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Zhang Y, Fu J, Lai J, Deng S, Guo Z, Zhong C, Tang J, Cao W, Wu Y. Reporting of Ethical Considerations in Qualitative Research Utilizing Social Media Data on Public Health Care: Scoping Review. J Med Internet Res 2024; 26:e51496. [PMID: 38758590 PMCID: PMC11143395 DOI: 10.2196/51496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 11/29/2023] [Accepted: 04/16/2024] [Indexed: 05/18/2024] Open
Abstract
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.
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Affiliation(s)
- Yujie Zhang
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Jiaqi Fu
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Jie Lai
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Shisi Deng
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Zihan Guo
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Chuhan Zhong
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Jianyao Tang
- Nanfang Hospital, Southern Medical University, Guangzhou, China
- School of Nursing, Southern Medical University, Guangzhou, China
| | - Wenqiong Cao
- Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yanni Wu
- Nanfang Hospital, Southern Medical University, Guangzhou, China
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Mazzeffi M, Strickland L, Coffman Z, Miller B, Hilton E, Kohan L, Keneally R, McNaull P, Elkassabany N. Cross sectional study of Twitter (X) use among academic anesthesiology departments in the United States. PLoS One 2024; 19:e0298741. [PMID: 38330078 PMCID: PMC10852312 DOI: 10.1371/journal.pone.0298741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 01/29/2024] [Indexed: 02/10/2024] Open
Abstract
Twitter (recently renamed X) is used by academic anesthesiology departments as a social media platform for various purposes. We hypothesized that Twitter (X) use would be prevalent among academic anesthesiology departments and that the number of tweets would vary by region, physician faculty size, and National Institutes of Health (NIH) research funding rank. We performed a descriptive study of Twitter (X) use by academic anesthesiology departments (i.e. those with a residency program) in 2022. Original tweets were collected using a Twitter (X) analytics tool. Summary statistics were reported for tweet number and content. The median number of tweets was compared after stratifying by region, physician faculty size, and NIH funding rank. Among 166 academic anesthesiology departments, there were 73 (44.0%) that had a Twitter (X) account in 2022. There were 3,578 original tweets during the study period and the median number of tweets per department was 21 (25th-75th = 0, 75) with most tweets (55.8%) announcing general departmental news and a smaller number highlighting social events (12.5%), research (11.1%), recruiting (7.1%), DEI activities (5.2%), and trainee experiences (4.1%). There was no significant difference in the median number of tweets by region (P = 0.81). The median number of tweets differed significantly by physician faculty size (P<0.001) with larger departments tweeting more and also by NIH funding rank (P = 0.005) with highly funded departments tweeting more. In 2022, we found that less than half of academic anesthesiology departments had a Twitter (X) account, and the median number of annual tweets per account was relatively low. Overall, Twitter (X) use was less common than anticipated among academic anesthesiology departments and most tweets focused on promotion of departmental activities or individual faculty. There may be opportunities for more widespread and effective use of Twitter (X) by academic anesthesiology departments including education about anesthesiology as a specialty.
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Affiliation(s)
- Michael Mazzeffi
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Lindsay Strickland
- Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Zachary Coffman
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Braden Miller
- Public Health Sciences, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Ebony Hilton
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Lynn Kohan
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Ryan Keneally
- Department of Anesthesiology and Critical Care Medicine, George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, United States of America
| | - Peggy McNaull
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
| | - Nabil Elkassabany
- Department of Anesthesiology, University of Virginia School of Medicine, Charlottesville, Virginia, United States of America
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Verma M, Moudgil N, Goel G, Pardeshi P, Joseph J, Kumar N, Singh K, Singh H, Kodali PB. People's perceptions on COVID-19 vaccination: an analysis of twitter discourse from four countries. Sci Rep 2023; 13:14281. [PMID: 37653001 PMCID: PMC10471683 DOI: 10.1038/s41598-023-41478-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 08/27/2023] [Indexed: 09/02/2023] Open
Abstract
More than six and half million people have died as a result of the COVID-19 pandemic till Dec 2022. Vaccination is the most effective means to prevent mortality and infection attributed to COVID-19. Identifying public attitudes and perceptions on COVID-19 vaccination is essential to strengthening the vaccination programmes. This study aims to identify attitudes and perceptions of twitter users towards COVID-19 vaccinations in four different countries. A sentiment analysis of 663,377 tweets from October 2020 to September 2022 from four different countries (i.e., India, South Africa, UK, and Australia) was conducted. Text mining using roBERTA (Robustly Optimized Bert Pretraining approach) python library was used to identify the polarity of people's attitude as "negative", "positive" or "neutral" based on tweets. A sample of 2000 tweets (500 from each country) were thematically analysed to explore the people's perception concerning COVID-19 vaccines across the countries. The attitudes towards COVID-19 vaccines varied by countries. Negative attitudes were observed to be highest in India (58.48%), followed by United Kingdom (33.22%), Australia (31.42%) and South Africa (28.88%). Positive attitudes towards vaccines were highest in the United Kingdom (21.09%). The qualitative analysis yielded eight themes namely (i) vaccine shortages, (ii) vaccine side-effects, (iii) distrust on COVID-19 vaccines, (iv) voices for vaccine equity, (v) awareness about vaccines, (vi) myth busters, (vii) vaccines work and (viii) vaccines are safe. The twitter discourse reflected the evolving situation of COVID-19 pandemic and vaccination strategies, lacunae and positives in the respective countries studied.
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Affiliation(s)
- Manah Verma
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, 147004, India
| | - Nikhil Moudgil
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, 147004, India
| | - Gaurav Goel
- School of Energy and Environment, Thapar Institute of Engineering and Technology, Patiala, Punjab, 147004, India
| | - Peehu Pardeshi
- Jamsetji Tata School of Disaster Studies, Tata Institute of Social Sciences, Deonar, Mumbai, 400088, India
- Tata Center for Technology and Design, Indian Institute of Technology Bombay, Mumbai, India
| | - Jacquleen Joseph
- Jamsetji Tata School of Disaster Studies, Tata Institute of Social Sciences, Deonar, Mumbai, 400088, India
| | - Neeraj Kumar
- Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, 147004, India
- School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
- Faculty of computing and IT, King Abdulaziz University, Jeddah, Saudi Arabia
- Department of Computer Science and Engineering, Graphics Era University, Dehradun, India
- Department of Electrical and Computer Engineering, Lebanese American University, Beirut, Lebanon
| | - Kulbir Singh
- Department of Civil Engineering, MM Engineering College, Maharishi Markandeshwar (Deemed to Be University), Mullana-Ambala, 133207, Haryana, India
| | - Hari Singh
- Chemistry Department, RIMT UNIVERSITY, Mandi Gobindgarh, Punjab, 147301, India
| | - Prakash Babu Kodali
- Department of Public Health and Community Medicine, Central University of Kerala, Kasaragod, Kerala, 671320, India.
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Blau A, Sela Y, Grinberg K. Public Perceptions and Attitudes on the Image of Nursing in the Wake of COVID-19. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:4717. [PMID: 36981622 PMCID: PMC10048593 DOI: 10.3390/ijerph20064717] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/03/2023] [Accepted: 03/05/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND The COVID-19 pandemic in recent years has given nursing teams a unique place in this war, and an opportunity to change public opinion. The perceptions have the power to affect the users of health services, the nurses' performance, health policy, and even the choice to become a nurse. AIM To examine the relationship between the public's perceptions and attitudes to the nursing profession compared with other healthcare professions, and to examine the relationship with the image of nursing in the wake of the COVID-19 pandemic. DESIGN AND METHODS This study is a cross-sectional study, with a descriptive correlational design. Specifically, 80 respondents, men and women aged 18-75, joined a survey consisting of an anonymous questionnaire. RESULTS A positive relationship was found between the public's perceptions and attitudes to nursing compared with other professions and the image of nursing in the wake of COVID-19, so the more positive public opinion was, the more positive the image of nursing would be. CONCLUSION In the wake of COVID-19, the public's opinion and perception of the nursing profession compared to other professions and their attitudes to nurses are more positive. It is important to continue to explore which factors most affected and changed the image of nursing during the pandemic, and to design strategies to preserve the improved image of nursing among the public on an ongoing basis.
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Affiliation(s)
- Ayala Blau
- Nursing Sciences Department, Ariel University, Ariel 40700, Israel
| | - Yael Sela
- Nursing Sciences Department, Faculty of Social and Community Sciences, Ruppin Academic Center, Emek-Hefer 4025000, Israel
| | - Keren Grinberg
- Nursing Sciences Department, Faculty of Social and Community Sciences, Ruppin Academic Center, Emek-Hefer 4025000, Israel
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Tokac U, Brysiewicz P, Chipps J. Public perceptions on Twitter of nurses during the COVID-19 pandemic. Contemp Nurse 2022; 58:414-423. [PMID: 36370034 DOI: 10.1080/10376178.2022.2147850] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
BACKGROUND The use of social media platforms to convey public opinions and attitudes has exponentially increased over the last decade on topics related to health. In all these social media postings related to the pandemic, specific attention has been focused on healthcare professionals, specifically nurses. OBJECTIVE This study aimed to explore how the keyword 'nurse' is located in COVID-19 pandemic-related tweets during a selected period of the pandemic in order to assess public perception. METHODS Tweets related to COVID-19 were downloaded from Twitter for the period January 1st, 2020, to November 11th, 2021. Sentiment analysis was used to identify opinions, emotions, and approaches expressed in tweet which included 'nurse', 'COVID-19', and 'pandemic' as either keyword or hashtags. RESULTS A total of 2,440,696 most used unique words in the downloaded 582,399 tweets were included and the sentiment analysis indicated that 24.4% (n = 595,530) of the tweets demonstrated positive sentiment while 14.1% (n = 343,433) of the tweets demonstrated negative sentiment during COVID-19. Within these results, 17% (n = 416,366) of the tweets included positive basic emotion words of trust and 4.9% (n = 120,654) of joy. In terms of negative basic emotion words, 9.9% (n = 241,758) of the tweets included the word fear, 8.3% (n = 202,179) anticipation, 7.9% (n = 193,145) sadness, 5.7% (n = 139,791) anger, 4.2% (n = 103,936) disgust, and 3.6% (n = 88,338) of the tweets included the word surprised. CONCLUSIONS It is encouraging to note that with the advent of major health crises, public perceptions on social media, appears to portray an image of nurses which reflects the professionalism and values of the profession.
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Affiliation(s)
- Umit Tokac
- UMSL College of Nursing, University of Missouri, One University Boulevard, St Louis, MO 63131-4400, USA
| | - Petra Brysiewicz
- Discipline of Nursing, School of Nursing and Public Health, University of KwaZulu-Natal, Mazisi Kunene Road, Glenwood, Durban, 4041, South Africa
| | - Jennifer Chipps
- School of Nursing, Faculty of Community Health Sciences, University of the Western Cape, 14 Blanckenberg Road, Belville, Capetown, South Africa
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