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The Internet is an important tool to deliver health behavior interventions, yet little is known about Internet access and use of health-related information, or support, by the intended intervention recipients.
Our aim was to evaluate whether health-related Internet use differed as a function of common health-risk behaviors (excessive alcohol consumption, smoking, low fruit/vegetable intake, inactive/sedentary lifestyle, unprotected sun exposure, or obesity).
Sociodemographic, health behavior characteristics, and information on Internet access and use were assessed in the nationally representative US Health Information National Trends Survey (HINTS) 4. Data from 3911 participants collated in 2011/12 were included.
Of the 78.2% (95% CI 76.1-80.1) of participants who had ever accessed the Internet, approximately three-quarters (78.2%, 95% CI 75.4-80.7) had obtained health-related information online last year. About half had used the Internet as the first source of health-related information (47.8%, 95% CI 44.8-50.7) or to access behavioral support (56.9%, 95% CI 53.7-60.0) in the last year. Adjusting for sociodemographic determinants of going online (being younger, white, female, with at least college education) revealed few differences in Internet access and use between health-risk behaviors. Participants with inadequate sun protection were less likely to access the Internet (OR 0.59, 95% CI 0.04-0.88) and those with low fruit/vegetable intake were less likely to have gone online to obtain health-related information last year (OR 0.60, 95% CI 0.45-0.80). Smokers in particular were likely to use the Internet to obtain behavioral support (OR 1.90, 95% CI 1.35-2.68).
Internet access and use to obtain health-related information and support is widespread and mostly independent of engagement in various health-risk behaviors. However, those with low fruit/vegetable intake or inadequate sun-protective behaviors may be more difficult to reach with Internet-based interventions. In addition, when developing online health promotions, relevant sociodemographic determinants of Internet use need to be targeted to maximize their impact.
Over the last decade, global access to the Internet has dramatically increased such that over 80% of the US population now uses the Internet [
Health interventions try to modify health-risk behaviors, which can be defined as actions that cause preventable morbidity and mortality. Tobacco smoking and overeating alone contribute to 8 million avoidable global deaths every year [
It is encouraging that Internet-based interventions, as a novel way to engage those who persist with health-risk behaviors, have been shown to have a small but clinically significant effect on promoting health behavior change [
However, despite the recent proliferation of eHealth, relatively little is known about the actual reach of Internet interventions [
It is possible that the Internet and Internet-based support are accessed either more or less frequently by those who are the intended target. If the former is the case, then this further adds to the potential of the Internet as a preferred medium to deliver health interventions. Yet, if the latter is the case, then Internet-based interventions may not be as beneficial as assumed and may have suboptimal real-world effectiveness at population level despite proven efficacy in clinical trials. This would require that dissemination channels for Internet-based interventions be changed, for instance, by making intended users aware of such interventions through their health care providers or by using targeted marketing. Additionally, knowing more about what kind of person does or does not engage with eHealth can inform intervention design, for example, in terms of providing adequate or enhanced functionality and effective tailoring based on user characteristics to encourage those who are currently not making the most of the Internet to use this resource to improve their health [
Data are therefore needed on access to and reach of Internet-based interventions as well as sociodemographic determinants of use to aid development and optimization of online material. As North America has one of the highest rates of penetration of Internet access [
1. What is the prevalence of general Internet use, and does this differ as a function of sociodemographic characteristics and engagement in specific health-risk behaviors?
2. What is the prevalence of Internet use to access health-related information and support online, and does this differ as a function of sociodemographic characteristics and engagement in specific health-risk behaviors?
Data come from Health Information National Trends Survey (HINTS) 4 (Cycle 1), a national probability survey of adults aged 18 or older in the civilian non-institutionalized population of the United States that assesses usage and trends in health information access and understanding (
HINTS screenshot.
Age, employment status (employed; yes/no), marital status (married; yes/no), ethnicity (white; yes/no), and educational attainment (college education or above; yes/no) were recorded. General health was assessed with an established single item asking participants to rate their health as “excellent”, “very good”, “good”, “fair”, or “poor” [
Alcohol consumption was determined by asking on how many days per week during the last 30 days participants had at least one drink of an alcoholic beverage (defined as a standard measure of alcohol in beer, wine, wine cooler, cocktail, or other liquor). Participants were also asked how many drinks they consumed on the days they did drink. US guidelines for alcohol consumption state that moderate alcohol consumption constitutes an average of one drink per day for women and two drinks per day for men [
Cigarette smoking was assessed by asking participants whether they had smoked at least 100 cigarettes in their lifetime, and if so, whether they smoked every day, some days, or not at all nowadays. This information was used to calculate a binary variable reflecting any current (daily or non-daily) cigarette use (current smoking; yes/no).
Diet was assessed by asking participants how many cups of fruit (including 100% pure fruit juice) or vegetables (including 100% pure vegetable juice) they consumed each day. Examples of what a cup means (eg, one large banana, 12 baby carrots) were provided. Based on standard guidelines recommending at least 5 servings (roughly equivalent to 2.5 cups) of fruit and vegetables per day [
Physical activity was determined by asking on how many days a week participants engaged in bouts of exercise of at least moderate intensity, and how long a typical bout lasted. In addition participants were asked how many hours per day on average they sat and watched TV or movies, surfed the Web, or played computer games (excluding active gaming). US guidelines recommend at least 30 minutes of moderate physical activity on 5 days a week [
Sun-protective behavior was assessed by asking participants how many times they had used a tanning bed or booth in the last year, as well as whether and how often they use sunscreen when outside for more than one hour on a sunny day (always, often, sometimes, rarely, never; do not go out on sunny days). Following sun-safe guidelines that recommend minimizing exposure to ultraviolet radiation [
Participants also self-reported anthropometric measures that were converted into Body Mass Index (BMI in kg/m2) and used to compute obesity (BMI≥30; yes/no).
Internet use and access to health information online were measured by the following:
Ever use of Internet: Access to the Internet was established by asking participants whether they ever went online to access the Internet or to send and receive emails.
Internet use for health-related information last year: Access to online health information was determined by asking whether participants had used the Internet in the last year to look for health or medical information for themselves.
Internet first source for health-related information: Participants were asked to pick one item from a list to indicate where they would first go if they had a strong need to get information about health or medical topics. The list comprised family, friends/co-workers, doctors/health care professionals, books, brochures, libraries, specialized organizations, magazines/newspapers, complementary/alternative practitioner, telephone helpline, or the Internet. This list was used to create a variable to denote use of the Internet as a first port of call for health-related information.
Internet use for behavioral support last year: Participants were prompted to indicate various specific uses of the Internet over the last year (eg, to buy medicine or vitamins online, to look for health care providers, to write an online diary or blog on health topics). This list of uses was used to create a variable denoting use of the Internet for behavioral support (use of websites to help with diet, weight, smoking cessation, or physical activity; participation in online support groups for people with similar health or medical issues; downloading of health-related information to a mobile device or visiting “a social networking” site to read and share about medial topics).
Out of a total of 3959 participants, only those who provided information on Internet use and at least one health-risk behavior (3911/3959, 98.79%) were included in the analytic sample. In univariable analysis, differences in categorical and continuous variables between those who did and did not access the Internet, or between those who did and did not use online resources for health-related information and support, were compared with chi-square and
As shown in
Univariable associations of health-related Internet use with sociodemographic, health characteristics, and health-risk behavior.
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Totala (N=3911) | Ever use of Internet | Internet use for health-related information last yearb | Internet first source for health-related informationb | Internet use for behavioral support last yearb | |||||
Yes (n=2886) | No (n=1025) | Yes (n=2222) | No (n=650) | Yes (n=1318) | No (n=1459) | Yes (n=1321) | No (n=1236) | |||
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Age in years, mean (SD) | 46.35 (18.01) | 42.88 (15.57) | 58.91 (21.00)c | 42.48 (15.69) | 44.06 (17.04) | 42.30 (14.82) | 43.71 (16.94) | 39.78 (13.99) | 47.59 (17.70)c |
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Male, % (n) | 48.50 (1576) | 47.87 (1130) | 50.76 (446) | 45.38 (841) | 57.14 (286)c | 50.00 (524) | 45.95 (568) | 45.02 (449) | 51.78 (550)c |
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White, % (n) | 80.54 (2819) | 82.05 (2183) | 74.87 (636)c | 82.41 (1689) | 82.00 (486) | 81.39 (1023) | 83.09 (1089) | 79.11 (978) | 84.83 (964) |
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Married, % (n) | 51.23 (2015) | 52.75 (1604) | 45.66 (411)c | 52.79 (1241) | 53.54 (359) | 52.85 (732) | 54.30 (816) | 49.96 (697) | 58.53 (732)c |
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Employed, % (n) | 55.90 (2036) | 61.28 (1756) | 36.26 (280)c | 61.93 (1396) | 59.82 (354) | 63.08 (854) | 59.53 (837) | 62.83 (878) | 60.74 (678) |
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College education, % (n) | 64.10 (2672) | 73.88 (2311) | 28.08 (361)c | 77.47 (1835) | 61.83 (467)c | 78.13 (1111) | 71.79 (1118)c | 77.51 (1103) | 72.73 (972) |
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Poor health, % (n) | 15.04 (623) | 12.36 (343) | 25.00 (280) | 12.97 (268) | 9.97 (71) | 14.19 (156) | 10.82 (174) | 13.92 (161) | 9.93 (132) |
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BMI, mean (SD) | 27.66 (6.53) | 27.51 (6.32) | 28.25 (7.27) | 27.50 (6.35) | 27.59 (6.99) | 27.52 (6.36) | 27.55 (6.73) | 27.82 (6.77) | 27.07 (6.39) |
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Excessive alcohol consumption | 15.06 (484) | 15.47 (368) | 13.57 (116) | 15.52 (286) | 15.34 (80) | 14.84 (178) | 15.66 (181) | 15.89 (190) | 15.87 (141) |
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Current smoking | 17.78 (615) | 16.15 (419) | 23.71 (196)c | 15.34 (316) | 19.34 (101) | 16.65 (199) | 15.32 (206) | 19.84 (240) | 11.70 (130)c |
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Low fruit/ vegetable intake | 55.98 (2066) | 54.85 (1492) | 60.06 (574) | 52.54 (1115) | 63.72 (369)c | 58.20 (706) | 52.20 (732)c | 54.91 (676) | 54.67 (640) |
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Inactive/ sedentary lifestyle | 14.54 (545) | 11.74 (324) | 25.25 (221)c | 10.93 (229) | 14.70 (94) | 13.01 (154) | 11.09 (158) | 12.10 (137) | 11.91 (151) |
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Unprotected sun exposure | 87.69 (3309) | 86.97 (2414) | 90.29 (895)c | 86.60 (1853) | 88.33 (549) | 86.97 (1119) | 86.86 (1208) | 87.48 (1101) | 85.67 (1035) |
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Obese | 28.88 (1122) | 27.69 (819) | 33.40 (303)c | 27.94 (638) | 27.07 (177) | 26.51 (356) | 28.76 (434) | 28.64 (417) | 24.49 (299) |
aAll counts in table are unweighted.
bRestricted to those who have ever used the Internet.
c
General Internet use was common as nearly four out of five participants indicated that they had ever used it (78.2%, 95% CI 76.1-80.1). Univariable analysis showed that participants who engaged in any health-risk behaviors (with the exception of excessive alcohol consumption and low fruit/vegetable intake) were significantly less likely to have ever used the Internet (see
However, after controlling for sociodemographic and other characteristics in multivariable analysis, only participants with unprotected sun exposure remained less likely to have ever used the Internet (
Multivariable associations of health-related Internet use with sociodemographic, health characteristics, and health-risk behavior.
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Ever use of Internet | Internet use for health-related information last yearc | Internet first source for health-related informationc | Internet use for behavioral support last yearc | |
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Age | 0.94 (0.92-0.95)d | 0.99 (0.98-1.00) | 1.00 (0.99-1.00) | 0.97 (0.96-0.98)d |
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Male | 0.65 (0.47-0.89)d | 0.64 (0.45-0.90)d | 1.11 (0.56-1.44) | 0.69 (0.50-0.93)d |
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White | 2.15 (1.44-3.20)d | 0.92 (0.57-1.49) | 0.90 (0.56-1.47) | 0.71 (0.46-1.10) |
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Married | 1.69 (1.25-2.28)d | 1.06 (0.78-1.44) | 0.95 (0.77-1.17) | 0.99 (0.74-1.34) |
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Employed | 1.40 (0.89-2.21) | 1.11 (0.77-1.60) | 1.19 (0.90-1.56) | 1.00 (0.69-1.45) |
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College education | 7.40 (5.47-10.0)d | 2.17 (1.40-3.36)d | 1.42 (0.97-2.08) | 1.41 (1.01-1.98)d |
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Poor health | 0.79 (0.51-1.22) | 1.77 (1.03-3.05)d | 1.40 (0.83-2.37) | 1.43 (0.93-2.21) |
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BMI | 0.99 (0.95-1.02) | 1.00 (0.97-1.03) | 1.00 (0.98-1.02) | 1.03 (1.00-1.05)d |
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Excessive alcohol use | 0.61 (0.34-1.08) | 0.86 (0.54-1.36) | 0.83 (0.53-1.31) | 0.86 (0.59-1.24) |
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Current smoking | 0.62 (0.38-1.02) | 0.78 (0.47-1.29) | 0.97 (0.67-1.39) | 1.90 (1.35-2.68)d |
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Low fruit/vegetable intake | 1.03 (0.70-1.52) | 0.60 (0.45-0.80)d | 1.32 (1.04-1.68)d | 0.97 (0.69-1.36) |
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Inactive/ sedentary lifestyle | 0.80 (0.36-1.75) | 0.62 (0.37-1.05) | 1.22 (0.80-1.87) | 0.94 (0.53-1.68) |
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Unprotected sun exposure | 0.59 (0.40-0.88)d | 0.94 (0.66-1.35) | 0.97 (0.75-1.26) | 1.01 (0.67-1.53) |
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Obese | 0.91 (0.60-1.38) | 1.03 (0.72-1.49) | 0.91 (0.67-1.24) | 1.32 (1.00-1.75) |
aEstimates from model including all sociodemographic & health characteristics but no health-risk behaviors. bEstimates in separate models for each health-risk behavior, including sociodemographic & health characteristics covariates (BMI omitted from models with “Obese” as health-risk behavior).
cRestricted to those who have ever used the Internet.
d
Among those who had ever accessed the Internet, over three-quarters of participants (78.2%, 95% CI 75.4-80.7) had used it to obtain health-related information during the last year. Participants with low fruit/vegetable consumption were less likely to have sought health-related information online in the last year both in univariable analysis (
Nearly half of Internet users reported that they would look online first whenever they urgently required health-related information (47.8%, 95% CI 44.8-50.7). A higher proportion of those with, rather than without, low fruit and vegetable intake said they would use the Internet as a first source for information on health and medical topics. This was the case both in univariable analysis (
Over half of all those who had ever been online also reported using the Internet to access some sort of health-related behavioral support in the last year (56.9%, 95% CI 53.7-60.0). Both univariable (
Our findings provide up-to-date information on Internet access in the United States and demonstrate its widespread use to obtain health-related and medical information and support. In agreement with other national data [
Nonetheless, the findings also suggest that the Internet may not be equally effective for addressing all types of health-risk behaviors. In particular, the Internet may be less effective for promoting sun-protective behaviors and related awareness campaigns as Internet access is lower in the at-risk population, even after taking sociodemographic confounders into account. The reasons for this are unclear. It may in part reflect lower Internet penetration of rural areas where poor sun-protective behavior can be more prevalent [
There were also sociodemographic correlates of Internet use that were mostly independent of health-related behaviors. Access to the Internet and gaining health-related information and support online was associated with being younger, female, having at least college level education and less so with white ethnicity and being married. Importantly, the observed associations of health-risk behaviors with reduced access to the Internet were attenuated but not eradicated when controlling for sociodemographic determinants. Although this suggests that the Internet may be a good medium to deliver health promotion messages and interventions to those with health-risk behaviors, it also indicates a need to be aware that older, male, non-white, and less educated people could be less likely to benefit from the availability of online health-related support. Indeed, many of the characteristics that were associated with limited access or use of the Internet to obtain health-related and medical information in this study such as unemployment, worse education, and being single are also linked with detrimental health behaviors (eg, [
Our results have a number of implications. The Internet appears to have sufficient reach to engage people who display various risky health behaviors and, given its other advantages, is therefore a good medium to deliver online interventions to address excessive alcohol use, overeating, and physical inactivity. Based on our findings, smoking cessation interventions in particular may benefit from being delivered online. However, as access to the Internet and its use for obtaining health-related information is more limited among people with inadequate sun protection and with low fruit and vegetable intake, Internet-based interventions to change these behaviors may be less effective and require additional promotion. For instance, it may be important to supplement such interventions with print material and tailored advertising in health care outlets to reach the target population. Moreover, even though access to the Internet has grown exponentially over the last 15 years, this access is not equal across all population characteristics [
The study has a number of limitations inherent to most surveys. Findings rely on self-reported data, and this may have introduced biases due to systematic misreporting or forgetting. For instance, participants may underreport their alcohol [
Overall, our results suggests that the Internet has a wide reach and should be an effective tool to provide support and information for improving most health-risk behaviors but that sociodemographic characteristics of users need to be taken into consideration when developing online health promotion material.
Body Mass Index
Health Information National Trends Survey
LS and JB are part of the UK Centre for Tobacco and Alcohol Studies. JB’s post is funded by a fellowship from the UK Society for the Study of Addiction. SGS is funded by the Optum Institute (UnitedHealthcare) and Northwestern University.
None declared.