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Since the rise of the internet, online health information seeking has become a worldwide phenomenon. However, health and health communication are inherently culture bound. A data-driven cross-country comparison enables us to better understand how cultural factors moderate the association between individual-level determinants and online health information seeking.
The objective of the study was to examine similarities and differences in determinants of internet cancer information seeking between the US and Chinese general public (excluding cancer patients and survivors) under the framework of a behavioral model of health services use.
This study used Health Information National Trends Survey (HINTS) 2017 (US data) and HINTS-China 2017 data to answer the research question. It focused on people with no cancer history and with internet access. For the HINTS 2017, the sample size was 2153; for the HINTS-China 2017, the sample size was 2358. To compare China and the United States, the researchers selected the same set of study variables for each dataset. Under the framework of the behavioral model of health services use, these predictors were predisposing factors, enabling factors, and need factors.
In terms of the predisposing factors, a higher age, college degree or above, being currently unemployed, and having a family history of cancer were associated with internet cancer information seeking for the Chinese respondents; none of these factors were related to information seeking for the US respondents, although a lower age was associated with information seeking. Regarding the enabling conditions, lower trust in family members and friends as reliable information sources was the only factor associated with information seeking for the Chinese respondents, while no enabling factor was related to information seeking for the US respondents. Regarding the need factors, perceived health status was not related to information seeking for the Chinese respondents, while perception of poorer health condition was related to information seeking for the US respondents. Higher cancer fear was related to information seeking for both groups, but the magnitude of association was smaller for the Chinese respondents than for the US respondents.
Overall, under the framework of the behavioral model of health services use, the results based on multivariate logistic regression reveal clear patterns of cross-country/cultural differences in the factors associated with internet cancer information seeking behaviors: predisposing characteristics and enabling conditions are more important in China, while perceived needs are more significant in the US. Such differences might reflect possible US-China differences in job environment (eg, job pressure) and culture (individualism vs collectivism and family structure).
A milestone in monitoring the US public’s access to and use of health information is the Health Information National Trends Survey (HINTS) initiated by the National Cancer Institute [
To fulfill the mission of the international expansion of the HINTS program, this study used HINTS and HINTS-China data collected in 2017 [
We not only reviewed studies on cancer information seeking on the internet, which are limited in number, but also reviewed research concerning generalized online health information seeking to present a more complete picture of the factors that potentially play a role. Regardless of the theoretical models used, the predictors of major concern in existing studies include mainly demographics [
The effects of demographic and structural variables are rather stable. According to HINTS data, Americans who refer to the internet for health information are younger than those who do not [
Most studies on generic health information seeking concentrate on people’s perceptions of risk, personal health status, self-efficacy, media trust, social support, and satisfaction with caregivers. Those with higher levels of perceived risks and fears and lower levels of confidence about their health status are more likely to search for health information on the internet [
We used the behavioral model of health services as the theoretical framework to organize the predictor variables of internet cancer information seeking, as the model evaluates the extent to which 3 sets of predictor variables (predisposing factors, enabling factors, and need factors) influence people’s use of health services [
This study focused on how individual-level predisposing, enabling, and need factors are associated with information seeking and how their relationships vary as a function of the country group. Predisposing characteristics were age; gender; education; ethnicity; the status of a person in his or her community; general health attitudes, values, and knowledge; and genetic characteristics [
Health communication scholars have paid increasing attention to internet health information seeking in the US and Europe, but little is known about China, where more than 4 million patients were diagnosed with cancer in 2015 [
China and the US vary in issues related to cancer control. First, the types of common cancers in China differ from those in the US. In China, lung cancer has the highest incidence rate [
Chinese culture differs from US culture. China is collectivistic, while the US is more individualistic [
Although the US has a longer history of internet commercialization, China has recently begun to take the lead in the commercialization of new media applications, which have penetrated every social stratum [
On the basis of the preceding discussion, this study plans to answer the following research question:
How do China and the US differ in the associations between predisposing/enabling/need factors and internet cancer information seeking behaviors among people without a history of cancer?
This study used HINTS 2017 (US data) and HINTS-China 2017 data to answer the research question. HINTS 2017 had a final sample size of 3285. Of the respondents, 2756 had no history of cancer (current patients or survivors); thus, these respondents were the focus of the study.
HINTS-China is an effort jointly launched by the Chinese Ministry of Health Center for Health Education, Renmin University of China, the Chinese National Cancer Center, and George Mason University and was recently joined by Beijing Normal University [
Because online health information seeking is directly related to physical access to the internet, this study excluded those without internet access from the final model because it is obvious that those without internet access cannot search for cancer information on the web. The US sample contained 750 respondents who had never accessed the internet, and the Chinese sample had 723. Thus, the sample sizes of cancer-free populations with internet access were 2,153 and 2,358 for the US and China, respectively.
To compare China and the US, the researchers selected the same set of study variables as predictors in HINTS 2017 and HINTS-China 2017. Additionally, there were slight differences in the measurement scales of these predictors between countries, so recoding was conducted to facilitate comparison. Measurements of the predisposing, enabling, need, and outcome variables were as follows.
Gender was recoded as female, with 1 = female and 0 = male. Educational attainment for the US and China was converted from 7-point and 6-point scales, respectively, to 4-point scales, with 1 = “Less than high school,” 2 = “High school,” 3 = “Vocational school,” and 4 = “College and above.” Marital status for both countries was recoded as “Currently married,” with 1 = “Yes” and 0 = “No.” Similarly, current occupational status was converted to “Currently employed,” with 1= “Yes” and 0 = “No.” Current smoking status was assessed by 2 items, which were the same in both countries’ surveys. The first item was a filter question, “Have you smoked at least 100 cigarettes in your entire life?,” with 2 choices, (1) “Yes” and (2) “No.” Only those who answered “Yes” were presented with the second item, “How often do you now smoke cigarettes?,” with 3 choices (1) “Every day,” (2) “Some days,” and (3) “Not at all.” To combine the items into a single item, the researchers counted “No” for the first item as “Not at all” for the second item. BMI was calculated from height and weight using the standard formula. Both the Chinese and US surveys collected height and weight data. Family cancer history was measured using one item in both surveys. The US survey had 3 choices, (1) “Yes,” (2) “No,” and (3) “Not sure.” The Chinese version broke “Yes” into “Close relatives” and “Distant relatives.” They were recoded as a single variable, with 1 = “Yes” (including “Close relatives” and “Distant relatives”) and 0 = “No or not sure.”
Household annual income was originally measured at the interval level in China, which differs from the categorical income range used in HINTS 2017. Income in the Chinese version was recoded as a categorical variable in 4 quartiles (from “50,000 RMB yuan and below” to “150,001 RMB yuan and above” with a 50,000-RMB interval). Income in the US version, with 9 original categories, was also recoded in quartiles: “$0 to $19,999,” “$20,000 to $49,999,” “$50,000 to $99,999,” and “$100,000 or more.”
HINTS in both countries measured people’s trust in social institutions and information channels as reliable health information sources. However, the Chinese and US surveys differed slightly in the design of the attributes of each question item. First, the US survey measured only people’s trust in the generic internet, while the Chinese survey measured people’s trust in 8 typical internet applications. Then, the researchers averaged the trust score for the 8 internet applications to create an overall score for trust in the internet for the Chinese data. Second, the US survey used a single item to measure people’s trust in family or friends, while the Chinese survey measured them separately. Thus, the researchers averaged them to create a single score. Third, the US survey measured people’s trust in newspapers or magazines, while the Chinese survey measured them separately. The researchers created a new item using the mean score. Fourth, the US survey measured trust using a 4-point scale, with 1 = “Not at all” and 4 = “A lot.” In contrast, the Chinese survey measured trust using a 5-point scale, with 1 = “Very untrustworthy” and 5 = “Very trustworthy.” The 4-point scale used in the US survey was converted numerically into a 5-point scale to make the comparison more straightforward. Taking into account the goal of the study, the researchers categorized trust variables into 5 groups. The first category was trust in social institutions, including government agencies, religious organizations, and charities, which were combined into an additive index. The second category was trust in traditional media channels, including print media, television, and radio, which were combined into an additive index (Cronbach alpha for US=.77; Cronbach alpha for China=.85). Trust in the internet, doctors, and family members and friends were used as they were in the following logistic regression analysis.
Self-confidence about personal health or perceived health status was measured on a 5-point scale, with 1 = Poor and 5 = Excellent. The scales for both countries were the same.
Both surveys measured fatalism about cancer, which was assessed by 4 items such as “It seems like everything causes cancer” and “When I think about cancer, I automatically think about death.” The US survey used a 4-point scale, with 1 = “Strongly agree” and 4 = “Strongly disagree.” The scale in the Chinese survey was slightly different, with 1 = “Strongly disagree” and 5 = “Strongly agree.” The scale in the US survey was reversed and numerically converted into a 5-point scale, thus allowing the researchers to more easily compare the magnitudes of the coefficients. They were added to an index (Cronbach alpha for US=.63; Cronbach alpha for China=.75).
Fear of cancer was assessed using a single item on a 5-point scale, with 1= “Not at all” and 5= “Extremely.” The surveys for the two countries were identical.
Perceived cancer risk was assessed by asking the respondents, “How likely are you to get cancer in your lifetime?” with 1 = “Very unlikely” and 5 = “Very likely.” The surveys for the two countries were identical.
Online cancer information seeking was the outcome variable. In HINTS 2017, online cancer information seeking was binary, with 1 = “Yes” and 0 = “No,” while HINTS-China 2017 measured it using a 4-point scale. To make them comparable, the researchers recoded “Never” and “Rarely” as “No,” and converted “Often” and “Sometimes” to “Yes.”
In the first step, the researchers presented descriptive statistics of all the variables under examination. In the second step, the researchers used multivariate logistic regression to explore US-China differences in the associations between the 3 categories of the predictor variables and internet cancer information seeking (
The US HINTS sample had missing values in most variables selected for comparison, and the listwise approach would have resulted in the loss of 569 observations (over 25% of the US sample cases). To maximize the number of observations used in the analysis, this study used the R package MICE (Multivariate Imputation via Chained Equations) to impute the missing values. Specifically, the researchers applied the CART (classification and regression trees) algorithm for categorical variables and PMM (predictive mean matching) for numerical variables [
Odds ratio of logistic regressions of predisposing, enabling, and need variables of internet cancer information seeking.
Variables | Model 1 odds ratio (95% CI) | Model 2 odds ratio (95% CI) |
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Female (vs male) | 1.07 (0.89-1.28) | 1.11 (0.83-1.49) |
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Age | 0.99 (0.99-1.00)* | 1.02 (1.00-1.03)* |
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High school | 0.88 (0.62-1.24) | 1.08 (0.72-1.62) |
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Vocational school | 1.23 (0.87-1.73) | 1.58 (1.03-2.42) |
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College and above | 1.53 (1.08-2.18)* | 2.35 (1.50-3.68)* |
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Currently married (vs not) | 1.15 (0.95-1.39) | 0.97 (0.69-1.36) |
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Currently employed (vs not) | 0.80 (0.66-0.98)* | 0.66 (0.50-0.89)* |
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BMI | 0.99 (0.97-1.01) | 0.98 (0.94-1.03) |
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Family cancer history (vs not) | 1.51 (1.25-1.82)* | 2.23 (1.73-2.88)* |
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Some days | 1.04 (0.61-1.78) | 0.54 (0.20-1.46) |
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Not at all | 1.12 (0.85-1.48) | 0.94 (0.64-1.39) |
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$20,000 to $49,999 (50,001 to 100,000 RMB) | 0.74 (0.58-0.94)* | 0.70 (0.51-0.96)* |
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$50,000 to $99,999 (100,001 to 150,000 RMB) | 0.65 (0.49-0.86)* | 0.65 (0.43-0.99)* |
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$100,000 or more (150,001 RMB and above) | 0.76 (0.57-1.02) | 0.71 (0.48-1.06) |
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Social institutions | 0.99 (0.95-1.04) | 0.97 (0.90-1.04) |
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Traditional media | 1.02 (0.98-1.07) | 1.01 (0.95-1.08) |
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Internet | 1.18 (1.05-1.32)* | 1.43 (1.13-1.80)* |
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Doctors | 0.93 (0.84-1.04) | 0.96 (0.81-1.13) |
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Family and friends | 0.87 (0.78-0.97)* | 0.71 (0.59-0.86)* |
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Perceived health status | 0.83 (0.75-0.93)* | 0.94 (0.79-1.11) |
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Cancer fatalism | 1.02 (0.99-1.05) | 1.03 (0.99-1.08) |
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Cancer risk | 1.02 (0.92-1.14) | 0.97 (0.82-1.16) |
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Cancer fear | 1.45 (1.33-1.58)* | 1.28 (1.12-1.47)* |
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US (vs China) | 0.78 (0.58-1.06) | 2.03 (0.22-18.84) |
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US X Female | N/Aa | 0.96 (0.66-1.41) |
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US X Age | N/A | 0.97 (0.95-0.99)* |
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US X High school | N/A | 0.49 (0.21-1.11) |
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US X Vocational school | N/A | 0.54 (0.24-1.18) |
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US X College and above | N/A | 0.40 (0.18-0.90)* |
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US X Currently married | N/A | 1.19 (0.77-1.82) |
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US X Currently employed | N/A | 1.43 (0.95-2.14) |
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US X BMI | N/A | 1.00 (0.96-1.05) |
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US X Some days | N/A | 2.98 (0.87-1.16) |
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US X Not at all | N/A | 1.57 (0.87-2.85) |
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US X Family cancer history | N/A | 0.42 (0.29-0.61)* |
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US X $20,000 to $49,999 (50,001 to 100,000 RMB) | N/A | 1.15 (0.68-1.93) |
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US X $50,000 to $99,999 (100,001 RMB to 150,000 RMB) | N/A | 1.09 (0.59-1.99) |
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US X $100,000 or more (150,001 RMB and above) | N/A | 1.17 (0.63-2.18) |
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US X Social institutions | N/A | 1.03 (0.94-1.13) |
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US X Traditional media | N/A | 1.00 (0.92-1.09) |
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US X Internet | N/A | 0.80 (0.61-1.04) |
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US X Doctors | N/A | 0.99 (0.79-1.25) |
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US X Family and friends | N/A | 1.36 (1.08-1.73)* |
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US X Perceived health status | N/A | 0.81 (0.65-1.00)* |
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US X Cancer fatalism | N/A | 0.96 (0.90-1.02) |
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US X Cancer risk | N/A | 1.16 (0.92-1.45) |
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US X Cancer fear | N/A | 1.24 (1.03-1.49)* |
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aN/A: Not applicable.
*Asterisks represent the coefficients that are statistically significant at the
As seen in
Regarding the other selected variables, the Chinese sample had higher perceived health status, while the US sample had slightly higher cancer risk perception and fear of cancer. The cancer fatalism scores for both did not differ much. The US respondents reported many more relatives diagnosed with cancers than their Chinese counterparts. The US respondents reported higher trust in social institutions, the internet, and doctors, while the Chinese respondents had more trust in family members/friends and traditional media.
Descriptive statistics of dependent and independent variables for cancer-free respondents of the Health Information National Trends Survey (HINTS) 2017 and the HINTS-China 2017.
Variables | Categories or scales | US (N=2756) | China (N=3080) | |
Online cancer information seeking | Yes, n (%) | 411 (14.90%) | 322 (11.70%) | |
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Female | Yes, n (%) | 1607 (58.30%) | 1686 (61.17%) |
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Age | Years, mean (SD) | 54.4 (16.1) | 35.0 (11.5) |
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Education | Less than high school, n (%) | 190 (6.90%) | 494 (17.92%) |
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High school, n (%) | 507 (18.40%) | 744 (27.01%) | |
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Vocational school, n (%) | 813 (29.50%) | 719 (26.10%) | |
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College and above, n (%) | 1246 (45.20%) | 798 (28.96%) | |
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Currently married | Yes, n (%) | 1428 (51.80%) | 1944 (70.55%) |
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Currently employed | Yes, n (%) | 1499 (54.40%) | 2065 (74.94%) |
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BMI | kg/m2, mean (SD) | 28.45 (6.46) | 22.6 (3.17) |
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Smoking status | Every day, n (%) | 282 (10.25%) | 421 (15.26%) |
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Some days, n (%) | 104 (3.78%) | 65 (2.37%) | |
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Not at all, n (%) | 2370 (85.98%) | 2270 (82.37%) | |
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Family cancer history | Yes, n (%) | 1915 (69.47%) | 620 (22.50%) |
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Annual family income | $0 to $19,999 / 50,000 RMB and below, n (%) | 511 (18.55%) | 757 (27.47%) |
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$20,000 to $49,999 / 100,001 RMB to 150,000 RMB, n (%) | 752 (27.27%) | 1081 (39.22%) | |
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$50,000 to $99,999 / 100,001 RMB to 150,000 RMB, n (%) | 840 (30.47%) | 400 (14.52%) | |
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$100,000 or more / 150,001 RMB and above, n (%) | 653 (23.71%) | 518 (18.79%) | |
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Trust in social institutions | 3 items; 3-15, mean (SD) | 8.72 (2.66) | 8.49 (2.33) |
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Trust in traditional media | 3 items; 3-15, mean (SD) | 7.54 (2.62) | 8.78 (2.66) |
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Trust in internet | 1-5, mean (SD) | 3.32 (1.07) | 2.72 (0.75) |
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Trust in doctors | 1-5, mean (SD) | 4.51 (0.83) | 3.87 (0.96) |
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Trust in family and friends | 1-5, mean (SD) | 3.10 (0.95) | 3.85 (0.81) |
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Perceived health status | 1-5, mean (SD) | 3.41 (0.95) | 3.98 (0.78) |
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Cancer fatalism | 4 items; 4-20, mean (SD) | 12.48 (3.34) | 12.30 (3.19) |
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Cancer risk | 1-5, mean (SD) | 3.06 (0.96) | 2.24 (0.86) |
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Cancer fear | 1-5, mean (SD) | 2.51 (1.10) | 2.18 (1.01) |
The results of Model 1 suggest that younger people (OR=0.99, 95% CI 0.99-1.00) who had obtained at least a college degree (OR=1.53, 95% CI 1.08-2.18), were currently not employed (OR=0.80, 95% CI 0.66-0.98), and had a family history of cancer (OR=1.51, 95% CI 1.25-1.82) were more likely to search for cancer information on the internet. In terms of enabling conditions, those who earned a moderate income (OR=0.74, 95% CI 0.58-0.94; OR=0.65, 95% CI 0.49-0.86), trusted the internet as a reliable source of information (OR=1.18, 95% CI 1.05-1.32), and distrusted family members and friends as reliable information sources (OR=0.87, 95% CI 0.78-0.97) were more likely to search the internet for cancer information. In addition, those who perceived themselves to be in poor health (OR=0.83, 95% CI to 0.75-0.93) and feared cancer (OR=1.45, 95% CI 1.33-1.58) were more likely to search the internet for cancer information.
According to the results of the tests of interaction terms in Model 2, as shown in
On the basis of the significance tests of the interaction terms, the researchers further calculated conditional odds ratios of predictor variables for each country group (
According to
The odds ratios for two need variables were statistically significant. Perceived health status was associated with internet cancer information seeking only in the US sample (OR=0.76, 95% CI 0.65-0.87]), not for the Chinese sample (OR=.94, 95% CI 0.79-1.11). Cancer fear was related to the dependent variable for both samples. However, the conditional odds ratio for the US sample (OR=1.59, 95% CI 1.41-1.79) was larger than that for the Chinese sample (OR=1.28, 95% CI 1.12-1.47), and
Bivariate and conditional odds ratios (ORs) for logistic regression of predisposing, enabling, and need variables of internet cancer information seeking.
Variable | US | China | ||||
Bivariate OR (95% CI) | Conditional OR (95% CI) | Bivariate OR (95% CI) | Conditional OR (95% CI) | |||
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Female (vs male) | 1.18 (0.93-1.49) | 1.07 (0.83-1.37) | 1.17 (0.92-1.47) | 1.11 (0.83-1.49) | ||
Age | 0.99 (0.98-0.99)* | 0.99 (0.98-1.00)* | 1.01 (1.00-1.02)* | 1.02 (1.00-1.03)* | ||
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High school | 0.46 (0.23-0.90)* | 0.53 (0.26-1.08) | 1.01 (0.69-1.48) | 1.08 (0.72-1.62) | ||
Vocational school | 0.71 (0.38-1.31) | 0.85 (0.44-1.65) | 1.09 (0.75-1.6) | 1.58 (1.03-2.42)* | ||
College and above | 0.75 (0.41-1.35) | 0.94 (0.48-1.84) | 1.53 (1.06-2.2)* | 2.35 (1.50-3.68)* | ||
Currently married (vs not) | 1.03 (0.82-1.30) | 1.15 (0.88-1.49) | 0.89 (0.70-1.13) | 0.97 (0.69-1.36) | ||
Currently employed (vs not) | 1.07 (0.84-1.35) | 0.95 (0.71-1.25) | 0.62 (0.49-0.80)* | 0.66 (0.50-0.89)* | ||
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Some days | 1.86 (0.94-3.67) | 1.6 (0.78-3.28) | 0.57 (0.22-1.49) | 0.54 (0.20-1.46) | ||
Not at all | 1.19 (0.78-1.81) | 1.48 (0.94-2.34) | 1.14 (0.83-1.56) | 0.94 (0.64-1.39) | ||
Family cancer history (vs not) | 1.05 (0.82-1.35) | 0.94 (0.72-1.23) | 2.72 (2.14-3.44)* | 2.23 (1.73-2.88)* | ||
BMI | 1.00 (0.98-1.01) | 0.99 (0.97-1.01) | 0.98 (0.94-1.01) | 0.98 (0.94-1.03) | ||
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$20,000 to $49,999 (50,001 to 100,000 RMB) | 0.78 (0.53-1.13) | 0.81 (0.53-1.22) | 0.79 (0.59-1.05) | 0.70 (0.51-0.96)* | ||
$50,000 to $99,999 (100,001 to 150,000 RMB) | 0.66 (0.45-0.94)* | 0.71 (0.46-1.09) | 0.72 (0.49-1.05) | 0.65 (0.43-0.99)* | ||
$100,000 or more (150,001 RMB and above) | 0.81 (0.56-1.17) | 0.83 (0.52-1.34) | 0.93 (0.66-1.31) | 0.71 (0.48-1.06) | ||
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Social institutions | 1.02 (0.96-1.08) | 1.00 (0.94-1.06) | 1.01 (0.96-1.07) | .97 (0.90-1.04) | ||
Traditional media | 1.02 (0.96-1.09) | 1.01 (0.95-1.07) | 1.04 (0.99-1.09) | 1.01 (0.95-1.08) | ||
Internet | 1.17 (0.99-1.38) | 1.14 (0.99-1.31) | 1.25 (1.06-1.47)* | 1.43 (1.13-1.8)* | ||
Doctors | 0.97 (0.79-1.19) | 0.95 (0.80-1.12) | 0.94 (0.82-1.07) | 0.96 (0.81-1.13) | ||
Family and friends | 0.96 (0.81-1.13) | 0.97 (0.84-1.11) | 0.73 (0.62-0.85)* | 0.71 (0.59-0.86)* | ||
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Perceived health status | 0.77 (0.68-0.87)* | 0.76 (0.65-0.87)* | 0.75 (0.65-0.87)* | 0.94 (0.79-1.11) | ||
Cancer fatalism | 1.05 (1.01-1.1)* | 0.99 (0.95-1.03) | 1.04 (1.00-1.08)* | 1.03 (0.99-1.08) | ||
Cancer risk | 1.35 (1.19-1.54)* | 1.13 (0.98-1.29) | 1.25 (1.09-1.43)* | 0.97 (0.82-1.16) | ||
Cancer fear | 1.66 (1.49-1.85)* | 1.59 (1.41-1.79)* | 1.38 (1.24-1.54)* | 1.28 (1.12-1.47)* |
*Asterisks represent the coefficients that are statistically significant at the
This study used HINTS 2017 of the US and HINTS-China 2017 data to compare the associations between factors related to online cancer information seeking. Under the framework of the behavioral model of health services use, the results reveal clear patterns of cross-country differences: the Chinese respondents’ internet cancer information seeking was associated more with the predisposing and enabling variables, while the US respondents’ information seeking was related more to the need variables. Specifically, the internet cancer information-seeking behavior of the Chinese respondents was associated with the predisposing characteristics educational attainment, employment status, and family cancer history, while that of the US respondents was not related to any of the predisposing characteristics. For enabling conditions, the internet cancer information seeking of the Chinese respondents was related to trust in family and friends as reliable health information sources, while that of the US respondents was not correlated with any enabling factor. For need variables, the internet cancer information seeking of the Chinese respondents was not related to perceived health status, while that of the US respondents was negatively associated with perceived health condition, and the magnitude of the association between cancer fear and internet cancer information seeking was stronger for the US respondents than for the Chinese respondents. These cross-country differences reveal that the extent to which predisposing characteristics, enabling conditions, and perceived needs are related to internet cancer information seeking is possibly subject to the nature of a country’s cultural and structural characteristics. The importance of predisposing characteristics and enabling conditions outweighs perceived needs in countries where, for example, the culture is more collectivistic or information channel credibility is of greater concern. The perceived needs of individuals may play a larger role in more individualistic cultures.
Conventional wisdom holds that people with high socioeconomic status have high internet and health literacy, which in turn allows them to use new technologies to satisfy their cognitive and emotional needs. However, the association between being employed and information seeking suggests that working overtime and having a more active social life, by-products of being employed and financially secure in China, may limit the available time for online cancer information seeking. China has a fairly strong family-oriented culture [
Additionally, the Chinese online cancer information seekers trusted family and friends as reliable information sources more than nonseekers did, which did not apply to the US respondents. This shows that when family members are trusted as sources of information, they can displace the internet as cancer information sources in China. Although
The US-China differences in the associations of need factors, such as perceived personal health status and cancer fear, might reveal individualistic versus collectivistic cultural influences. Perceived personal health status was associated with online cancer information seeking only for the US respondents and not for the Chinese respondents. Previous studies have suggested that people in individualistic cultures tend to pay more attention to personal wellbeing [
In this study, differences in the associations of age and educational attainment may be related to the composition of the sample respondents. For the Americans, the higher the age, the less likely they were to search for cancer information on the web; for the Chinese, the opposite was true. As
This study is not without limitations. First, as it tried to select the exact same set of variables to be compared, it excluded several important variables related to health cognition because either the Chinese or US survey did not measure them. Although the researchers made the utmost efforts to unify the measures of all the variables used in the analysis, some, such as trust in social institutions and information channels, were not identically designed, which may have impacted the results to some extent. This study is based on secondary data from HINTS. Explanations of cross-country/cultural differences involve speculation based on theoretical and practical reasoning, so future researchers are advised to further explore the precise mechanism of how culture influences internet cancer information seeking by measuring antecedents to variables such as cancer fear.
The study has other limitations as well. The researchers used two cross-sectional surveys, so causal relationships cannot be truly established. The data used in this study were only from the HINTS, and cross-country/cultural differences could be confirmed only with more replications based on additional sources of data. In this study, all the measures were self-reported, and in this context, cultural differences in response style are likely to occur, or respondents may differ in their interpretation of the questions.
Despite these limitations, this study makes unique theoretical and practical contributions to the literature and practice. By comparing HINTS 2017 and HINTS-China 2017 data, this study found that predisposing characteristics and enabling conditions were more associated with internet cancer information seeking for the Chinese sample and that need factors were more related to information seeking for the US respondents. Such differences might reflect possible US-China differences in job environment (eg, job pressure) and culture (individualism vs collectivism and family structure). Future health communication researchers may consider incorporating cultural values into the study design when possible. Additionally, future studies in non-Western countries may consider focusing more on predisposing factors such as structural characteristics and enabling factors related to family structure. Because international charities and health nonprofits actively promote health causes in Asian and African countries, practitioners should consider not only being culturally sensitive but also placing culture at the center of their campaigns.
Health Information National Trends Survey
This research was supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China [grant ID: 15XNQ045].
None declared.