The Multiplex Genetic Testing Model proved useful in predicting test uptake among participants in a multiplex testing study. Having a positive attitude towards testing was the strongest predictor of test interest, which in turn predicted test uptake, as conceptualized in the model. Demographic characteristics predicted testing, with older participants being more interested in testing, suggesting that as participants approach middle age they may be increasingly motivated to learn about future health risks. There were trends toward white participants and college graduates having greater interest in testing. Our hypothesis that worry, perceived risk, and perceived severity would each be represented by a single domain that independently predicted attitudes was not confirmed.
Our findings suggest that study participants grouped their perceptions about the health threats generated from the eight conditions into two primary domains, cancers: lung, colorectal and skin, and metabolic conditions: type II diabetes, hypertension, coronary artery disease and high cholesterol. Perceived risk for the metabolic conditions was significantly correlated with worry in each of the domains, for metabolic conditions and for cancer. This suggests that while the domains were distinct, a higher perceived risk for the metabolic conditions was generalized to worry about cancer as well as worry about the metabolic conditions. Each of the two worry domains was separately correlated with perceived severity. So more worry about cancer predicted greater perceived severity of cancer and more worry about the metabolic conditions predicted greater perceived severity of the metabolic conditions.
Further, as was expected, perceived severity of one domain of conditions was significantly correlated with the other, and worry about one domain was also significantly correlated with worry about the other domain. The effect of illness representations and worry about one disease on another have been reported in other studies (DiLorenzo, et al, 2006
, Gerend, 2004
, Schnur, et. al., 2006
The remainder of our model constructs; response efficacy and attitudes all represented a single domain each suggesting measurement of an overarching psychological construct for all eight of the conditions combined. It is notable that initial perceptions are generated by two large categories of conditions (metabolic and cancer) but the variables that pertain more directly to multiplex testing measure a single construct domain. The findings may be explained by the context of multiplex testing. The closer one gets to the decision to undergo testing, all considerations about testing must be channeled into one choice as there was no option to be tested for only one of the categories of conditions.
Yet it was only perceived severity of the metabolic conditions that was correlated with general response efficacy and the remainder of the key variables in predicting uptake. Remarkably, perceived risk for cancer did not make a significant contribution and was dropped from the model. This supports recent evidence demonstrating that worry has an advantage over risk perception in predicting health behaviors (Cameron, et al, 2009
, Schmiege et al, 2009
). Our findings suggest that while perceived risk, perceived severity and worry are key to the initial processing of information about a health threat, they are less important in predicting response-efficacy and don’t predict attitudes toward testing as we had hypothesized.
Importantly, response efficacy was seen to directly influence attitudes towards testing, consistent with similar results found by van den Berg and colleagues who used PMT to frame decisions about prenatal screening (van den Berg et al., 2008
). Related beliefs about perceived control have been seen as motivators for undergoing a variety of health screening tests (Decruyenaere, Evers-Kiebooms, Welkenhuysen, Denayer, & Claes, 2000
; Gooding et al., 2006
; Lagerlund, Hedin, Sparen, Thurfjell, & Lambe, 2000; McClenahan, Shevlin, Adamson, Bennett, & O'Neill, 2007
; Newell, Modeste, Marshak, & Wilson, 2009
; Shiloh, Petel, Papa, & Goldman, 1998
; Wong, 2009
), suggesting a significant role for perceived confidence in one’s ability to control health outcomes.
Response efficacy was operationally defined as the belief that multiplex testing can help reduce the chances of getting each of the diseases included in the test. It is remarkable that it was found to predict attitudes towards testing since multiplex genetic testing per se cannot reduce risk for any of the conditions. The explanation for our finding assumes the existence of two further beliefs: that the diseases being tested can be prevented effectively by early detection and application of appropriate behavioral or medical interventions; and that one has the ability to perform behaviors related to decreasing the risk (self-efficacy beliefs). It is possible that the prominent role of response efficacy in predicting attitudes lies partly with the web-based Multiplex Initiative educational materials. They may have left participants feeling confident in their ability to use the test results to reduce their health risks. On the website it stated: “People who have risk versions of genes may be more harmed by their health habits than their genes; You cannot change your genes, but you can change your health habits; We do not know much about how having risk versions of genes affects how our body responds to health habits, such as our diet, exercise and cigarette smoking.”
From a practical perspective, it is important to understand the source of positive beliefs in the outcomes of testing. Do they originate from educational materials about testing? Or do they stem from belief in the power of medical information and the value of new medical technology and its promise for reducing disease? Some of these values and beliefs may be subject to persuasion or influence and others may be intrinsic to the individuals making decisions whether to undergo testing. This study was not designed to answer the question about the relationship between the information provided and response efficacy, but results from the larger Multiplex Initiative cohort revealed that a majority of participants had high levels of confidence that behavior change could reduce their disease risk (McBride et al., 2009
Overall, our results offer powerful evidence for associations among key constructs from prevalent theories of health behavior, with a significant role for constructs from the TPB: attitudes and intentions. These constructs were highly predictive of testing intent and ultimately test uptake and accounted for the majority of the variance in test choice offering evidence for the importance of an expanded conceptual model for multiplex genetic testing uptake. The decision to undergo testing for multiple common conditions was an intentional, planned behavior, with attitudes toward testing as a major predictor of intent and uptake.
Strengths and Limitations
SEM analysis offers an advantage over other methods by measuring unobserved constructs, simultaneously addressing multiple relationships between constructs, and accommodating relationships of dependence that integrate covariance (DiLalla, 2008
). Furthermore, this is the first report to model decisions about obtaining genetic testing for multiple common health conditions.
Our study is, however, limited in several respects. We examined a subset of the larger group of Multiplex Initiative participants. Although the sub-sample used in this study was not significantly different from participants accessing the website based on socio-demographic variables, they did have slightly higher intentions and test uptake. Thus, our subset may not be fully representative of the larger group. The fact that most of the variables in our model were measured using an additional survey on the Multiplex Initiative website suggests that the participants selected for inclusion may have been more highly motivated or otherwise distinct. Additionally, the measure of intentions was assessed just prior to response efficacy and attitudes, which may have introduced an order effect on how the latter variables were assessed.
Our study was correlational in nature. A recent review of the experimental literature (Webb & Sheeran, 2006
) suggested that intentional control of health behavior may be more limited than correlational studies suggest. Thus, future studies that manipulate attitudes and intentions in experimental groups (compared to a control group) should be designed to further validate our findings about the predictors of multiplex testing uptake.
Future studies should carefully examine underlying values and beliefs that may determine positive attitudes towards testing. These constructs, including response efficacy, may offer important understanding of the origins of positive attitudes towards multiplex testing. They also may represent relevant constructs to influence. For example, if in the future multiplex genetic testing were shown to provide health benefits, it would be useful to enhance positive beliefs in the ability of testing to reduce disease risk through providing information on risk-reducing activities and the ways that others have successfully adopted them.