ArticleeHealth Evaluation and Dissemination Research
Introduction
Although eHealth research is relatively recent,1, 2 it has produced several important efficacious interventions.3, 4, 5, 6 There have also been important lessons learned in eHealth assessment and research methodology.7, 8 As in most areas, however, there is a substantial gap between what is known and what is implemented in applied settings.9, 10
The purpose of this article is to identify information that, if provided, would greatly aid those making decisions about adoption of eHealth programs. Viewed from a developer/evaluator perspective, these same actions should substantially increase the probability of successful program dissemination.
Section snippets
Perspective
This section covers fundamental “context” type questions—information about the who, what, when, where, and how of eHealth programs. In terms of who participates in eHealth programs, one of the earliest concerns about eHealth has been the “digital divide.” When Internet applications first became available there was a pattern, frequently seen with other innovations11 in which earlier adoptees tended to be highly educated, young, white males.12, 13 This pattern has become more complex over the
Practical eHealth Studies
The majority of evidence-based healthcare procedures fail to translate into practice.22, 23 Part of the reason for this failure to translate is because of the research methods most often used to evaluate interventions. In particular, typical designs do not address external validity concerns or provide information relevant to policymakers or to those considering program adoption.24, 25, 26 To address this issue, Tunis et al.24 have proposed criteria for “practical clinical trials,” which can
Evaluation Frameworks
For eHealth developers who wish to have their program widely adopted, there is much to be said for following a translation framework throughout the planning, implementation, analysis, reporting, and refinement of their product. It is beyond the scope of this paper to discuss the relative advantages of the different frameworks,11, 44, 45, 46 but almost all are influenced by the pioneering work of Rogers’s diffusion of innovations model,11 and of Green and Kreuter’s PRECEDE-PROCEED model.44
This
Evaluation Challenges and Recommendations
The reader may be thinking, “well, these issues are worth considering, but is it really feasible to integrate all of them into a typical study, and without a huge budget?” The answer, fortunately, is yes: it is possible. Many of the evaluation recommendations, such as specifying denominators of settings and patients approached, tracking costs, collecting automated measures of user engagement, and analyzing representativeness and robustness require few financial resources and do not involve any
Conclusion
Great progress has been made in eHealth, and as evidenced by the papers in this issue, a lot has been learned in a relatively short period of time. However, to better understand the potential for and public health impact of eHealth programs, several changes are recommended in the development and evaluation of eHealth programs (Table 4).
A common theme throughout the NIH 2005 eHealth Research Meeting, on which this series of papers is based, was the importance of taking a user-centered approach
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