Lung Cancer Messages on Twitter: Content Analysis and Evaluation

Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review

BACKGROUND

The internet community has become a significant source for researchers to conduct qualitative studies analyzing users' views, attitudes, and experiences about public health. However, few studies have assessed the ethical issues in qualitative research using social media data.

OBJECTIVE

This study aims to review the reportage of ethical considerations in qualitative research utilizing social media data on public health care.

METHODS

We performed a scoping review of studies mining text from internet communities and published in peer-reviewed journals from 2010 to May 31, 2023. These studies, limited to the English language, were retrieved to evaluate the rates of reporting ethical approval, informed consent, and privacy issues. We searched 5 databases, that is, PubMed, Web of Science, CINAHL, Cochrane, and Embase. Gray literature was supplemented from Google Scholar and OpenGrey websites. Studies using qualitative methods mining text from the internet community focusing on health care topics were deemed eligible. Data extraction was performed using a standardized data extraction spreadsheet. Findings were reported using PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines.

RESULTS

After 4674 titles, abstracts, and full texts were screened, 108 studies on mining text from the internet community were included. Nearly half of the studies were published in the United States, with more studies from 2019 to 2022. Only 59.3% (64/108) of the studies sought ethical approval, 45.3% (49/108) mentioned informed consent, and only 12.9% (14/108) of the studies explicitly obtained informed consent. Approximately 86% (12/14) of the studies that reported informed consent obtained digital informed consent from participants/administrators, while 14% (2/14) did not describe the method used to obtain informed consent. Notably, 70.3% (76/108) of the studies contained users' written content or posts: 68% (52/76) contained verbatim quotes, while 32% (24/76) paraphrased the quotes to prevent traceability. However, 16% (4/24) of the studies that paraphrased the quotes did not report the paraphrasing methods. Moreover, 18.5% (20/108) of the studies used aggregated data analysis to protect users' privacy. Furthermore, the rates of reporting ethical approval were different between different countries (P=.02) and between papers that contained users' written content (both direct and paraphrased quotes) and papers that did not contain users' written content (P<.001).

CONCLUSIONS

Our scoping review demonstrates that the reporting of ethical considerations is widely neglected in qualitative research studies using social media data; such studies should be more cautious in citing user quotes to maintain user privacy. Further, our review reveals the need for detailed information on the precautions of obtaining informed consent and paraphrasing to reduce the potential bias. A national consensus of ethical considerations such as ethical approval, informed consent, and privacy issues is needed for qualitative research of health care using social media data of internet communities.

Pediatric Cancer Communication on Twitter: Natural Language Processing and Qualitative Content Analysis

BACKGROUND

During the COVID-19 pandemic, Twitter (recently rebranded as "X") was the most widely used social media platform with over 2 million cancer-related tweets. The increasing use of social media among patients and family members, providers, and organizations has allowed for novel methods of studying cancer communication.

OBJECTIVE

This study aimed to examine pediatric cancer-related tweets to capture the experiences of patients and survivors of cancer, their caregivers, medical providers, and other stakeholders. We assessed the public sentiment and content of tweets related to pediatric cancer over a time period representative of the COVID-19 pandemic.

METHODS

All English-language tweets related to pediatric cancer posted from December 11, 2019, to May 7, 2022, globally, were obtained using the Twitter application programming interface. Sentiment analyses were computed based on Bing, AFINN, and NRC lexicons. We conducted a supplemental nonlexicon-based sentiment analysis with ChatGPT (version 3.0) to validate our findings with a random subset of 150 tweets. We conducted a qualitative content analysis to manually code the content of a random subset of 800 tweets.

RESULTS

A total of 161,135 unique tweets related to pediatric cancer were identified. Sentiment analyses showed that there were more positive words than negative words. Via the Bing lexicon, the most common positive words were support, love, amazing, heaven, and happy, and the most common negative words were grief, risk, hard, abuse, and miss. Via the NRC lexicon, most tweets were categorized under sentiment types of positive, trust, and joy. Overall positive sentiment was consistent across lexicons and confirmed with supplemental ChatGPT (version 3.0) analysis. Percent agreement between raters for qualitative coding was 91%, and the top 10 codes were awareness, personal experiences, research, caregiver experiences, patient experiences, policy and the law, treatment, end of life, pharmaceuticals and drugs, and survivorship. Qualitative content analysis showed that Twitter users commonly used the social media platform to promote public awareness of pediatric cancer and to share personal experiences with pediatric cancer from the perspective of patients or survivors and their caregivers. Twitter was frequently used for health knowledge dissemination of research findings and federal policies that support treatment and affordable medical care.

CONCLUSIONS

Twitter may serve as an effective means for researchers to examine pediatric cancer communication and public sentiment around the globe. Despite the public mental health crisis during the COVID-19 pandemic, overall sentiments of pediatric cancer-related tweets were positive. Content of pediatric cancer tweets focused on health and treatment information, social support, and raising awareness of pediatric cancer.

Overview and characterization of penile cancer content across social media platforms

Background

Social media platforms (SMP) are an emerging resource that allows physicians, patients, and families to converse on cancer prevention, diagnosis, and treatment. We aimed to characterize penile cancer (PC) content shared on SMP.

Methods

We searched PC posts on Twitter, Facebook, and Instagram from July 1st, 2021, through June 30th, 2022. Two independent, blinded reviewers analyzed the hashtags: #PenileCancer, #PenileCancerAwareness, and #PenileNeoplasm. Descriptive statistics were used for posts characterization, Pearson´s correlation coefficient for associations, and Cohen's weighted kappa coefficient for inter-rater agreement rate.

Results

A total of 791 posts were analyzed, with Twitter accounting for 52%, Facebook for 12.2%, and Instagram for 35.5%, and. Most posts originated from high-income countries, such as the United Kingdom (48.8%). We found no correlation between the number of posts with PC incidence (p = 0.64) or users on SMP (p = 0.27). Most accounts were classified as "support and awareness communities" (43.6%) and "physicians and clinical researchers" (38.2%). Urology was the most common medical specialty to post (60.9%), followed by oncology (11.3%). Most posts were classified as "prevention and awareness for users" (45.1%). Global inter-reviewer agreement rate was almost perfect (k=0.95; p ≤ 0.01). On Twitter, "physicians and clinical researchers" shared more content on "treatment updates and medical papers published in medical journals," while on Facebook and Instagram, "support and awareness communities" focused on "personal and support comments."

Conclusion

Overall, the number of PC posts was low compared to other neoplasms across the SMP evaluated in this study. "Physicians and clinical researchers" shared more content on Twitter, while "support and awareness communities" on Facebook and Instagram. Encouraging the use of a common SMP among the medical community and general users could lead to a more effective communication between physicians, patients, and support groups, and to increased awareness of PC.

Perspectives and Experiences of Patients With Thyroid Cancer at a Global Level: Retrospective Descriptive Study of Twitter Data

BACKGROUND

Twitter has become a popular platform for individuals to broadcast their daily experiences and opinions on a wide range of topics and emotions. Tweets from patients with cancer could offer insights into their needs. However, limited research has been conducted using Twitter data to understand the needs of patients with cancer despite the substantial amount of health-related data posted on the platform daily.

OBJECTIVE

This study aimed to uncover the potential of using Twitter data to understand the perspectives and experiences of patients with thyroid cancer at a global level.

METHODS

 This retrospective descriptive study collected tweets relevant to thyroid cancer in 2020 using the Twitter scraping tool. Only English-language tweets were included, and data preprocessing was performed to remove irrelevant tweets, duplicates, and retweets. Both tweets and Twitter users were manually classified into various groups based on the content. Each tweet underwent sentiment analysis and was classified as either positive, neutral, or negative.

RESULTS

A total of 13,135 tweets related to thyroid cancer were analyzed. The authors of the tweets included patients with thyroid cancer (3225 tweets, 24.6%), patient's families and friends (2449 tweets, 18.6%), medical journals and media (1733 tweets, 13.2%), health care professionals (1093 tweets, 8.3%), and medical health organizations (940 tweets, 7.2%), respectively. The most discussed topics related to living with cancer (3650 tweets, 27.8%), treatment (2891 tweets, 22%), diagnosis (1613 tweets, 12.3%), risk factors and prevention (1137 tweets, 8.7%), and research (953 tweets, 7.3%). An average of 36 tweets pertaining to thyroid cancer were posted daily. Notably, the release of a film addressing thyroid cancer and the public disclosure of a news reporter's personal diagnosis of thyroid cancer resulted in a significant escalation in the volume of tweets. From the sentiment analysis, 53.5% (7025/13,135) of tweets were classified as neutral statements and 32.7% (4299/13,135) of tweets expressed negative emotions. Tweets from patients with thyroid cancer had the highest proportion of negative emotion (1385/3225 tweets, 42.9%), particularly when discussing symptoms.

CONCLUSIONS

 This study provides new insights on using Twitter data as a valuable data source to understand the experiences of patients with thyroid cancer. Twitter may provide an opportunity to improve patient and physician engagement or apply as a potential research data source.

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

BACKGROUND

Given the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews focus on the application of social media, and there is a lack of reviews that integrate the methods for analyzing social media information for health care.

OBJECTIVE

This scoping review aims to answer the following 4 questions: (1) What types of research have been used to investigate social media for health care, (2) what methods have been used to analyze the existing health information on social media, (3) what indicators should be applied to collect and evaluate the characteristics of methods for analyzing the contents of social media for health care, and (4) what are the current problems and development directions of methods used to analyze the contents of social media for health care?

METHODS

A scoping review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted. We searched PubMed, the Web of Science, EMBASE, the Cumulative Index to Nursing and Allied Health Literature, and the Cochrane Library for the period from 2010 to May 2023 for primary studies focusing on social media and health care. Two independent reviewers screened eligible studies against inclusion criteria. A narrative synthesis of the included studies was conducted.

RESULTS

Of 16,161 identified citations, 134 (0.8%) studies were included in this review. These included 67 (50.0%) qualitative designs, 43 (32.1%) quantitative designs, and 24 (17.9%) mixed methods designs. The applied research methods were classified based on the following aspects: (1) manual analysis methods (content analysis methodology, grounded theory, ethnography, classification analysis, thematic analysis, and scoring tables) and computer-aided analysis methods (latent Dirichlet allocation, support vector machine, probabilistic clustering, image analysis, topic modeling, sentiment analysis, and other natural language processing technologies), (2) categories of research contents, and (3) health care areas (health practice, health services, and health education).

CONCLUSIONS

Based on an extensive literature review, we investigated the methods for analyzing the contents of social media for health care to determine the main applications, differences, trends, and existing problems. We also discussed the implications for the future. Traditional content analysis is still the mainstream method for analyzing social media content, and future research may be combined with big data research. With the progress of computers, mobile phones, smartwatches, and other smart devices, social media information sources will become more diversified. Future research can combine new sources, such as pictures, videos, and physiological signals, with online social networking to adapt to the development trend of the internet. More medical information talents need to be trained in the future to better solve the problem of network information analysis. Overall, this scoping review can be useful for a large audience that includes researchers entering the field.

Cancer and COVID-19 Vaccines on Twitter:The Voice and Vaccine Attitude of Cancer Community

We investigate social media discourses on the relationship between cancer and COVID-19 vaccines focusing on the key textual topics, themes reflecting the voice of cancer community, authors who contribute to the discourse, and valence toward vaccines. We analyzed 6,427 tweets about cancer and COVID-19 vaccines, posted from when vaccines were approved in the U.S. (December 2020) to the February 2022. We mixed quantitative text mining, manual coding and statistical analysis, and inductive qualitative thematic analysis. Nearly 16% of the tweets posted by a cancer community member mentioned about refusal or delay of their vaccination at the state/local level during the initial rollout despite the CDC's recommendation to prioritize adults with high-risk medical conditions. Most tweets posted by cancer patients (pro = 82.4% vs. anti = 5.1%) and caregivers (pro = 89.2% vs. anti = 4.2%) showed positive valence toward vaccines and advocated for vaccine uptake increase among cancer patients and the general population. Vaccine hesitancy, self-reported adverse events, and COVID-19 disruption of cancer treatment also appeared as key themes. The cancer community called for actions to improve vaccination procedures to become safe and accessible especially for elderly cancer patients, develop COVID-19 vaccines suitable for varying type, stage, and treatment of cancer, and advance cancer vaccines. Future research should continue surveilling conversations around continuous impacts of COVID-19 interference with the cancer control continuum, beyond vaccination, focusing on the voice and concern of cancer community.

Assessment of Lung Cancer Screening Eligibility on NCI-Designated Cancer Center Websites

Online lung cancer screening assessments empower patients to learn about their risk for lung cancer and eligibility for screening. However, it is unknown whether these online assessments provide tailored recommendations that are consistent with national guidelines and include information to prepare patients for shared decision-making (SDM) consultations with their healthcare provider. In November 2019, we reviewed 71 NCI-Designated Cancer Center websites to identify US Preventive Services Task Force (USPSTF) guidelines for lung cancer screening eligibility and evidence-based features of shared decision-making (SDM). Only 11% of the websites included an online lung cancer screening assessment. Most assessments included tailored recommendations for screening eligibility based on USPSTF guidelines. Assessments designed to support SDM included both potential benefits and harms of undergoing lung cancer screening. Nearly all assessments directed adults to discuss the results with their healthcare provider and reinforced the importance of living a tobacco-free lifestyle. Online lung cancer screening assessments have the potential to put patients in control of knowledge about their lung cancer risk and screening eligibility. While nearly all assessments recommend patients to speak with their healthcare provider about their risk for lung cancer, patients may require more support to initiate and navigate SDM conversations with their providers.

Psychosocial Needs of Gynecological Cancer Survivors: Mixed Methods Study

BACKGROUND

Internet and social media platforms offer insights into the lived experiences of survivors of cancer and their caregivers; however, the volume of narrative data available is often cumbersome for thorough analysis. Survivors of gynecological cancer have unique needs, such as those related to a genetic predisposition to future cancers, impact of cancer on sexual health, the advanced stage at which many are diagnosed, and the influx of new therapeutic approaches.

OBJECTIVE

This study aimed to present a unique methodology to leverage large amounts of data from internet-based platforms for mixed methods analysis. We analyzed discussion board posts made by survivors of gynecological cancer on the American Cancer Society website with a particular interest in evaluating the psychosocial aspects of survivorship.

METHODS

All posts from the ovarian, uterine, and gynecological cancers (other than ovarian and uterine) discussion boards on the American Cancer Society Cancer Survivors Network were included. Posts were web scraped using Python and organized by psychosocial themes described in the Quality of Cancer Survivorship Care Framework. Keywords related to each theme were generated and verified. Keywords identified posts related to the predetermined psychosocial themes. Quantitative analysis was completed using Python and R Foundation for Statistical Computing packages. Qualitative analysis was completed on a subset of posts as a proof of concept. Themes discovered through latent Dirichlet allocation (LDA), an unsupervised topic modeling technique, were assessed and compared with the predetermined themes of interest.

RESULTS

A total of 125,498 posts made by 6436 survivors of gynecological cancer and caregivers between July 2000 and February 2020 were evaluated. Of the 125,489 posts, 23,458 (18.69%) were related to the psychosocial experience of cancer and were included in the mixed methods psychosocial analysis. Quantitative analysis (23,458 posts) revealed that survivors across all gynecological cancer discussion boards most frequently discussed the role of friends and family in care, as well as fatigue, the effect of cancer on interpersonal relationships, and health insurance status. Words related to psychosocial aspects of survivorship most often used in posts included "family," "hope," and "help." Qualitative analysis (20 of the 23,458 posts) similarly demonstrated that survivors frequently discussed coping strategies, distress and worry, the role of family and caregivers in their cancer care, and the toll of managing financial and insurance concerns. Using LDA, we discovered 8 themes, none of which were directly related to psychosocial aspects of survivorship. Of the 56 keywords identified by LDA, 2 (4%), "sleep" and "work," were included in the keyword list that we independently devised.

CONCLUSIONS

Web-based discussion platforms offer a great opportunity to learn about patient experiences of survivorship. Our novel methodology expedites the quantitative and qualitative analyses of such robust data, which may be used for additional patient populations.

New Data Resources, Linkages, and Infrastructure for Cancer Health Economics Research: Main Topics From a Panel Discussion

Although a broad range of data resources have played a key role in the substantial achievements of cancer health economics research, there are now needs for more comprehensive data that represent a fuller picture of the cancer care experience. In particular, researchers need information that represents more diverse populations; includes more clinical details; and provides greater context on individual- and neighborhood-level factors that can affect cancer prevention, screening, treatment, and survivorship, including measures of financial health or toxicity, health-related social needs, and social determinants of health. This article highlights 3 critical topics for cancer health economics research: the future of the National Cancer Institute's Surveillance, Epidemiology, and End Results-Centers for Medicare & Medicaid Services-linked data resources; use of social media data for cancer outcomes research; and multi-site-linked electronic health record data networks. These 3 topics represent different approaches to enhance data resources, linkages, and infrastructures and are complementary strategies to provide more complete information on activities involved in and factors affecting the cancer control continuum. These and other data resources will assist researchers in examining the complex and nuanced questions now at the forefront of cancer health economics research.

Understanding the lived experience of lung cancer: a European social media listening study

Background

Social media platforms are increasingly being used by stakeholders to generate, access, and share health-related information and experiences. Lung cancer is the most common cancer, impacting > 2 million patients globally. This observational study utilized a social listening approach to analyze social media trends and gain insights into stakeholder perceptions of lung cancer.

Methods

This social media study retrospectively collated data from open access blogs, forums, and social networking sites. Social media posts were collected between June 2019–May 2020 from 14 European countries. Using social media aggregator tools, posts comprising lung cancer and non-small cell lung cancer-specific terms were extracted. Manual and automated relevancy algorithms filtered the extracted information to provide the relevant dataset. This contextualized dataset was further mined to generate the final data for analysis.

Results

Of 1360 conversations analyzed, 42% were generated by patients/caregivers and 14% by healthcare professionals (HCPs). A majority of patients were 51–70 years old (approximately 50%) and 91% (n = 500/550) had late-stage cancer. Treatment (35%) and disease awareness (30%) were among the most discussed topic of the patient journey. Although the overall treatment sentiment was neutral, chemotherapy was the treatment type with the highest associated negative sentiment (28%); fewer negative sentiments were associated with immunotherapy (9%) and targeted therapy (2%), due to perceptions of longer survival outcomes and fewer side effects. In conversations that discussed clinical endpoints, “survivability” and “overall survival” (47 and 30%, respectively; n = 539) were most frequently mentioned by stakeholders. HCPs mostly used technical terms, whereas patients and caregivers used colloquial terms such as “getting rid of cancer”. Emotional wellness was identified to have a huge impact on quality of life in lung cancer. Delay or treatment cancellations due to COVID-19, lack of effective treatments and funding, and lack of empathy by physicians emerged as the key unmet needs among patients/caregivers.

Conclusions

Social listening proved to be an effective tool to explore stakeholders’ perceptions and their key unmet needs, typically not available in published literature or databases, and provides HCPs with valuable insights into the distress, doubts, and needs of lung cancer patients and caregivers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09505-4.

Twitter Conversations About Pancreatic Cancer by Health Care Providers and the General Public: Thematic Analysis

Background

 There is a growing interest in the pattern of consumption of health-related information on social media platforms.

Objective

We evaluated the content of discussions around pancreatic cancer on Twitter to identify subtopics of greatest interest to health care providers and the general public. 

Methods

 We used an online analytical tool (Creation Pinpoint) to quantify Twitter mentions (tweets and retweets) related to pancreatic cancer between January 2018 and December 2019. Keywords, hashtags, word combinations, and phrases were used to identify mentions. Health care provider profiles were identified using machine learning and then verified by a human analyst. Remaining user profiles were classified as belonging to the general public. Data from conversations were stratified qualitatively into 5 domains: (1) prevention, (2) survivorship, (3) treatment, (4) research, and (5) policy. We compared the themes of conversations initiated by health care providers and the general public and analyzed the impact of the Pancreatic Cancer Awareness Month and announcements by public figures of pancreatic cancer diagnoses on the overall volume of conversations. 

Results

 Out of 1,258,028 mentions of pancreatic cancer, 313,668 unique mentions were classified into the 5 domains. We found that health care providers most commonly discussed pancreatic cancer research (10,640/27,031 mentions, 39.4%), while the general public most commonly discussed treatment (154,484/307,449 mentions, 50.2%). Health care providers were found to be more likely to initiate conversations related to research (odds ratio [OR] 1.75, 95% CI 1.70-1.79, P<.001) and prevention (OR 1.49, 95% CI 1.41-1.57, P<.001) whereas the general public took the lead in the domains of treatment (OR 1.63, 95% CI 1.58-1.69, P<.001) and survivorship (OR 1.17, 95% CI 1.13-1.21, P<.001). Pancreatic Cancer Awareness Month did not increase the number of mentions by health care providers in any of the 5 domains, but general public mentions increased temporarily in all domains except prevention and policy. Health care provider mentions did not increase with announcements by public figures of pancreatic cancer diagnoses. After Alex Trebek, host of the television show Jeopardy, received his diagnosis, general public mentions of survivorship increased, while Justice Ruth Bader Ginsburg’s diagnosis increased conversations on treatment. 

Conclusions

Health care provider conversations on Twitter are not aligned with the general public. Pancreatic Cancer Awareness Month temporarily increased general public conversations about treatment, research, and survivorship, but not prevention or policy. Future studies are needed to understand how conversations on social media platforms can be leveraged to increase health care awareness among the general public.

Musawah: A Data-Driven AI Approach and Tool to Co-Create Healthcare Services with a Case Study on Cancer Disease in Saudi Arabia

The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it requires engaging with our environments, analyzing them, and making sustainable decisions regulated by triple bottom line (TBL). Poor healthcare systems affect individuals, societies, the planet, and economies. This paper proposes a data-driven artificial intelligence (AI) based approach called Musawah to automatically discover healthcare services that can be developed or co-created by various stakeholders using social media analysis. The case study focuses on cancer disease in Saudi Arabia using Twitter data in the Arabic language. Specifically, we discover 17 services using machine learning from Twitter data using the Latent Dirichlet Allocation algorithm (LDA) and group them into five macro-services, namely, Prevention, Treatment, Psychological Support, Socioeconomic Sustainability, and Information Availability. Subsequently, we show the possibility of finding additional services by employing a topical search over the dataset and have discovered 42 additional services. We developed a software tool from scratch for this work that implements a complete machine learning pipeline using a dataset containing over 1.35 million tweets we curated during September–November 2021. Open service and value healthcare systems based on freely available information can revolutionize healthcare in manners similar to the open-source revolution by using information made available by the public, the government, third and fourth sectors, or others, allowing new forms of preventions, cures, treatments, and support structures.

Oncofertility and Fertility Preservation in Cancer Patients Across the Twitterverse

PURPOSE

Infertility is a major problem affecting children, adolescents, and young adults (AYAs) with cancer, either due to the disease itself or because of oncologic treatment. Oncofertility (OF) focuses on counseling cancer patients about fertility risks and preservation options. However, OF and fertility preservation (FP) conversations on Twitter and their impact are unknown. We aim to characterize the users and type of content of these conversations.

MATERIALS AND METHODS

This observational study analyzed tweets with the hashtags "#Oncofertility" and "#FertilityPreservation" over eight months. We classified Twitter accounts by user type and country. Tweets were categorized by content type, and retweets and likes were quantified. Descriptive statistics were used for analysis.

RESULTS

A total of 399 tweets from 223 different accounts were evaluated. Twitter accounts comprised 22 countries and stemmed from high, upper-middle, and lower-middle-income countries in 86.5%, 5.4%, and 6.3%, respectively; no accounts from low-income countries were found. Accounts were mostly from physicians (37%) and healthcare centers (20%); we did not find any patient accounts. The most common content category was informative tweets directed to patients (30.8%), followed by discussion/sharing of medical papers (25.6%). Only 14.5% of tweets contained information about children and adolescents. Still, only 4.5% were aimed at children. Retweets were absent in 16.5% of the tweets, and 80.7% did not have comments.

CONCLUSION

OF and FP discussions on Twitter were limited to interactions among medical professionals. Also, advocacy groups showed limited activity on social media. Even though a significant proportion of tweets directed to patients were found, no active involvement of patients was observed. Finally, limited number of tweets (4.5%) were directed to children and adolescents. There is a need to raise awareness about the effects of cancer on fertility in this group. Currently, Twitter is not a resource of information for children and AYAs with cancer who need OF counseling and fertility preservation. Our results open a debate on how to promote the use of social media in the future to improve the quality of OF information available, awareness, and care since there is an unmet need for fertility preservation access in young cancer patients.

Social media analytics and reachability evaluation - #Diabetes

BACKGROUND AND AIMS

Diabetes as a lifestyle disorder could be effectively managed by creating awareness among people through social media. Understanding the content of Twitter messages will aid in strategizing health communication about diabetes to the community through Twitter. This study aimed to analyze the content, sentiment, and reachability of diabetes related tweets posted in India.

METHODS

Diabetes related messages from India were collected via Twitter's Application Programming Interface for April 2019. Themes and subthemes of tweet content were identified from randomly selected tweets. The tweets were coded as the source, themes, and subthemes manually. Sentiment analysis of the tweets was done by a lexicon-based approach. The reachability of tweets was assessed based on re-tweet and favorite counts.

RESULTS

Out of 1840 tweets, 57.28% were from organizations and 42.72% were from individuals. The largest proportion of tweet messages were informative (50.76%), followed by promotional tweets (21.52%). The largest proportion of tweets were positive (40.4%) followed by neutral (31.14%) tweets. Among the six major themes, the diabetes story had the highest reachability.

CONCLUSIONS

The outcome of this study would aid public health professionals in planning information dissemination and communication regarding diabetes on Twitter so that the right information reaches a wider population.

Understanding the Lived Experience of Patients with Melanoma: Real-World Evidence Generated through a European Social Media Listening Analysis (Preprint)

Background

Cutaneous melanoma is an aggressive malignancy that is proposed to account for 90% of skin cancer–related mortality. Individuals with melanoma experience both physical and psychological impacts associated with their diagnosis and treatment. Health-related information is being increasingly accessed and shared by stakeholders on social media platforms.

Objective

This study aimed to assess how individuals living with melanoma across 14 European countries use social media to discuss their needs and provide their perceptions of the disease.

Methods

Social media sources including Twitter, forums, and blogs were searched using predefined search strings of keywords relating to melanoma. Manual and automated relevancy approaches filtered the extracted data for content that provided patient-centric insights. This contextualized data was then mined for insightful concepts around the symptoms, diagnosis, treatment, impacts, and lived experiences of melanoma.

Results

A total of 182,400 posts related to melanoma were identified between November 2018 and November 2020. Following exclusion of irrelevant posts and using random sampling methodology, 864 posts were identified as relevant to the study objectives. Of the social media channels included, Twitter was the most commonly used, followed by forums and blogs. Most posts originated from the United Kingdom (n=328, 38%) and Spain (n=138, 16%). Of the relevant posts, 62% (n=536) were categorized as originating from individuals with melanoma. The most frequently discussed melanoma-related topics were treatment (436/792, 55%), diagnosis and tests (261/792, 33%), and remission (190/792, 24%). The majority of treatment discussions were about surgery (292/436, 67%), followed by immunotherapy (52/436, 12%). In total, 255 posts discussed the impacts of melanoma, which included emotional burden (n=179, 70%), physical impacts (n=61, 24%), effects on social life (n=43, 17%), and financial impacts (n=10, 4%).

Conclusions

Findings from this study highlight how melanoma stakeholders discuss key concepts associated with the condition on social media, adding to the conceptual model of the patient journey. This social media listening approach is a powerful tool for exploring melanoma stakeholder perspectives, providing insights that can be used to corroborate existing data and inform future studies.

Is there alignment amongst scientific literature, news media and patient forums regarding topics?: A study of breast and lung cancer

Purpose

During recent years, web technologies and mass media have become prevalent in the context of medicine and health. Two examples of important web technologies used in health are news media and patient forums. Both have a significant role in shaping patients' perspective and behaviour in relation to health and illness, as well as the way that they might choose or change their treatment. In this paper, the authors investigated the application of web technologies using the data analysis approach. The authors did this analysis from the point of view of topics being discussed and disseminated via patients and journalists in breast and lung cancer. The study also investigated the (dis)alignment amongst these two groups and scientists in terms of topics.

Design/methodology/approach

Three data sets comprised documents published between 2014 and 2018 obtained from ProQuest and Web of Science Medline databases, alongside data from three major patient forums on breast and lung cancer. The analysis and visualisation in this paper have been done using the udpipe, igraph R packages and VOSviewer.

Findings

The study’s findings showed that in general scientists focussed more on prognosis and treatment of cancer, whereas patients and journalists focussed more on detection, prevention and role of social and emotional support. The only exception was for news coverage of lung cancer where the largest cluster was related to treatment, research in cancer treatment and therapies. However, when comparing coverage by scientists and journalists in terms of treatment, the focus of news articles in both cancer types was mainly on chemotherapy and complimentary therapies. Finally, topics such as lifestyle or pain management were only discussed by breast cancer patients.

Originality/value

The results obtained from this study may provide valuable insights into topics of interest for each group of scientists, journalist and patients as well as (dis)alignment among them in terms of topics. These findings are important as scientific research is heavily dependent on communication, and research does not exist in a bubble. Scientists and journalists can gain insights from patients' experiences and needs, which in turn may help them to have a more holistic and realistic view.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-06-2020-0228

A Study of the Effects of the COVID-19 Pandemic on the Experience of Back Pain Reported on Twitter® in the United States: A Natural Language Processing Approach

The COVID-19 pandemic has changed our lifestyles, habits, and daily routine. Some of the impacts of COVID-19 have been widely reported already. However, many effects of the COVID-19 pandemic are still to be discovered. The main objective of this study was to assess the changes in the frequency of reported physical back pain complaints reported during the COVID-19 pandemic. In contrast to other published studies, we target the general population using Twitter as a data source. Specifically, we aim to investigate differences in the number of back pain complaints between the pre-pandemic and during the pandemic. A total of 53,234 and 78,559 tweets were analyzed for November 2019 and November 2020, respectively. Because Twitter users do not always complain explicitly when they tweet about the experience of back pain, we have designed an intelligent filter based on natural language processing (NLP) to automatically classify the examined tweets into the back pain complaining class and other tweets. Analysis of filtered tweets indicated an 84% increase in the back pain complaints reported in November 2020 compared to November 2019. These results might indicate significant changes in lifestyle during the COVID-19 pandemic, including restrictions in daily body movements and reduced exposure to routine physical exercise.

COVID-19 Vaccine Hesitancy in Canada: Content Analysis of Tweets Using the Theoretical Domains Framework

Background

With the approval of two COVID-19 vaccines in Canada, many people feel a sense of relief, as hope is on the horizon. However, only about 75% of people in Canada plan to receive one of the vaccines.

Objective

The purpose of this study is to determine the reasons why people in Canada feel hesitant toward receiving a COVID-19 vaccine.

Methods

We screened 3915 tweets from public Twitter profiles in Canada by using the search words “vaccine” and “COVID.” The tweets that met the inclusion criteria (ie, those about COVID-19 vaccine hesitancy) were coded via content analysis. Codes were then organized into themes and interpreted by using the Theoretical Domains Framework.

Results

Overall, 605 tweets were identified as those about COVID-19 vaccine hesitancy. Vaccine hesitancy stemmed from the following themes: concerns over safety, suspicion about political or economic forces driving the COVID-19 pandemic or vaccine development, a lack of knowledge about the vaccine, antivaccine or confusing messages from authority figures, and a lack of legal liability from vaccine companies. This study also examined mistrust toward the medical industry not due to hesitancy, but due to the legacy of communities marginalized by health care institutions. These themes were categorized into the following five Theoretical Domains Framework constructs: knowledge, beliefs about consequences, environmental context and resources, social influence, and emotion.

Conclusions

With the World Health Organization stating that one of the worst threats to global health is vaccine hesitancy, it is important to have a comprehensive understanding of the reasons behind this reluctance. By using a behavioral science framework, this study adds to the emerging knowledge about vaccine hesitancy in relation to COVID-19 vaccines by analyzing public discourse in tweets in real time. Health care leaders and clinicians may use this knowledge to develop public health interventions that are responsive to the concerns of people who are hesitant to receive vaccines.

Social media analytics in nutrition research: a rapid review of current usage in investigation of dietary behaviours

OBJECTIVE

Social media analytics (SMA) has a track record in business research. The utilisation in nutrition research is unknown, despite social media being populated with real-time eating behaviours. This rapid review aimed to explore the use of SMA in nutrition research with the investigation of dietary behaviours.

DESIGN

The review was conducted according to rapid review guidelines by WHO and the National Collaborating Centre for Methods and Tools. Five databases of peer-reviewed, English language studies were searched using the keywords 'social media' in combination with 'data analytics' and 'food' or 'nutrition' and screened for those with general population health using SMA on public domain, social media data between 2014 and 2020.

RESULTS

The review identified 34 studies involving SMA in the investigation of dietary behaviours. Nutrition topics included population nutrition health investigations, alcohol consumption, dieting and eating out of the home behaviours. All studies involved content analysis with evidence of surveillance and engagement. Twitter was predominant with data sets in tens of millions. SMA tools were observed in data discovery, collection and preparation, but less so in data analysis. Approximately, a third of the studies involved interdisciplinary collaborations with health representation and only two studies involved nutrition disciplines. Less than a quarter of studies obtained formal human ethics approval.

CONCLUSIONS

SMA in nutrition research with the investigation of dietary behaviours is emerging, nevertheless, if consideration is taken with technological capabilities and ethical integrity, the future shows promise at a broad population census level and as a scoping tool or complementary, triangulation instrument.

Look who's talking now: Cancer in primary care on Twitter. An observational study

Background

Twitter is a microblogging platform that helps share information. It is a dynamic tool that has been embraced by many user types including consumers and healthcare professionals (HCPs). Currently, there are no data on how cancer in primary care features on Twitter.

Aim

To explore the type of users and information shared about cancer in primary care on Twitter.

Design & setting

A descriptive exploratory study took place of publicly available Twitter data.

Method

Tweets were searched between July 2015 and June 2017 for ‘GP’, ‘general practice’, ‘primary care’, or ‘general practitioner’ in conjunction with ‘cancer’. A 20% random sample was coded for geographic location, user type, type of tweet, and theme. Tweet sentiment was analysed using R package sentimentr. Content that gained traction was compared by combining original tweets, retweets, favourites, and duration.

Results

There were a total of 3413 tweets from 1611 users in 44 countries. Consumers were the largest user group followed by health organisations, healthcare professionals, and the media. The most common theme across user types was diagnostic delay. Other themes that emerged included cancer screening, symptom awareness, and early diagnosis. Consumers published more negative tweets, particularly in relation to diagnostic delay. Health organisations focused on symptom awareness and screening. Over half of media tweets were stories that featured delayed diagnosis or screening.

Conclusion

A broad range of users engage with Twitter to share information about cancer in primary care. Content is different between user groups, but diagnostic delay and symptom awareness are common themes. Healthcare and professional organisations may need to consider approaches to counter negative messages about diagnostic delay.

What people share about the COVID-19 outbreak on Twitter? An exploratory analysis

BACKGROUND

The recent outbreak of respiratory illness caused by COVID-19 in Wuhan, China, has received global attention as it has infected thousands of individuals there, and later it has also been reported from other countries internationally. This study aims at performing an exploratory study on Twitter to understand the information shared among the community regarding the COVID-19 outbreak.

METHODS

COVID-19 related tweets were collected from Twitter using keywords from 18 January to 25 January 2020. Top-ranking tweets were taken as samples and then categorised based on the content. Expressions or opinion tweets were analysed qualitatively to understand the mindset of the people regarding the outbreak. Theme wise reachability evaluation of the messages was also performed.

RESULTS

Based on the content of the tweets, five themes were evolved: (1) general information; (2) health information; (3) expressions; (4) humour and (5) others. 57.42% of messages are general information followed by expressive tweets (24.12%). Humorous messages were liked the most, whereas health information tweets were retweeted the maximum. Fear was the predominant emotion expressed in the messages.

CONCLUSION

The results of the study would be useful to focus on the dissemination of the right information and effective communication on Twitter related to health and outbreak management.

Promoting Clinical Conversations about Lung Cancer Screening: Exploring the Role of Perceived Online Social Support

The perceived availability of online social support may contribute to patient-provider conversations about lung cancer screening. This study examines how the perceived availability of instrumental and emotional online social support is associated with patient-provider communication about lung cancer screening among adults who meet U.S. Preventive Services Taskforce (USPSTF) eligibility criteria and live with a COPD diagnosis. In April 2018, 575 adults completed an online survey after being recruited from a large southeastern academic medical center's broad research registry and website listing. Nearly half of the participants were 55-to-80 years old (41%), a current or former smoker who had quit smoking within the past 15 years (42%), and reported a smoking prevalence of 30 pack years or more (PPY; 41%). Results demonstrate that having a COPD diagnosis, identifying as male, and being a current or former tobacco smoker resulted in greater odds of having a clinical conversation about lung cancer screening. Conversely, meeting the 30 PPY smoking and 55-to-80 age thresholds lowered the odds of having these conversations. A high degree of instrumental and emotional online social support was associated with a greater incidence of annual patient-provider conversations about screening. This combination of perceived online social support was especially useful for patients with COPD.

Conversations and Misconceptions About Chemotherapy in Arabic Tweets: Content Analysis

Background

Although chemotherapy was first introduced for the treatment of cancer more than 60 years ago, the public understanding and acceptance of chemotherapy is still debatable. To the best of our knowledge, no study has assessed the conversations and misconceptions about chemotherapy as a treatment for cancer on social media platforms among the Arabic-speaking populations.

Objective

The aim of this study was to assess the types of conversations and misconceptions that were shared on Twitter regarding chemotherapy as a treatment for cancer among the Arabic-speaking populations.

Methods

All Arabic tweets containing any of the representative set of keywords related to chemotherapy and written between May 1, 2017 and October 31, 2017 were retrieved. A manual content analysis was performed to identify the categories of the users, general themes of the tweets, and the common misconceptions about chemotherapy. A chi-square test for independence with adjusted residuals was used to assess the significant associations between the categories of the users and the themes of the tweets.

Results

A total of 402,157 tweets were retrieved, of which, we excluded 309,602 retweets and 62,651 irrelevant tweets. Therefore, 29,904 tweets were included in the final analysis. The majority of the tweets were posted by general users (25,774/29,904, 86.2%), followed by the relatives and friends of patients with cancer (1913/29,904, 6.4%). The tweets were classified into 9 themes; prayers and wishes for the well-being of patients undergoing chemotherapy was the most common theme (20,288/29,904, 67.8%), followed by misconceptions about chemotherapy (2084/29,904, 7.0%). There was a highly significant association between the category of the users and the themes of the tweets (χ²₄₀= 16904.4, P<.001).

Conclusions

Our findings support those of the previous infodemiology studies that Twitter is a valuable social media platform for assessing public conversations, discussions, and misconceptions about various health-related topics. The most prevalent theme of the tweets in our sample population was supportive messages for the patients undergoing chemotherapy, thereby suggesting that Twitter could play a role as a support mechanism for such patients. The second most prevalent theme of the tweets in our study was the various misconceptions about chemotherapy. The findings of our exploratory analysis can help physicians and health care organizations tailor educational efforts in the future to address different misconceptions about chemotherapy, thereby leading to increased public acceptance of chemotherapy as a suitable mode of treatment for cancer.

Public Perception of Artificial Intelligence in Medical Care: Content Analysis of Social Media

Background

High-quality medical resources are in high demand worldwide, and the application of artificial intelligence (AI) in medical care may help alleviate the crisis related to this shortage. The development of the medical AI industry depends to a certain extent on whether industry experts have a comprehensive understanding of the public’s views on medical AI. Currently, the opinions of the general public on this matter remain unclear.

Objective

The purpose of this study is to explore the public perception of AI in medical care through a content analysis of social media data, including specific topics that the public is concerned about; public attitudes toward AI in medical care and the reasons for them; and public opinion on whether AI can replace human doctors.

Methods

Through an application programming interface, we collected a data set from the Sina Weibo platform comprising more than 16 million users throughout China by crawling all public posts from January to December 2017. Based on this data set, we identified 2315 posts related to AI in medical care and classified them through content analysis.

Results

Among the 2315 identified posts, we found three types of AI topics discussed on the platform: (1) technology and application (n=987, 42.63%), (2) industry development (n=706, 30.50%), and (3) impact on society (n=622, 26.87%). Out of 956 posts where public attitudes were expressed, 59.4% (n=568), 34.4% (n=329), and 6.2% (n=59) of the posts expressed positive, neutral, and negative attitudes, respectively. The immaturity of AI technology (27/59, 46%) and a distrust of related companies (n=15, 25%) were the two main reasons for the negative attitudes. Across 200 posts that mentioned public attitudes toward replacing human doctors with AI, 47.5% (n=95) and 32.5% (n=65) of the posts expressed that AI would completely or partially replace human doctors, respectively. In comparison, 20.0% (n=40) of the posts expressed that AI would not replace human doctors.

Conclusions

Our findings indicate that people are most concerned about AI technology and applications. Generally, the majority of people held positive attitudes and believed that AI doctors would completely or partially replace human ones. Compared with previous studies on medical doctors, the general public has a more positive attitude toward medical AI. Lack of trust in AI and the absence of the humanistic care factor are essential reasons why some people still have a negative attitude toward medical AI. We suggest that practitioners may need to pay more attention to promoting the credibility of technology companies and meeting patients’ emotional needs instead of focusing merely on technical issues.

Coronavirus, Ageism, and Twitter: An Evaluation of Tweets about Older Adults and COVID-19

OBJECTIVES

In March 2020, the World Health Organization declared coronavirus disease 2019 (COVID‐19) a pandemic. High morbidity and mortality rates of COVID‐19 have been observed among older adults and widely reported in both mainstream and social media. The objective of this study was to analyze tweets related to COVID‐19 and older adults, and to identify ageist content.

DESIGN

We obtained a representative sample of original tweets containing the keywords “elderly,” “older,” and/or “boomer” plus the hashtags “#COVID19” and/or “#coronavirus.”

SETTING

Tweets posted between March 12 and March 21, 2020.

MEASUREMENTS

We identified the type of user and number of followers for each account. Tweets were classified by three raters as (1) informative, (2) personal accounts, (3) personal opinions, (4) advice seeking, (5) jokes, and (6) miscellaneous. Potentially offensive content, as well as that downplaying the severity of COVID‐19 because it mostly affects older adults, was identified.

RESULTS

A total of 18,128 tweets were obtained, of which a random sample of 351 was analyzed. Most accounts (91.7%) belonged to individuals. The most common types of tweets were personal opinions (31.9%), followed by informative tweets (29.6%), jokes/ridicule (14.3%), and personal accounts (13.4%). Overall, 72 tweets (21.9%) likely intended to ridicule or offend someone and 21.1% had content implying that the life of older adults was less valuable or downplayed the relevance of COVID‐19.

CONCLUSION

Most tweets related to COVID‐19 and older adults contained personal opinions, personal accounts, and jokes. Almost one‐quarter of analyzed tweets had ageist or potentially offensive content toward older adults. J Am Geriatr Soc 68:1661‐1665, 2020.

A Systematic Framework for Analyzing Patient-Generated Narrative Data: Protocol for a Content Analysis

Background

Patient narrative data in online health care forums (communities) are receiving increasing attention from the scientific community for implementing patient-centered care. Natural language processing (NLP) methods are gaining more and more attention because of the enormous data volume. However, state-of-the-art NLP still cannot meet the need of high-resolution analysis of patients’ narratives. Manual qualitative analysis still plays a pivotal role in answering complicated research questions from analyzing patient narratives.

Objective

This study aimed to develop a systematic framework for qualitative analysis of patient-generated narratives in online health care forums.

Methods

Our systematic framework consists of 4 phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results. Data collection and data preparation phases are constructed based on text mining methods for identifying appropriate online health forums for data collection, differentiating posts of patients from other stakeholders, protecting patients’ privacy, sampling, and choosing the unit of analysis. Content analysis phase is built on the framework method, which facilitates and accelerates the identification of patterns and themes by an interdisciplinary research team. In the end, the focus of interpretation of the results phase is to measure the data quality and interpret the findings regarding the dimensions and aspects of patients’ experiences and concerns in their original contexts.

Results

We demonstrated the usability of the proposed systematic framework using 2 case studies: one on determining factors affecting patients’ attitudes toward antidepressants and another on identifying the disease management strategies in patient with diabetes facing financial difficulties. The framework provides a clear step-by-step process for systematic content analysis of patient narratives and produces high-quality structured results that can be used for describing patterns or regularities in patients’ experiences, generating and testing hypotheses, and identifying areas of improvement in the health care systems.

Conclusions

The systematic framework is a rigorous and standardized method for qualitative analysis of patient narratives. Findings obtained through such a process indicate authentic dimensions and aspects of patient experiences and shed light on patients’ concerns, needs, preferences, and values, which are the core of patient-centered care.

International Registered Report Identifier (IRRID)

RR1-10.2196/13914

The social dynamics of lung cancer talk on Twitter, Facebook and Macmillan.org.uk

People with lung cancer and others affected by the condition are using social media to share information and support, but little is known about how these behaviours vary between different platforms. To investigate this, we extracted posts from Twitter (using relevant hashtags), the Lung Cancer Support Group on Facebook and the Macmillan.org.uk lung cancer discussion forum for a single month. Interaction Process Analysis revealed that all three platforms were used more for giving than seeking information, opinion or suggestions. However, interaction types (including sentiment) varied between platforms, reflecting their digital architectures, user-base and inclusion of a moderator. For example, a higher percentage of information-seeking and sentiment marked the Macmillan.org.uk, compared with Twitter and the Facebook Group. Further analysis of the messages using a four-dimensional typology of social support revealed that emotional and informational support types were most prevalent on the Macmillan.org.uk forum, closely followed by the Facebook Group. Contrary to expectations, Twitter posts showed the most companionship support, reflecting the use of hashtags as user-generated signals of community belonging and interests. Qualitative analysis revealed an unanticipated sub-category of spiritual support, which featured uniquely in the Lung Cancer Support Group on Facebook. There was little evidence of trolling or stigma, although some users remarked that lung cancer was unfairly resourced compared with other cancers. These findings provide new insights about how people affected by lung cancer use social media and begin to elucidate the value of different platforms as channels for patient engagement and support, or as potential research data sources.

Areas of Interest and Stigmatic Attitudes of the General Public in Five Relevant Medical Conditions: Thematic and Quantitative Analysis Using Twitter

BACKGROUND

Twitter is an indicator of real-world performance, thus, is an appropriate arena to assess the social consideration and attitudes toward psychosis.

OBJECTIVE

The aim of this study was to perform a mixed-methods study of the content and key metrics of tweets referring to psychosis in comparison with tweets referring to control diseases (breast cancer, diabetes, Alzheimer, and human immunodeficiency virus).

METHODS

Each tweet's content was rated as nonmedical (NM: testimonies, health care products, solidarity or awareness and misuse) or medical (M: included a reference to the illness's diagnosis, treatment, prognosis, or prevention). NM tweets were classified as positive or pejorative. We assessed the appropriateness of the medical content. The number of retweets generated and the potential reach and impact of the hashtags analyzed was also investigated.

RESULTS

We analyzed a total of 15,443 tweets: 8055 classified as NM and 7287 as M. Psychosis-related tweets (PRT) had a significantly higher frequency of misuse 33.3% (212/636) vs 1.15% (853/7419; P<.001) and pejorative content 36.2% (231/636) vs 11.33% (840/7419; P<.001). The medical content of the PRT showed the highest scientific appropriateness 100% (391/391) vs 93.66% (6030/6439; P<.001) and had a higher frequency of content about disease prevention. The potential reach and impact of the tweets related to psychosis were low, but they had a high retweet-to-tweet ratio.

CONCLUSIONS

We show a reduced number and a different pattern of contents in tweets about psychosis compared with control diseases. PRT showed a predominance of nonmedical content with increased frequencies of misuse and pejorative tone. However, the medical content of PRT showed high scientific appropriateness aimed toward prevention.

Characterizing Media Content and Effects of Organ Donation on a Social Media Platform: Content Analysis

BACKGROUND

The lack of organ donors has become a barrier for the development of organ transplantation programs, and many countries are currently facing a severe shortage of deceased organs. Media campaigns on social media have the potential to promote organ donation. However, little is known about what kind of media content is the most appropriate for this purpose.

OBJECTIVE

This study aimed to analyze media posts regarding organ donation on Weibo, a social media platform, and to identify the media themes that are most advantageous in promoting public awareness and attitudes concerning organ donation.

METHODS

Based on 16 million social media users' posts randomly extracted from January 1 to December 31, 2017, 1507 reposts of 141 distinct media posts relevant to organ donation were found. We analyzed the media posts' themes and examined their effects in promoting public awareness about organ donation by comparing the number of reposts and comments they prompted. The themes' impact on attitude toward organ donation was gauged using the comments indicating support and intentions for organ donation.

RESULTS

Overall, 5 major themes were identified from the media posts, among which "organ donation behaviors" constituted the highest proportion (58/141, 41.13%). However, themes of "statistical descriptions of organ donation" and "meaningfulness of donation" were the most influential in promoting awareness on organ donation: approximately 3 of 10 commenters for the former theme and 2 of 10 commenters for the latter expressed intentions to become organ donors. These two themes, along with "meaningfulness of organ donation for society," a subtheme of "meaningfulness of donation," were the most effective for evoking support and intentions for donation.

CONCLUSIONS

A discrepancy was revealed between the media themes that were the most salient on the media agenda and those that were the most effective in increasing organ donation awareness and intentions on social media. These findings provide guidance for campaigns on organ donation. The results also suggest the potential of campaigns on social media for promoting prosocial health behaviors and highlight the importance of strategic message design for serving this goal.

Multilevel Opportunities to Address Lung Cancer Stigma across the Cancer Control Continuum

The public health imperative to reduce the burden of lung cancer has seen unprecedented progress in recent years. Fully realizing the advances in lung cancer treatment and control requires attention to potential barriers in their momentum and implementation. In this analysis, we present and evaluate the argument that stigma is a highly significant barrier to fulfilling the clinical promise of advanced care and reduced lung cancer burden. This evaluation of the stigma of lung cancer is based on a multilevel perspective that incorporates the individual, persons in the individual's immediate environment, the health care system, and the larger societal structure that shapes perceptions and decisions. We also consider current interventions and interventional needs within and across aspects of the lung cancer continuum, including prevention, screening, diagnosis, treatment, and survivorship. Current evidence suggests that stigma detrimentally affects psychosocial, communication, and behavioral outcomes over the entire lung cancer control continuum and across multiple levels. Interventional efforts to alleviate stigma in the context of lung cancer show promise, yet more work is needed to evaluate their impact. Understanding and addressing the multilevel role of stigma is a crucial area for future study to realize the full benefits offered by lung cancer prevention, control, and treatment. Coordinated, interdisciplinary, and well-conceptualized efforts have the potential to reduce the barrier of stigma in the context of lung cancer and facilitate demonstrable improvements in clinical care and quality of life.