Creating a database of internet-based clinical trials to support a public-led research programme: A descriptive analysis

Anne Brice, Amy Price, Amanda Burls, Anne Brice, Amy Price, Amanda Burls

Abstract

Background: Online trials are rapidly growing in number, offering potential benefits but also methodological, ethical and social challenges. The International Network for Knowledge on Well-being (ThinkWell™) aims to increase public and patient participation in the prioritisation, design and conduct of research through the use of technologies.

Objective: We aim to provide a baseline understanding of the online trial environment, determining how many trials have used internet-based technologies; how they have been used; and how use has developed over time.

Methods: We searched a range of bibliographic databases to March 2015, with no date limits, supplemented by citation searching and references provided by experts in the field. Results were screened against inclusion and exclusion criteria, and included studies mapped against a number of key dimensions, with key themes developed iteratively throughout the process.

Results: We identified 1992 internet-based trials to March 2015. The number of reported studies increased substantially over the study timeframe. The largest number of trials were conducted in the USA (49.7%), followed by The Netherlands (10.2%); Australia (8.5%); the United Kingdom (5.8%); Sweden (4.6%); Canada (4%); and Germany (2.6%). South Korea (1.5%) has the highest number of reported trials for other continents. There is a predominance of interventions addressing core public health challenges including obesity (8.6%), smoking cessation (5.9%), alcohol abuse (7.7%) and physical activity (10.2%); in mental health issues such as depression (10.9%) and anxiety (5.6%); and conditions where self-management (16.6%) or monitoring (8.1%) is a major feature of care.

Conclusions: The results confirm an increase in the use of the internet in trials. Key themes have emerged from the analysis and further research will be undertaken in order to investigate how the data can be used to improve trial design and recruitment, and to build an open access resource to support the public-led research agenda.

Keywords: Internet-based clinical trials; information retrieval; information science; patient and public involvement; randomised controlled trial as topic.

Conflict of interest statement

None declared.

Figures

Figure 1.
Figure 1.
Cumulative growth in internet-based RCTs.

References

    1. ThinkWell: The international network for knowledge about wellbeing, (2015, accessed 17 April 2015).
    1. Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical practice. J Gen Intern Med 2012; 27: 1361–1367.
    1. Edwards AGK, Naik G, Ahmed H, et al. Personalised risk communication for informed decision making about taking screening tests. Cochrane Database Syst Rev 2013; 2: CD001865.
    1. Stacey D, Légaré F, Col NF, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2014; 1: CD001431.
    1. Coulter A. Making shared decision-making a reality: No decision about me, without me, (2011, accessed 17 April 2015).
    1. Corrigan K. Number of consumer health apps to reach 13,000 by next summer, (2011, accessed 5 April 2015).
    1. Eysenbach G, Powell J, Englesakis M, et al. Health related virtual communities and electronic support groups: Systematic review of the effects of online peer to peer interactions. BMJ 2004; 328: 1166.
    1. Webb T, Joseph J, Yardley L, et al. Using the internet to promote health behavior change: A systematic review and meta-analysis of the impact of theoretical basis, use of behavior change techniques, and mode of delivery on efficacy. J Med Internet Res 2010; 12: e4.
    1. Fox S and Duggan M. Health Online 2013: One in three American adults have gone online to figure out a medical condition, (2013, accessed 19 April 2015).
    1. Department of Health. Change for Life, (2015, accessed 4 June 2015).
    1. Department of Health. NHS Choices, (2015 accessed 4 June 2015).
    1. Department of Health. (2015, accessed 17 April 2015).
    1. Wyatt JC. Digital healthcare: When, for whom, and at what cost? (2013, accessed 5 June 2015).
    1. Eysenbach G, Kohler C. Does the internet harm health? Database of adverse events related to the internet has been set up. BMJ 2002; 324: 239.
    1. Kiley R. Does the internet harm health? Some evidence exists that the internet does harm health. BMJ 2002; 324: 238–239.
    1. Van Deursen AJ. Internet skill-related problems in accessing online health information. Int J Med Inform 2012; 81: 61–72.
    1. Farmer SEJ, Bernardotto M, Singh V. How good is Internet self-diagnosis of ENT symptoms using Boots WebMD symptom checker? Clin Otolaryngol 2011; 36: 517–518.
    1. Neter E, Brainin E. eHealth Literacy: Extending the digital divide to the realm of health information. J Med Internet Res 2012; 14: e19.
    1. Viswanath K, Ackerson LK. Race, Ethnicity, language, social class, and health communication inequalities: A nationally-representative cross-sectional study. PLoS One 2011; 6: e14550.
    1. Pak R, Price M, Thatcher J. Age-sensitive design of online health information: Comparative usability study. J Med Internet Res 2009; 11: e45.
    1. Han K, Shih PC, Rosson MB, et al. Understanding local community attachment, engagement and social support networks mediated by mobile technology. Interact Comput 2014; Nov 17, DOI:10.1093/iwc/iwu040 (online).
    1. O'Mara-Eves A, Brunton G, McDaid D, et al. Community engagement to reduce inequalities in health: A systematic review, meta-analysis and economic analysis. Public Health Res 2013; 1: i–525.
    1. Ziebland S. Why listening to health care users really matters. J Health Serv Res Policy 2012; 17: 68–69.
    1. Coleman A, Checkland K, Mcdermott I, et al. Patient and public involvement in the restructured NHS. J Integr Care 2011; 19: 30–36.
    1. Mockford C, Staniszewski S, Griffiths F, et al. The impact of patient and public involvement on UK NHS health care: A systematic review. Int J Qual Health 2012; 24: 28–38.
    1. Department of Health. Patient and public involvement in health: The evidence for policy implementation, (2004, accessed 17 April 2015).
    1. Barham L. Public and patient involvement at the UK National Institute for Health and Clinical Excellence. Patient 2011; 4: 1–10.
    1. Ocloo JE, Fulop NJ. Developing a ‘critical’ approach to patient and public involvement in patient safety in the NHS: Learning lessons from other parts of the public sector? Health Expect 2012; 15: 424–432.
    1. Oliver S. Public involvement in research: Making sense of the diversity. J Health Serv Res Policy 2015; 20: 45.
    1. Chalmers I, Glasziou P. Avoidable waste in the production and reporting of research evidence. Lancet 2009; 374: 86–89.
    1. Hibbard JH, Greene J. What the evidence shows about patient activation: Better health outcomes and care experiences; fewer data on costs. Health Aff 2013; 32: 207–214.
    1. Stewart R and Oliver S. A systematic map of studies of patients' and clinicians' research priorities, (2008, accessed 6 June 2015).
    1. Moran R, Davidson P. An uneven spread: A review of public involvement in the National Institute of Health research's health technology assessment program. Int J Technol Assess Health Care 2011; 27: 343–347.
    1. Partridge N, Scadding J. The James Lind Alliance: Patients and clinicians should jointly identify their priorities for clinical trials. Lancet 2004; 364: 1923–1924.
    1. Testing Treatments Interactive, (2013, accessed 17 April 2015).
    1. Tallon D, Chard J, Dieppe P. Relation between agendas of the research community and the research consumer. Lancet 2000; 355: 2037–2040.
    1. Chalmers I. What do I want from health research and researchers when I am a patient? BMJ 1995; 310: 1315–1318.
    1. INVOLVE. Guidance on the use of social media to actively involve people in research, (2014, accessed 19 April 2015).
    1. Campbell MK, Snowdon C, Francis D, et al. Recruitment to randomised trials: Strategies for trial enrolment and participation study: The STEPS study. Health Technol Assess 2007; 11: 1–126.
    1. Freiman JA, Chalmers TC, Smith H, et al. The importance of beta, the type II error and sample size in the design and interpretation of the randomized control trial. Survey of 71 “negative” trials. N Engl J Med 1978; 299: 690–694.
    1. Rose D, Williamson T. Developing the evidence base of patient and public involvement in health and social care research: The case for measuring impact. Int J Consum Stud 2011; 35: 628–632.
    1. Hazell L, Shakir SA. Under-reporting of adverse drug reactions: A systematic review. Drug Saf 2006; 29: 385–396.
    1. Mello MM, Clarridge BR, Studdert DM. Academic medical centers' standards for clinical-trial agreements with industry. N Engl J Med 2005; 352: 2202–2210.
    1. Trouiller P, Torreele E, Olliaro P, et al. Drugs for neglected diseases: A failure of the market and a public health failure? Trop Med Int Health 2001; 6: 945–951.
    1. World Health Organization. Public-private partnerships for neglected diseases: Opportunities to address pharmaceutical gaps for neglected diseases. In: Priority medicines for Europe and the world project “a public health approach to innovation”. Chapter 8.1, (2005, accessed 18th December 2006).
    1. The EQUATOR network: enhancing the quality and transparency of health research, (2015, accessed 19 April 2015).
    1. Department of Health. The NHS Constitution, (2013, accessed 17 April 2015).
    1. Jones CW, Handler L, Crowell KE, et al. Non-publication of large randomized clinical trials: Cross sectional analysis. BMJ 2013; 347: f6104.
    1. Kelly MA, Oldham J. The Internet and randomised controlled trials. Int J Med Inform 1997; 47: 91–99.
    1. Paul J, Seib R, Prescott T. The internet and clinical trials: Background, online resources, examples and issues. J Med Internet Res 2005; 7: e5.
    1. Murray E. Methodological challenges in online trials. J Med Internet Res 2009; 1192: e9.
    1. Hoffmann T, English T, Glasziou P. Reporting of interventions in randomised trials: An audit of journal Instructions to Authors. Trials 2014; 15: 20.
    1. Lorencatto F, West R, Stavri Z, et al. How well is the intervention content described in published reports of smoking cessation interventions? Nicotine Tob Res 2013; 15: 1274–1282.
    1. Newton NC, Andrews G, Teesson M, et al. Delivering prevention for alcohol and cannabis using the internet: A cluster randomised controlled trial. Prev Med 2009; 48: 579–584.
    1. Kypri K, Hallett J, Howat P, et al. Randomized controlled trial of proactive web-based alcohol screening and brief intervention for university students. Arch Intern Med 2009; 169: 1508–1511.
    1. Graham AL, Cobb NK, Papandonatos GD, et al. A randomized trial of internet and telephone treatment for smoking cessation. Arch Int Med 2011; 171: 46–53.
    1. Almeida FA, You W, Harden SM, et al. Effectiveness of a worksite-based weight loss randomized controlled trial: The worksite study. Obesity 2015; 23: 737–745.
    1. Powell J, Hamborg T, Stallard N, et al. Effectiveness of a web-based cognitive-behavioral tool to improve mental well-being in the general population: Randomized controlled trial. J Med Internet Res 2013; 15: e2.
    1. Broekhuizen K, Kroeze W, van Poppel MN, et al. A systematic review of randomized controlled trials on the effectiveness of computer-tailored physical activity and dietary behavior promotion programs: An update. Ann Behav Med 2012; 44: 259–286.
    1. Civljak M, Stead LF, Hartmann-Boyce J, et al. Internet-based interventions for smoking cessation. Cochrane Database Syst Rev 2013; 7: CD007078.
    1. Murray E, Burns J, See Tai S, et al. Interactive health communication applications for people with chronic disease. Cochrane Database Syst Rev 2005; 4: CD004274.
    1. Shahab L, McEwen A. Online support for smoking cessation: A systematic review of the literature. Addiction 2009; 104: 1792–1804.
    1. NICE. Computerized cognitive behaviour therapy for depression and anxiety. Technology Appraisal 97, (2006, accessed 20 April 2015).
    1. UK DUETS, (2015, accessed 6 June 2015).
    1. Fenton M, Brice A and Chalmers I. Harvesting and publishing patients’ unanswered questions about the effects of treatments, ,Brice,Chalmers%20UK%20DUETs%20Harvesting%20uncertainties.pdf (2009, accessed 6 June 2015).
    1. Brice A and Burls A. Working with uncertainty: The role of DUETs in harvesting what we don’t know, (2008, accessed 6 June 2015).
    1. Department of Health. No health without mental health: A cross-government mental health outcomes strategy for people of all ages, (2011, accessed 17 April 2015).
    1. The InterTASC Information Specialists' Sub-Group Search Filter Resource, (Accessed 17 April 2015; archived by WebCite® at ).
    1. Wong SS, Wilczynski NL, Haynes RB. Optimal CINAHL search strategies for identifying therapy studies and review articles. J Nurs Scholarsh 2006; 38: 194–199.
    1. Eady AM, Wilczynski NL, Haynes RB. PsycINFO search strategies identified methodologically sound therapy studies and review articles for use by clinicians and researchers. J Clin Epidemiol 2008; 61: 34–40.
    1. Sharon L, Wong SS, Wilczynski NL, et al. Developing optimal search strategies for detecting clinically sound treatment studies in EMBASE. J Med Libr Assoc 2006; 94: 41–47.
    1. Gluud C, Nikolova D. Likely country of origin in publications on randomised controlled trials and controlled clinical trials during the last 60 years. Trials 2007; 8: 7.
    1. Loria A, Arroyo P. Language and country preponderance trends in MEDLINE and its causes. J Med Libr Assoc 2005; 93: 381–385.
    1. Michie S, Ashford S, Falko F, et al. A refined taxonomy of behaviour change techniques to help people change their physical activity and healthy eating behaviours: The CALO-RE taxonomy. Psychol Health 2011; 26: 1479–1498.
    1. US National Library of Medicine. MeSH: Medical Subject Headings, (2015, accessed 20 April 2015).
    1. World Health Organisation. A Taxonomy for Patient Safety, (2015, accessed 20 April 2015).
    1. NICE taxonomy, (2011, accessed 2015).
    1. Hoffmann T, English T, Glasziou P. Reporting of interventions in randomised trials: An audit of journal Instructions to Authors. Trials 2014; 15: 20.
    1. Grimshaw JM, Eccles MP, Lavis JN, et al. Knowledge translation of research findings. Implement Sci 2012; 7: 50.
    1. Haynes RB, Ackloo E, Sahota N, et al. Interventions for enhancing medication adherence. Cochrane Database Syst Rev 2008; 16: CD000011.
    1. Brice A, Price A and Burls A. PLOT-IT: Public empowerment and engagement in clinical trials, (2014, Accessed 18 April 2015).
    1. Brice A, Price A, Burls A, et al. A protocol for a systematic review of methodological and qualitative factors that might influence the effectiveness of internet-based controlled clinical trials: Evidence mapping and syntheses, (2014, accessed: 26 June 2015).

Source: PubMed

3
Abonner