The growth of the Internet provides an unprecedented opportunity for the public to access a cornucopia of health-related information. The vast compendium of health-related information on the Web appeases the public’s long-standing desires for more detailed medical information (Charles, Gafni, & Whelan, 1997) and a more participatory role in health management (Guadagnoli & Ward, 1998). Because approximately 30%–50% of medication misuse is a result of lack of information (Farley, 1995), the potential reliance on the Web as a source of information may contribute positively to public health. Information retrieved from online sources is often used by patients in discussions with health-care providers (Aspden & Katz, 2001), which suggests that the Web can empower individuals through enhanced interactions (Rice, 2001).
That this opportunity, as well as opportunities to promote education and affective well-being, may not be fully taken advantage of is the basis of much of the research on the manner in which self-efficacy influences the social benefits of technological utilization (Bandura, 2002). Underlying this line of research is the notion that access to information communication technologies (ICTs) is not entirely a function of physical access to resources, but also a function of the ability to utilize such resources effectively to achieve desired outcomes. According to social cognitive theory, the ability to utilize ICTs successfully to achieve desired outcomes is predicated in part by self-efficacy.
Bandura (1997) defines self-efficacy as an individual’s belief in his or her ability to perform a task successfully. Self-efficacy arises from the interpretation of information from primarily four information sources: mastery experience (e.g., previous performance), vicarious experience, social influence, and emotional states. Based on these four sources of information, individuals evaluate information about their capabilities and regulate their choices and efforts accordingly. Thus, self-efficacy can determine not only what endeavors to pursue, but also how much effort will be put forth toward these endeavors and the individual’s resilience toward adversity. With respect to ICTs, one may have access to ICTs, but low self-efficacy may hinder the ability of an individual to utilize them to reap their associated benefits, including locating online health-related information with accountability standards.
Silbert, Lundberg, and Musacchio (1997) defined accountability standards as a “set of quality moorings” to help “consumers and professionals alike to reasonably judge whether what they are reading is credible, reasonable, or useful.” These accountability standards include identification of authorship, attribution of sources, currency of content, and disclosure of site ownership and sponsorships. These accountability standards were subsequently expanded by the American Medical Association (Winker et al., 2000). Recent studies found an association between presence of accountability standards and information accuracy (Kunst, Groot, Latthe, Latthe, & Khan, 2002; Meric et al., 2002; Winker et al., 2000).
Thus, locating online health information with accountability standards is an important outcome in self-efficacy research because many health-related sites provide information that is of poor quality, inaccurate, and inconsistent with established professional guidelines (Berland et al., 2001; Griffiths & Christensen, 2000). To reap the benefits of ICTs, one must be able to parse out the quality of health information available online. Thus, this study is concerned with the effects of Internet self-efficacy on finding health-related information that is accountable within the AMA guidelines (Winker et al., 2000).
Bandura (1997) conceived self-efficacy as an individual’s self-perception that varies across circumstances, rather than as a global disposition that can be measured by a single omnibus scale. Thus, domain specific measures of self-efficacy should assess the different levels of task demands necessary for successful completion within a specific domain.
Per Bandura’s suggestion that self-efficacy scales be tailored to specific domains, several self-efficacy scales pertaining to the computer and Internet domain have recently been developed (Compeau & Higgins, 1995; Eastin & LaRose, 2000). Because self-efficacy is context-specific, these self-efficacy measures assess the competence to perform a range of tasks associated with the computer (Compeau & Higgins, 1995) and the Internet (Eastin & LaRose, 2000). Moreover, the judgment of what one can accomplish with the skills possessed, rather than the skill set in and of itself, is the basis of self-efficacy. Thus, these scale items differentiate between component skills (e.g., opening a Web browser) and the behaviors one can accomplish with the skill set (e.g., finding information on the Web). Studies utilizing such scales posit that people with higher computer/Internet self-efficacy are more likely to achieve the benefits associated with utilization of ICTs.
A self-efficacy outcome pertinent to online health management is finding health-related information that is accountable. Although previous research has found a direct association between self-efficacy and perceptions of source credibility in an information seeking context (Eastin & LaRose, 2000; Hofstetter, Zuniga, & Dozier, 2001), there are two issues these studies do not address. First, these studies, as well as other studies that have explored the relationship between self-efficacy and various ICT-related outcomes, do not take into account the influence that the varying types of search tasks have on outcome. The specificity of the search task can determine a search’s level of difficulty and the amount of effort needed to successfully accomplish the online task (Kim & Allen, 2002). Thus, task difficulty would represent a form of adversity for individuals with low self-efficacy. Previous research indicates that individuals with low self-efficacy tend to give up under adversity (Bandura & Schunk, 1981). Thus, the direct relationship between self-efficacy and the outcome of finding information that is perceived to be credible, as demonstrated by previous studies, may occur for only difficult Internet search tasks and not for comparatively less challenging search tasks.
Second, previous related studies have not examined the effect of self-efficacy on website accountability. Instead, while these studies demonstrate a direct relationship between self-efficacy and the expectation of finding information that is perceived to be credible, the association is limited to expected outcomes, where one or more items from a self-reported questionnaire assess participants’ expectations of finding credible information online. Thus, these studies measure only expected outcomes rather than actual outcomes. An expected outcome “is a judgment of the likely consequences” (Bandura, 2002, p. 21) produced by a task, while an outcome is the actual realization of the consequences produced by the task. Expected outcomes, rather than actual outcomes, have been used in constructing and validating self-efficacy scales that have demonstrated the relationship between self-efficacy and finding credible online information (Eastin & LaRose, 2000; Hofstetter et al., 2001). It is feasible to ascertain the outcome of finding credible information online within an experimental setting where the website accountability standards are gauged. The current study addresses these shortcomings by examining the role of self-efficacy in two search tasks that differ in task specificity. This is achieved in an experimental study in which participants actively locate online health-related information.
Website Accountability as a Measure of Credibility
The credibility of a website is a perceived judgment of the believability of the source (Metzger, Flanagin, Eyal, Lemus, & McCann, 2003). Sources in credibility research have included media, organizations, and the individual spokesperson (O’Keefe, 2002); more recently, the individual website has been viewed as the source (Eighmey & McCord, 1998; Shon, Marshall, & Musen, 2000; Wathen & Burkell, 2002). What constitutes a website’s credibility is based on the individual receiver’s perceptions of the source’s believability. Because credibility judgments are subjectively based, they are not objective measures of the quality of information.
While adherence to these guidelines in and of itself does not ensure protection against falsification of information, websites containing more AMA benchmarks (Silberg et al., 1997) were less likely to have inaccurate information than sites with fewer AMA benchmarks (Meric et al., 2002). For other related quality benchmarks, there is a statistically significant relationship between website quality markers and objective measures of information accuracy (Kunst et al., 2002). Thus, there is an association between information accuracy and presence of quality benchmarks (Kunst et al., 2002; Meric et al., 2002). Yet another reason that AMA benchmarks serve as markers of quality of information is that many sites do not have the AMA quality markers. For example, recent reviews of website adherence to AMA guidelines indicate that the majority of the sampled websites related to food allergies and cystic fibrosis did not indicate a date of last revisions (Anselmo, Lash, Stieb, & Haver, 2004; Stieb, Wang, & Haver, 2002). In contrast, adherence to these guidelines is required for all sites associated with the AMA (Winker et al., 2000).
While these guidelines have practical application, there is also a theoretical basis for them. Specifically, the literature on source credibility indicates that in the absence of knowledge of the source, judgments of the source’s credibility are made based on the efficacy of the content or message (Austin & Dong, 1994; Slater & Rouner, 1997). That is, the judgments of the message, such as the presence or absence of specific elements of a message, are the basis for the determination of the perceived credibility of the source. Such reliance on message cues to determine source credibility is also found in situations where little information is available about the source (Eagly & Chaiken, 1993). Recent research suggests that health information seekers have little knowledge of the source, as the majority of health information seekers do not have a specific site in mind during a Web search session (Pew, 2002).
Thus, it is feasible to ascertain the outcome of finding credible online information within an experimental setting by having participants select one website from their search session and subsequently have independent coders content analyze the selected site for the presence of elements of the AMA website accountability guidelines.
Self-Efficacy Outcome in ICTs Context—Website Accountability
Previous studies found a direct relationship between self-efficacy and the expectation of finding online information that is perceived to be credible (Eastin & LaRose, 2000; Hofstetter et al., 2001). Hofstetter et al. (2001) argued that for tasks that pertain to information seeking, credibility is associated with self-efficacy. Eastin & LaRose (2000) demonstrated that Internet self-efficacy is directly associated with outcome expectations related to attaining information, including procuring information that is perceived to be trustworthy. In both studies, self-efficacy has a direct effect on the expectation of finding credible health-related information. Such outcome expectations are a result of self-efficacy perceptions. Compeau and Higgins (1995) noted that “individuals with a weak sense of self-efficacy will be frustrated more easily by obstacles to their performance and will respond by lowering their perceptions of their capability.” Hence, those with lower self-efficacy will have lower expectations of finding online information that would be deemed credible. In addition, those with lower self-efficacy will expend less effort on the task. If one expects less, then one would expend less effort on the task. Moreover, the lack of effort toward the task also manifests itself in the face of obstacles, where those with lower self-efficacy tend to give up more quickly than those with higher self-efficacy. Thus, based on Bandura’s (1997) construct of self-efficacy and empirical studies on self-efficacy and outcome expectations of finding credible information, self-efficacy will influence the selection of sites with greater website accountability.
ICT-related studies that assess the effects of self-efficacy (Ford, Miller, & Moss, 2001; Nahl, 1996; Thompson, Meriac, & Cope, 2002; Tsai & Tsai, 2003) have utilized experimental settings in which participants actively performed an online task. While these studies have examined search efficiency and accuracy and other related performance variables, none of the studies have examined website accountability as a task outcome. In general, these studies explore the effect of self-efficacy on performance by comparing individuals who are high vs. low on self-efficacy (e.g., Nahl, 1996). Thus, we can expect that the accountability of the website that high-self-efficacy individuals find in their search tasks will be higher than the accountability ratings of the websites that low-self-efficacy individuals find in their search. These observations are stated in the following hypothesis:
H1: Website accountability will be higher for websites selected by high Internet self-efficacy individuals than for low Internet self-efficacy individuals.
Influence of Task Specificity on Self-Efficacy Outcomes
Self-efficacy studies in the ICT context often examine the effect of self-efficacy on outcomes for only one specific online search task. For example, one study examined the effects of self-efficacy for locating information on psychologists (Thompson et al., 2002), while another study examined the effects of self-efficacy for acquiring science information online (Tsai & Tsai, 2003). These and other related studies do not take into account that some online search tasks are inherently more difficult to complete successfully than others.
When the effects of self-efficacy are examined within one search task, any differences found for performance and subsequent outcomes do not reflect the difficulty of the task. Hence, the performance and outcomes of low- and high-self-efficacy individuals for one search task may provide an incomplete picture of the influence of self-efficacy. It is, thus, important to consider the influence of self-efficacy in terms of search tasks of varying difficulty. For comparatively less difficult search tasks, while high-self-efficacy individuals should demonstrate better performance and achieve better outcomes than low-self-efficacy individuals, the difference may not be significant. In contrast, for more difficult search tasks, the self-efficacy outcomes may be significant. Exploring the influence of task difficulty and self-efficacy on outcomes can reveal the extent to which self-efficacy influences desired outcomes in the ICT context. That is, rather than coming up with the general observation that self-efficacy influences the adoption and utilization of ICTs to retrieve accountable information, we can determine if the relationship differs according to search task, thus further defining the conditions by which self-efficacy is most influential. This, in turn, will provide a better understanding of which online health-related information-seeking goals can be achieved by high- compared to low-self-efficacy individuals.
The search task is one of the most important elements to understanding electronic information seeking (Ingwersen, 1992). Previous research has found that search task specificity influences search patterns and behavior because varying tasks require different information-seeking skills (Marchionini, 1989; Saracevic & Kantor, 1988). A search task is a goal in that it “is the manifestation of an information seeker’s problem and is what drives information-seeking actions” (Marchionini, 1995, p. 36). Task can be characterized by the specificity of the goal, which is defined as the variability of appropriate answers available to achieve the goal (Marchionini, 1995). Search task specificity has numerous related terminology, including “broad” and “specific” tasks (Saracevic & Kantor, 1988), “open” and “closed” tasks (Marchionini, 1989), “known-item search” and “subject search” (Drabenstott, 1984), and “general” and “specific” (Qiu, 1993), the latter of which are the terms used in the current study. A general search task pertains to a more abstract idea of the subject of the search task. In contrast, a specific task is more concrete in that it specifies a particular information element to be sought.
As the specificity of the task decreases, more effort is required to complete the task (Marchionini, 1995). This suggests, as defined in the current study, that a general search task would require more effort than a specific search task. The amount of effort required to complete a task presents a barrier to task completion. Thus, the specific search task would be least aversive to successful task completion, and the general search task would be most aversive. When self-efficacy is taken into account along with task specificity, differences in website accountability for high and low self-efficacy should be more pronounced in the more difficult search task, such that individuals high in self-efficacy would locate websites with higher website accountability than those low in self-efficacy. This interaction effect is stated in the following hypothesis:
H2: There will be an Internet self-efficacy by task specificity interaction, such that high-self-efficacy individuals will locate sites higher in website accountability than low-self-efficacy individuals in the more difficult search task, but there will be no significant difference in the easier search task.
Influence of Self-Efficacy and Search Type on Task Perseverance
Self-efficacy beliefs determine how long individuals will persevere when confronted with obstacles. Bandura (2002) noted that the management of information on the Internet is a complex task, one in which self-efficacy can determine the successful utilization of the electronic environment. Previous research has demonstrated that under obstacles to task completion, low-self-efficacy individuals tend to give up and/or exert less effort (Bandura, 1982, 1997; Bandura & Schunk, 1981; Nahl, 1996; Wood & Bandura, 1998). Specific to online information seeking, Nahl (1996) found that for a class with no previous Internet experience, students in the lower third percentile for self-efficacy dropped out of a Web-related course. Given such adversity, utilization of ICTs and its associated benefits may not be realized for those low in self-efficacy. Specific to the outcome of finding health-related information that is accountable, certain search tasks may present more adversity than others.
In the current study, the amount of time spent completing the task is a measure of perseverance, similar to the Nahl (1996) study. Based on previous findings on the effects of self-efficacy on perseverance, self-efficacy has a main effect on perseverance (total time spent on search). However, when self-efficacy is taken into account together with task specificity, differences in the total time spent for search tasks for high- and low-self-efficacy individuals should be more pronounced in the more difficult search task. As a result, those low in self-efficacy would exert less effort and end the search task sooner than their high self-efficacy counterparts. Thus, there should be a main effect of self-efficacy on performance (total time spent on search) and an interaction between self-efficacy and task specificity.
H3: High-self-efficacy participants will spend more time on the search task than low-self-efficacy participants.
H4: There will be an Internet self-efficacy by task specificity interaction, such that high-self-efficacy individuals will spend more time searching online than low-self-efficacy individuals in the general search task, but there will be no significant difference in the specific search task.