Nonoptimal exposure to Internet interventions has been pointed out as a major concern in the field of development, evaluation, and implementation of Internet interventions [19
]. According to the diffusion of innovations theory [25
], characteristics of (potential) users and characteristics of an intervention (ie, the innovation) are associated with adoption and implementation of interventions. The present review is one of the first to systematically investigate which specific characteristics of an Internet intervention can be associated with better exposure to the intervention and its contents. The study was qualitative in nature and allowed us to point out indications of possible patterns in associations between intervention characteristics and exposure. Of the categories of potential exposure-improving intervention elements that we distinguished in the review (the number of interactive behavior change strategies used, and whether the intervention included interactive elements, peer support, counselor support, email and/or phone contact, update of the intervention website, and intervention incentives), peer and counselor support were related to a longer visit duration, and email/phone contact and update of the intervention website were related to a higher frequency of website log-ins. There were a large variety of potentially exposure-increasing elements applied in the various interventions, and there was a large variety and little consistency in the exposure measures that were reported.
In previous studies, interactively delivered educational content, such as the provision of computer-tailored feedback and goal setting, has been indicated as a potentially exposure-improving element [26
]. The active involvement required for using interactive elements, the personal relevance of feedback, and goals generated may result in more involvement in and better exposure to an intervention program. In this study, however, we did not find an association between the number of interactive behavior change strategies and exposure. This may be due to the fact that there was little variability in the use of these elements. For example, in about three quarters of the interventions, some type of tailored feedback was provided. What this review showed is that there was a marked difference in the use of other interactive educational content between the interventions for the various target behaviors. This may reflect differences in the importance of the underlying determinants and change methods needed to facilitate effective and maintained change in the various behaviors. It may also reflect that Internet applications are more advanced for the promotion of some of the health related behaviors (eg, promotion of physical activity, weight management, and smoking cessation) than for others.
Peer support was offered more often in weight management, alcohol, and smoking cessation interventions as compared with the other behaviors. Based on our criteria, peer support was related to more time spent on the intervention website. This does not necessarily mean, however, that visitors are exposed to and actively engaged in the intervention content, but they may at least be chatting about their target behavior, for example, in a forum or a chat room. Furthermore, it should be noted that previous studies reported that peer support is used to a limited extent and that not all visitors may use peer support [26
]. Peer support was, for example, more often sought by smoking quitters than by visitors that continued smoking [70
], and women have been found to be more likely to post more messages than men on a message board about smoking cessation [71
Counselor support was more often a distinct part of the weight management and smoking cessation interventions. The results indicate that counselor support was related to a longer website visit. Although there were an insufficient number of interventions in our study to draw any conclusions about the potential relation between counselor support and revisiting intervention websites, there may be a positive relation. These findings may add positively to the results of previous single studies where inconsistent findings were reported for the relation of counselor support and submission of dietary reports. Tate et al [63
], for example, showed that additional human email counseling resulted in higher online diary submissions, whereas Webber et al [64
] found the opposite.
Nearly half of the interventions sent email/phone prompts to encourage revisits. Next to that, weight management interventions made more use of emails sent by counselors, whereas physical activity and smoking cessation interventions used automatically generated emails to send intervention content. This review shows that email/phone contact might indeed be useful in promoting repeated visits as has already been indicated in single studies addressing this topic. Furthermore, the postulation that regular updates of the intervention website would be related to repeated visits seems to be supported by the findings of this review. There is growing evidence that repeated website visits are necessary to achieve sustainable changes [22
]. However, disappointing results regarding revisiting have been published, as website visits tend to decrease sharply after the initial weeks of participation [4
]. It is, therefore, promising that email prompts and regular updates of intervention content may contribute to more visits, since these are relatively easy to implement exposure-promoting strategies.
Another important finding in this review is that there was a large variety in the report of objective exposure measures but also that many studies that did not report exposure data at all. We had to exclude 29 publications solely because they did not present any objective exposure measures. The number of log-ins on the intervention website was the most frequently reported exposure measure, but this measure was presented in different ways, which limited the options of pooling the data. Other often-presented exposure measures were completion of the initial visit, visit duration, and completion of the intervention program in case revisits were required. It is not only important that objective exposure measures (eg, starting intervention, completing modules/intervention, frequency of visiting, and duration of visit) are presented in studies evaluating Internet interventions [32
], but it is also important that these measures are presented in a standardized way. Furthermore, for the purpose of systematic reviews, it is very important that accurate and complete descriptions of intervention content and interactive applications are provided in the future. This would make it possible to compare and pool different studies and enlarge the strength of the conclusions that can be drawn. In addition, objective exposure measures should be linked to visitor characteristics to get a more thorough impression about who is reached with what kind of intervention and to what extent. Furthermore, this registration on the individual level would also make it possible to study possible mediating effects of exposure to these objective exposure outcome measures.
To be able to relate the potentially exposure-improving intervention characteristics with exposure measures, we developed a matrix containing both elements. We listed all studies in this matrix by categorizing them according to, for example, the number of interactive behavior change strategies used and the presence of peer or counselor support and the result of the exposure outcome. From this qualitative integrative approach, we derived that peer support was associated with a longer stay on the website, whereas email/phone contact and update of the intervention website were related to more log-ins on the intervention website. We did not find an indication of better exposure to the intervention for the other categories of potential exposure-enhancing intervention characteristics, even if these have been indicated as such in previous studies [26
]. This is also in contrast with the findings of individual studies in which a more extensive version of an intervention with more interactive characteristics was compared with a more basic version. A more interactive intervention resulted, for example, in a longer visit to the intervention [31
] and in more log-ins on the intervention website [28
]. One possible reason for not finding differences in exposure according to the use of more as compared with fewer interactive behavior change strategies is the way in which we divided the interventions (< 3 or ≥ 3 interactive behavior change strategies) and that we pooled all the interventions targeting different health-related behaviors together.
The findings of our study are partly in line with the only other study that investigated the same topic among adolescents and young adults [102
]. Similar to our study, they also found a heterogeneity of exposure measures and identified different exposure-increasing methods and strategies, such as tailored feedback, use of interactive elements, email support, and reminders. Furthermore, single studies showed that more interactive interventions resulted in a higher exposure to the intervention content than a basic version. Nevertheless, we have to keep in mind that younger people use the Internet differently than adults [3
There are some limitations to this review study that need to be mentioned. The search strategies were limited to include only peer-reviewed English language publications. Therefore, we could have missed important “gray literature” and publication in languages other than English. Next, for this review we relied on the information that was provided in the published literature regarding the description of the intervention and identification of potentially exposure-promoting methods and strategies. Some of the intervention descriptions were very brief, and even the more extensive descriptions available in the literature may not always have been complete. Therefore, we may have missed some of the potential exposure-promoting elements that an intervention contained. In addition, this review can be qualified as a qualitative review as the extracted data from the included studies were summarized and not statistically pooled, which limits the strength of the conclusions that can be drawn. Finally, the used cutoff points for making a ranking within the categories of potential exposure-promoting interventions elements (ie, < 3 or ≥ 3 interactive behavior change strategies, and yes vs no interactive elements) may not have been sensitive enough to detect differences in exposure.
The studies included in this review showed that in the Internet interventions currently available, a wide variety of potentially exposure-improving methods and strategies were used. These methods and strategies were markedly different for the healthy lifestyle behaviors that were studied. Also, a large variety of objective exposure outcome measures were used and there was a lack of consistency in exposure measures reported. Peer support, counselor support, email/phone contact with visitors through sending intervention content and prompts and updates of the intervention website were indicated to result in a longer visit and more log-ins on the website, respectively. More research is needed to gain insight into how intervention characteristics can be used to improve exposure to Internet interventions. More accurate and consistent description of intervention content and more consistency in the report of objective exposure outcomes are recommended. This will enable researchers to better assess associations between intervention characteristics and exposure to health behavior change Internet interventions in the future.