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Maxfield LK, Emmers-Sommer TM. Resilience Building Discourse in Online Spaces: A Comparative Analysis of User Statements Following the Disclosure of a Break in Alcohol Abstinence. Alcohol 2025:S0741-8329(25)00057-6. [PMID: 40311766 DOI: 10.1016/j.alcohol.2025.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 04/14/2025] [Accepted: 04/23/2025] [Indexed: 05/03/2025]
Abstract
This study investigates statements made by individuals who either disclose having experienced a break in alcohol abstinence or provide a first-level response to such disclosures. An average month of public Reddit data were examined, resulting in 193 posts and 1238 responses. Post statements were binarily considered according to eight a priori categories, primarily guided by the communication resilience process scale (CRPS; Wilson et al., 2021). Coded response posts were collapsed into sets corresponding to initial posts, facilitating the saturation comparison of resilience building statements between initial and response posts. Results indicate that responses were more resilience-heavy than initial posts, suggesting users looking to disclose an abstinence break have a good chance of experiencing resilience building responses. Notably, the top three resilience building categories identified in this study were identical for initial and response posts. Discussion, implications, and future research directions regarding communicating resilience and resilience building discourse follow.
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Affiliation(s)
- Lynda K Maxfield
- Department of Communication Studies, University of Nevada, Las Vegas.
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2
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Levy DA, Jordan HS, Lalor JP, Smirnova JK, Hu W, Liu W, Yu H. Individual Factors That Affect Laypeople's Understanding of Definitions of Medical Jargon. HEALTH POLICY AND TECHNOLOGY 2024; 13:100932. [PMID: 39650577 PMCID: PMC11618823 DOI: 10.1016/j.hlpt.2024.100932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2024]
Abstract
Objective Patients have difficulty understanding medical jargon in electronic health record (EHR) notes. Lay definitions can improve patient comprehension, which is the goal of the NoteAid project. We assess whether the NoteAid definitions are understandable to laypeople and whether understandability differs with respect to layperson characteristics. Methods Definitions for jargon terms were written for laypersons with a 4th-to-7th-grade reading level. 300 definitions were randomly sampled from a corpus of approximately 30,000 definitions. 280 laypeople (crowdsource workers) were recruited; each layperson rated the understandability of 20 definitions. Understandability was rated on a 5-point scale. Using a generalized estimating equation model (GEE) we analyzed the relationship between understandability and age, sex, race/ethnicity, education level, native language, health literacy, and definition writer. Results Overall, 81.1% (95% CI: 76.5-85.7%) of the laypeople reported that the definitions were understandable. Males were less likely to report understanding the definitions than females (OR: 0.73, 95% CI: 0.63-0.84). Asians, Hispanics, and those who marked their race/ethnicity as "other" were more likely to report understanding the definitions than whites (Asians: OR: 1.43, 95% CI: 1.17-1.73; Hispanics: OR: 1.86, 95% CI: 1.33-2.59; Other: OR: 2.48, 95% CI: 1.65-3.74). Laypeople whose native language was not English were less likely to report understanding the definitions (OR: 0.51, 95% CI: 0.36-0.74). Laypeople with lower health literacy were less likely to report understanding definitions (health literacy score 3: OR: 0.51, 95% CI: 0.43-0.62; health literacy score 4: OR: 0.40, 95% CI: 0.29-0.55). Conclusion Understandability of definitions among laypeople was high. There were statistically significant race/ethnic differences in self-reported understandability, even after controlling for multiple demographics.
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Affiliation(s)
- David A. Levy
- Department of Computer Science, University of Massachusetts Lowell, Lowell, MA
| | - Harmon S. Jordan
- Assistant Professor, Tufts University School of Medicine, Boston, MA
| | - John P. Lalor
- Department of IT, Analytics, and Operations, Mendoza College of Business, University of Notre Dame, Notre Dame, IN
| | | | - Wen Hu
- Center for Biomedical and Health Research in Data Sciences, University of Massachusetts Lowell, Lowell, MA
| | - Weisong Liu
- Center for Biomedical and Health Research in Data Sciences, University of Massachusetts Lowell, Lowell, MA
| | - Hong Yu
- Center for Biomedical and Health Research in Data Sciences, University of Massachusetts Lowell, Lowell, MA
- Manning College of Information and Computer Sciences, University of Massachusetts Amherst, Amherst, MA
- Center for Healthcare Organization & Implementation Research, Veterans Affairs Bedford Healthcare System, Bedford, MA
- Miner School of Computer and Information Sciences, University of Massachusetts Lowell, Lowell, MA
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3
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Mallya MM, Liu-Zarzuela J, Munoz IB, Shotwell J. Assessing the Educational Value of YouTube Kids Videos Related to Anxiety, Depression, and Attention-Deficit/Hyperactivity Disorder. J Am Acad Child Adolesc Psychiatry 2024; 63:1179-1181. [PMID: 39029787 DOI: 10.1016/j.jaac.2024.05.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/09/2024] [Accepted: 07/10/2024] [Indexed: 07/21/2024]
Abstract
This Letter to the Editor reports the findings of a study we undertook to assess the quality and content of the mental health information that is provided to children via YouTube Kids. For videos on depression and anxiety, we found that all videos were useful or neutral (neither useful nor misleading). In contrast, most videos on attention-deficit/hyperactivity disorder (ADHD) were useful or neutral, but few were deemed misleading. Many of the videos on depression, anxiety, and ADHD promoted supportive statements and help-seeking behavior. Recommendations include calling on social media platforms to continue moderating content and involving more health care professionals and/or individuals with lived experiences to create accurate but engaging videos.
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Etumuse B, Greer M, Onyemachi J, El-Abed Y, Kamma S, Shah JD, Tran HT, Hussain N, Pittelkow TP, D’Souza RS. Medical Misinformation and Quality of Public Video Content on Cannabis for Chronic Pain Management: A Cross-Sectional Analysis of the YouTube Platform. J Pain Res 2024; 17:3577-3586. [PMID: 39526076 PMCID: PMC11550692 DOI: 10.2147/jpr.s479200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Accepted: 10/30/2024] [Indexed: 11/16/2024] Open
Abstract
Background As cannabis legalization expands nationally and globally, its use for chronic pain increases, prompting people to seek information on social media platforms like YouTube. This study evaluates the accuracy and quality of information of popular YouTube videos on cannabis for chronic pain. Methods Using search terms related to cannabis for pain, the top 66 videos by view count were selected. Each video was classified as useful, misleading, or neither. The quality and reliability of each video were assessed using the modified DISCERN, mDISCERN, score and the Global Quality Scale, GQS. The video characteristics, usefulness classification, mDISCERN scores, and GQS scores were summarized. Continuous and categorical outcomes were compared using t-test and chi-square, respectively. Results Of the 66 videos, 22.73% (n=15) were classified as useful, and 77.27% (n=51) were classified as neither. Of useful videos, 40.00% (n=6) were uploaded by physicians, 40.00% (n=6) were uploaded by corporations, and 6.67% (n=1) were uploaded by an independent user. Of videos classified as neither useful nor misleading, news sources uploaded 27.45% (n=14) of these videos (P=0.02). Physicians uploaded 37.50% (n = 18) of videos with a GQS score ≥3 (P=0.04), while independent users uploaded significantly more videos with a mDISCERN score <3 (22.20%, P=0.02). Useful videos had a mean GQS of 4.00 ± 0.65 compared to a mean GQS of 2.76 ± 0.86 for videos deemed neither (P<0.0001). Conclusion This study suggests a moderate quality of YouTube content on cannabis use for chronic pain. Given cannabis's growing popularity and potential for misinformation on popular social media platforms, healthcare professionals and organizations should consider uploading educational videos on this topic on YouTube.
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Affiliation(s)
- Bright Etumuse
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Majesty Greer
- Howard University College of Medicine, Washington, DC, USA
| | - Jane Onyemachi
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | | | - Sai Kamma
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Jay D Shah
- Department of Anesthesiology, Baylor College of Medicine, Houston, TX, USA
| | - Henry Tuan Tran
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Nasir Hussain
- Department of Anesthesiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Thomas P Pittelkow
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ryan S D’Souza
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
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Gupta A, Beletsky A, Shen AY, Chin W, Liu C, Reddy R. YouTube as a Source of Medical Information About Peripheral Nerve Stimulation. Neuromodulation 2024:S1094-7159(24)01185-1. [PMID: 39520457 DOI: 10.1016/j.neurom.2024.09.472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Revised: 08/30/2024] [Accepted: 09/03/2024] [Indexed: 11/16/2024]
Abstract
OBJECTIVES YouTube is an important source of medical information for various medical topics and procedures. The purpose of the present study is to appraise the quality of medical information available on YouTube on the topic of peripheral nerve stimulation (PNS) for chronic pain. MATERIALS AND METHODS A total of 53 videos were appraised by four individuals using three scales for appraisal: 1) the Modified DISCERN scale, 2) the Journal of American Medical Association (JAMA) Benchmark scoring, and 3) the Global Quality Scale. Descriptive characteristics and author type of each video were recorded. The mean scores of these scales among all four reviewers based on author type were calculated. One-way analysis of variance was used to compare mean scores of the three scales among author types, and post hoc pairwise Tukey's honestly significant difference test was used to evaluate for significant differences between mean scores. Furthermore, mean scale scores of videos above and below the total average-view count and total average "thumbs ups" were calculated and compared. RESULTS Most videos (n = 31, 58.5%) were submitted from private practice. The mean Modified DISCERN and JAMA scores of videos by academic and society authors (M = 3.54 and 2.83, respectively) were significantly higher (p < 0.05) than the mean Modified DISCERN and JAMA scores of videos by private practice authors (M = 2.10 and 2.03, respectively). Interestingly, the mean scale scores of videos with above-average view counts were found to be lower than scores of videos with below-average view counts across all three scoring instruments. CONCLUSIONS YouTube videos on PNS stimulation for chronic pain are low to moderate in quality. Videos from academic sources were higher in quality than were private practice videos. Furthermore, videos with above-average view counts had lower mean scores on all three instruments, suggesting most of the viewership had watched lower-quality video content.
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Affiliation(s)
- Abhinav Gupta
- Department of Anesthesiology, Division of Pain, University of California San Diego, La Jolla, CA, USA.
| | - Alexander Beletsky
- Department of Anesthesiology, Riverside Community Hospital, Riverside, CA, USA
| | - Alice Y Shen
- Department of Anesthesiology, Division of Pain, University of California San Diego, La Jolla, CA, USA
| | - Wesley Chin
- Department of Anesthesiology, Riverside Community Hospital, Riverside, CA, USA
| | - Cherry Liu
- Department of Anesthesiology, Riverside Community Hospital, Riverside, CA, USA
| | - Rajiv Reddy
- Department of Anesthesiology, Division of Pain, University of California San Diego, La Jolla, CA, USA
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Nelms MW, Javidan A, Chin KJ, Vignarajah M, Zhou F, Tian C, Lee Y, Kayssi A, Naji F, Singh M. YouTube as a source of education in perioperative anesthesia for patients and trainees: a systematic review. Can J Anaesth 2024; 71:1238-1250. [PMID: 38902576 DOI: 10.1007/s12630-024-02791-5] [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: 11/06/2023] [Revised: 03/15/2024] [Accepted: 03/16/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND Online video sharing platforms like YouTube (Google LLC, San Bruno, CA, USA) have become a substantial source of health information. We sought to conduct a systematic review of studies assessing the overall quality of perioperative anesthesia videos on YouTube. METHODS We searched Embase, MEDLINE, and Ovid for articles published from database inception to 1 May 2023. We included primary studies evaluating YouTube videos as a source of information regarding perioperative anesthesia. We excluded studies not published in English and studies assessing acute or chronic pain. Studies were screened and data were extracted in duplicate by two reviewers. We appraised the quality of studies according to the social media framework published in the literature. We used descriptive statistics to report the results using mean, standard deviation, range, and n/total N (%). RESULTS Among 8,908 citations, we identified 14 studies that examined 796 videos with 59.7 hr of content and 47.5 million views. Among the 14 studies that evaluated the video content quality, 17 different quality assessment tools were used, only three of which were externally validated (Global Quality Score, modified DISCERN score, and JAMA score). Per global assessment rating of video quality, 11/13 (85%) studies concluded the overall video quality as poor. CONCLUSIONS Overall, the educational content quality of YouTube videos evaluated in the literature accessible as an educational resource regarding perioperative anesthesia was poor. While these videos are in demand, their impact on patient and trainee education remains unclear. A standardized methodology for evaluating online videos is merited to improve future reporting. A peer-reviewed approach to online open-access videos is needed to support patient and trainee education in anesthesia. STUDY REGISTRATION Open Science Framework ( https://osf.io/ajse9 ); first posted, 1 May 2023.
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Affiliation(s)
- Matthew W Nelms
- Department of Anesthesia, McMaster University, Hamilton, ON, Canada
| | - Arshia Javidan
- Division of Vascular Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Ki Jinn Chin
- Department of Anesthesiology & Pain Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Fangwen Zhou
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - Chenchen Tian
- Department of Anesthesiology & Pain Medicine, University of Toronto, Toronto, ON, Canada
| | - Yung Lee
- Division of General Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada
| | - Ahmed Kayssi
- Division of Vascular Surgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Faysal Naji
- Division of Vascular Surgery, Department of Surgery, McMaster University, Hamilton, ON, Canada
| | - Mandeep Singh
- Department of Anesthesiology and Pain Medicine, University of Toronto, 399 Bathurst St, Toronto, ON, M5T 2S6, Canada.
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7
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Greer M, Kamma S, Tran H, Etumuse B, Shah JD, El-Abed Y, Onyemachi JO, Hussain N, Pittelkow TP, D’Souza RS. Misinformation Persists in Complementary Health: Evaluating the Reliability and Quality of YouTube-Based Information on the Use of Acupuncture for Chronic Pain. J Pain Res 2024; 17:1509-1518. [PMID: 38646592 PMCID: PMC11032134 DOI: 10.2147/jpr.s459475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 04/06/2024] [Indexed: 04/23/2024] Open
Abstract
Introduction Acupuncture is commonly used to treat chronic pain. Patients often access public social media platforms for healthcare information when querying acupuncture. Our study aims to appraise the utility, accuracy, and quality of information available on YouTube, a popular social media platform, on acupuncture for chronic pain treatment. Methods Using search terms such as "acupuncture for chronic pain" and "acupuncture pain relief", the top 54 videos by view count were selected. Included videos were >1 minute duration, contained audio in English, had >7000 views, and was related to acupuncture. One primary outcome of interest was categorizing each video's usefulness as useful, misleading, or neither. Another primary outcome of interest was the quality and reliability of each video using validated instruments, including the modified DISCERN (mDISCERN) tool and the Global Quality Scale (GQS). The means were calculated for the video production characteristics, production sources, and mDISCERN and GQS scores. Continuous and categorical outcomes were compared using Student's t-test and chi-square test, respectively. Results Of the 54 videos, 57.4% were categorized as useful, 14.8% were misleading, and 27.8% were neither. Useful videos had a mean GQS and mDISCERN score of 3.77±0.67 and 3.48±0.63, respectively, while misleading videos had mean GQS and mDISCERN score of 2.50±0.53 and 2.38±0.52, respectively. 41.8% of the useful videos were produced by a healthcare institution while none of the misleading videos were produced by a healthcare institution. However, 87.5% of the misleading videos were produced by health media compared to only 25.8% of useful videos from health media. Discussion As patients increasingly depend on platforms like YouTube for trustworthy information on complementary health practices such as acupuncture, our study emphasizes the critical need for more higher-quality videos from unbiased healthcare institutions and physicians to ensure patients are receiving reliable information regarding this topic.
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Affiliation(s)
- Majesty Greer
- Howard University College of Medicine, Washington, DC, USA
| | - Sai Kamma
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Henry Tran
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Bright Etumuse
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Jay D Shah
- Department of Anesthesiology, Baylor College of Medicine, Houston, TX, USA
| | - Youshaa El-Abed
- College of Osteopathic Medicine, Kansas City University, Kansas City, MO, USA
| | - Jane O Onyemachi
- University of Texas Medical Branch School of Medicine, Galveston, TX, USA
| | - Nasir Hussain
- Department of Anesthesiology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Thomas P Pittelkow
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ryan S D’Souza
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN, USA
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Sedlakova J, Daniore P, Horn Wintsch A, Wolf M, Stanikic M, Haag C, Sieber C, Schneider G, Staub K, Alois Ettlin D, Grübner O, Rinaldi F, von Wyl V. Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review. PLOS DIGITAL HEALTH 2023; 2:e0000347. [PMID: 37819910 PMCID: PMC10566734 DOI: 10.1371/journal.pdig.0000347] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 08/14/2023] [Indexed: 10/13/2023]
Abstract
Digital data play an increasingly important role in advancing health research and care. However, most digital data in healthcare are in an unstructured and often not readily accessible format for research. Unstructured data are often found in a format that lacks standardization and needs significant preprocessing and feature extraction efforts. This poses challenges when combining such data with other data sources to enhance the existing knowledge base, which we refer to as digital unstructured data enrichment. Overcoming these methodological challenges requires significant resources and may limit the ability to fully leverage their potential for advancing health research and, ultimately, prevention, and patient care delivery. While prevalent challenges associated with unstructured data use in health research are widely reported across literature, a comprehensive interdisciplinary summary of such challenges and possible solutions to facilitate their use in combination with structured data sources is missing. In this study, we report findings from a systematic narrative review on the seven most prevalent challenge areas connected with the digital unstructured data enrichment in the fields of cardiology, neurology and mental health, along with possible solutions to address these challenges. Based on these findings, we developed a checklist that follows the standard data flow in health research studies. This checklist aims to provide initial systematic guidance to inform early planning and feasibility assessments for health research studies aiming combining unstructured data with existing data sources. Overall, the generality of reported unstructured data enrichment methods in the studies included in this review call for more systematic reporting of such methods to achieve greater reproducibility in future studies.
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Affiliation(s)
- Jana Sedlakova
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Institute of Biomedical Ethics and History of Medicine, University of Zurich, Zurich, Switzerland
| | - Paola Daniore
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
| | - Andrea Horn Wintsch
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Center for Gerontology, University of Zurich, Zurich, Switzerland
- CoupleSense: Health and Interpersonal Emotion Regulation Group, University Research Priority Program (URPP) Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland
| | - Markus Wolf
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Mina Stanikic
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Christina Haag
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Chloé Sieber
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
| | - Gerold Schneider
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Department of Computational Linguistics, University of Zurich, Zurich, Switzerland
| | - Kaspar Staub
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute of Evolutionary Medicine, University of Zurich, Zurich, Switzerland
| | - Dominik Alois Ettlin
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Center of Dental Medicine, University of Zurich, Zurich, Switzerland
| | - Oliver Grübner
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Department of Geography, University of Zurich, Zurich, Switzerland
| | - Fabio Rinaldi
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Dalle Molle Institute for Artificial Intelligence (IDSIA), Switzerland
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Fondazione Bruno Kessler, Trento, Italy
- Swiss Institute of Bioinformatics, Switzerland
| | - Viktor von Wyl
- Digital Society Initiative, University of Zurich, Zurich, Switzerland
- Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
- Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland
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Jeyaraman M, Ramasubramanian S, Kumar S, Jeyaraman N, Selvaraj P, Nallakumarasamy A, Bondili SK, Yadav S. Multifaceted Role of Social Media in Healthcare: Opportunities, Challenges, and the Need for Quality Control. Cureus 2023; 15:e39111. [PMID: 37332420 PMCID: PMC10272627 DOI: 10.7759/cureus.39111] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2023] [Indexed: 06/20/2023] Open
Abstract
Social media, leveraging Web 2.0 technologies, plays a vital role in healthcare, medical education, and research by fostering collaboration and enabling research dissemination. Healthcare professionals use these platforms to improve public health literacy, but concerns about misinformation and content accuracy persist. In 2023, platforms like Facebook (Meta Platforms, Inc., Menlo Park, California, United States), YouTube (Google LLC, Mountain View, California, United States), Instagram (Meta Platforms, Inc.), TikTok (ByteDance Ltd, Beijing, China), and Twitter (X Corp., Carson City, Nevada, United States) have become essential in healthcare, offering patient communication, professional development, and knowledge-sharing opportunities. However, challenges such as breaches of patient confidentiality and unprofessional conduct remain. Social media has transformed medical education, providing unique networking and professional development opportunities. Further studies are needed to determine its educational value. Healthcare professionals must follow ethical and professional guidelines, particularly regarding patient privacy, confidentiality, disclosure rules, and copyright laws. Social media significantly impacts patient education and healthcare research. Platforms like WhatsApp (Meta Platforms, Inc.) effectively improve patient compliance and outcomes. Yet, the rapid dissemination of false news and misinformation on social media platforms presents risks. Researchers must consider potential biases and content quality when extracting data. Quality control and regulation are crucial in addressing potential dangers and misinformation in social media and healthcare. Stricter regulations and monitoring are needed due to cases of deaths resulting from social media trends and false news spread. Ethical frameworks, informed consent practices, risk assessments, and appropriate data management strategies are essential for responsible research using social media technologies. Healthcare professionals and researchers must judiciously use social media, considering its risks to maximize benefits and mitigate potential drawbacks. By striking the right balance, healthcare professionals can enhance patient outcomes, medical education, research, and the overall healthcare experience.
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Affiliation(s)
- Madhan Jeyaraman
- Orthopaedics, ACS Medical College and Hospital, Dr MGR (M.G.Ramachandran) Educational and Research Institute, Chennai, IND
| | | | - Shanmugapriya Kumar
- Respiratory Medicine, Sri Lalithambigai Medical College and Hospital, Dr MGR (M.G.Ramachandran) Educational and Research Institute, Chennai, IND
| | - Naveen Jeyaraman
- Orthopaedics, Shri Sathya Sai Medical College and Research Institute, Sri Balaji Vidyapeeth, Nellikuppam, IND
| | - Preethi Selvaraj
- Community Medicine, Sri Lalithambigai Medical College and Hospital, Dr MGR (M.G.Ramachandran) Educational and Research Institute, Chennai, IND
| | - Arulkumar Nallakumarasamy
- Orthopaedics and Traumatology, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, IND
- Orthopedics, Institute of Medical Sciences, Banaras Hindu University, Varanasi, IND
| | | | - Sankalp Yadav
- Medicine, Shri Madan Lal Khurana Chest Clinic, Moti Nagar, New Delhi, IND
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10
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Dusetzina PhD SB, Enewold Mph PhD L, Gentile PhD D, Ramsey Md PhD SD, Halpern MT. New Data Resources, Linkages, and Infrastructure for Cancer Health Economics Research: Main Topics From a Panel Discussion. J Natl Cancer Inst Monogr 2022; 2022:68-73. [PMID: 35788378 DOI: 10.1093/jncimonographs/lgac016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 04/06/2022] [Indexed: 11/14/2022] Open
Abstract
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.
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Affiliation(s)
| | | | | | - Scott D Ramsey Md PhD
- Fred Hutchinson Cancer Center, Hutchinson Institute for Cancer Outcomes Research, Seattle, WA, USA
| | - Michael T Halpern
- Healthcare Delivery Research Program, National Cancer Institute, Bethesda, MD, USA
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11
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D'Souza RS, Daraz L, Hooten WM, Guyatt G, Murad MH. Users' Guides to the Medical Literature series on social media (part 1): how to interpret healthcare information available on platforms. BMJ Evid Based Med 2022; 27:11-14. [PMID: 34933925 DOI: 10.1136/bmjebm-2021-111817] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/09/2021] [Indexed: 01/21/2023]
Affiliation(s)
- Ryan S D'Souza
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota, USA
| | - Lubna Daraz
- School of Library and Information Science, University of Montreal, Montreal, Quebec, Canada
| | - W Michael Hooten
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota, USA
| | - Gordon Guyatt
- Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Ontario, Canada
| | - Mohammad Hassan Murad
- Kern Center for the Science of Healthcare Delivery, Mayo Clinic Hospital, Rochester, Minnesota, USA
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D'Souza RS, Daraz L, Hooten WM, Guyatt G, Murad MH. Users' Guides to the Medical Literature series on social media (part 2): how to appraise studies using data from platforms. BMJ Evid Based Med 2022; 27:15-20. [PMID: 34933929 DOI: 10.1136/bmjebm-2021-111850] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/09/2021] [Indexed: 01/04/2023]
Affiliation(s)
- Ryan S D'Souza
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota, USA
| | - Lubna Daraz
- School of Library and Information Science, University of Montreal, Montreal, Quebec, Canada
| | - W Michael Hooten
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic Hospital, Rochester, Minnesota, USA
| | - Gordon Guyatt
- Department of Health Research Methods, Evidence, and Impact (HEI), McMaster University, Hamilton, Ontario, Canada
| | - Mohammad Hassan Murad
- Kern Center for the Science of Healthcare Delivery, Mayo Clinic Hospital, Rochester, Minnesota, USA
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D'Souza RS, Kilgore AE, D'Souza S. Manifestations of Pain during the COVID-19 Pandemic Portrayed on Social Media: A Cross-Sectional Study. PAIN MEDICINE 2021; 23:229-233. [PMID: 34668551 DOI: 10.1093/pm/pnab305] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/08/2021] [Accepted: 10/14/2021] [Indexed: 12/27/2022]
Affiliation(s)
- Ryan S D'Souza
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine, Rochester, MN
| | - Anthony E Kilgore
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine, Phoenix, AZ
| | - Shawn D'Souza
- Virginia Commonwealth University School of Medicine, Richmond, VA
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Ji M, Xie W, Huang R, Qian X. Automatic Diagnosis of Mental Healthcare Information Actionability: Developing Binary Classifiers. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182010743. [PMID: 34682483 PMCID: PMC8536017 DOI: 10.3390/ijerph182010743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 12/04/2022]
Abstract
We aimed to develop a quantitative instrument to assist with the automatic evaluation of the actionability of mental healthcare information. We collected and classified two large sets of mental health information from certified mental health websites: generic and patient-specific mental healthcare information. We compared the performance of the optimised classifier with popular readability tools and non-optimised classifiers in predicting mental health information of high actionability for people with mental disorders. sensitivity of the classifier using both semantic and structural features as variables achieved statistically higher than that of the binary classifier using either semantic (p < 0.001) or structural features (p = 0.0010). The specificity of the optimized classifier was statistically higher than that of the classifier using structural variables (p = 0.002) and the classifier using semantic variables (p = 0.001). Differences in specificity between the full-variable classifier and the optimised classifier were statistically insignificant (p = 0.687). These findings suggest the optimised classifier using as few as 19 semantic-structural variables was the best-performing classifier. By combining insights of linguistics and statistical analyses, we effectively increased the interpretability and the diagnostic utility of the binary classifiers to guide the development, evaluation of the actionability and usability of mental healthcare information.
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Affiliation(s)
- Meng Ji
- School of Languages and Cultures, University of Sydney, Sydney 2006, Australia;
- Correspondence:
| | - Wenxiu Xie
- Department of Computer Science, City University of Hong Kong, Hong Kong 999077, China;
| | - Riliu Huang
- School of Languages and Cultures, University of Sydney, Sydney 2006, Australia;
| | - Xiaobo Qian
- School of Computer Science, South China Normal University, Guangzhou 510631, China;
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