How could strategies which aim to improve dissemination of and exposure to Internet-delivered interventions be tested on effectiveness?
It is recommended (Crutzen, De Nooijer, Brouwer, Oenema, Brug, & De Vries, submitted) to conduct experimental research in more controlled settings to increase evidence-based insight into effectiveness of strategies regarding dissemination of and exposure to Internet-delivered interventions, before applying these strategies in practice. Advantage of such a controlled setting is the minimisation of possible confounding effects. Disadvantage of these experimental settings, however, is the isolated way in which strategies are tested on effectiveness, which is less comparable with real-life implementation.
Even if strategies are immediately applied in practice, there are appropriate designs, such as a time series design (Chen et al., 2005; Murry, Stam, & Lastovicka, 1993), to test effectiveness of these strategies. In such a design, strategies are first applied separately. Subsequently, combinations of several strategies are applied. Intervention use is monitored during the whole period to determine which strategy or combination between them is most effective. Although this design is more sensitive to confounding effects (e.g. changing environment), strategies are tested in a less isolated way and this could give more insight into effectiveness regarding dissemination and exposure in real life.
If all methods described above are inapplicable due to limited resources, one could test the effectiveness of dissemination strategies by simply asking visitors where they came from and how they heard about the intervention (Gordon, Akers, Severson, Danaher, & Boles, 2006). Although this method is based on self-report and therefore less objective, it is easily applicable and less time consuming. Yet, this method remains a last resort (when all else fails).
Dissemination and exposure do not only depend on the intervention itself, however, but also on its users. There is evidence that the acquisition of skills to use a website may influence its adoption (Paswan & Ganesh, 2003). It has also been shown, however, that Internet self-efficacy is not a significant predictor of exposure (Steele, Mummery, & Dwyer, 2007). If familiarity with a website increases, then perceived usability influences loyalty to the website (Casal