo app marketplaces (App Store and Google Play) were searched in January 2018, and the search was completed by May 2020. The search terms used were "stop smoking," "quit smoking," and "smoking cessation." The apps were categorized into 3 types (combined, multifunctional, and informational). The tailored guideline of Clinical Practice Guideline for Treating Tobacco Use and Dependence was utilized for evaluating app content (or functions), and the Mobile App Rating Scale (MARS) was used to evaluate the quality. Chi-square test was performed for the general characteristics, and one-way analysis of variance was performed for MARS analysis. To identify the general features of the apps that could be associated with the MARS and content scores, multiple regression analysis was done. All analyses were performed using SAS software (ver. 9.3).ResultsAmong 1543 apps, 104 apps met the selection criteria of this study. These 104 apps were categorized as combined type (n=44), functional type (n=31), or informational type (n=29). A large amount of content specified in the guideline was included in the apps, most notably in the combined type, followed by the multifunctional and informational type; the MARS scores followed the same order (3.64, 3.26, and 3.0, respectively). Regression analysis showed that the sector in which the developer was situated and the feedback channel with the developer had a significant impact on both the content and MARS scores. In addition, problematic apps such as those made by unknown developers or copied and single-function apps were shown to have a large market share.ConclusionsThis study is the first to evaluate the content and quality of smoking cessation apps by classification. The combined type had higher-quality content and functionality than other app types. The app developer type and feedback channel with the app developer had a significant impact on the overall quality of the apps. In addition, problematic apps and single-function apps were shown to have a large market share. Our results will contribute to the use and development of better smoking cessation apps after considering the problems identified in this study.
| S-EPMC8895289 | biostudies-literature