Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Public Health
Published in: BMC Public Health 1/2011

Open Access 01-12-2011 | Research article

Public Claims about Automatic External Defibrillators: An Online Consumer Opinions Study

Authors: Arthur G Money, Julie Barnett, Jasna Kuljis

Published in: BMC Public Health | Issue 1/2011

Login to get access

Abstract

Background

Patients are no longer passive recipients of health care, and increasingly engage in health communications outside of the traditional patient and health care professional relationship. As a result, patient opinions and health related judgements are now being informed by a wide range of social, media, and online information sources. Government initiatives recognise self-delivery of health care as a valuable means of responding to the anticipated increased global demand for health resources. Automated External Defibrillators (AEDs), designed for the treatment of Sudden Cardiac Arrest (SCA), have recently become available for 'over the counter' purchase with no need for a prescription. This paper explores the claims and argumentation of lay persons and health care practitioners and professionals relating to these, and how these may impact on the acceptance, adoption and use of these devices within the home context.

Methods

We carry out a thematic content analysis of a novel form of Internet-based data: online consumer opinions of AED devices posted on Amazon.com, the world's largest online retailer. A total of #83 online consumer reviews of home AEDs are analysed. The analysis is both inductive, identifying themes that emerged from the data, exploring the parameters of public debate relating to these devices, and also driven by theory, centring around the parameters that may impact upon the acceptance, adoption and use of these devices within the home as indicated by the Technology Acceptance Model (TAM).

Results

Five high-level themes around which arguments for and against the adoption of home AEDs are identified and considered in the context of TAM. These include opinions relating to device usability, usefulness, cost, emotional implications of device ownership, and individual patient risk status. Emotional implications associated with AED acceptance, adoption and use emerged as a notable factor that is not currently reflected within the existing TAM.

Conclusions

The value, credibility and implications of the findings of this study are considered within the context of existing AED research, and related to technology acceptance theory. From a methodological perspective, this study demonstrates the potential value of online consumer reviews as a novel data source for exploring the parameters of public debate relating to emerging health care technologies.
Literature
1.
Tian Y: Organ donationon Web 2.0: Contentand audience analysis of organ donation videos on YouTube. Health Communication. 2010, 25: 238-246. 10.1080/10410231003698911.CrossRefPubMed
2.
Horton RC: Second opinion: Doctors, diseases and decisions in modern medicine. 2003, London, UK: Granta Books
3.
Chung DS, Kim S: Blogging activity among cancer patients and their companions. Journal of the American Society for Information Science and Technology. 2008, 59: 297-306. 10.1002/asi.20751.CrossRef
4.
Nettleton S, Hanlon G: 'Pathways to the doctor' in the information age. New Technologies in Health Care. Edited by: Webster A. 2006, Basingstoke, UK: Palgrave, 57-70.CrossRef
5.
Lorig KR, Ritter PL, Dost A, Plant K, Laurent DD, McNeil I: The expert patients programme online, a 1-year study of an Internet-based self-management programme for people with long-term conditions. Chronic Illness. 2008, 4: 247-256. 10.1177/1742395308098886.CrossRefPubMed
6.
Jiménez-Pernett J, de Labry-Lima AO, Bermúdez-Tamayo C, García-Gutiérrez JF, Salcedo-Sánchez M: Use of the internet as a source of health information by Spanish adolescents. British Medical Council Medical Informatics & Decision Making. 2010, 10: 1-6.CrossRef
7.
Fadden G, Shooter M, Holsgrove G: Involving carers and service users in the training of psychiatrists. Psychiatric Bulletin. 2005, 29: 270-274. 10.1192/pb.29.7.270.CrossRef
8.
Gutteridge R, Dobbins K: Service user and carer involvement in learning and teaching: A faculty of health staff perspective. Nurse Education Today. 2010, 30: 509-514. 10.1016/j.nedt.2009.10.019.CrossRefPubMed
9.
Shrestha LB: Population ageing in developing countries. Health Affairs. 2000, 19: 204-212. 10.1377/hlthaff.19.3.204.CrossRefPubMed
10.
Darzi A, (Ed.): High quality care for all: NHS next stage review final report. 2008, London: Department of Health
11.
Newman J, Kuhlmann E: Evidence-informed patient choice: Practical issues of involving patients in decisions about health care technologies. Journal of European Social Policy. 2007, 17: 99-111. 10.1177/0958928707075191.CrossRef
12.
Thompson AGH: The meaning of patient involvement and participation in health care consultations: A taxonomy. Social Science and Medicine. 2006, 67: 1297-1310.
13.
Taylor A, Wilson R, Agamanolis S: A Home Health Monitoring System Designed to Support Carers in Their Caring Role. International Conference on eHealth, Telemedicine, and Social Medicine. 2009, Cancun, Mexico. IEEE Press, 2009
14.
Deber RB, Kraetschmer N, Urowitz S, Sharpe N: Patient, consumer, client, or customer: what do people want to be called?. Health Expectations. 2005, 8: 345-351. 10.1111/j.1369-7625.2005.00352.x.CrossRefPubMed
15.
Matusitz J, Breen GM: Telemedicine: Its effects on health communication. Health Communication. 2007, 21: 73-83.CrossRefPubMed
16.
Macias W, McMillan S: The return of the house call: The role of Internet-based interactivity in bringing health information home to older adults. Health Communication. 2008, 23: 34-44. 10.1080/10410230701805174.CrossRefPubMed
17.
18.
Buis LR, Carpenter S: Health and medical content and its relationships with blogger credentials and blog host. Health Communication. 2009, 24: 703-710. 10.1080/10410230903264014.CrossRefPubMed
19.
Wang Z, Walther JB, Pingree S, Hawkins RP: Health information, credibility, homophily, and influence via the Internet: Web sites versus discussion groups. Health Communication. 2008, 23: 358-368. 10.1080/10410230802229738.CrossRefPubMed
20.
Scola-Streckenbach S: Experience-based information: The role of web-based patient networks in consumer health information services. Journal of Consumer Health on the Internet. 2008, 12: 216-236. 10.1080/15398280802143657.CrossRef
21.
Ziebland S: The importance of being expert: The quest for cancer information on the internet. Social Science & Medicine. 2004, 59: 1783-1793. 10.1016/j.socscimed.2004.02.019.CrossRef
22.
Morris J, Royle GT: Offering patients a choice of surgery for early breast cancer: A reduction in anxiety and depression in patients and their husbands. Social Science & Medicine. 1998, 26: 583-585.CrossRef
23.
24.
Hennig-Thurau T, Gwinner KP, Walsh G, Gremler DD: Electronic word-of-mouth via consumer-opinion platforms. Journal of Interactive Marketing. 2004, 18: 38-52. 10.1002/dir.10073.CrossRef
25.
Rier D: Internet social support groups as moral agents: The ethical dynamics of HIV+ status disclosure. Sociology of Health and Illness. 2007, 29: 1043-1058. 10.1111/j.1467-9566.2007.01023.x.CrossRefPubMed
26.
Adair CE, Marcoux G, Williams A, Reimer M: The Internet as a source of data to support the development of a quality-of-life measure for eating disorders. Qualitative Health Research. 2006, 16: 539-546.CrossRef
27.
Fleitas J: Spinning tales from the World Wide Web: Qualitative research in an electronic environment. Qulaitative Health Research. 1998, 8: 283-292. 10.1177/104973239800800211.CrossRef
28.
Chen Y, Fay S, Wang Q: Marketing implications of online consumer product reviews. 2003
29.
Piller C: Everyone Is A Critic in Cyberspace. Los Angeles Times, (Dec 3). 1999
30.
Seale C, Charteris-Black J, McFarlane A, McPherson A: Interviews and Internet forums: A comparison of two sources of qualitative data. Qulalitative Health Research. 2009, 20: 595-606.CrossRef
31.
Goldfarb A, Prince J: Internet adoption and usage patterns are different: Implications for the digital divide. Information Economics and Policy. 2008, 20: 2-15. 10.1016/j.infoecopol.2007.05.001.CrossRef
32.
Nelson MK: Watching children: Describing the use of baby monitors on Epinions.com. Journal of Family Issues. 2008, 29: 516-538. 10.1177/0192513X07310319.CrossRef
33.
Hutchinson MD, Callans DJ: Should doctors recommend defibrillators for use at home after myocardial infarction?. British Medical Journal. 2009, 339: 80-81.CrossRef
34.
Bardy GH, Lee KL, Mark DB, Poole JE, Toff WD, Tonkin AE, Smith W, Dorian P, Packer DL, White R, et al: Home use of automated external defibrillators for sudden cardiac arrest. The New England Journal of Medicine. 2008, 358: 1793-1804. 10.1056/NEJMoa0801651.CrossRefPubMed
35.
Papadakis M, Sharma S, Cox S, Sheppard MN, Panoulas VF, Behr ER: The magnitude of sudden cardiac death in the young: a death certificate-based review in England and Wales. Europace. 2009, 11: 1353-1358. 10.1093/europace/eup229.CrossRefPubMed
36.
Mosesso VN, Davis EA, Auble TE, Paris PM, Yealy DM: Use of automated external defibrillators by police officers for treatment of out-of-hospital cardiac arrest. Annals of Emergency Medicine. 1998, 32: 200-207. 10.1016/S0196-0644(98)70137-4.CrossRefPubMed
37.
Valenzuela TD, Roe DJ, Nichol PH, Clark LL, Spaite DW, Hardman BS: Outcomes of rapid defibrillation by security officers after cardiac arrest in casinos. The New England Journal of Medicine. 2000, 343: 1206-1209. 10.1056/NEJM200010263431701.CrossRefPubMed
38.
39.
40.
41.
Wik L, Dorph E, Auestad B, Steen PA: Evaluation of defibrillator-basic cardiopulmonary resuscitation programme for non medical personnel. Resuscitation. 2003, 56: 167-172. 10.1016/S0300-9572(02)00351-9.CrossRefPubMed
42.
Caffrey SL, Willoughby PJ, Pepe PE, Becker LB: Public use of automated external defibrillators. The New England Journal of Medicine. 2002, 347: 1242-1247. 10.1056/NEJMoa020932.CrossRefPubMed
43.
McDaniel CM, Berry VA, Haines DE, DiMarco JP: Automatic external defibrillation of patients after myocardial infarction by family members: practical aspects and psychological impact of training. Pacing and Clinical Electrophysiology. 1988, 11: 2029-2034. 10.1111/j.1540-8159.1988.tb06345.x.CrossRefPubMed
44.
Chen MA, Eisenberg MS, Meischke H: Impact of in-home defibrillators on postmyocardial infarction patients and their significant others: An interview study. Heart and Lung. 2002, 31: 173-185. 10.1067/mhl.2002.124344.CrossRefPubMed
45.
Lee Y, Kozar KA, Larsen KRT: The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems. 2003, 12: 752-780.
46.
47.
Bagozzi RP: The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association of Information Systems. 2007, 8: 244-254.
48.
Davis FD: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 1989, 13: 319-340. 10.2307/249008.CrossRef
49.
Yarborough AK, Smith TB: Technology acceptance amongst physicians. Medical Care Research and Review. 2007, 64: 650-672. 10.1177/1077558707305942.CrossRef
50.
Yi M, Jackson JD, Park JS, Probst JC: Understanding information technology acceptance by individual professionals: towards an integrative view. Information and Management. 2006, 43: 350-363. 10.1016/j.im.2005.08.006.CrossRef
51.
Lishana X, Chiuana YC, Choolanib M, Chuanc CH: The perception and intention to adopt female-focused healthcare applications (FHA): A comparison between healthcare workers and non-healthcare workers. International Journal of Medical Informatics. 2009, 78: 248-258. 10.1016/j.ijmedinf.2008.07.014.CrossRef
52.
Van Schaik P, Bettany-Saltikov JA, Warren JG: Clinical acceptance of a low-cost portable system for postural assessment. Behaviour and Information Technology. 2002, 21: 47-57. 10.1080/01449290110107236.CrossRef
53.
Chang H: Application of the extended technology acceptance model to picture archiving and communication systems in dental hospitals. Journal of the Korean Society of Medical Informatics. 2009, 15: 265-272. 10.4258/jksmi.2009.15.3.265.CrossRef
54.
Wu J, Wang S, Lin L: Mobile computing acceptance factors in the healthcare industry. International Journal of Medical Information. 2007, 76: 66-77. 10.1016/j.ijmedinf.2006.06.006.CrossRef
55.
Wu J, Shen W, Lin L, Greenes RA, Bates DW: Testing the technology acceptance model for evaluating healthcare professionals' intention to use an adverse event reporting system. International Journal for Quality in Health Care. 2008, 20: 123-129.CrossRefPubMed
56.
Hennington AH, Janz BD: Information Systems and healthcare XVI: physician adoption of electronic medical records: applying the UTAUT model in a healthcare context. Communications of the Association for Information Systems. 2007, 19: 60-80.
57.
Wu PF, Qu Y, Preece JJ: Why an emergency alert system isn't adopted: the impact of socio-technical context. 22nd BCS Human-Computer Interaction Conference (HCI 2008). 2008, Liverpool, UK, British Computer Society, 101-104.
58.
Boyatzis RE: Transforming qualitative information: Thematic analysis and code development. 1998, Thousand Oaks, CA, USA: Sage Publications
59.
Joffe H, Yardley L: Content and thematic analysis. Research Methods for Clinical and Health Psychology. Edited by: Marks DF, Yardley L. 2004, London, UK: Sage Publications, 56-66.
60.
Braun V, Clarke V: Using thematic analysis in psychology. Qualitative Research in Psychology. 2006, 3: 77-101.CrossRef
61.
Clark-Carter D: Doing Quantitative Psychological Research: From Design to Report. 1997, London: Psychology Press
62.
Ginossar T: Online participation: A content analysis of differences in utilization of two online cancer communities by men and women, patients and family members. Health Communication. 2008, 23: 1-12. 10.1080/10410230701697100.CrossRefPubMed
63.
Donnelle L, Hoffman-Goetz L: An exploratory study of Canadian Aboriginal online health care forums. Health Communication. 2008, 23: 270-281. 10.1080/10410230802056388.CrossRef
64.
Khalid HM, Helander MG: Customer emotional needs in product design. Concurrent Engineering. 2006, 14: 197-206. 10.1177/1063293X06068387.CrossRef
65.
Barnett J, Breakwell GM: The social amplification of risk and the hazard sequence: The October 1995 oral contraceptive pill scare. Health, Risk and Society. 2003, 5: 301-313. 10.1080/13698570310001606996.CrossRef
66.
Morgan MG, Fischhoff G, Bostrom A, Atman CJ: Risk communication: A mental models approach. 2002, Cambridge, UK: Cambridge University Press
Metadata
Title
Public Claims about Automatic External Defibrillators: An Online Consumer Opinions Study
Authors
Arthur G Money
Julie Barnett
Jasna Kuljis
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2011
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/1471-2458-11-332

Other articles of this Issue 1/2011

BMC Public Health 1/2011 Go to the issue

Research article

Hyperhomocysteinemia is independently associated with albuminuria in the population-based CoLaus study

Research article

Isolation of non-tuberculous mycobacteria from pastoral ecosystems of Uganda: Public Health significance

Correspondence

Variability in school closure decisions in response to 2009 H1N1: a qualitative systems improvement analysis

Research article

Prevalence and type distribution of human papillomavirus infection in women from North Sardinia, Italy

Research article

Completeness and timeliness of tuberculosis notification in Taiwan

Research article

Obesity, smoking, alcohol consumption and years lived with disability: a Sullivan life table approach