This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
The fact that patient satisfaction with primary care clinical practices and physician-patient communications has decreased gradually has brought a new opportunity to the online channel as a supplementary service to provide additional information.
In this study, our objectives were to examine the process of cognitive knowledge expectation-confirmation from eHealth users and to recommend the attributes of a “knowledge-intensive website.”. Knowledge expectation can be defined as users’ existing attitudes or beliefs regarding expected levels of knowledge they may gain by accessing the website. Knowledge confirmation is the extent to which user’s knowledge expectation of information systems use is realized during actual use. In our hypothesized research model, perceived information quality, presentation and attractiveness as well as knowledge expectation influence knowledge confirmation, which in turn influences perceived usefulness and end user satisfaction, which feeds back to knowledge expectation.
An empirical study was conducted at the National Cancer Center (NCC), Republic of Korea (South Korea), by evaluating its official website. A user survey was administered containing items to measure subjectively perceived website quality and expectation-confirmation attributes. A study sample of 198 usable responses was used for further analysis. We used the structural equation model to test the proposed research model.
Knowledge expectation exhibited a positive effect on knowledge confirmation (beta = .27, P < .001). The paths from information quality, information presentation, and website attractiveness to knowledge confirmation were also positive and significant (beta = .24, P < .001; beta = .29, P < .001; beta = .18, P < .001, respectively). Moreover, the effect of knowledge confirmation on perceived usefulness was also positively significant (beta = .64, P < .001). Knowledge expectation together with knowledge confirmation and perceived usefulness also significantly affected end user satisfaction (beta = .22 P < .001; beta = .39, P < .001; beta = .25, P < .001, respectively).
Theoretically, this study has (1) identified knowledge-intensive website attributes, (2) enhanced the theoretical foundation of eHealth from the information systems (IS) perspective by adopting the expectation-confirmation theory (ECT), and (3) examined the importance of information and knowledge attributes and explained their impact on user satisfaction. Practically, our empirical results suggest that perceived website quality (ie, information quality, information presentation, and website attractiveness) is a core requirement for knowledge building. In addition, our study has also shown that knowledge confirmation has a greater effect on satisfaction than both knowledge expectation and perceived usefulness.
The Internet is rapidly growing and is increasingly used as an open, anonymous, and democratic source of health information and knowledge [
eHealth is an emerging field in the intersection of medical informatics, public health,and business, referring to health services and information delivered or enhanced through the Internet and related technologies. In a broader sense, the term characterizes not only a technical development, but also a stateofmind, a way of thinking, an attitude, and a commitment for networked, global thinkingto improve health care locally, regionally, and worldwide by using information and communication technology.
According to the above definition, the knowledge of what consumers find as satisfactory information in the health context has great implications, as customers may act seriously upon this information [
The main purpose of this study was to theorize the attributes of ”knowledge-intensive websites” based on the expectation-confirmation theory (ECT) and integrate these with eHealth from prior IS research. In order to maximize the function of websites as knowledge and information sources, we empirically measure website effectiveness by emphasizing the information as knowledge elements of eHealth services in that the benefits of health care are highly associated with the intrinsic value of information [
To achieve our purposes, we carried out an empirical study at the National Cancer Center (NCC), Republic of Korea (South Korea), by evaluating its official website. By considering the fact that among people with cancer, the Internet has become a major source of health information (eg, [
The research reported here also makes several contributions to both research and practice. From a theoretical perspective, we presented the concept of a knowledge-intensive website for eHealth. We proposed and validated a range of criteria needed to establish the knowledge-based website as a main information source for patients and/or Internet users. Second, it extends the ECT in the eHealth context to explain how initial knowledge expectation together with website quality influence knowledge confirmation as an actual knowledge outcome gained by users after assessing the information and how these factors influenced postconsumption expectations that may lead to improved consumer satisfaction, which has not been examined in previous literature. Third, this paper focused on the importance of information and knowledge of an eHealth website, which is a new paradigm in the eHealth research area.
This paper is organized as follows: We begin by presenting the basic concept of expectation confirmation theory. In the third section, we describe our research model and hypotheses development. In the fourth section, we provide a description of the methodology that we relied upon to select and analyze the data, and in the fifth section, we present the results of data analysis. The sixth section presents the discussion of the study’s key findings and its limitations. And in the last section, implications and future research are discussed.
The expectancy confirmation paradigm is primarily cognitive in nature because the comparison process in confirmation judgments requires the deliberate processing of information [
Rust et al [
To tackle these limitations, we measured both preknowledge and postknowledge expectations in one model. While preacceptance expectation is based on secondhand experience (eg, others’ opinions or information disseminated through mass media), postacceptance expectation is formed by the customers’ firsthand experience and is more realistic [
The conceptual model that presents the hypothetical relationships is illustrated in
Definitions of constructs
Construct | Definition |
Knowledge expectation (Adapted from [ |
Customers’ existing attitudes or beliefs regarding expected levels of knowledge they may gain by accessing the website |
Knowledge confirmation (Adapted from [ |
A cognitive belief (the extent to which user’s knowledge expectation of information systems use is realized during actual use) derived from prior information systems use |
Information quality [ |
Quality of the information system output |
Information presentation [ |
The degree to which information presentation effectively facilitates interpretation and understanding |
Website attractiveness [ |
Website’s graphic style, that is, the tangible aspect of the online environment that reflects the “look and feel” of the website |
Perceived usefulness [ |
An individual’s salient belief that using the technology (website) will enhance his or her job performance |
Consumer satisfaction [ |
The summary psychological state resulting when the emotion surrounding confirmed or disconfirmed expectations are coupled with the customer’s prior feelings about the consumption experience |
Research model.
With respect to expectations as comparative referents, it is argued that this expectation influences the confirmation paradigm [
Perceived quality may represent perceived performance of a product or service [
Chiu et al [
Bliermel and Hassanein [
Liao et al [
The direct relationship between expectation and customer satisfaction has been proposed in prior research (eg, [
Confirmation is positively associated with satisfaction as it implies realization of the expected benefits of information systems use, while disconfirmation (to the extent where perceived performance lags expectation) indicates failure to achieve expectation [
Perceived usefulness is the main reason that people decide to use and accept new information systems [
As far as possible, items used to measure each construct were based on preexisting instruments, and some of these were modified specifically for this study. Information quality items were adopted from Wixom and Todd [
Our research used the website satisfaction survey, conducted by the National Cancer Center in South Korea. The survey applied a national probability sampling methodology to assess Korean residents’ perceptions regarding cancer information and other issues delivered by National Cancer Center. The objective of this survey was to measure customer satisfaction and identify the effectiveness of media usage to distribute the cancer-related information. The questionnaire was administered online by posting the electronic form on the NCC (National Cancer Center) website. When users entered the website, the questionnaire was presented on a new browser window (pop-up window). Data were collected from September 18, 2009 through December 28, 2009. Cash rewards were provided for respondents. Upon the completion of this survey, 200 responses had been collected. In the present study, we excluded data from respondents with an elementary school education level as our
Of the 198 respondents, 71.2% (141) were female. The majority of respondents (100) were from 20 to 29 years of age (50.5%), while 52 were from 30 to 39 years of age (26.3%). More than half (67.7% or 134) of respondents had a university degree. Among the 198 respondents, 47.5% (94) obtained information about cancer information from the Internet, 19.7% (39), from television, 8.6% (17), from family, 8.1% (16) from a medical center, and the remaining 16.2% (32) obtained information about cancer from friends, books, cancer clubs, newsletters, hospital instructions, and other resources. The percentages of respondents that heard about the NCC website by word of mouth and through Internet searches were 44.4% (88) and 40.9% (81) respectively, while others learned of the website from various other sources (eg, brochures, newsletters, advertisements, and recommendations). Furthermore, among the respondents, approximately 59.6% (118) were members of the general population, followed by 22.2% (44) who were family members or other relatives of patients, 14.1% (28) who were researchers/academics, and only 4.0% (8) who were patients. Lastly, we also asked the respondents to indicate how the information they obtained was used. More than 70% (73.2% or 145) of respondents used the information as resource or reference material, while 26.3% (52) and 17.2% (34) used it as self-learning and to educate cancer patients, respectively.
Prior to data analysis, the research instrument was assessed for its reliability as well as its construct validity. Construct validity assessment was performed through confirmatory factor analysis (CFA) using LISREL 8.7 (Scientific Software International, Inc, Lincolnwood, IL). Each scale item was modeled as a reflective indicator of its latent construct. The seven constructs were allowed to covary in the CFA model. First, we checked the scale validity by examining the goodness of fit of the overall CFA model using criteria suggested by Choudhury and Karahanna [
Confirmatory factor analysis results
Variable and Item | Item Number | Standardized |
Construct Reliability | Average Variance |
|
|
.92 | .68 | |||
The website provides accurate information. | IQ1 | .84 | |||
The website provides up-to-date information. | IQ2 | .74 | |||
The website provides relevant information. | IQ3 | .82 | |||
The website provides the content that supports the website's intended purpose. | IQ4 | .86 | |||
The website consists of appropriate level of information detail. | IQ5 | .88 | |||
|
.87 | .63 | |||
The overview, table of contents, and/or summaries/headings are clearly organized. | IP1 | .79 | |||
The structure of information presentation is logical. | IP2 | .84 | |||
The information presented is understandable. | IP4 | .77 | |||
The amount of information presented was just right. | IP5 | .78 | |||
|
.93 | .69 | |||
Overall, the website's color use is attractive. | WA1 | .87 | |||
This website has visually attractive screen layouts. | WA2 | .87 | |||
This website has an attractive screen background and pattern. | WA3 | .85 | |||
This website has eye-catching images or title on homepage. | WA4 | .82 | |||
The multimedia contents are attractive. | WA5 | .80 | |||
This website is fun to explore. | WA6 | .74 | |||
|
.84 | .72 | |||
Using this website will increase my knowledge level about cancer-related subjects. | KE2 | .87 | |||
Using this website will improve my skills through a learning process. | KE3 | .83 | |||
|
.92 | .86 | |||
I have learned new knowledge by using this website (as I expected). | KC1 | .93 | |||
I have improved my skills by using this website (as I expected). | KC2 | .92 | |||
|
.90 | .69 | |||
Web tutorial/e-learning | PU1 | .89 | |||
Tutorial material in a printable PDF file/e-books | PU2 | .85 | |||
PowerPoint slide presentation | PU3 | .79 | |||
Testimonial and Q/A content | PU4 | .79 | |||
|
.92 | .86 | |||
Considering all things, I'm very satisfied with this website. | SF1 | .92 | |||
Overall, my interaction with this website is very satisfying. | SF2 | .93 |
Discriminant validity
Variable | IQ | IP | WA | KE | KC | PU | SF |
Information quality (IQ) | .83 | ||||||
Information presentation (IP) | .72 | .80 | |||||
Website attractiveness (WA) | .51 | .65 | .83 | ||||
Knowledge expectation (KE) | .59 | .54 | .48 | .85 | |||
Knowledge confirmation (KC) | .70 | .69 | .61 | .62 | .92 | ||
Perceived usefulness (PU) | .52 | .59 | .45 | .51 | .54 | .83 | |
User satisfaction (SF) | .57 | .65 | .71 | .54 | .61 | .56 | .92 |
We tested the possibility of common method bias by adopting Harman method bias [
Equation 1:
Equation 2:
Equation 3:
Where:
N is the number of samples,
Hypothetical correlation among constructs (n = 198)
Variable | IQ | IP | WA | KE | KC | UF | PU | SF |
IQ | .83 | |||||||
IP | .72* | .80 | ||||||
WA | .51* | .65* | .83 | |||||
KE | .59* | .54* | .48** | .85 | ||||
KC | .70* | .69* | .61* | .62* | .92 | |||
UF | .19 | .17 | .08 | .18 | .21 | 1.00 | ||
PU | .52* | .59* | .45** | .51* | .54* | .24 | .83 | |
SF | .57* | .65* | .71* | .54* | .61* | .24 | .56* | .92 |
|
.50* | .57* | .44** | .49** | .52* | .00 | ||
|
.54* | .66* | .47** | .59* | .56* | .00 | ||
|
.55* | .64* | .70* | .52* | .59* | .00 | .53* | |
|
.60* | .73* | .76* | .62* | .64* | .00 | .60* |
*
**
Therefore, we concluded that common method bias does not seem to be a serious problem in this study. Regarding multicollinearity, variance inflation factor (VIF) scores were measured for all constructs as in Gable et al [
The structural equation model was used to test the eight hypotheses proposed in this study (see
Thus, hypotheses 2, 3 and 4 were accepted. Moreover, the effect of knowledge confirmation on perceived usefulness was also positively significant (beta = .64,
Hypotheses results.
Korea has one of the most advanced information technology and IT infrastructure in the world, supporting the diffusion of eHealth technology not only domestically, but also outside the country. Therefore, eHealth has become one of the most important elements for public health care, health informatics, and other related technologies in South Korea. As one of the initial public health care services in this country, the National Cancer Center, initiated by the Ministry of Health and Welfare, South Korea, also delivers its services through the Internet. One of the main functions of this website is providing cancer information in various forms, including electronic learning, e-books, multimedia presentations, and testimonials [
First, our empirical research showed that knowledge expectation was positively associated with actual knowledge confirmed by users after accessing the eHealth website (ie, met expectation). Unlike the traditional ECT in marketing research, our findings confirmed that higher preknowledge expectation may lead to higher postknowledge confirmation. We argued that users or patients’ expectations motivate them to access the website, with the assumption that they will gain more knowledge. This finding also supports Joyce and Piper’s [
Second, this study also found that website quality (ie, information quality, information presentation, and website attractiveness) also influenced the actual knowledge confirmation. Additionally, from our survey, online searching for cancer information is the most popular choice for obtaining information compared with other conventional alternatives. Grounded on this finding, we argued that computer-based information has been an effective strategy for knowledge transfer in the health care context [
Third, the findings confirmed the positive relationship between knowledge confirmation and perceived usefulness (postexpectation variable) suggesting that users’ perceptions of the usefulness of information provided by an eHealth website may be influenced by their confirmation level. Considering the fact that this confirmation level was influenced by website quality, we argued that when the expectation and information quality attributes are both measured in the preconsumption stage, postexpectation is related to information quality [
Fourth, the effects of knowledge expectation, knowledge confirmation, and perceived usefulness on end user satisfaction were also statistically significant. Through these findings, we posit that user satisfaction is determined by expectation of the knowledge and confirmation of expectation following actual use represented by perceived usefulness [
Beyond its contribution, this study also has limitations. First, we only investigated the predictor side of satisfaction. Further research is needed to study the outcome side of the satisfaction model (eg, the relationship between satisfaction and intention to use and the relationship between satisfaction and negative word of mouth). Second, even though a range of statistical methods has been used to ensure the validity and reliability of our data, further research is needed to measure the expectation and confirmation at adoption and postadoption to validate the results. Third, this study was based in Korea and used only one specific cancer website. Future research can explore the importance of information and knowledge for different respondents in different countries.
This study provides implications for both research and practice. Theoretical implications of this research are threefold: (1) identification of the attributes of knowledge-intensive websites; (2) enhancement of the theoretical foundation of eHealth from the information systems perspective by adopting ECT; and (3) examination of the importance of information and knowledge and explanation of their impact. First, the raising of concerns about the validity of information on the Internet has been a challenge for eHealth centers whose goal is to provide knowledgeable information presented in an appropriate format and posted on an interactive website. Our study also suggests that an intensive website should be able to influence the cognitive skills of users in learning and absorbing knowledge. Further research may address this initial finding to study how the website attributes presented in this study together with other attributes (eg, service quality) influence consumers’ attitudes in a different sense.
Second, this study has enhanced the concept of electronic health care from the information systems perspective by providing theoretical explanations through the adoption of ECT. By demonstrating that preknowledge expectations and perceived information performance influence actual knowledge acquisition, the results indicate that when patients and or users enter a health care website, they bring a certain level of expectation that by accessing and turning on the website, they may improve and gain some new information and knowledge, while explicitly, this process is also influenced by perceived performance. We also argued that during the consumption process, the user’s expectations might be adjusted by confirmation, resulting in greater or lower postexpectation beliefs (perceived usefulness). Thus, our study suggests the important linkage of these variables for eHealth satisfaction literature. We measured preexpectation with
Third, this study examined the online information performance construct by studying its effects on influencing the knowledge cognition process. Recognizing that transfer of knowledge to patients or end users may help them to participate in the decision-making process toward their health condition, we suggest that further research is needed to examine the roles of other information media, such as mobile information services. Moreover, it is also a challenge for information systems researchers to become involved actively in this area, particularly to examine how to deliver health information in various electronic formats.
Practically, our empirical results indicate that information performance is a core requirement for knowledge building. Through this study, we argued that having accurate, high quality cancer or general health care information published on a reliable website can provide individuals with knowledge and help the consumers to obtain more useful materials. Furthermore, this research suggests that information on eHealth websites should be presented attractively. Online health care can also provide an opportunity for health care centers to learn how to provide online information innovatively to attract more patients or Internet users. The information presentation in various formats (eg, multimedia/power point and e-book) can utilize multiple sensory channels to convey information to users, which, in turn, builds respective mental representations in both verbal and nonverbal system [
The authors gratefully acknowledge the financial support of the National Cancer Center, Korea (Grant numbers NCC-0960350 and NCC-1010131), and the Ministry of Health and Welfare, Republic of Korea.
None declared
Min Kyung Lim originated the study and supervised all aspects of its implementation. Chulmo Koo had responsibility for the design, analysis, and write-up for this study. Yulia Wati assisted with analyses and writing the article. Keeho Park oversaw the collection and analysis of claims data and gave critical input into the design of the study and interpretation of the results.
Measurement Items.
adjusted goodness of fit index
average variance extracted
confirmatory factor analysis
comparative fit index
common method variance
composite reliability
degrees of freedom
expectation confirmation theory
goodness of fit index
information presentation
information quality
information systems
knowledge confirmation
knowledge expectation
marker variable
National Cancer Center
normed fit index
perceived usefulness
root mean square error of approximation
satisfaction
user frequency
variance inflation factor