Online health information seeking behaviors among Chinese elderly

Library & Information Science Research 38 (2016) 272–279

Contents lists available at ScienceDirect

Library & Information Science Research

Online health information seeking behaviors among Chinese elderly Dan Wu ⁎, Yizhe Li School of Information Management, Wuhan University, 299 Bayi Road, Wuhan, Hubei 430072, China

a r t i c l e

i n f o

Article history: Received 20 January 2015 Received in revised form 8 November 2015 Accepted 31 August 2016 Available online 7 September 2016

a b s t r a c t The Internet has become an important source of health information for elderly people in China. A controlled user experiment was conducted to understand how Chinese elderly people search for online health information. Twenty elderly people completed three search tasks based on three different health information seeking contexts. Online health information seeking behavior patterns of the elderly were found to include reselecting from results pages, following hyperlinks, and using a query reformulation patter. There was no significant difference with respect to emotion and the three task contexts, as elderly people have positive attitudes regarding the health information seeking process, but cognition within the three task contexts displayed significant differences. There was a significant correlation between education and Internet search proficiency regarding task search performance, while health condition, familiarity with the Internet and credibility of online health information were found to be primary factors that influenced the decision of the elderly to search for online health information. © 2016 Elsevier Inc. All rights reserved.

1. Introduction The world is increasingly an aging society. The United Nations Population Division (2002) predicted that the total global aging population over 60 years would be nearly 2 billion by 2050, which would account for 21% of the world's population. With the largest elderly population in the world, China will be among the first nations to face the issues that derive from this trend in demographics. According to the statistical report of the people's republic of China on the development of social services in 2012, 14.3% of the total Chinese population, about 194 million, were age 60 or over by the end of 2012 (Li, 2013). Meanwhile, with the global development of information technology, the Internet has become an important information source for the elderly. The 34th statistical report on Internet development in China reported that as of mid-2014, China's Internet penetration had reached 46.9% and users over the age of 50 accounted for 7.3% of all users as the popularity of the Internet has gradually spread to the elderly from the young (China Internet Network Information Center, 2014). 1.1. Problem statement Health is one of the most important issues affecting the elderly, and thus, it receives the most attention (Agusta, 2012; Williamson, 1995). As elderly people take more initiative to participate in their healthcare decisions, the ability to acquire effectively adequate health information support affects them as they seek to address or solve health problems. ⁎ Corresponding author. E-mail address: [email protected] (D. Wu).

http://dx.doi.org/10.1016/j.lisr.2016.08.011 0740-8188/© 2016 Elsevier Inc. All rights reserved.

Therefore, accessing online health information is becoming increasingly more important for the elderly in China, as it allows them to participate in their own healthcare. However, there are few studies about online health information seeking behaviors (HISBs) of the elderly. Hence, examining how elderly people seek, understand, and assess online health information could enable the development of better services to the elderly for seeking online health information. 2. Literature review 2.1. Health information needs and sources for the elderly Elderly people need access to health information regarding such issues as special diseases, diagnoses, treatments, drugs, healthcare, and health policies. However, it is important to keep in mind that their needs change over time along with changes in their health conditions (Torp, Hanson, Hauge, Ulstein, & Magnusson, 2008; Washington, Meadows, Elliott, & Koopman, 2011; Xie, Wang, Feldman, & Zhou, 2010). Previous studies have found that the elderly primarily obtain health information from social networks, such as healthcare providers, family members and friends, and from information systems, such as the Internet, broadcasts, and television (Agusta, 2012; Gollop, 1997; Hirakawa, Kuzuya, Enoki, & Uemura, 2011; Niemelä, Huotari, & Kortelainen, 2012). Research indicates that the elderly have greater trust in those with whom they are able to discuss their health actively as opposed to nonliving sources such as the Internet (Chaudhuri, Le, White, Thompson, & Demiris, 2013), thus the design of online healthcare information systems should consider users' real health information seeking behaviors (Johnson, 2014), especially when considering

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279

that online health information has an impact on people's healthcare outcomes (Xiao, Sharman, Rao, & Upadhyaya, 2014). Elderly people in China are using the Internet at an increasing rate, as it is an easy and useful way for older people to address their health needs and concerns (Wong, Yeung, Ho, Tse, & Lam, 2014). Previous studies have focused on health information needs, information search strategies and influencing factors of online HISBs. However, studies about elderly people's online HISB patterns are relatively few, and the online HISB differences among different health information seeking contexts have not been explored. 2.2. Online health information seeking behaviors among the elderly Online HISBs include ways in which individuals obtain information about their health, health promoting activities, health risks, and illnesses (Lambert & Loiselle, 2007). Several studies have demonstrated that elderly people's health information seeking abilities are low and that the elderly tend to rely more on their prior experiences (Chin, Fu, & Kannampallil, 2009; Hanson, 2010). However, their success in developing strategies to find health information is also dependent on their experiences, and this may offset disadvantages such as cognitive decline (Curzon, Wilson, & Whitney, 2005). Some researchers have examined behavioral features of query formulation, search strategies, and results evaluations (Huang, Hansen, & Xie, 2012). Previous studies that have examined the factors that influence online health information seeking behaviors of the elderly can be divided into two types: personal information of the individual, such as age, gender, health information literacy and cognitive ability; and characteristics of the health information itself, such as intelligibility, presentation, and credibility (Anker, Reinhart, & Feeley, 2011; Koch & Hägglund, 2009; Xie & Bugg, 2009; Zamarian, Benke, Buchler, Wenter, & Delazer, 2010). Among these factors, the elderly rely on their cognitive abilities and existing knowledge structures for every search behavior; however, their cognitive abilities tend to decline with age (Sharit, Hernández, Czaja, & Pirolli, 2008; Slegers, Van Boxtel, & Jolles, 2012; Wild et al., 2012). Being equipped with professional domain knowledge and Internet search knowledge could help the elderly choose keywords and search strategies to complete tasks efficiently (Stronge, Rogers, & Fisk, 2006). To date, most health information literacy interventions were founded and developed by public libraries and government agencies. Substantial evidence indicates that interventions could improve elderly health literacy, computer skills, and decision-making skills regarding medical issues (Blažun, Saranto, & Rissanen, 2012; Xie, 2011a, 2011b).

273

elderly under the different contexts. This is addressed in the second research question: RQ2: What are the differences in Chinese elderly's online health information seeking behaviors with respect to the three health information seeking task contexts? To improve Chinese elderly's online health information seeking abilities and thus facilitate their active participation in their healthcare decisions, the factors that influence their behaviors as they search for online health information need to be identified. The third research question asks: RQ3: What factors affect the Chinese elderly's online health information seeking task performance? 3.2. Participants Twenty elderly people were recruited from a senior activity center at Wuhan University where retired people could participate in group activities or take courses, such as computer and dance. The participants were required to be older than 55 years (China's retirement age is over 60 for males and over 55 for females) and had to have searched for online health information during the past month. The age range of participants was 55 to 81 years (M = 64; SD = 6.93). Among these participants, 75% were women, 80% had received at least a high school degree, 50% used the Internet every day, and 40% accessed the Internet at least two or three times per week. Almost half, 45%, reported their online information seeking ability to be “general”, 35% reported it to be “not very good” and only 20% reported it to be “relatively good”. With respect to health, 25% of the participants had a chronic health condition, 65% stated that they had a general health condition and 10% stated that they were in good health. 3.3. Procedure The experiment sessions were conducted in a computer room of a senior activity center. Each session lasted approximately 2.5 h, and an experiment administrator worked with one participant per session. Participants used a laptop in the computer room that was installed with Video Screens Experts; the laptop was running Windows XP, with an external mouse and keyboard. Before each session, experiment administrators explained the goals and procedure of the experiment, and asked the participants to complete a questionnaire asking about their basic demographics, frequency of Internet use, familiarity with online health information searches, and health condition.

3. Research design 3.1. Research questions Few works have studied the online health information seeking behaviors of China's elderly population and none of them have looked at the behavioral patterns of HISBs of the elderly population. This leads to the first research question: RQ1: What are the characteristics and behavior patterns of Chinese elderly's online health information searching behavior? HISBs occur within three contexts (Lambert & Loiselle, 2007): a) coping with a health-threatening situation, which has become an increasingly central issue; b) participating in medical decision making where obtained information contributes to the individual's identification of possible options, evaluation of various choices, and reduction of uncertainty and doubt about alternatives; and c) behavioral changes and preventive behaviors. Although information alone does not guarantee healthy behavior, acquiring adequate information may motivate individuals to make positive changes with respect to their health practices. However, there are few studies that have focused on online HISBs of the elderly under different health information seeking contexts or that have evaluated the affective or cognitive differences in the

Table 1 Search tasks under different health information seeking contexts. Task contexts

Search tasks

Task context 1: coping with a health-threatening situation

Task 1: One of your friends suffers from epilepsy. If he has a seizure, he may faint. You want to use the Internet to find information about reducing physical risk during an epileptic seizure. Please write down 2–3 first aid measures. Task 2: One of your friends was diagnosed with type II diabetes. The doctor suggested he inject insulin to control his blood sugar. You want to use the Internet determine when a diabetic patient must inject insulin. Please write down 2–3 conditions. Task 3: One of your friends has suffered from hypertension for a long time. You want to use the Internet find diet and exercise advice that will to help control blood pressure, in place of medications. Please write down 2–3 websites that contain diet and exercise information for hypertensive patients.

Task context 2: participation and involvement in medical decision making

Task context 3: behavior changes and preventive behaviors

274

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279

The participants were assigned three search tasks (Table 1) that were designed to explore three contexts related to people seeking health information (Lambert & Loiselle, 2007). These tasks were also related to health problems commonly experienced by elderly people in China. The participants were instructed to finish each task within 20 min. If a participant needed more time to finish a task, he or she was told to either continue the search for another 10 min or abandon the current search and move on to the next search task. After completing each task, the participants were requested to complete two questionnaires that measured their cognitive and emotional states. Since the same sample participants performed the three tasks sequentially, there could have been potential learning effects that could not be controlled; this is a limitation in this experiment. After they had completed all search tasks, each participant was interviewed about his or her feelings on the search process. The five interview questions were: (1) What challenges did you encounter during your searches? (2) How do you feel about today's session? (3) What prior experience or skills helped you in your searches today? (4) When would you use the Internet for health information in your daily life? (5) Do you find the online information to be understandable and credible? 3.4. Measures There were three measures used in this study: the participants' task performance scores, emotion/affective scores, and cognition scores. Two healthcare experts were invited to score the search answers of the elderly participants, according to scoring criteria developed by the researchers (see Table 2), and based on previous studies (Harris, 1997; Stoker & Cooke, 1994). If the participant just wrote down the answers based on their prior experience without finding the answer through the Internet, a score of zero would be recorded. Emotion and cognition were measured on a 5-point Likert scale ranging from 1 (strongly disagree) to 5 (strongly agree) for five items (Table 3). The items were organized in a gradation of the retrieval process, based on previous studies (Huang et al., 2012; Kim, 2008; Sharit et al., 2008; Stronge et al., 2006; Wild et al., 2012; Xie, 2011a, 2011b). The Cronbach's α coefficients of these two questionnaires which measured emotion and cognition were 0.955 and 0.863, indicating the questionnaires were effective. 3.5. Data analysis Using the data captured by Video Screens Experts, the researchers manually coded each search step. Codes for these experiments were adapted as necessary to describe the selected search entrance, length and content of search query, number of result pages browsed, and task answers selected. Behavioral sequence codes were also analyzed to explore the most frequent behavioral patterns. A correlation analysis was performed to examine how the participants' age, level of education,

Table 3 Measures of emotion and cognition. Emotion (5 items)

Cognition (5 items)

No. 1: I felt very confident that I could find the answers to the search task (Wild et al., 2012; Xie, 2011a, 2011b) No. 2: I was able to address everything in the task search process (Kim, 2008)

No. 1: I completely understood the meaning of this search task.

No. 3: After completing the task search, I felt great (Huang et al., 2012) No. 4: I thought this search was very successful and I was able to find the correct answers (Huang et al., 2012) No. 5: I thought the time given to complete this search was sufficient for me.

No. 2: I had adequate knowledge about this search task prior to the experiment (Sharit et al., 2008) No. 3: I knew the answers to this search task before the experiment (Stronge et al., 2006) No. 4: I was able to find the answers to this task on the Internet. No. 5: I consider the answers I found to be correct and credible.

and Internet searching familiarity affected their search performance. Also, repeated measures ANOVA was used to analyze the emotion and cognition variables' inner-task contexts and inter-task contexts differences. Interview records were manually transcribed into text using ATLAS.ti qualitative data analysis software to code the interviews and extract the main views of the participants based on the five interview questions. 4. Results 4.1. Task performance and influence factors Among the three search tasks, task 1 had the highest mean score at 88 (SD = 8.92), task 2 had the lowest mean score at 71 (SD = 28.62), and the score for task 3 was 78 (SD = 18.97). Task 2 was assumed to be the most difficult task for the elderly participants. This may due to the task context as it dealt with participation and involvement in medical decision making and therefore required further searching to find the health information requested. To confirm whether the data followed a normal distribution, the Kolmogorov–Smirnov Test was calculated (p = 0.770, 0.059, 0.352). Since the values of p were N 0.05 in total, the task scores were determined to be normally distributed. A Spearman correlation analysis was performed to investigate how different variables, such as age, familiarity of searching, level of education and frequency of computer use, influenced task search performance. The results revealed that level of education had a significant impact on task performance in task 1, and familiarity with Internet searching had a significant impact on task performance in task 2 (Table 4). Age and frequency of computer use exhibited no significant correlation with user task performance. As mentioned above, sound recordings of the interviews for question 1 were first transcribed into text and then were coded using ATLAS.ti (Table 5). The results showed that 30% of the participants had no difficulty completing the search tasks. Further, the greatest

Table 2 Task performance scoring criteria. Criteria

Weights Level (%) A (80 to 100)

Reliability

10

Accuracy

40

Comprehensiveness 40 Logicality

10

The answers come from authority resources. The content of answers was correct. The answers were complete and meet the requirements The typesetting of the answers were coherent and no repeated.

B (40 to 79)

C (0 to 39)

The answers were selected from reliable resources. The answers were not entirely correct, exist few mistakes. The answers were not complete, exist omission according to the requirement. The typesetting of the answers were relatively coherent, but few repeated

The resources were not reliable, such as ads. The answers were basically wrong and stray. The answers were greater incomplete. The typesetting of the answers were incoherent and a large number of repeated.

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279 Table 4 Task performance correlated factors analysis (*p b 0.05).

Task 1 Score Task 2 Score Task 3 Score

Correlation Sig. (two-sided) Correlation Sig. (two-sided) Correlation Sig. (two-sided)

Age

Familiarity of search

Level of education

Frequency of computer use

0.023 0.925 −0.210 0.375 −0.265 0.260

−0.086 0.720 −0.552* 0.012 −0.358 0.122

0.484* 0.031 0.246 0.297 0.308 0.186

−0.095 0.690 −0.272 0.245 0.072 0.764

challenges were slow word typing speed and lack of familiarity with Pinyin, followed by computer use, online health information judgment and lack of search experience. ATLAS.ti was also used to code the sentences relevant to interview questions 4 and 5. The results indicated that the participants in good health did not initiate health information searches unless they were experiencing health problems, and 40% of them tended to use Baidu (the largest Chinese search engine) to find the health information they needed. However, one individual with health problems tended to engage frequently in online health information searches. Another 20% often visited special health websites and sought information about their own diseases. Moreover, those users who searched the Internet proficiently were also more active in information seeking, while computer novices would only use traditional information channels. For example, one participant said, “Sometimes I want to seek health information on the Internet, but a lack of computer knowledge and skills make it inconvenient for me to surf the Internet”. According to the data from the interviews with respect to question 5, elderly people considered online health information to be easily understandable but not entirely credible. While 40% of the users thought online health information was very easy to understand, 60% agreed that some medical professional knowledge, such as pathology, was relatively difficult to understand. With respect to the credibility of the online information, 85% of the participants doubted the credibility, though they did affirm its consultative value. As an elderly male participant stated, “Some online health information issued by hospital sites is believable, but some information on the advertising websites must be carefully distinguished. If it is wrong, I will not adopt it”. Only 15% of the participants considered online health information to be credible. “I am convinced of the online health information regarding drug control, body exercise and so on, and I think it is not swindled information but sound doctor advice”. 4.2. Characteristics of search behavior based on processing 4.2.1. Search entrance choosing behavior Huang et al. (2012) used four mutually exclusive categories to describe elderly people's online health information search strategies: browser built-in search box, browser address bar search, web search engine, and health website search. In this study, however, all the participants used search engines to find information and rarely switched search entrance (the participants were free to use any online search tools in our experiment). Baidu, the largest Chinese search engine in the world, was the most frequently used search engine. This result is likely due to their daily experiences with this search engine.

275

4.2.2. Query constructing behavior Overall, the 20 participants submitted a total of 89 queries for 60 task searches (averaging 1.5 queries per task). The results suggest that there are four characteristics of elderly people’ query construction behavior (Table 6). First, elderly people spend more energy in query formulation. The average length of queries was 8.4 Chinese characters (max = 20, min = 1) and the average time was 122 s (max = 8 min, min = 14 s). Some previous studies have shown that people tend to formulate short queries; for example, an average length in Baidu was 6.4 Chinese characters (Ma & Feng, 2005). Second, participants preferred to use query suggestions supplied by the search engine. Of the queries, 37.1% originated from search engine suggestions. Furthermore, 86.5% of the queries were formulated in completed questions, that is, the participants preferred to copy the search task descriptions. Third, the participants rarely used advanced search strategies. Such strategies accounted for only 5.6% of all queries, which was similar to previous studies that found that users preferred simple searches and that only a few can use advanced strategies correctly (Deng, 2003). Finally, the participants did not often reconstruct their search queries. The average number of query trials was approximately 1.7. This was consistent with a previous study that revealed the average number of query trials was approximately 1.2 (Huang et al., 2012). 4.2.3. Search results browsing behavior The participants clicked on a total of 200 web pages during their search processes (3.3 per search task). Elderly people were inclined to click on links in a web page they were viewing, and thus, 19.5% of the web pages they visited were links to other websites. Moreover, 89.1% of all browsed web pages were located on the first page of the search engine's results page. Search engine behavior research has found that users generally view few of the pages returned by searches (Jansen & Spink, 2006), and Deng (2003) found that approximately 70% of users only scanned the first results page in Google, and on average users visited 1.7 pages for each search. 4.2.4. Search results selection behaviors All the participants' answers were obtained from 82 web pages. The results suggest that elderly people preferred to locate relevant information in question and answer community websites such as Baidu Knows and 39 Health Website. Furthermore, the participants, for the most part, selected the first 5 pages in the results list and 20.7% of those were the first webpage. This indicates that elderly people trust and rely on the results ranking of the search engine. 4.3. Online information searching behavioral pattern Based on data from the participants' search process video records and from previous research, search behavior was divided into 4 stages (search engine use, query submission, results page decision and response evaluation) and 14 behavior codes (Table 7). Through repetitive coding sequence analysis, the most frequent online health information search behavior patterns were identified: 1. Reselection from result pages pattern. The coding sequence /ISR/RS/ WC/, which was the most frequent sequence, occurred 65 times. Reselection from result pages indicated that users quickly clicked on one webpage then scanned and judged whether the content

Table 5 Task search barriers analysis. Keywords

Term frequency

Keywords

Term frequency

Have no difficulty Input words Computer use Information judgment

6 8 6 3

Search experience Not accustomed to use experiment-computer Task unfamiliarity

2 2 1

276

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279

Table 6 Query formulation analysis. Content composition

Table 8 Means and standard deviations of affective measures. Query resource

Complete questions Phrase Manual input System suggestion 77

12

56

Use of logical search strategy

33

5

Task context

1 2

was relevant. If it was not relevant, they went back to the results page and clicked on another webpage until they found one that they believed contained the relevant information. In the experiment, this pattern was repeated up to 6 times for a single task search. 2. Following the hyperlinks pattern. The coding sequence /HC/WS/ occurred 31 times. In this scenario, the participants first clicked on a webpage, scanned it, and then followed the hyperlinks they felt were relevant to the task and thus abandoned the original page. The results suggest that hyperlinks in a webpage provide support for those who have less experience searching the web as this type of user prefers hyperlinks because they are straightforward, easy to manipulate, and allow the user to avoid result page reselection or query reformulation. 3. Query reformulation pattern. The coding sequence /QC/RS/WC/ was repeated 28 times. After browsing the results page feedback of the search engine or scanning a few web pages, the participants realized there was no relevant information based on the name or abstract of these websites. They then reformulated a search query to develop a new search until they found the relevant information. While query reformulation was a common strategy in a general web search, elderly people did not want to perform such a reformulation as it required advanced search skills and energy. These three patterns above were the most common HISB patterns exhibited by the elderly participants. Additional patterns included a page-turning pattern and a search entrance replacement pattern. The results indicate that users tended to adopt browsing-related behaviors. /RS/ and /WS/ were repeated 239 times, accounting for 30.2% of all searching behavior except judgment behavior (choose answers and close webpage). 4.4. Affective and cognitive differences under different task contexts 4.4.1. Emotional/affective difference analysis Statistical analysis showed that the participants had high scores for the emotional/affective domain, with a mean value of 4.0, and task 2 had the lowest score among the three tasks (Table 8). The participants felt more confident in the pre-search than in the post-search, and they were satisfied with their search results, as evidenced by a score of 4.0. The participants had positive feelings when searching for online health information despite their less successful search performances. Moreover, task difficulty had a passive influence on user emotion. Repeated measures ANOVA was conducted to test the differences in the three task contexts and between the contexts. The Effect of Subjects Test and Parameter Estimation analysis, indicated that none of the differences were significant. Sound recordings of interviews for question 2 were coded using ATLAS.ti software, and results indicated that 75% of Table 7 Search behavior and codes.

3 Total

Question

M SD M SD M SD M SD

Code

Search behavior

Code

Initial search entrance Replace search entrance Initial search query Reconstruct search query Browse search result Click into webpage Scan webpage

SO SC QO QC RS WC WS

Click hyperlink in webpage Back to initial result page Repeat click webpage Back to previous page Result page down Choose answer Close webpage

HC ISR WD WR IRT CV DL

No. 2

No. 3

No. 4

No. 5

4.25 0.910 3.90 0.912 4.25 0.910 4.13 0.911

3.95 1.050 3.90 0.912 3.90 0.968 3.92 0.962

3.95 1.050 4.00 0.973 4.15 0.988 4.03 0.991

4.05 0.999 4.00 0.918 4.30 0.865 4.12 0.922

3.85 0.988 3.90 0.968 4.15 0.875 3.97 0.938

the participants said they “felt very well” during the experiment and 25% felt that the search tasks were “easy and pleasant”.

4.4.2. Cognitive difference analysis The scores for the cognitive domain were lower than those for the emotion domain (Table 9). With respect to task context, task 3 had the highest scores because it was about daily diet and healthcare, a topic with which the participants are quite familiar. With respect to the specific questions, questions 1 and 5 had high scores (M = 4.0), indicating the participants understood the task and the online health information very well. Questions 2 and 3 received lower scores (M = 3.3, 2.8 respectively), highlighting the participants' lack of Internet search knowledge and medical knowledge. To determine whether users' cognition differed within and between the three task contexts, repeated measures ANOVA was conducted (Table 10). The Effect of Subjects Test and Parameter Estimation analysis revealed that there were no significant differences among the three task contexts, but question 3 exhibited a significant difference in task context 1 and task context 2; question 4 had a significant difference in task context 1 and task context 2. These results indicate that medical professional knowledge had a significant difference among the various contexts. For example, task context 2 was about making decision regarding the treatment of diseases treatment, a task that required more medical knowledge. Thus, it was more difficult to find relevant information. This analysis also indicated that the difference in online information search knowledge between task contexts 1 and 3 was significant. From the D-value point perspective, task context 3 minus task context 1 (0.65) and task context 3 minus task context 2 (0.65) in question 2 were large though not significant. This suggests that the medical knowledge domain caused differences among different task contexts. Sound recordings of interviews for question 3 were coded using ATLAS.ti software (see Table 11). Many (85%) of the participants said their prior experience was “very helpful” in completing the experiment. From the participants' perspective, the health information search experience was the most beneficial, followed by task cognition and computer use. These participants relied heavily on computer/Internet skills, experience, and knowledge when they searched for online health information.

Table 9 Means and standard deviations of cognitive measures. Task context

Search behavior

No. 1

1 2 3 Total

Question

M SD M SD M SD M SD

No. 1

No. 2

No. 3

No. 4

No. 5

3.85 0.988 4.05 0.999 4.00 0.973 3.97 0.974

3.05 1.276 3.10 1.410 3.70 1.261 3.28 1.329

2.50 1.433 2.40 1.273 3.35 1.268 2.75 1.373

3.60 0.995 3.85 0.875 4.20 0.834 3.88 0.922

3.90 1.119 4.05 0.759 4.00 0.918 3.98 0.930

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279

277

Table 10 Results of parameter estimation similar to regression analysis based on different task contexts and questions. Dependent variable

Parameter

B

Standard deviation

t

Sig.

No. 3

Intercept [Task context = 1] [Task context = 2] [Task context = 3] Intercept [Task context = 1] [Task context = 2] [Task context = 3]

3.350 −0.850 −0.950 0a 4.200 −0.600 −0.350 0a

0.297 0.420 0.420 . 0.202 0.286 0.286 .

11.291 −2.026 −2.264 . 20.785 −2.100 −1.225 .

0.000 0.047 0.027 . 0.000 0.040 0.226 .

No. 4

National Institute on Aging and the National Library of Medicine of the National Institutes of Health (NIH) websites (Xie & Bugg, 2009).

5. Discussion 5.1. Online health information seeking behavioral patterns and characteristics of the elderly The analyses showed that when searching for online health information, elderly people exhibited three obvious behavioral patterns: reselecting from result pages, following hyperlinks, and query reformulation. They also preferred browsing-related behaviors. Compared with general group web searches, the elderly were not inclined to scroll down results pages to find more information, and 90% only viewed the first results page. The elderly also examined fewer web pages and preferred to follow hyperlinks within websites to find information. The findings suggest that elderly people relied on the support functions supplied by the search engine. This phenomenon could be explained by considering that elderly people have less search experience and declining cognitive abilities, which leads to a lack of confidence in their search ability. For example, when constructing queries, they were inclined to follow a drop-down list or a related search supplied by the search engine. When browsing and selecting information, they visited the pages that were ranked at the top on the results page and they were highly inclined to follow hyperlinks within websites. This was consistent with other research, which showed that the participants with less search expertise used more suggestions and saved more documents (Niu & Kelly, 2014) and that elderly people prefer to use links on the web pages because the links are more visible and seem to be less complicated than the search engines (Fairweather, 2008). Some participants asked our experiment administrators often how to correctly complete the search tasks during the search process. In general, the participants preferred to use search tools with which they were familiar and were hesitant to change. They were also reluctant to adjust their search queries. They tended to stay with their initial search strategy, rarely used advanced search strategies, and visited the websites with which they were the most familiar. Compared with elderly people's online HISBs in America (Huang et al., 2012), the elderly in China visit fewer special health websites during their daily lives, and when seeking online health information, most of them go directly to the web search engine, as few have mastered more advanced methods, such as health website searches. In contrast, the elderly in America use search strategies, such as browser built-in search boxes, browser address bar searches, web search engines and health website searches when seeking online health information. The reasons may be that China's elderly have lower health information literacy, and the government has not established and authorized special health websites for the elderly in China while the elderly in America can find high-quality health and medical information through the

Table 11 Analysis of helpful experience for the task search. Keywords

Term frequency

Keywords

Term frequency

Helpful Health information searching

17 9

Task cognition Computer use

8 6

5.2. Behavioral differences among different task contexts With respect to the participants' emotional/affective results, although the search task scores were not very high regardless of the task contexts, the participants expressed positive attitudes without significant difference among task contexts. Most users felt delight across the whole experiment, and some felt that it had enhanced their health-related knowledge and search skills. These findings are consistent with a previous study that found that emotional control had no significant effect on search performance (Kim, 2008) and despite older adults' low success rate in finding information, they expressed a high level of satisfaction regarding their search experience (Huang et al., 2012). Regarding the cognitive results, there were significant differences among different task contexts according to the repeated measures ANOVA tests. Task context 3 dealt with a healthcare information search that was the most common for elderly adults, and thus, the participants demonstrated high cognitive scores. Furthermore, the knowledge related to the different health information seeking task contexts had significant differences. Previous research on age differences related to web search ability has often concluded that elderly people are generally not good at using the Internet to find information and that their poorer performance is explained by a decline in their general cognitive abilities. Overall, when the participants sought health information in task context 1 (coping with a health-threatening situation), they performed the best because it was a problem-centered health information search. Task context 2 (participation and involvement in medical decision making), by contrast, required the participants to seek more health information to reduce uncertainty and decide on the best option. Thus, this was considered the most complicated task. In task context 3 (behavior change and preventive behavior), the participants were much more actively engaged in the search. This may be because seeking healthcare information such as diet and exercise is common in their daily lives. Through the interviews it was determined that the participants considered online health information to be beneficial with respect to their health condition, but they did not sufficiently use the Internet to solve health problems when they were undergoing a health/medical issue. 5.3. Factors influencing online health information seeking behavior Both education and Internet search familiarity significantly affected task performance (p b 0.05), while age, profession, health condition and frequency of computer use had no significant influence on user performance. Furthermore, elderly people were more dependent on their prior search experience for completing a difficult task, while people who were proficient in using the Internet were able to more easily complete the same task. However, with respect to the easier tasks, users with higher education performed better. The findings indicate that health condition, Internet search experience, and credibility of health information were the main factors influencing the decisions of the elderly to seek health information

278

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279

online actively. People with perceived poor health status had adequate Internet search experiences and more frequently sought health information online. High-quality health information is the key factor when elderly people make health decisions (Xie & Bugg, 2009). Slater and Zimmerman (2002) studied five different search engines and found that the percentage of search results based on non-scientifically approved health claims could be as high as 43% among certain search engines. Gao (2010) assessed 16 Chinese health websites and found the quality of these websites to be rather ordinary as the good and bad were intermingled. Thus, they suggested that users should be cautious when using online health information to make medical decisions. As current online health information is lacking in quality control in China, there was some added cognitive bias exhibited by the participants in this study regarding online health information. The elderly considered this factor to be a disadvantage regarding their use of online health information. 5.4. Limitations Several limitations must be considered when interpreting the results. First, the participants were recruited through a senior activity center at the Wuhan University, and over half of them were retired from the university. Thus, the sample, on average, was comprised of people with a higher education compared to the general elderly population in China. Second, the study was based on three health related online search tasks that required only minimal effort and time. This may have an effect on the participants' search behaviors due to their prior experiences. 6. Conclusion This study offers a unique in-depth look at health information searching behavior among Chinese elderly. The lack of computer and Internet skills, the lack of Internet search skills and the lack of medical knowledge were the primary challenges the participants encountered when seeking online health information. As previous research has reported, the elderly who possess more Internet experience are more likely to search for online health information (Chang & Im, 2014). Most of the elderly participants reported that what they had learned through computer-based health literacy intervention had positively affected their involvement in their own healthcare (Xie, 2012). This indicates that effectively educating the elderly population with respect to computer and Internet use and online health information access could improve the abilities of this special population to seek online health information. Given demographic trends, especially in China, investment in such programs would be well worth the effort. Acknowledgement This research is supported by the grant from National Program for Support of Top-notch Young Professionals in China. References Agusta, P. (2012). Elderly peoples' information behaviour: Accepting support from relative. Libri, 62(2), 135–144. Anker, A. E., Reinhart, A. M., & Feeley, T. H. (2011). Health information seeking: A review of measures and methods. Patient Education and Counseling, 82(3), 346–354. Blažun, H., Saranto, K., & Rissanen, S. (2012). Impact of computer training courses on reduction of loneliness of older people in Finland and Slovenia. Computers in Human Behavior, 28(4), 1202–1212. Chang, S. J., & Im, E. (2014). A path analysis of Internet health information seeking behaviors among older adults. Geriatric Nursing, 35(2), 137–141. Chaudhuri, S., Le, T., White, C., Thompson, H., & Demiris, G. (2013). Examining health information–seeking behaviors of older adults. CIN: Computers, Informatics, Nursing, 31(11), 547–553. Chin, J., Fu, W., & Kannampallil, T. (2009). Adaptive information search: Age-dependent interactions between cognitive profiles and strategies. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Boston, MA, April 4–9, 2009 (pp. 1683–1692). New York, NY: ACM.

China Internet Network Information Center (2014). China Internet network development statistic report. Retrieved from http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/ 201407/P020140721507223212132.pdf Curzon, P., Wilson, J., & Whitney, G. (2005). Successful strategies of older people for finding information. Interacting with Computers, 17(6), 660–671. Deng, X. Z. (2003). On Internet users' information behavior in searching and browsing. Journal of the China Society for Scientific and Technical Information, 22(6), 653–658. Fairweather, P. (2008). How older and younger adults differ in their approach to problem solving on a complex website. Proceedings of the International ACM SIGACCESS Conference on Computers and Accessibility, 10, 67–72. Gao, Q. (2010). Evaluation of Chinese health information websites. Chinese Journal of Medical Library and Information Science, 19(2), 40–44. Gollop, C. J. (1997). Health information-seeking behavior and older African American women. Bulletin of the Medical Library Association, 85(2), 141–146. Hanson, V. L. (2010). Influencing technology adoption by older adults. Interacting with Computers, 22(6), 502–509. Harris, R. (1997). Evaluating Internet research sources. Retrieved from http://www. virtualsalt.com/evalu8it.htm Hirakawa, Y., Kuzuya, M., Enoki, H., & Uemura, K. (2011). Information needs and sources of family caregivers of home elderly patients. Archives of Gerontology and Geriatrics, 52(2), 202–205. Huang, M., Hansen, D., & Xie, B. (2012). Older adults' online health information seeking behavior. (Chair) In J. -E. Mai (Ed.), Proceedings of the 2012 iConference, Toronto, Ontario, Canada, February 7–10 (pp. 338–345). Retrieved from http://dl.acm.org/ citation.cfm?id=2132220 Jansen, B. J., & Spink, A. (2006). How are we searching the World Wide Web? A comparison of nine search engine transaction logs. Information Processing & Management, 42, 248–263. Johnson, D. J. (2014). Health-related information seeking: Is it worth it? Information Processing & Management, 50, 708–717. Kim, K. (2008). Effects of emotion control and task on Web searching behavior. Information Processing & Management, 44(1), 373–385. Koch, S., & Hägglund, M. (2009). Health informatics and the delivery of care to older people. Maturitas, 63(3), 195–199. Lambert, S. D., & Loiselle, C. G. (2007). Health information seeking behavior. Qualitative Health Research, 17(8), 1006–1019. Li, Fan. (2013). 2012年全国60岁以上人口1.94亿 占总人口14.3% [2012: 194 million, 14.3%, of the population is aged 60 or over]. Retrieved from http://www.cncaprc.gov.cn/ contents/37/21268.html Ma, H., & Feng, J. L. (2005). User searching behavior on Chinese search engines based on query analysis. Journal of the China Society for Scientific and Technical Information, 24(6), 718–722. Niemelä, R., Huotari, M., & Kortelainen, T. (2012). Enactment and use of information and the media among older adults. Library & Information Science Research, 34, 212–219. Niu, X., & Kelly, D. (2014). The use of query suggestions during information search. Information Processing & Management, 50, 218–234. Sharit, J., Hernández, M. A., Czaja, S. J., & Pirolli, P. (2008). Investigating the roles of knowledge and cognitive abilities in older adult information seeking on the web. ACM Transactions on Computer-Human Interaction, 15(1), 1–25. Slater, M. D., & Zimmerman, D. E. (2002). Characteristics of health-related web sites identified by common internet portals. JAMA: The Journal of the American Medical Association, 288(3), 316. Slegers, K., Van Boxtel, M. P. J., & Jolles, J. (2012). Computer use in older adults: Determinants and the relationship with cognitive change over a 6 year episode. Computers in Human Behavior, 28(1), 1–10. Stoker, D., & Cooke, A. (1994). Evaluation of networked information sources. In A. Helal, & J. W. Weiss (Eds.), Information superhighway: The role of librarians, information scientists and intermediaries: Proceedings of the 17th International Essen Symposium, 24–27 October 1994 (pp. 287–312). Essen, Germany: Universitätsbibliothek Essen. Stronge, A. J., Rogers, W. A., & Fisk, A. D. (2006). Web-based information search and retrieval: Effects of strategy use and age on search success. Human Factors, 48(3), 434–446. Torp, S., Hanson, E., Hauge, S., Ulstein, I., & Magnusson, L. (2008). A pilot study of how information and communication technology may contribute to health promotion among elderly spousal carers in Norway. Health & Social Care in the Community, 16(1), 75–85. United Nations Population Division (2002). World population ageing: 1950–2050. Retrieved from http://www.un.org/esa/population/publications/worldageing19502050/index. htm Washington, K. T., Meadows, S. E., Elliott, S. G., & Koopman, R. J. (2011). Information needs of informal caregivers of older adults with chronic health conditions. Patient Education and Counseling, 83(1), 37–44. Wild, K. V., Mattek, N. C., Maxwell, S. A., Dodge, H. H., Jimison, H. B., & Kaye, J. A. (2012). Computer-related self-efficacy and anxiety in older adults with and without mild cognitive impairment. Alzheimer's & Dementia, 8(6), 544–552. Williamson, K. (1995). Older adults: Information, communication and telecommunications. (Unpublished doctoral dissertation) Monash, Australia: RMIT University. Wong, C. K. M., Yeung, D. Y., Ho, H. C. Y., Tse, K., & Lam, C. (2014). Chinese older adults' Internet use for health information. Journal of Applied Gerontology, 33(3), 316–335. Xiao, N., Sharman, R., Rao, H. R., & Upadhyaya, S. (2014). Factors influencing online health information search: An empirical analysis of a national cancer-related survey. Decision Support Systems, 57, 417–427. Xie, B. (2011a). Experimenting on the impact of learning methods and information presentation channels on older adults' e-health literacy. Journal of the American Society for Information Science & Technology, 62, 1797–1807.

D. Wu, Y. Li / Library & Information Science Research 38 (2016) 272–279 Xie, B. (2011b). Older adults, e-health literacy, and collaborative learning: An experimental study. Journal of the American Society for Information Science & Technology, 62, 933–946. Xie, B. (2012). Improving older adults' e-health literacy through computer training using NIH online resources. Library & Information Science Research, 34, 63–71. Xie, B., & Bugg, J. M. (2009). Public library computer training for older adults to access high-quality Internet health information. Library & Information Science Research, 31, 155–162. Xie, B., Wang, M., Feldman, R., & Zhou, L. (2010). Health information and decision-making preferences in the internet age: A pilot study using the health information wants (HIW) questionnaire. ACM International Conference on Health Informatics, 1 (pp. 610–619). Zamarian, L., Benke, T., Buchler, M., Wenter, J., & Delazer, M. (2010). Information about medications may cause misunderstanding in older adults with cognitive impairment. Journal of the Neurological Sciences, 298(1–2), 46–51.

279

Dan Wu is a professor in School of Information Management, Wuhan University, China, and associate chair of the Department of Library Science. She earned her PhD in library and information science in 2008 from Peking University. Her research focuses on information retrieval, user behavior, and information organization. She has published in many journals, including ASLIB Proceedings, Electronic Library, Information Processing & Management, Journal of Information Science, Library Hi Tech, Online Information Review, and Program: Electronic Library and Information Systems, among others. She has also received many research grants from institutions such as the National Social Science Foundation of China. Yizhe Li is a master student's in School of Information Management, Wuhan University, China. Her research interests are in the areas of information seeking behavior.