Social Network Behavior and Engagement Within a Smoking Cessation Facebook Page

Supporting and Incentivizing Peer Leaders for an Internet-Based Private Peer Community for Youths With Type 1 Diabetes: Social Network and Directed Content Analysis

BACKGROUND

Youths with type 1 diabetes (T1D) frequently experience stigma. Internet-based peer communities can mitigate this through social support but require leaders to catalyze exchange. Whether nurturing potential leaders translates into a central role has not been well studied. Another issue understudied in such communities is lurking, the viewing of exchanges without commenting or posting.

OBJECTIVE

We aimed to assess the centrality of the peer leaders we selected, trained, and incentivized within the Canadian Virtual Peer Network (VPN)-T1D. This is a private Facebook (Meta Platforms, Inc) group that we created for persons aged 14 to 24 years with T1D. We specifically sought to (1) compare a quantitative estimate of network centrality between peer leaders and regular members, (2) assess the proportions of network exchanges that were social support oriented, and (3) assess proportions of high engagement (posts, comments, reactions, and votes) and low engagement (lurking) exchanges.

METHODS

We recruited peer leaders and members with T1D from prior study cohorts and clinics. We trained 10 leaders, provided them with a monthly stipend, and encouraged them to post on the private Facebook group we launched on June 21, 2017. We extracted all communications (posts, messages, reactions, polls, votes, and views) that occurred until March 20, 2020. We calculated each member's centrality (80% of higher engagement communications comprising posts, comments, and reactions plus 20% of members with whom they connected). We divided each member's centrality by the highest centrality to compute the relative centrality, and compared the mean values between leaders and members (linear regression). We calculated the proportions of communications that were posts, comments, reactions, and views without reaction. We performed content analysis with a social support framework (informational, emotional, esteem-related, network, and tangible support), applying a maximum of 3 codes per communication.

RESULTS

VPN-T1D gained 212 regular members and 10 peer leaders over 33 months; of these 222 members, 26 (11.7%) exited. Peer leaders had 10-fold higher relative centrality than regular members (mean 0.53, SD 0.26 vs mean 0.04, SD 0.05; 0.49 difference; 95% CI 0.44-0.53). Overall, 91.4% (203/222) of the members connected at least once through posts, comments, or reactions. Among the 75,051 communications, there were 5109 (6.81%) posts, comments, and polls, 6233 (8.31%) reactions, and 63,709 (84.9%) views (lurking). Moreover, 54.9% (3430/6253) of codes applied were social support related, 66.4% (2277/3430) of which were informational (eg, insurance and travel preparation), and 20.4% (699/3430) of which were esteem related (eg, relieving blame).

CONCLUSIONS

Designating, training, and incentivizing peer leaders may stimulate content exchange and creation. Social support was a key VPN-T1D deliverable. Although lurking accounted for a high proportion of the overall activity, even those demonstrating this type of passive participation likely derived benefits, given that the network exit rate was low.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/18714.

Graph theoretical way of understanding protein-protein interaction in ovarian cancer

Cancer is a major research area in the medical field. Precise assessment of non-similar cancer types holds great significance in according to better treatment and reducing the risk of destructiveness in patients’ health. Cancer comprises a ambient that differs in response to therapy, signaling mechanisms, cytology and physiology. Netting theory and graph theory jointly gives a viable way to probe the proteomic specific data of cancer types such as ovarian, colon, breast, oral, cervical, prostate, and lung. We observe that the P2P(protein-protein) interaction Nettings of the cancerous tissues blended with the seven cancers and normal have same structural attributes. But some of these point to desultory changes from the disease Nettings to normal implying the variation in the dealings and bring out the redoing in the complicacy of various cancers. The Netting-based approach has a pertinent role in precision oncology. Cancer can be better dealt with through mutated pathways or Nettings in preference to individual mutations and that the utility value of repositioned drugs can be understood from disease modules in molecular Nettings. In this paper, we demonstrate how the graph theory and neural Nettings act as vital tools for understanding cancer and other types such as ovarian cancer at the zeroth level.

Exploring the Use of a Facebook-Based Support Group for Caregivers of Children and Youth With Complex Care Needs: Qualitative Descriptive Study

BACKGROUND

Caregivers of children and youth with complex care needs (CCN) require substantial support to ensure the well-being of their families. Web-based peer-to-peer (P2P) support groups present an opportunity for caregivers to seek and provide timely informational and emotional support. Despite the widespread use of social media for health-related support across diverse patient and caregiver populations, it is unclear how caregivers of children and youth with CCN use and potentially benefit from these groups.

OBJECTIVE

The aim of this study is to explore the use of a web-based P2P support group for caregivers of children and youth with CCN in New Brunswick, Canada, and investigate factors related to its use by members.

METHODS

The study sample consisted of individuals who joined a closed Facebook group and an analysis of content published to the group. In phase 1, a Facebook group was developed in consultation with a patient and family advisory council, and members were recruited to the group. Phase 2 of this study consisted of an observation period during which posts and related interactions (ie, likes, loves, and comments) by members were collected. In phase 3, a web-based survey was distributed, and semistructured interviews were conducted with a subsample of group members. Survey and interview data were analyzed using thematic analysis.

RESULTS

A total of 108 caregivers joined the Facebook group between October 2020 and March 2021. There were 93 posts with 405 comments and 542 associated interactions (448/542, 82.7% likes and 94/542, 17.3% loves). Of these 93 posts, 37 (40%) were made by group members, and 56 (60%) were made by moderators. Of the 108 members, a subsample of 39 (36.1%) completed a web-based survey, and 14 (13%) participated in the interviews. Content analyses of posts by members revealed that inquiry (17/37, 46%), informational (15/37, 41%), and emotional posts (4/37, 11%) were the most common. Emotional posts received the highest number of interactions (median 24.5). In total, 5 themes emerged from the interviews related to the use of the group and mediating factors of interactions between group members: resource for information, altruistic contribution, varying level of engagement, perceived barriers to and facilitators of group activity, and moderators as contributing members.

CONCLUSIONS

These findings demonstrate that caregivers of children and youth with CCN seek geography-specific P2P support groups to meet informational and social support needs. This study contributes to the knowledge on how caregivers use Facebook groups to meet their support needs through moderate and passive engagement.

Contextualizing Engagement With Health Information on Facebook: Using the Social Media Content and Context Elicitation Method

Background

Most of what is known regarding health information engagement on social media stems from quantitative methodologies. Public health literature often quantifies engagement by measuring likes, comments, and/or shares of posts within health organizations’ Facebook pages. However, this content may not represent the health information (and misinformation) generally available to and consumed by platform users. Furthermore, some individuals may prefer to engage with information without leaving quantifiable digital traces. Mixed methods approaches may provide a way of surpassing the constraints of assessing engagement with health information by using only currently available social media metrics.

Objective

This study aims to discuss the limitations of current approaches in assessing health information engagement on Facebook and presents the social media content and context elicitation method, a qualitatively driven, mixed methods approach to understanding engagement with health information and how engagement may lead to subsequent actions.

Methods

Data collection, management, and analysis using the social media content and context elicitation method are presented. This method was developed for a broader study exploring how and why US Latinos and Latinas engage with cancer prevention and screening information on Facebook. The study included 20 participants aged between 40 and 75 years without cancer who participated in semistructured, in-depth interviews to discuss their Facebook use and engagement with cancer information on the platform. Participants accessed their Facebook account alongside the researcher, typed cancer in the search bar, and discussed cancer-related posts they engaged with during the previous 12 months. Engagement was defined as liking, commenting, and/or sharing a post; clicking on a post link; reading an article in a post; and/or watching a video within a post. Content engagement prompted questions regarding the reasons for engagement and whether engagement triggered further action. Data were managed using MAXQDA (VERBI GmbH) and analyzed using thematic and content analyses.

Results

Data emerging from the social media content and context elicitation method demonstrated that participants mainly engaged with cancer prevention and screening information by viewing and/or reading content (48/66, 73%) without liking, commenting, or sharing it. This method provided rich content regarding how US Latinos and Latinas engage with and act upon cancer prevention and screening information on Facebook. We present 2 emblematic cases from the main study to exemplify the additional information and context elicited from this methodology, which is currently lacking from quantitative approaches.

Conclusions

The social media content and context elicitation method allows a better representation and deeper contextualization of how people engage with and act upon health information and misinformation encountered on social media. This method may be applied to future studies regarding how to best communicate health information on social media, including how these affect assessments of message credibility and accuracy, which can influence health outcomes.

Linking Network Characteristics of Online Social Networks to Individual Health: A Systematic Review of Literature

Social networks have long been viewed as a structural determinant of health. With the proliferation of digital technologies, numerous studies have examined the health implications of online social networks (OSNs). However, the mechanisms through which OSNs may influence individual health are poorly understood. Employing a social network approach, this paper presents a systematic review of the literature examining how network characteristics of OSNs are linked to individuals' health behavior and/or status. Drawing on keyword searches in nine databases, we identified and analyzed 22 relevant articles from 1,705 articles published prior to 2017. The findings show that individual health is associated with a number of network characteristics, including both individual-level attributes (e.g., centrality) and network-level attributes (e.g., density, clustering). All of the included studies (n = 22) have focused on egocentric networks, and nine studies also collected whole network data of online health communities. Based on our review, we highlight three fruitful areas in the application of OSNs in public health: (1) disease and risk detection, (2) disease prevention and intervention, and (3) health behavior change. However, the precise mechanisms and causal pathways through which OSNs affect health remain unclear. More theoretically grounded, longitudinal, and mixed methods research is needed to advance this line of research.

Application of Automated Text Analysis to Examine Emotions Expressed in Online Support Groups for Quitting Smoking

Online support groups offer social support and an outlet for expressing emotions when dealing with health-related challenges. This study examines whether automated text analysis of emotional expressions using Linguistic Inquiry and Word Count (LIWC) can identify emotions related to abstinence expressed in online support groups for quitting smoking, suggesting promise for offering targeted mood management to members. The emotional expressions in 1 month of posts by members of 36 online support groups were related to abstinence at month end. Using the available LIWC dictionary, posts were scored for overall positive emotions, overall negative emotions, anxiety, anger, sadness, and an upbeat emotional tone. Greater expressions of negative emotions, and specifically anxiety, related to nonabstinence, while a more upbeat emotional tone related to abstinence. The results indicate that automated text analysis can identify emotions expressed in online support groups for quitting smoking and enable targeted delivery of mood management to group members.

Facebook Users' Interactions, Organic Reach, and Engagement in a Smoking Cessation Intervention: Content Analysis

Background

Facebook 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.

Objective

This research aimed at understanding how Facebook users’ interactions correlate with organic reach and engagement regarding the same smoking cessation support contents.

Methods

The 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.

Results

Surprisingly, we found a significant negative correlation between organic reach and the “like” reaction (r_s=–0.418; P<.001). The strongest significant positive correlations of organic reach were observed with the “haha” reaction (r_s=0.396; P<.001), comments (r_s=0.368; P<.001), and the “love” reaction (r_s=0.264; P<.001). Furthermore, nonfan reach correlated positively with “shares” (r_s=0.388; P<.001) and clicks (r_s=0.135; P<.001), while fan reach correlated positively with the “haha” reaction (r_s=0.457; P<.001), comments (r_s=0.393; P<.001), and the “love” reaction (r_s=0.310; P<.001). Contrary to expectations, the “like” reaction was sharply separated by significant negative correlations from “wow” (r_s=–0.077; P=.013), “sad” (r_s=–0.120; P<.001), “angry” reactions (r_s=–0.136; P<.001), and comments (r_s=–0.130; P<.001). Additionally, a high rate of negative Facebook interactions was significantly associated with “wow” (r_s=0.076; P=.016) and “sad” reactions (r_s=0.091; P=.003).

Conclusions

This 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.

Social Network Analysis of an Online Smoking Cessation Community to Identify Users' Smoking Status

Objectives

Users share valuable information through online smoking cessation communities (OSCCs), which help people maintain and improve smoking cessation behavior. Although OSCC utilization is common among smokers, limitations exist in identifying the smoking status of OSCC users (“quit” vs. “not quit”). Thus, the current study implicitly analyzed user-generated content (UGC) to identify individual users’ smoking status through advanced computational methods and real data from an OSCC.

Methods

Secondary data analysis was conducted using data from 3,833 users of BcomeAnEX.org. Domain experts reviewed posts and comments to determine the authors’ smoking status when they wrote them. Seven types of feature sets were extracted from UGC (textual, Doc2Vec, social influence, domain-specific, author-based, and thread-based features, as well as adjacent posts).

Results

Introducing novel features boosted smoking status recognition (quit vs. not quit) by 9.3% relative to the use of text-only post features. Furthermore, advanced computational methods outperformed baseline algorithms across all models and increased the smoking status prediction performance by up to 12%.

Conclusions

The results of this study suggest that the current research method provides a valuable platform for researchers involved in online cessation interventions and furnishes a framework for on-going machine learning applications. The results may help practitioners design a sustainable real-time intervention via personalized post recommendations in OSCCs. A major limitation is that only users’ smoking status was detected. Future research might involve programming machine learning classification methods to identify abstinence duration using larger datasets.

Use of social media data for disease based social network analysis and network modeling: A Systematic Review

Burden due to infectious and noncommunicable disease is increasing at an alarming rate. Social media usage is growing rapidly and has become the new norm of communication. It is imperative to examine what is being discussed in the social media about diseases or conditions and the characteristics of the network of people involved in discussion. The objective is to assess the tools and techniques used to study social media disease networks using network analysis and network modeling. PubMed and IEEEXplore were searched from 2009 to 2020 and included 30 studies after screening and analysis. Twitter, QuitNet, and disease-specific online forums were widely used to study communications on various health conditions. Most of the studies have performed content analysis and network analysis, whereas network modeling has been done in six studies. Posts on cancer, COVID-19, and smoking have been widely studied. Tools and techniques used for network analysis are listed. Health-related social media data can be leveraged for network analysis. Network modeling technique would help to identify the structural factors associated with the affiliation of the disease networks, which is scarcely utilized. This will help public health professionals to tailor targeted interventions.

The perception of nurses towards their roles during the COVID-19 pandemic

PURPOSE

The study aims to evaluate the available content on local Jordanian Facebook nursing groups regarding perception of their roles during coronavirus pandemic.

METHOD

Researchers used the Facebook search engine to select local Facebook groups.

RESULTS

Nurses were perceived to perform a constructive role when acting as the first-line health provider, having a public awareness role and providing care for patients. Advocating and supporting the sick and their families, ignoring and underestimating their role, nurses have a positive perception of their roles during the coronavirus pandemic. Besides being responsible for their daily activities during the epidemic, they had additional roles of ensuring the safety and contentment of their patients.

CONCLUSION

In general, nurses in Jordan perceived their roles during the COVID-19 outbreak to be constructive. They performed the task of supporting and advocating for the sick and their families. Despite these efforts during the outbreak.

IMPLICATION FOR NURSING

Nurses in general, nursing leaders and managers are in the forefront of responding to the unique needs of their workforces during the COVID-19 crisis. There must be an explicit adoption of strategy in all clinical environments and other clinical institutions to enhance the nurse image among themselves and community members.

Connectedness Based on Shared Engagement Predicts Remote Biochemically Verified Quit Status Within Smoking Cessation Treatment Groups on Facebook

INTRODUCTION

Engagement with online content and online social network integration are associated with smoking behavior change, but less is known about social dynamics of shared engagement between participants in group-based social media interventions.

METHODS

Participants were 251 young adult smokers aged 18 to 25 assigned to one of 29 secret Facebook groups tailored to their readiness to quit smoking ("pre-contemplation," "contemplation," and "preparation"). Groups varied in size and were randomly assigned to receive monetary incentives for engagement. All groups received daily posts for 90 days and were assessed for remote biochemically verified smoking abstinence at the end of the intervention. Across 29 groups, we examined associations between group features (group size, incentive condition, readiness to quit) with how connected members were within the group based on shared engagement with the same content (measured by density). At the individual level, we examined associations between 7-day biochemically verified smoking abstinence and how connected an individual was within the group (measured by degree centrality).

RESULTS

After adjusting for comment volume, being in a contemplation group (vs. pre-contemplation group) was associated with a decrease in comment-based density. Individual degree centrality was significantly associated with biochemically verified smoking abstinence for both comments and likes.

CONCLUSIONS

Future group-based social media interventions for smoking cessation may want to focus on promoting connected engagement between participants, rather than simply quantity of engagement.

IMPLICATIONS

Participants in a smoking cessation intervention delivered through Facebook groups were more likely to have biochemically verified smoking abstinence if they were more connected to the rest of the group via shared engagement. Promoting shared engagement between participants may be more likely to promote behavior change than volume of engagement alone.

EREBOTS: Privacy-Compliant Agent-Based Platform for Multi-Scenario Personalized Health-Assistant Chatbots

Context. Asynchronous messaging is increasingly used to support human–machine interactions, generally implemented through chatbots. Such virtual entities assist the users in activities of different kinds (e.g., work, leisure, and health-related) and are becoming ingrained into humans’ habits due to factors including (i) the availability of mobile devices such as smartphones and tablets, (ii) the increasingly engaging nature of chatbot interactions, (iii) the release of dedicated APIs from messaging platforms, and (iv) increasingly complex AI-based mechanisms to power the bots’ behaviors. Nevertheless, most of the modern chatbots rely on state machines (implementing conversational rules) and one-fits-all approaches, neglecting personalization, data-stream privacy management, multi-topic management/interconnection, and multimodal interactions. Objective. This work addresses the challenges above through an agent-based framework for chatbot development named EREBOTS. Methods. The foundations of the framework are based on the implementation of (i) multi-front-end connectors and interfaces (i.e., Telegram, dedicated App, and web interface), (ii) enabling the configuration of multi-scenario behaviors (i.e., preventive physical conditioning, smoking cessation, and support for breast-cancer survivors), (iii) online learning, (iv) personalized conversations and recommendations (i.e., mood boost, anti-craving persuasion, and balance-preserving physical exercises), and (v) responsive multi-device monitoring interface (i.e., doctor and admin). Results. EREBOTS has been tested in the context of physical balance preservation in social confinement times (due to the ongoing pandemic). Thirteen individuals characterized by diverse age, gender, and country distribution have actively participated in the experimentation, reporting advancements in the physical balance and overall satisfaction of the interaction and exercises’ variety they have been proposed.

Low-Income Parents' Perceptions of and Engagement With a Digital Behavioral Parent Training Program: A Mixed-Methods Study

BACKGROUND: Parent training is a method for strengthening parenting skills, reducing child behavior problems, and promoting positive parent-child relationships. However, few parents have access to these evidence-based programs. The ezParent program, a tablet-based delivery adaptation of the group-based Chicago Parent Program, is a parent training program designed to address the needs of families raising young children in urban poverty. AIMS: This study aimed to explore (a) parents' perceptions of the benefits and barriers associated with their use of the ezParent program and (b) the ways in which the ezParent components and perceived usability varied by program use (module completion). METHOD: An explanatory mixed-methods design was used with the overall intent to use the qualitative data to help explain in greater detail the quantitative results. RESULTS: Fifty-nine parents of 2- to 5-year-old children from two pediatric primary care clinics serving predominantly low-income and racial/ethnic minority families in Chicago (Cohort 1) and Baltimore (Cohort 2) participated in follow-up interviews. Among those interviewed, 23 (38.9.5%) parents completed all six modules and 12 parents (20.3%) completed none of the modules. However, of those 12, 8 (67%) logged in to the program and completed portions of Module 1. Parents who completed more modules reported more program benefits, and those who completed fewer modules reported more barriers. CONCLUSIONS: Exploring users' experience with current digital applications, researchers and application developers can better design future tablet-based interventions to be both effective and acceptable by consumers.

Barriers to distance learning during the COVID-19 outbreak: A qualitative review from parents' perspective

AIMS

The goal of this study was to review the content posted in available local Jordanian Facebook groups to explore the perceptions of parents regarding the challenges of distance learning faced by their children during the coronavirus outbreak in Jordan.

METHOD

The Facebook search engine was used to identify local Facebook groups. The search keywords included distance learning, parents, and Jordan. Several faculty professors reviewed the posts and discussion flow on distance learning posted in Facebook groups from March 15th to April 25th 2020.

RESULTS

The study identified a total of 248 posts and threads which categorized thematically for further analysis. The selected threads and answers revealed four underlying themes: (1) personal barriers (2) technical barriers (3) logistical barriers and (4) financial barriers.

CONCLUSION

Overall, parents were not limited to their daily routines during the pandemic. They performed the responsibility of helping school in teaching students. Many parents faced many types of barriers in their endeavors to assist their children with distance learning during the pandemic.

Type 1 Diabetes Mellitus Virtual Patient Network as a Peer Support Community: Protocol for Social Network Analysis and Content Analysis

Background

Type 1 Diabetes Mellitus Virtual Patient Network (T1DM-VPN) is a private Facebook group for youths with type 1 diabetes mellitus (T1DM) in Canada intended to facilitate peer-to-peer support. It was built on the finding that stigma is prevalent among youth with T1DM and impedes self-management.

Objective

We aim to determine if T1DM-VPN provides support as intended and to ascertain what type of members provide support. Specifically, we will (1) identify text consistent with any one of 5 social support categories, (2) describe the network by visualizing its structure and reporting basic engagement statistics, and (3) determine whether being a designated peer leader is related to a member’s centrality (ie, importance in the network) and how frequently they offer social support.

Methods

We will manually extract interaction data from the Facebook group (posts, comments, likes/reactions, seen) generated from June 21, 2017 (addition of first member), to March 1, 2020. Two researchers will independently code posts and comments according to an existing framework of 5 social support categories—informational, emotional, esteem, network, and tangible—with an additional framework for nonsocial support categories. We will calculate how frequently each code is used. We will also report basic engagement statistics (eg, number of posts made per person-month) and generate a visualization of the network. We will identify stable time intervals in the history of T1DM-VPN by modeling monthly membership growth as a Poisson process. Within each interval, each member’s centrality will be calculated and standardized to that of the most central member. We will use a centrality formula that considers both breadth and depth of connections (centrality = 0.8 × total No. of connections + 0.2 × total No. of interactions). Finally, we will construct multivariate linear regression models to assess whether peer leader status predicts member centrality and the frequency of offering social support. Other variables considered for inclusion in the models are gender and age at diagnosis.

Results

T1DM-VPN was launched in June 2017. As of March 1, 2020, it has 196 patient-members. This research protocol received ethics approval from the McGill University Health Centre Research Ethics Board on May 20, 2020. Baseline information about each group member was collected upon addition into the group, and collection of interaction data is ongoing as of May 2020.

Conclusions

This content analysis and social network analysis study of a virtual patient network applies epidemiological methods to account for dynamic growth and activity. The results will allow for an understanding of the topics of importance to youth with T1DM and how a virtual patient network evolves over time. This work is intended to serve as a foundation for future action to help youth improve their experience of living with diabetes.

International Registered Report Identifier (IRRID)

PRR1-10.2196/18714

Pharmacists' perception of their role during COVID-19: a qualitative content analysis of posts on Facebook pharmacy groups in Jordan

OBJECTIVE

This study aimed to evaluate the content available on Facebook pharmacy groups in Jordan regarding the perception of the pharmacists' role during the coronavirus pandemic in Jordan.

METHODS

Researchers identified Facebook pharmacy groups through the search engine on the Facebook website. The main search keywords were pharmacy, pharmacist, pharmacists, and Jordan using both Arabic and English. Two researchers analyzed the posts and discussion threads on local pharmacy Facebook groups in a period between March 20th and April 3rd. A total of 184 posts and threads were identified for the purpose of the study.

RESULTS

Identified threads and responses resulted in three overarching themes: pharmacists having a positive role during the pandemic, taking additional responsibilities and services, and having passive or negative roles. A positive role was seen in pharmacists acting as first-line healthcare providers, creating public's awareness regarding COVID-19, and being responsible for chronic medication refill during the pandemic. Taking additional responsibilities was summarized in home deliveries and involvement in industrial and corporate efforts to deal with the pandemic. A passive/negative role was seen mostly among hospital pharmacists not being proactive during the pandemic and by pharmacists trying to maximize profits during pandemic time.

CONCLUSIONS

Pharmacists perceived their role as a positive role during the coronavirus pandemic. Not only they took responsibilities for their daily services during the crises, but they took additional responsibilities to assure patient safety and satisfaction.

30+ years of media analysis of relevance to chronic disease: a scoping review

BACKGROUND

Chronic, non-communicable diseases are a significant public health priority, requiring action at individual, community and population levels, and public and political will for such action. Exposure to media, including news, entertainment, and advertising media, is likely to influence both individual behaviours, and attitudes towards preventive actions at the population level. In recent years there has been a proliferation of research exploring how chronic diseases and their risk factors are portrayed across various forms of media. This scoping review aims to map the literature in this area to identify key themes, gaps, and opportunities for future research in this area.

METHODS

We searched three databases (Medline, PsycINFO and Global Health) in July 2016 and identified 499 original research articles meeting inclusion criteria: original research article, published in English, focusing on media representations of chronic disease (including how issues are framed in media, impact or effect of media representations, and factors that influence media representations). We extracted key data from included articles and examined the health topics, media channels and methods of included studies, and synthesised key themes across studies.

RESULTS

Our findings show that research on media portrayals of chronic disease increased substantially between 1985 and 2016. Smoking and nutrition were the most frequent health topics, and television and print were the most common forms of media examined, although, as expected, research on online and social media channels has increased in recent years. The majority of studies focused on the amount and type of media coverage, including how issues are framed, typically using content analysis approaches. In comparison, there was much less research on the influences on and consequences of media coverage related to chronic disease, suggesting an important direction for future work.

CONCLUSIONS

The results highlight key themes across media research of relevance to chronic disease. More in-depth syntheses of studies within the identified themes will allow us to draw out the key patterns and learnings across the literature.

Practical and Ethical Considerations for Schools Using Social Media to Promote Physical Literacy in Youth

The rapid development of social media has led to its increased use by children and adolescents for health and well-being purposes. Accordingly, social interactions resulting from social media use can be further integrated into physical and health education pedagogy. Given the relationship between increased physical literacy and positive health outcomes, best practices and lessons learned from social media use in the healthcare industry should be adopted by health and physical educators practicing in schools. Thus, the purpose of this paper is to comment on several practical and ethical challenges and opportunities associated with using social media to improve physical literacy among youth. Specifically, two of the most prominent issues are discussed in depth: (1) integration of social media in physical education settings that educate children and adolescents about the biopsychosocial effects of physical activity, and (2) use of wearable technologies among youth to accrue experiences that enhance physical literacy competencies. In our opinion, health and physical educators who utilize the ALL-ENGAGE Playbook described in this commentary will successfully reach, engage, and impact students with popular social media that adequately promotes physical literacy, including through experiential use of wearable technologies.

Using Facebook for Qualitative Research: A Brief Primer

As Facebook continues to grow its number of active users, the potential to harness data generated by Facebook users also grows. As much of Facebook users’ activity consists of creating (and commenting on) written posts, the potential use of text data for research is enormous. However, conducting a content analysis of text from Facebook users requires adaptation of research methods used for more traditional sources of qualitative data. Furthermore, best practice guidelines to assist researchers interested in conducting qualitative studies using data derived from Facebook are lacking. The purpose of this primer was to identify opportunities, as well as potential pitfalls, of conducting qualitative research with Facebook users and their activity on Facebook and provide potential options to address each of these issues. We begin with an overview of information obtained from a literature review of 23 studies published between 2011 and 2018 and our own research experience to summarize current approaches to conducting qualitative health research using data obtained from Facebook users. We then identify potential strategies to address limitations related to current approaches and propose 5 key considerations for the collection, organization, and analysis of text data from Facebook. Finally, we consider ethical issues around the use and protection of Facebook data obtained from research participants. In this primer, we have identified several key considerations that should aid health researchers in the planning and execution of qualitative studies involving content analysis of text data from Facebook users.

Social media for tobacco smoking cessation intervention: a review of the literature

PURPOSE OF REVIEW

Social media platforms have the potential to reach large audiences and deliver intervention content in an interactive format. Yet, little is known about the efficacy of social media for smoking cessation treatment or which specific features best promote participant engagement and behavior change. This article seeks to evaluate the current literature on the use of social media interventions to support smoking cessation.

RECENT FINDINGS

Findings suggest that social media interventions are feasible and can be utilized effectively for smoking cessation treatment. Greater participant engagement with intervention content appears to be associated with positive changes in smoking behaviors in most, but not all studies reviewed.

SUMMARY

Smoking cessation interventions on social media hold promise to help smokers quit. Future randomized trials with longer follow-up intervals are needed to expand the current evidence base, as are studies that systematically investigate strategies to improve participant engagement with interventions.

"Like you are fooling yourself": how the "Stoptober" temporary abstinence campaign supports Dutch smokers attempting to quit

Background

The Stoptober temporary abstinence campaign challenges smokers to engage in a collective quit attempt for 28 days. The campaign is based on social contagion theory, SMART (i.e., Specific, Measurable, Attainable, Realistic and Time-sensitive) goal setting and PRIME (i.e., Plans, Responses, Impulses, Motives and Evaluations) theory. Although Stoptober was found to yield impressive 28-day quit rates, relapse rates remained substantial. Therefore, we examined how Stoptober supported smokers in their attempt to quit and how the campaign’s effectiveness could be strengthened.

Methods

In 2016, we conducted semi-structured interviews with 23 Stoptober participants in the Netherlands. Data were analyzed thematically.

Results

Respondents explained how social contagion-based components had familiarized them with Stoptober, motivated them to participate, and created a pro-smoking cessation social norm. Setting SMART goals was reported as “fooling yourself”, since it distracted respondents from their goal of quitting for good and helped them perceive that temporary abstinence was achievable. Respondents also illustrated the usefulness of PRIME theory. They typically used an individual selection of available supports that varied over time. To achieve long-term abstinence, respondents expressed the need for additional social network support and interactive, personalized and professional support during and after the campaign.

Conclusions

Stoptober supports smokers in their attempts to quit and generally according to the campaign’s theoretical principles. Added to available evidence, this finding supports the continuation and wider implementation of Stoptober, while connecting the campaign to social networks and regular smoking-cessation services to help improve long-term abstinence rates.

Electronic supplementary material

The online version of this article (10.1186/s12889-019-6833-y) contains supplementary material, which is available to authorized users.

Mining User-Generated Content in an Online Smoking Cessation Community to Identify Smoking Status: A Machine Learning Approach

Online smoking cessation communities help hundreds of thousands of smokers quit smoking and stay abstinent each year. Content shared by users of such communities may contain important information that could enable more effective and personally tailored cessation treatment recommendations. This study demonstrates a novel approach to determine individuals' smoking status by applying machine learning techniques to classify user-generated content in an online cessation community. Study data were from BecomeAnEX.org, a large, online smoking cessation community. We extracted three types of novel features from a post: domain-specific features, author-based features, and thread-based features. These features helped to improve the smoking status identification (quit vs. not) performance by 9.7% compared to using only text features of a post's content. In other words, knowledge from domain experts, data regarding the post author's patterns of online engagement, and other community member reactions to the post can help to determine the focal post author's smoking status, over and above the actual content of a focal post. We demonstrated that machine learning methods can be applied to user-generated data from online cessation communities to validly and reliably discern important user characteristics, which could aid decision support on intervention tailoring.

How Social Networks May Influence Cancer Patients' Situated Identity and Illness-Related Behaviors

Little research is currently available that captures variation in the degree to which individuals who have, or had cancer in the past (but are in remission) integrate their cancer experience into their sense of self or their cancer-associated identity. Such research should cover how those identities shape personal narratives within existing or new social networks so that, ultimately, we understand the implications for treatment choices and health outcomes. Particularly understudied are the social factors influencing the incorporation of cancer into identity, learning, and behavior. Social network analysis captures specific relationships, what they offer, and the structure or constellation of these relationships around someone who has cancer or has had cancer. Some studies point to potential cultural differences in ethnic or social groups in how social influences on the cancer experience play out in terms of individual coping strategies. In some populations, social cohesion or tight networks are common and of particular importance to individuals and include social institutions like church communities. Social status might also generate social pressures not typically noticed or experienced by other groups. We will discuss how social network analysis can be used to elucidate these factors and, conversely, how the specific context of cancer diagnosis can be used through social network analysis to better understand the role of community in helping individuals address situations of severe adversity.

Missing the mark for patient engagement: mHealth literacy strategies and behavior change processes in smoking cessation apps

OBJECTIVE

To examine how Transtheoretical Model (TTM)'s processes of change and mHealth literacy strategies are employed in mobile smoking cessation apps.

METHODS

A purposive sample of 100 iTunes apps were coded to assess descriptive (price, type, developer, user-rating) and engagement metrics, including processes of change and mHealth literacy strategies (plain language, usability, interactivity). One-way ANOVAs and independent samples t-tests examined associations between descriptive and engagement metrics.

RESULTS

Over half of the apps included 7 (78%) processes of change. Fewer included self-liberation (36%) and reinforcement management (34%). Most apps incorporated plain language, but few integrated usability and interactivity strategies. Hypnotherapy and informational apps included more behavioral processes of change than apps incorporating a combination of features, including gaming, cigarette trackers, and motivational coaching (p<0.01).

CONCLUSION

Apps included behavior change processes but rarely incorporated usability and interactivity features to promote patient engagement. Engagement metrics did not vary by app user-ratings, price-to-download, or developer, including for-profit organizations or government and educational institutions.

PRACTICE IMPLICATIONS

Providers should acknowledge the popularity of smoking cessation apps as potential cessation aids and communicate their benefits and drawbacks to patients. Future efforts to improve smoking cessation apps should focus on enhancing the quality of tailored and interactive content.

An exploration of the Facebook social networks of smokers and non-smokers

BACKGROUND

Social networks influence health behavior, including tobacco use and cessation. To date, little is known about whether and how the networks of online smokers and non-smokers may differ, or the potential implications of such differences with regards to intervention efforts. Understanding how social networks vary by smoking status could inform public health efforts to accelerate cessation or slow the adoption of tobacco use.

OBJECTIVES

These secondary analyses explore the structure of ego networks of both smokers and non-smokers collected as part of a randomized control trial conducted within Facebook.

METHODS

During the trial, a total of 14,010 individuals installed a Facebook smoking cessation app: 9,042 smokers who were randomized in the trial, an additional 2,881 smokers who did not meet full eligibility criteria, and 2,087 non-smokers. The ego network for all individuals was constructed out to second-degree connections. Four kinds of networks were constructed: friendship, family, photo, and group networks. From these networks we measured edges, isolates, density, mean betweenness, transitivity, and mean closeness. We also measured diameter, clustering, and modularity without ego and isolates. Logistic regressions were performed with smoking status as the response and network metrics as the primary independent variables and demographics and Facebook utilization metrics as covariates.

RESULTS

The four networks had different characteristics, indicated by different multicollinearity issues and by logistic regression output. Among Friendship networks, the odds of smoking were higher in networks with lower betweenness (p = 0.00), lower transitivity (p = 0.00), and larger diameter (p = 0.00). Among Family networks, the odds of smoking were higher in networks with more vertices (p = .01), less transitivity (p = .04), and fewer isolates (p = .01). Among Photo networks, none of the network metrics were predictive of smoking status. Among Group networks, the odds of smoking were higher when diameter was smaller (p = .04). Together, these findings suggested that compared to non-smokers, smokers in this sample had less connected, more dispersed Facebook Friendship networks; larger but more fractured Family networks with fewer isolates; more compact Group networks; and Photo networks that were similar in network structure to those of non-smokers.

CONCLUSIONS

This study illustrates the importance of examining structural differences in online social networks as a critical component for network-based interventions and lays the foundation for future research that examines the ways that social networks differ based on individual health behavior. Interventions that seek to target the behavior of individuals in the context of their social environment would be well served to understand social network structures of participants.

Design Considerations for mHealth Programs Targeting Smokers Not Yet Ready to Quit: Results of a Sequential Mixed-Methods Study

Background

Mobile health (mHealth) smoking cessation programs are typically designed for smokers who are ready to quit smoking. In contrast, most smokers want to quit someday but are not yet ready to quit. If mHealth apps were designed for these smokers, they could potentially encourage and assist more people to quit smoking. No prior studies have specifically examined the design considerations of mHealth apps targeting smokers who are not yet ready to quit.

Objective

To inform the user-centered design of mHealth apps for smokers who were not yet ready to quit by assessing (1) whether these smokers were interested in using mHealth tools to change their smoking behavior; (2) their preferred features, functionality, and content of mHealth programs addressing smoking; and (3) considerations for marketing or distributing these programs to promote their uptake.

Methods

We conducted a sequential exploratory, mixed-methods study. Qualitative interviews (phase 1, n=15) were completed with a demographically diverse group of smokers who were smartphone owners and wanted to quit smoking someday, but not yet. Findings informed a Web-based survey of smokers from across the United States (phase 2, n=116). Data were collected from April to September, 2016.

Results

Findings confirmed that although smokers not yet ready to quit are not actively seeking treatment or using cessation apps, most would be interested in using these programs to help them reduce or change their smoking behavior. Among phase 2 survey respondents, the app features, functions, and content rated most highly were (1) security of personal information; (2) the ability to track smoking, spending, and savings; (3) content that adaptively changes with one’s needs; (4) the ability to request support as needed; (5) the ability to earn and redeem awards for program use; (6) guidance on how to quit smoking; and (7) content specifically addressing management of nicotine withdrawal, stress, depression, and anxiety. Results generally did not vary by stage of change for quitting smoking (precontemplation vs contemplation). The least popular feature was the ability to share progress via social media. Relevant to future marketing or distribution considerations, smokers were price-sensitive and valued empirically validated programs. Program source, expert recommendations, and user ratings were also important considerations.

Conclusions

Smokers who are not yet ready to quit represent an important target group for intervention. Study findings suggest that many of these individuals are receptive to using mHealth tools to reduce or quit smoking, despite not having made a commitment to quit yet. The preferences for specific mHealth intervention features, functionality, and content outlined in this paper can aid addiction treatment experts, design specialists, and software developers interested in creating engaging interventions for smokers who want to quit in the future but are not yet committed to this important health goal.

Social Skills Training for Adolescents With Autism Spectrum Disorder Using Facebook (Project Rex Connect): A Survey Study

BACKGROUND

Adolescents with autism spectrum disorder (ASD) spend more time using electronic screen media than neurotypical peers; preliminary evidence suggests that computer-assisted or Web-based interventions may be beneficial for social skills acquisition. The current generation of adolescents accesses the Internet through computers or phones almost daily, and Facebook is the most frequently used social media platform among teenagers. This is the first research study to explore the use of Facebook as a therapeutic tool for adolescents with ASD.

OBJECTIVE

To study the feasibility and clinical impact of using a Web-based social platform in combination with social skills training for adolescents with ASD.

METHODS

This pilot study enrolled 6 participants (all males; mean age 14.1 years) in an online social skills training group using Facebook. Data was collected on the participants' social and behavioral functioning at the start and conclusion of the intervention. Outcome measures included the Social Responsiveness Scale-2, the Social Skills Improvement System Rating Scale, and the Project Rex Parent Survey. Participants were surveyed at the conclusion of the intervention regarding their experience.

RESULTS

No statistically significant differences in measurable outcomes were observed. However, the online addition of Facebook was well received by participants and their parents. The Facebook intervention was able to be executed with a careful privacy protocol in place and at minimal safety risk to participants.

CONCLUSIONS

The utilization of Facebook to facilitate delivery of social skills training for adolescents with ASD appears to be feasible, although the clinical impact of such an addition is still unclear. It is important to note that social difficulties of participants persisted with the addition of the online platform and participants still required assistance to engage with peers in an online environment. A Web-based intervention such as the one utilized in this study has the potential to reach a mass number of patients with ASD and could address disparities in access to in-person treatment services. However, the complexity and evolving nature of Facebook's website and privacy settings leads to a number of unique online safety concerns that may limit its clinical utility. Issues encountered in our study support the development of an alternative and closed Web-based social platform designed specifically for the target audience with ASD; this platform could be a safer and more easily moderated setting for aiding in social skills development. Despite a small sample size with no statistically significant improvements of target symptoms, the use of electronic screen media as a therapeutic tool for adolescents with ASD is still a promising area of research warranting further investigation. Our study helps inform future obstacles regarding feasibility and safety.