With the increasingly widespread use of Internet and mobile phone technology, it is worth noting that emerging technologies can play a role not only in recruitment of study participants but also in many other areas of research (e.g., surveillance, interventions, clinical trials). Technologies such as text messaging, e-mailing, web-based interventions, and geographic information systems are currently being used to identify and reach at-risk populations and offer promising opportunities for future studies (for example, see Bowen et al., 2008; Carpenter et al., 2010; Geanuracos et al., 2007).
Randomized controlled trials. Since the work of Fisher (1925) was published, it has been recognized that randomization lends credibility to estimates of causal relationships that cannot be matched by other research designs. RCTs measure an intervention’s effect by randomly assigning individuals (or groups of individuals) to an intervention group or a control group. In health research, RCTs typically are used to assess the efficacy of a behavioral or clinical intervention, such as in a drug trial, or participation in a risk reduction program.
While RCTs, at their best, can have high internal validity, concerns invariably remain with regard to external validity. For example, a particular AIDS treatment that is found to be effective in an RCT conducted with middle-aged white men in the United States might be less effective for other subpopulations. An RCT of the efficacy of a behavioral intervention to prevent the acquisition of HIV among men who have sex with men in six U.S. cities over a period of 48 months, known colloquially as the EXPLORE study, used HIV infection as the primary efficacy outcome (HIV Prevention Trials Network, 2011). In a sample of 4,295 participants, 39.7 percent reported having a history of childhood sexual abuse (Mimiaga et al., 2009). In prior studies, rates of childhood sexual abuse reported by men who have sex with men ranged from 11 to 37 percent (Brennan et al., 2007), while the rate of such abuse among the general population of men had been estimated at 5 to 10 percent (Finkelhor, 1994). Analysis of data