Factors Associated with Cancer Message Believability: a Mixed Methods Study on Simulated Facebook Posts.
Ontology highlight
ABSTRACT:
SUBMITTER: Trivedi N
PROVIDER: S-EPMC8213533 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BACKGROUND:Incidence rate of cancer is increasing worldwide, with longer life expectancy being one of the main causes. Yet, between 30% and 50% of cancer cases are preventable, and early detection contributes to a better prognosis. This makes health communication strategies essential. Facebook, the world's most used social networking site in 2017 and 2018, can be a useful tool for disseminating powerful messages on health promotion, prevention, and early detection. OBJECTIVE:We aimed to (1) offer ways of optimizing health messages about cancer on Facebook, focusing on topics, such as risk factors, prevention, treatment, early diagnosis, and cure, and (2) investigate which aspects of these messages generate greater engagement. METHODS:To verify what generates greater engagement in topics related to cancer on Facebook, we analyzed 16 Brazilian pages with the main theme of cancer. We performed a manual analysis of texts, content, and engagement rates. Finally, we developed a software program to operationalize the analysis of Facebook posts. The tool we devised aims to automate the analysis of any Facebook page with cancer as the main theme. RESULTS:We analyzed 712 posts over a 1-month period. We divided the posts into the following 8 categories: "Testimonies or real-life stories," "Solidarity," "Anniversaries," "Science and health," "Events," "Institutional," "Risk factors," and "Beauty." The pages were also organized into groups according to the type of profile to which they belonged (ie, hospitals or foundations, informative, nongovernmental organizations, and personal pages).The results showed that the categories generating greater engagement in Brazil were not those with the highest percentage of cancer-related content. For instance, in the "Informative" group the "Testimonies or real-life stories" category generated an engagement of 79.5%. However, only 9.5% (25/261) of the content within the relevant time period dealt with such topics. Another example concerns the category "Science and health." Despite being the one with the highest number of posts (129/261, 49.4%), it scored 5th in terms of engagement. This investigation served as the basis for the development of a tool designed to automate the analysis of Facebook pages. The list of categories and keywords generated by this analysis was employed to feed the system, which was then able to categorize posts appearing on a Facebook page. We tested the system on 163 posts and only 34 were classified incorrectly, which amounts to a 20.8% error rate (79.2% accuracy). CONCLUSIONS:The analysis we conducted by categorizing posts and calculating engagement rates shows that the potential of Facebook pages is often underutilized. This occurs because the categories that generate the greatest engagement are often not those most frequently used. The software developed in this research may help administrators of cancer-related pages analyze their posts more easily and increase public interest as a result.
| S-EPMC6315252 | biostudies-literature
Project description:BACKGROUND:The field of infodemiology uses health care trends found in public networks, such as social media, to track and quantify the spread of disease. Type 2 diabetes is on the rise worldwide, and social media may be useful in identifying prediabetes through behavior exhibited through social media platforms such as Facebook and thus in designing and administering early interventions and containing further progression of the disease. OBJECTIVE:This pilot study is designed to investigate the social media behavior of individuals with prediabetes, before and after diagnosis. Pre- and postdiagnosis Facebook content (posts) of such individuals will be used to create a taxonomy of prediabetes indicators and to identify themes and factors associated with an actual diagnosis of prediabetes. METHODS:This is a single-center exploratory retrospective study that examines 20 adults with prediabetes. The investigators will code Facebook posts 3 months before through 3 months after prediabetes diagnosis. Data will be analyzed using both qualitative content analysis methodology as well as quantitative methodology to characterize participants and compare their posts pre- and postdiagnosis. RESULTS:The project was funded for 2015-2018, and enrollment will be completed by the end of 2018. Data coding is currently under way and the first results are expected to be submitted for publication in 2019. Results will include both quantitative and qualitative data about participants and the similarities and differences between coded social media posts. CONCLUSIONS:This pilot study is the first step in creating a taxonomy of social media indicators for prediabetes. Such a taxonomy would provide a tool for researchers and health care professionals to use social media postings for identifying those at greater risk of having prediabetes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID):DERR1-10.2196/10720.
| S-EPMC6315248 | biostudies-literature
Project description:BackgroundSubstance use among young pregnant women is a common and significant public health concern associated with a number of adverse outcomes for both mothers and infants. Social media posts by young women can provide valuable, real-world insight into their perceptions of substance use immediately before and during pregnancy.ObjectiveThe aim of this study was to characterize the frequency and content of posts regarding substance use in the year before pregnancy and during pregnancy among young mothers.MethodsFacebook posts were mined from young pregnant women (age, 16-24 years) who consented from 2 Midwest primary care clinics that serve a predominantly low-income community. Natural language processing was used to identify posts related to substance use by keyword searching (eg, drunk, drugs, pot, and meth). Using mixed-methods techniques, 2 investigators iteratively coded and identified major themes around substance use from these mined Facebook posts. Outcome measures include the frequency of posts and major themes expressed regarding substance use before and during pregnancy.ResultsWomen in our sample (N=43) had a mean age of 21 (SD 2.3) years, and the largest subgroup (21/43, 49%) identified as non-Hispanic black; 26% (11/43) identified as non-Hispanic white; 16% (7/43) as Hispanic; and 9% (4/43) as non-Hispanic mixed race, Native American, or other. The largest subgroup (20/43, 47%) graduated high school without further education, while 30% (13/43) completed only some high school and 23% (10/43) completed at least some postsecondary education. Young women discussed substance use on social media before and during pregnancy, although compared with the year before pregnancy, the average frequency of substance-related posts during pregnancy decreased. Themes identified included craving alcohol or marijuana, social use of alcohol or marijuana, reasons for abstaining from substance use, and intoxication.ConclusionsFacebook posts reveal that young pregnant women discuss the use of substances, predominantly alcohol and marijuana. Future work can explore clinical opportunities to prevent and treat substance use before and during pregnancy among young, at-risk mothers.
| S-EPMC6716430 | biostudies-literature
Project description:Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research have produced predictions slightly better than chance (AUCs = 0.56-0.58). In this study, Artificial Neural Network (ANN) models were constructed to predict suicide risk from everyday language of social media users. The dataset included 83,292 postings authored by 1002 authenticated Facebook users, alongside valid psychosocial information about the users. Using Deep Contextualized Word Embeddings for text representation, two models were constructed: A Single Task Model (STM), to predict suicide risk from Facebook postings directly (Facebook texts → suicide) and a Multi-Task Model (MTM), which included hierarchical, multilayered sets of theory-driven risk factors (Facebook texts → personality traits → psychosocial risks → psychiatric disorders → suicide). Compared with the STM predictions (0.621 ≤ AUC ≤ 0.629), the MTM produced significantly improved prediction accuracy (0.697 ≤ AUC ≤ 0.746), with substantially larger effect sizes (0.729 ≤ d ≤ 0.936). Subsequent content analyses suggested that predictions did not rely on explicit suicide-related themes, but on a range of text features. The findings suggest that machine learning based analyses of everyday social media activity can improve suicide risk predictions and contribute to the development of practical detection tools.
| S-EPMC7542168 | biostudies-literature
Project description:BackgroundChildhood cancers previously considered to be incurable now have 5-year survival rates up to 84%. Nevertheless, these patients remain at risk of morbidity and mortality from therapy-related complications. Thus, patient education and self-management strategies for promoting a healthy lifestyle are of tantamount importance for improving short- and long-term health outcomes. A Facebook-based "Healthy Teens for Soaam" (a Korean term for childhood cancers) program was developed to help improve knowledge and self-management practices of teens with cancer related to their disease and treatment.ObjectiveThe two-fold purpose of this usability study was (1) to describe the process of developing an 8-week Facebook-based intervention program for teens with cancer, and (2) to evaluate its usability to refine the program.MethodsMultiple phases and methods were employed to develop and evaluate the usability of the program. Study phases included: (1) needs assessment through focus group interviews and qualitative content analysis, (2) development of module content, (3) expert review and feedback on module content, (4) Facebook-based program development, (5) usability evaluation by heuristic evaluation, (6) usability evaluation by targeted end-user testing, and (7) modification and final version of the program. Usability of the final version was confirmed through feedback loops of these phases.ResultsBased on 6 focus group discussion sessions, it was determined that teens with cancer were interested in seeing stories of successful childhood cancer cases and self-management after discharge, and preferred multimedia content over text. Therefore, each Facebook module was redesigned to include multimedia materials such as relevant video clips tailored for teens. Usability assessed by heuristic evaluation and user testing revealed several critical usability issues, which were then revised. Potential end users tested the final program and perceived it to be usable and useful for teens with cancer.ConclusionsTo our knowledge, "Healthy Teens for Soaam" is the first Facebook-based intervention program for teens with cancer. We actively worked with current childhood cancer patients and survivors to develop and improve this program, achieved good usability, and met the expressed needs and preferences of target end users. This 8-week Facebook-based educational program for teens with cancer, developed as the first step of an upcoming intervention study, will be useful for improving knowledge and self-management strategies of teens.
| S-EPMC7420636 | biostudies-literature
Project description:Peer mentoring is a powerful pedagogical approach for supporting undergraduate medical students in their learning environment. However, it remains unclear what exactly peer mentoring is and whether and how undergraduate medical students use social media for peer-mentoring activities.We aimed at describing and exploring the Facebook use of undergraduate medical students during their first 2 years at a German medical school. The data should help medical educators to effectively integrate social media in formal mentoring programs for medical students.We developed a coding scheme for peer mentoring and conducted a mixed-methods study in order to explore Facebook groups of undergraduate medical students from a peer-mentoring perspective.All major peer-mentoring categories were identified in Facebook groups of medical students. The relevance of these Facebook groups was confirmed through triangulation with focus groups and descriptive statistics. Medical students made extensive use of Facebook and wrote a total of 11,853 posts and comments in the respective Facebook groups (n=2362 total group members). Posting peaks were identified at the beginning of semesters and before exam periods, reflecting the formal curriculum milestones.Peer mentoring is present in Facebook groups formed by undergraduate medical students who extensively use these groups to seek advice from peers on study-related issues and, in particular, exam preparation. These groups also seem to be effective in supporting responsive and large-scale peer-mentoring structures; formal mentoring programs might benefit from integrating social media into their activity portfolio.
| S-EPMC5041359 | biostudies-other
Project description:BackgroundAdolescents and young adults frequently post alcohol-related content (ie, alcoholposts) on social media. This is problematic because both social norms theory and social learning theory suggest that viewing alcoholposts of peers could increase drinking behavior. It is therefore paramount to understand the effects of exposure to alcoholposts on viewers.ObjectiveThis study aimed to investigate the causal effects of exposure to alcoholposts on alcohol consumption by using a rigorous design.MethodsWe conducted a 6-week longitudinal study during which alcoholposts were measured by a newly developed app that copied Facebook posts shared by participants (n=281) to a new social media environment. In addition, daily questionnaires assessed alcohol use. Effects of natural alcoholposts (ie, posted by the participants) were assessed in phase 1, and effects of experimental posts (ie, posted by fake participants) were explored in phase 2.ResultsResults showed that natural alcoholposts increased the occurrence and quantity of drinking the following day. That is, exposure to a single additional alcoholpost increased the log odds of drinking the next day by 0.27 (b=.27, credible interval [CI] .18 to .35). Furthermore, the number of natural alcoholposts had a positive (predictive) effect on the number of glasses drunk the next day (b=.21, CI .14 to .29). In phase 2 when experimental posts were also present, these effects decreased. Experimental posts themselves had hardly any effects.ConclusionsThis study illustrates clear and direct effects of exposure to alcoholposts on next-day alcohol consumption and suggests that alcoholposts represent an important societal problem that interventions need to address.
| S-EPMC8663476 | biostudies-literature
Project description:Taking advantage of 3 million English-language posts by Facebook public pages, this study answers the following questions: How did the amount of COVID-19 vaccine-related messages evolve? How did the moral expressions in the messages differ among sources? How did both the sources and the five moral foundations in posts influence the number of likes to posts, after controlling for the public page's features (e.g., age, followers)? Our research findings suggest that moral expression is prevalent in the COVID-19 vaccination posts, surpassing nonmoral content. Media sources, despite the high volume of posts, on average elicited fewer likes than all other sources. Although care and fairness were the two most used moral foundations, they were negatively related to likes. In contrast, the least used two moral values of authority and sanctity were positively related to likes. We conclude with a discussion of theoretical contributions and a recommendation of possible interventions.
| S-EPMC9451497 | biostudies-literature
Project description:Background: After traumatic brachial plexus injuries (BPI), the sudden loss of physical function is often accompanied by psychological distress. Given the complex nature and relative infrequency of the injury, BPI patients will often use online resources for information about their injury as well as emotional support. Questions/Purpose: Recognizing the influence of social media, we sought to search a popular social media platform to identify challenges faced by BPI patients and strategies used to overcome these challenges. Methods: We searched "traumatic brachial plexus injury" on Facebook and selected the 2 most popular BPI support groups. We collected posts regarding traumatic BPI from November 1, 2018 through November 1, 2019. We performed inductive and deductive thematic analysis of the posts to identify recurring topics, knowledge gaps, and peer interaction dynamics. Results: We analyzed 7694 posts from the 2 Facebook support groups. The following themes emerged: (1) BPI patients express discontent regarding the inability to use their arm and the slow or stagnant pace of recovery; (2) BPI patients are frustrated over their inability to retain their preinjury livelihood; and (3) BPI patients emphasize that acceptance and moving on are key components of adjustment to their condition. Some patients described the role of limb amputation in achieving these goals. Conclusions: Our analysis demonstrates the areas in which BPI patients are in need of emotional support. Adjustment to BPI might be facilitated through multidisciplinary care that addresses emotional aspects of recovery and emphasizes self-management skills, in addition to the traditional focus on physical function.
| S-EPMC8361598 | biostudies-literature
Project description:Analysis of population genetic structure has become a standard approach in population genetics. In polyploid complexes, clustering analyses can elucidate the origin of polyploid populations and patterns of admixture between different cytotypes. However, combining diploid and polyploid data can theoretically lead to biased inference with (artefactual) clustering by ploidy. We used simulated mixed-ploidy (diploid-autotetraploid) data to systematically compare the performance of k-means clustering and the model-based clustering methods implemented in STRUCTURE, ADMIXTURE, FASTSTRUCTURE and INSTRUCT under different scenarios of differentiation and with different marker types. Under scenarios of strong population differentiation, the tested applications performed equally well. However, when population differentiation was weak, STRUCTURE was the only method that allowed unbiased inference with markers with limited genotypic information (co-dominant markers with unknown dosage or dominant markers). Still, since STRUCTURE was comparatively slow, the much faster but less powerful FASTSTRUCTURE provides a reasonable alternative for large datasets. Finally, although bias makes k-means clustering unsuitable for markers with incomplete genotype information, for large numbers of loci (>1000) with known dosage k-means clustering was superior to FASTSTRUCTURE in terms of power and speed. We conclude that STRUCTURE is the most robust method for the analysis of genetic structure in mixed-ploidy populations, although alternative methods should be considered under some specific conditions.
| S-EPMC6781132 | biostudies-literature