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Laymouna M, Ma Y, Lessard D, Schuster T, Engler K, Lebouché B. Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review. J Med Internet Res 2024; 26:e56930. [PMID: 39042446 PMCID: PMC11303905 DOI: 10.2196/56930] [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: 02/02/2024] [Revised: 04/07/2024] [Accepted: 04/12/2024] [Indexed: 07/24/2024] Open
Abstract
BACKGROUND Chatbots, or conversational agents, have emerged as significant tools in health care, driven by advancements in artificial intelligence and digital technology. These programs are designed to simulate human conversations, addressing various health care needs. However, no comprehensive synthesis of health care chatbots' roles, users, benefits, and limitations is available to inform future research and application in the field. OBJECTIVE This review aims to describe health care chatbots' characteristics, focusing on their diverse roles in the health care pathway, user groups, benefits, and limitations. METHODS A rapid review of published literature from 2017 to 2023 was performed with a search strategy developed in collaboration with a health sciences librarian and implemented in the MEDLINE and Embase databases. Primary research studies reporting on chatbot roles or benefits in health care were included. Two reviewers dual-screened the search results. Extracted data on chatbot roles, users, benefits, and limitations were subjected to content analysis. RESULTS The review categorized chatbot roles into 2 themes: delivery of remote health services, including patient support, care management, education, skills building, and health behavior promotion, and provision of administrative assistance to health care providers. User groups spanned across patients with chronic conditions as well as patients with cancer; individuals focused on lifestyle improvements; and various demographic groups such as women, families, and older adults. Professionals and students in health care also emerged as significant users, alongside groups seeking mental health support, behavioral change, and educational enhancement. The benefits of health care chatbots were also classified into 2 themes: improvement of health care quality and efficiency and cost-effectiveness in health care delivery. The identified limitations encompassed ethical challenges, medicolegal and safety concerns, technical difficulties, user experience issues, and societal and economic impacts. CONCLUSIONS Health care chatbots offer a wide spectrum of applications, potentially impacting various aspects of health care. While they are promising tools for improving health care efficiency and quality, their integration into the health care system must be approached with consideration of their limitations to ensure optimal, safe, and equitable use.
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Affiliation(s)
- Moustafa Laymouna
- Department of Family Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada
- Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program, Research Institute of McGill University Health Centre, Montreal, QC, Canada
| | - Yuanchao Ma
- Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program, Research Institute of McGill University Health Centre, Montreal, QC, Canada
- Chronic and Viral Illness Service, Division of Infectious Disease, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
- Department of Biomedical Engineering, Polytechnique Montréal, Montreal, QC, Canada
| | - David Lessard
- Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program, Research Institute of McGill University Health Centre, Montreal, QC, Canada
- Chronic and Viral Illness Service, Division of Infectious Disease, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
| | - Tibor Schuster
- Department of Family Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada
| | - Kim Engler
- Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program, Research Institute of McGill University Health Centre, Montreal, QC, Canada
- Chronic and Viral Illness Service, Division of Infectious Disease, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
| | - Bertrand Lebouché
- Department of Family Medicine, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC, Canada
- Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program, Research Institute of McGill University Health Centre, Montreal, QC, Canada
- Chronic and Viral Illness Service, Division of Infectious Disease, Department of Medicine, McGill University Health Centre, Montreal, QC, Canada
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Chan PSF, Fang Y, Cheung DH, Zhang Q, Sun F, Mo PKH, Wang Z. Effectiveness of chatbots in increasing uptake, intention, and attitudes related to any type of vaccination: A systematic review and meta-analysis. Appl Psychol Health Well Being 2024. [PMID: 38886054 DOI: 10.1111/aphw.12564] [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] [Received: 12/23/2023] [Accepted: 05/16/2024] [Indexed: 06/20/2024]
Abstract
This systematic review and meta-analysis analyzed and summarized the growing literature on the effectiveness of chatbot-delivered interventions in increasing uptake, intention, and attitudes related to any type of vaccination. We identified randomized controlled studies (RCTs), quasi-experimental studies, and non-experimental studies from the following platforms: PubMed, Web of Science, MEDLINE, Global Health, APA PsycInfo, and EMBASE databases. A total of 12 eligible studies published from 2019 to 2023 were analyzed and summarized. In particular, one RCT showed that a chatbot-delivered tailored intervention was more effective than a chatbot-delivered non-tailored intervention in promoting seasonal influenza vaccine uptake among older adults (50.5% versus 35.3%, p = 0.002). Six RCTs were included in the meta-analysis to evaluate the effectiveness of chatbot interventions to improve vaccination attitudes and intentions. The pooled standard mean difference (SMD) of overall attitude change was 0.34 (95% confidence intervals [CI]: 0.13, 0.55, p = 0.001). We found a non-significant trivial effect of chatbot interventions on improving intentions of vaccination (SMD: 0.11, 95% CI: -0.13, 0.34, p = 0.38). However, further evidence is needed to draw a more precise conclusion. Additionally, study participants reported high satisfaction levels of using the chatbot and were likely to recommend it to others. The development of chatbots is still nascent and rooms for improvement exist.
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Affiliation(s)
- Paul Shing-Fong Chan
- Centre for Health Behaviours Research, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Yuan Fang
- Department of Health and Physical Education, the Education University of Hong Kong, Hong Kong, SAR, China
| | - Doug H Cheung
- Center of Population Sciences for Health Equity, Florida State University, Tallahassee, FL, USA
| | - Qingpeng Zhang
- Musketeers Foundation Institute of Data Science, the University of Hong Kong, Hong Kong, SAR, China
- Department of Pharmacology and Pharmacy, LKS Faculty of Medicine, the University of Hong Kong, Hong Kong, SAR, China
| | - Fenghua Sun
- Department of Health and Physical Education, the Education University of Hong Kong, Hong Kong, SAR, China
| | - Phoenix K H Mo
- Centre for Health Behaviours Research, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong, SAR, China
| | - Zixin Wang
- Centre for Health Behaviours Research, JC School of Public Health and Primary Care, the Chinese University of Hong Kong, Hong Kong, SAR, China
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Chen BL, Lien HC, Yang SS, Wu SC, Chiang HH, Lin LC. Impact of Mobile Apps in Conjunction With Percutaneous Endoscopic Gastrostomy on Patients' Complications, Quality of Life, and Health-Related Self-Care Behaviors: Randomized Clinical Trial. JMIR Mhealth Uhealth 2023; 11:e48970. [PMID: 37862072 PMCID: PMC10625096 DOI: 10.2196/48970] [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: 05/13/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Percutaneous endoscopic gastrostomy (PEG) is commonly chosen for long-term enteral nutrition support. However, common complications of PEG include wound infection, leakage, obstruction, bleeding, dislodgement, pneumonia, peritonitis, and more. The anticipation of these complications by both patients and their family caregivers underscores the essential requirement of ongoing technical guidance for the daily care of PEG and the adoption of preventative strategies. OBJECTIVE This study aimed to establish and compare a health education program utilizing a tracking system for PEG using a mobile app (PEG app) and instant messaging software versus a paper-based health education program with instant messaging software. Their effectiveness in preventing complications, avoiding hospital readmissions, improving self-care practices, and enhancing quality of life outcomes was assessed. METHODS A randomized controlled trial design was used, and the study sample consisted of patients from a medical center in central Taiwan who underwent thoracic surgery or gastroenterology procedures. Inclusion criteria were being a new case undergoing his or her first gastric tube insertion and having the ability to operate a smartphone. Exclusion criteria were cases requiring tube replacement or nasogastric tubes. A total of 74 participants were enrolled, with 37 participants in the experimental group and 37 participants in the control group. Data collection took place from hospitalization until 1 month after discharge. The experimental group received care using the gastric tube tracking system (PEG app) and the Line app that included phone, text, and photo capture capabilities, while the control group received routine nursing care and used the Line app. RESULTS The experimental group demonstrated a significant reduction in the occurrence of complications compared with the control group (χ21=12.087, P=.001). Specifically, the occurrence of leakage events was significantly lower in the experimental group than in the control group (χ21=12.906, P=.001). However, the experimental group exhibited superior self-care ability compared with the control group (t72=2.203, P=.03). There was no significant difference in overall quality of life scores between the experimental and control groups (t72=1.603, P=.11). However, the experimental group showed better social aspects of quality of life than the control group (t72=2.164, P=.03). CONCLUSIONS Integration of the PEG app with instant messaging can enhance self-care ability, improve social aspects of quality of life, and reduce complications. The study results suggest that the PEG app could be used as an adjunct tool to promote patients' self-directed management of their gastric tube at home, particularly for patients who have undergone their first PEG placement and are being discharged from the hospital. TRIAL REGISTRATION Chinese Clinical Trial Registry ChiCTR2300071271; https://tinyurl.com/4vvy584e.
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Affiliation(s)
- Bi-Lian Chen
- Department of Nursing, National Yang Ming Chiao Tung University, Taipei City, Taiwan
- Department of Nursing, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Han-Chung Lien
- Division of Gastroenterology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shyh-Sheng Yang
- The Division of Thoracic Surgery, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Shiao-Chi Wu
- Institute of Health and Welfare Policy, National Yang Ming Chiao Tung University, Taipei City, Taiwan
| | - Hsien-Hsien Chiang
- Department of Nursing, National Yang Ming Chiao Tung University, Taipei City, Taiwan
| | - Li-Chan Lin
- Department of Nursing, Asia University, Taichung, Taiwan
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Passanante A, Pertwee E, Lin L, Lee KY, Wu JT, Larson HJ. Conversational AI and Vaccine Communication: Systematic Review of the Evidence. J Med Internet Res 2023; 25:e42758. [PMID: 37788057 PMCID: PMC10582806 DOI: 10.2196/42758] [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: 09/29/2022] [Revised: 05/09/2023] [Accepted: 07/31/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Since the mid-2010s, use of conversational artificial intelligence (AI; chatbots) in health care has expanded significantly, especially in the context of increased burdens on health systems and restrictions on in-person consultations with health care providers during the COVID-19 pandemic. One emerging use for conversational AI is to capture evolving questions and communicate information about vaccines and vaccination. OBJECTIVE The objective of this systematic review was to examine documented uses and evidence on the effectiveness of conversational AI for vaccine communication. METHODS This systematic review was conducted following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. PubMed, Web of Science, PsycINFO, MEDLINE, Scopus, CINAHL Complete, Cochrane Library, Embase, Epistemonikos, Global Health, Global Index Medicus, Academic Search Complete, and the University of London library database were searched for papers on the use of conversational AI for vaccine communication. The inclusion criteria were studies that included (1) documented instances of conversational AI being used for the purpose of vaccine communication and (2) evaluation data on the impact and effectiveness of the intervention. RESULTS After duplicates were removed, the review identified 496 unique records, which were then screened by title and abstract, of which 38 were identified for full-text review. Seven fit the inclusion criteria and were assessed and summarized in the findings of this review. Overall, vaccine chatbots deployed to date have been relatively simple in their design and have mainly been used to provide factual information to users in response to their questions about vaccines. Additionally, chatbots have been used for vaccination scheduling, appointment reminders, debunking misinformation, and, in some cases, for vaccine counseling and persuasion. Available evidence suggests that chatbots can have a positive effect on vaccine attitudes; however, studies were typically exploratory in nature, and some lacked a control group or had very small sample sizes. CONCLUSIONS The review found evidence of potential benefits from conversational AI for vaccine communication. Factors that may contribute to the effectiveness of vaccine chatbots include their ability to provide credible and personalized information in real time, the familiarity and accessibility of the chatbot platform, and the extent to which interactions with the chatbot feel "natural" to users. However, evaluations have focused on the short-term, direct effects of chatbots on their users. The potential longer-term and societal impacts of conversational AI have yet to be analyzed. In addition, existing studies do not adequately address how ethics apply in the field of conversational AI around vaccines. In a context where further digitalization of vaccine communication can be anticipated, additional high-quality research will be required across all these areas.
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Affiliation(s)
- Aly Passanante
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Ed Pertwee
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Leesa Lin
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Laboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Kristi Yoonsup Lee
- Laboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Joseph T Wu
- Laboratory of Data Discovery for Health, Hong Kong Science Park, Hong Kong, China (Hong Kong)
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China (Hong Kong)
| | - Heidi J Larson
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States
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Lin CF, Chang SH. Advanced Mobile Communication Techniques in the Fight against the COVID-19 Pandemic Era and Beyond: An Overview of 5G/B5G/6G. SENSORS (BASEL, SWITZERLAND) 2023; 23:7817. [PMID: 37765874 PMCID: PMC10536366 DOI: 10.3390/s23187817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 09/09/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023]
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has severely affected people's lives worldwide in an unexpected manner. According to the World Health Organization (WHO), several viral epidemics continue to occur and pose a significant public health problem. Until May 2023, there have been 676 million cases of COVID-19 infections and over 6.8 million deaths, globally. This paper surveys the role and effectiveness of advanced fifth-generation (5G)/beyond 5G (B5G)/sixth-generation (6G) technologies, combined with mobile applications (apps) and the Internet of Medical Things (IoMT), in detecting, managing, and mitigating the spread of COVID-19 and designing smart healthcare infrastructures for future pandemics. Analyzing and summarizing the research of relevant scholars based on the impact of 5G/B5G/6G and other technologies on COVID-19. The study tabulates the technical characteristics and effectiveness of different technologies in the context of COVID-19, summarizing the research of previous scholars. Challenges and design issues in the implementation of advanced information and telecommunication systems were demonstrated. These technologies can inspire the design of smart healthcare infrastructures to combat future virus pandemics.
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Affiliation(s)
- Chin-Feng Lin
- Department of Electrical Engineering, National Taiwan Ocean University, Keelung 20224, Taiwan
| | - Shun-Hsyung Chang
- Department of Microelectronics Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 81157, Taiwan
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Denecke K, Romero OR, Merolli M, Miron-Shatz T, Gabarron E, Petersen C. How Participatory Health Informatics Catalyzes One Digital Health. Yearb Med Inform 2023; 32:48-54. [PMID: 38147849 PMCID: PMC10751117 DOI: 10.1055/s-0043-1768727] [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] [Indexed: 12/28/2023] Open
Abstract
OBJECTIVE To identify links between Participatory Health Informatics (PHI) and the One Digital Health framework (ODH) and to show how PHI could be used as a catalyst or contributor to ODH. METHODS We have analyzed the addressed topics within the ODH framework in previous IMIA Yearbook contributions from our working group during the last 10 years. We have matched main themes with the ODH's framework three perspectives (individual health and wellbeing, population and society, and ecosystem). RESULTS PHI catalysts ODH individual health and wellbeing perspective by providing a more comprehensive view on human health, attitudes, and relations between human health and animal health. Integration of specific behavior change techniques or gamification strategies in digital solutions are effective to change behaviors which address the P5 paradigm. PHI supports the population and society perspective through the engagement of the various stakeholders in healthcare. At the same time, PHI might increase a risk for health inequities due to technologies inaccessible to all equally and challenges associated with this. PHI is a catalyst for the ecosystem perspective by contributing data into the digital health data ecosystem allowing for analysis of interrelations between the various data which in turn might provide links among all components of the healthcare ecosystem. CONCLUSION Our results suggest that PHI can and will involve topics relating to ODH. As the ODH concept crystalizes and becomes increasingly influential, its themes will permeate and become embedded in PHI even more. We look forward to these developments and co-evolution of the two frameworks.
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Affiliation(s)
| | - Octavio Rivera Romero
- Instituto de Ingeniería Informática (I3US), Universidad de Sevilla, Sevilla, Spain
- Electronic Technology Department, Universidad de Sevilla, Sevilla, Spain
| | - Mark Merolli
- Department of Physiotherapy, School of Health Sciences, the University of Melbourne, Australia
- Centre for Digital Transformation of Health, The University of Melbourne, Australia
| | - Talya Miron-Shatz
- Faculty of Business Administration, Ono Academic College, Israel
- Winton Centre for Risk and Evidence Communication, Cambridge University, England
| | - Elia Gabarron
- Norwegian Centre for E-health Research, University Hospital of North Norway, Tromsø, Norway
- Department of Education, ICT and Learning, Østfold University College, Halden, Norway
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Kobayashi T, Tomoi H, Nishina Y, Harada K, Tanaka K, Sasaki S, Inaba K, Mitaka H, Takahashi H, Passanante A, Lau EHY, Naito T, Larson H, Wu J, Lin L, Yamada Y. Effect of a mobile app chatbot and an interactive small-group webinar on COVID-19 vaccine intention and confidence in Japan: a randomised controlled trial. BMJ Glob Health 2023; 8:bmjgh-2022-010370. [PMID: 37247873 DOI: 10.1136/bmjgh-2022-010370] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 05/09/2023] [Indexed: 05/31/2023] Open
Abstract
INTRODUCTION We investigated the effect of social media-based interventions on COVID-19 vaccine intention (VI) and confidence in Japan. METHODS We conducted a three-arm randomised controlled trial between 5 November 2021 and 9 January 2022 during a low incidence (<1000/day) of COVID-19 in Japan in the midst of the second and the third waves. Japanese citizens aged ≥20 who had not received any COVID-19 vaccine and did not intend to be vaccinated were randomly assigned to one of the following three groups: (1) a control group, (2) a group using a mobile app chatbot providing information on COVID-19 vaccines and (3) a group using interactive webinars with health professionals. VI and predefined Vaccine Confidence Index (VCI) measuring confidence in the importance, safety and effectiveness were compared before and after the interventions under intention-to-treat principle. Logistic regression models were used to investigate the effect of each intervention on postintervention VI and changes of VCI compared with control. RESULTS Among 386 participants in each group, 359 (93.0%), 231 (59.8%) and 207 (53.6%) completed the postsurvey for the control, chatbot and webinar groups, respectively. The average duration between the intervention and the postsurvey was 32 days in chatbot group and 27 days in webinar group. VI increased from 0% to 18.5% (95% CI 14.5%, 22.5%) in control group, 15.4% (95% CI 10.8%, 20.1%) in chatbot group and 19.7% (95% CI 14.5%, 24.9%) in webinar group without significant difference (OR for improvement=0.8 (95% CI 0.5, 1.3), p=0.33 between chatbot and control, OR=1.1 (95% CI 0.7, 1.6), p=0.73 between webinar and control). VCI change tended to be larger in chatbot group compared with control group without significant difference (3.3% vs -2.5% in importance, OR for improvement=1.3 (95% CI 0.9, 2.0), p=0.18; 2.5% vs 1.9% in safety, OR=1.1 (95% CI 0.7, 1.9), p=0.62; -2.4% vs -7.6% in effectiveness, OR=1.4 (95% CI 0.9, 2.1), p=0.09). Improvement in VCI was larger in webinar group compared with control group for importance (7.8% vs -2.5%, OR=1.8 (95% CI 1.2, 2.8), p<0.01), effectiveness (6.4% vs -7.6%, OR=2.2 (95% CI 1.4, 3.4), p<0.01) and safety (6.0% vs 1.9%, OR=1.6 (95% CI 1.0, 2.6), p=0.08). CONCLUSION This study demonstrated that neither the chatbot nor the webinar changed VI importantly compared with control. Interactive webinars could be an effective tool to change vaccine confidence. Further study is needed to identify risk factors associated with decreased vaccine confidence and investigate what intervention can increase VI and vaccine confidence for COVID-19 vaccines. TRIAL REGISTRATION NUMBER UMIN000045747.
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Affiliation(s)
- Takaaki Kobayashi
- Division of Infectious Diseases, Department of Internal Medicine, University of Iowa Hospitals & Clinics, Iowa City, Iowa, USA
- Department of General Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Hana Tomoi
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health, London, UK
- School of Tropical Medicine and Global Health, Nagasaki University, Nagasaki, Japan
| | - Yuka Nishina
- Department of General Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Ko Harada
- Department of Medicine, Mount Sinai Beth Israel Hospital, New York, New York, USA
| | - Kyuto Tanaka
- Division of Pulmonary Medicine, Department of Internal Medicine, Nippon Kokan Hospital, Kawasaki, Kanagawa, Japan
| | - Shugo Sasaki
- Department of General Internal Medicine, Saitama Medical University Hospital, Iruma-gun, Saitama, Japan
| | - Kanako Inaba
- Department of Obstetrics and Gynecology, Kanto Central Hospital of the Mutual Aid Association of Public School Teachers, Setagaya-ku, Tokyo, Japan
| | - Hayato Mitaka
- Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Hiromizu Takahashi
- Department of General Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Aly Passanante
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health, London, UK
| | - Eric H Y Lau
- Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Toshio Naito
- Department of General Medicine, Juntendo University Graduate School of Medicine, Bunkyo-ku, Tokyo, Japan
| | - Heidi Larson
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health, London, UK
- Institute for Health Metrics & Evaluation, University of Washington, Seattle, Washington, USA
| | - Joseph Wu
- Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- The University of Hong Kong - Shenzhen Hospital, Shenzhen, China
| | - Leesa Lin
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine Faculty of Epidemiology and Public Health, London, UK
- Laboratory of Data Discovery for Health (D24H), Hong Kong SAR, China
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Yuji Yamada
- Brookdale Department of Geriatrics and Palliative Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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Zhu P, Tatar O, Haward B, Steck V, Griffin-Mathieu G, Perez S, Dubé È, Zimet G, Rosberger Z. Examining an Altruism-Eliciting Video Intervention to Increase COVID-19 Vaccine Intentions in Younger Adults: A Qualitative Assessment Using the Realistic Evaluation Framework. Vaccines (Basel) 2023; 11:vaccines11030628. [PMID: 36992212 DOI: 10.3390/vaccines11030628] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 03/03/2023] [Accepted: 03/06/2023] [Indexed: 03/18/2023] Open
Abstract
COVID-19 vaccine-induced immunity wanes over time, and with the emergence of new variants, additional “booster” doses have been recommended in Canada. However, booster vaccination uptake has remained low, particularly amongst younger adults aged 18–39. A previous study by our research team found that an altruism-eliciting video increased COVID-19 vaccination intentions. Using qualitative methods, the present study aims to: (1) identify the factors that influence vaccine decision-making in Canadian younger adults; (2) understand younger adults’ perceptions of an altruism-eliciting video designed to increase COVID-19 vaccine intentions; and (3) explore how the video can be improved and adapted to the current pandemic context. We conducted three focus groups online with participants who: (1) received at least one booster vaccine, (2) received the primary series without any boosters, or (3) were unvaccinated. We used deductive and inductive approaches to analyze data. Deductively, informed by the realist evaluation framework, we synthesized data around three main themes: context, mechanism, and intervention-specific suggestions. Within each main theme, we deductively created subthemes based on the health belief model (HBM). For quotes that could not be captured by these subthemes, additional themes were created inductively. We found multiple factors that could be important considerations in future messaging to increase vaccine acceptance, such as feeling empowered, fostering confidence in government and institutions, providing diverse (such as both altruism and individualism) messaging, and including concrete data (such as the prevalence of vulnerable individuals). These findings suggest targeted messaging tailored to these themes would be helpful to increase COVID-19 booster vaccination amongst younger adults.
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Affiliation(s)
- Patricia Zhu
- Lady Davis Institute for Medical Research (LDI), Jewish General Hospital, Montreal, QC H3T 1E2, Canada
| | - Ovidiu Tatar
- Lady Davis Institute for Medical Research (LDI), Jewish General Hospital, Montreal, QC H3T 1E2, Canada
- Research Center, Centre Hospitalier de l'Université de Montréal (CRCHUM), Montreal, QC H2X 0A9, Canada
| | - Ben Haward
- Lady Davis Institute for Medical Research (LDI), Jewish General Hospital, Montreal, QC H3T 1E2, Canada
| | - Veronica Steck
- Department of Psychology, McGill University, Montreal, QC H3A 1G1, Canada
| | - Gabrielle Griffin-Mathieu
- Lady Davis Institute for Medical Research (LDI), Jewish General Hospital, Montreal, QC H3T 1E2, Canada
| | - Samara Perez
- Department of Oncology, McGill University, Montreal, QC H4A 3T2, Canada
- Psychosocial Oncology Program, Cedars Cancer Center, McGill University Health Center, Montreal, QC H3A 3J1, Canada
| | - Ève Dubé
- Department of Anthropology, Laval University, Quebec, QC G1V 0A6, Canada
| | - Gregory Zimet
- Department of Pediatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Zeev Rosberger
- Lady Davis Institute for Medical Research (LDI), Jewish General Hospital, Montreal, QC H3T 1E2, Canada
- Department of Psychology, McGill University, Montreal, QC H3A 1G1, Canada
- Department of Oncology, McGill University, Montreal, QC H4A 3T2, Canada
- Department of Psychiatry, McGill University, Montreal, QC H3A 1A1, Canada
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