| Background and Significance: Health communication researchers have given considerable attention to explaining why people seek and avoid health information. Perceptions of risk and efficacy have been given central roles in information-seeking studies. Especially noteworthy is Rimal and Real's Risk Perception Attitude (RPA) framework, which classifies people into four discrete groups with different proclivities to seek information based on their efficacy and risk perceptions on a health topic. People who are Responsive see themselves as efficacious, and at high risk, and are thus predicted to seek health information. People who are Avoidant consider themselves to be at high risk, but have low efficacy, which leads them to be information nonseekers. Individuals low in both perceived risk and efficacy are classified as Indifferent because they are not expected to be motivated to seek information. Proactive people consider themselves to be at low risk, but efficacious. Given their low risk, they are also expected to be nonseekers of information. Each of these studies tested the main RPA framework postulates. Further, rather than ignoring the cases that did not conform to framework predictions, the following studies identified the individuals that behaved counter to expectations and assessed alternate reasons for their behavior. This approach was employed to inform future revisions of health information models that move beyond risk and efficacy as the primary determinants of health information seeking.;Specific Aims: Study 1. To test the RPA framework predictions about information seeking intentions within the context of four health topics. Additionally, to examine cases that did not conform to the RPA framework predictions. Study 2. To provide an additional test of the RPA framework and to examine potential factors that could account for unexpected behavior in regards to cancer-related information. Study 3. To further test the RPA framework predictions and assess factors associated with behavior inconsistent with model expectations. Additionally, to broaden the measurement of health information responses to address seeking, avoidance, and disinterest.;Methods: Specific aim 1 was accomplished by recruiting participants to complete an online survey about their intended information seeking in regards to hypertension, hypercholesterolemia, alcohol dependence, and diabetes. Then risk, efficacy and additional variables were used to explain intended behaviors and nonconforming cases. Specific aim 2 involved a secondary data analysis that tested the main postulates of the RPA framework and examined the role of additional variables in explaining individuals' unexpected health information seeking. Specific aim 3 was accomplished by recruiting individuals to complete an online survey. They were presented with a list of medical conditions and were asked to identify a condition about which they would seek information, a condition about which they would be disinterested in information, and a condition about which they would avoid information. For each medical condition, follow up questions measured their perceived risk, efficacy, and additional explanatory variables.;Results: Study 1. Support was found for the RPA framework. However, among those whose behavior was not explained by risk and efficacy, the additional variables assessed (i.e., low topic relevance, prior knowledge, curiosity, and concern for others) provided explanatory power. Study 2. The RPA framework received partial support. However, nearly half of the respondents behaved counter to predictions. Many of these cases could be explained by individuals' trust in health information sources, confidence in their information-seeking abilities, challenges finding information, and diagnoses of cancer for self or a family member. Study 3. The RPA framework was largely unsupported, but the goal of distinguishing between avoidance and disinterest was successful. Individuals' three responses to health information were explained partially by risk and efficacy, but curiosity, prior knowledge, and personal and family diagnoses also played important roles in differentiating between seeking, disinterest, and avoidance.;Discussion: Risk and efficacy, while predictors of health information seeking, do not tell the whole story. Systematically identifying the nonconforming cases, rather than dismissing them as errors of prediction, provided insight about additional predictors of health information seeking. Additionally, a more comprehensive understanding of health information seeking intentions was gained by differentiating between nonseeking that is motivated by disinterest versus avoidance. Collectively, these studies suggest that we must look beyond risk and efficacy when building a more comprehensive model of health information seeking. Future theoretical models would benefit from the inclusion of orientations toward health (e.g., health consciousness), situational factors (e.g., personal and family diagnoses), and topic-specific knowledge and curiosities. |
