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Many patients with chronic medical conditions search the internet to obtain medical advice and health information to improve their health condition and quality of life. Diabetes is a common chronic disease that disproportionately affects different race and ethnicity groups in the United States. In the existing literature on the popularity of internet health information seeking among persons with a chronic medical condition, there are limited data on US adults living with diabetes.
This study aims to examine the factors associated with internet health information seeking among US adults living with diabetes and whether there is a disparity in internet health information seeking stratified by race and ethnicity.
We conducted a cross-sectional study using the Health Information National Trends Survey data from 2017 to 2020. We selected our study sample based on respondents’ reports on whether they were told they had diabetes, and our primary outcome was internet health information–seeking behavior. We used 2 multivariable logistic regression models to examine the effects of sociodemographic factors and other covariates on the internet health information–seeking behavior of adults with diabetes. Jackknife replicate weights were used to provide bias-corrected variance estimates.
Our study sample included 2903 adults who self-reported that they had diabetes. In total, 60.08% (1744/2903) were non-Hispanic White individuals, 46.88% (1336/2850) were men, and 64% (1812/2831) had some college or graduate education. The prevalence of internet health information seeking in this population was 64.49% (1872/2903), and the main factors associated with internet health information seeking included education level (some college vs less than high school: odds ratio [OR] 1.42, 95% CI 1.44-1.88; and college graduate or higher vs less than high school: OR 2.50, 95% CI 1.79-3.50), age (age group ≥65 years vs age group 18-44 years: OR 0.46, 95% CI 0.34-0.63), and household income level (
The findings from this study suggest that internet health information seeking is common among US adults living with diabetes. Internet health information could influence the relationship between health care providers and adults living with diabetes and improve their self-management and quality of life.
Health information seeking through internet platforms is increasingly popular [
Diabetes mellitus is a common chronic medical condition that disproportionately affects the US adult population. Results obtained from the 2011 to 2016 National Health and Nutrition Examination Surveys data indicated that the prevalence of total diabetes among adult non-Hispanic White individuals with diagnosed diabetes was approximately 12%. In non-Hispanic Black and Hispanic individuals, the prevalence was approximately 20% and 22%, respectively [
Research suggests that information accessibility is an efficient tool and support necessary to improve chronic medical conditions, including diabetes [
There is a shortage of data on the internet health information–seeking pattern among adults with diabetes in the United States. Given the growing popularity of internet health information–seeking behavior and the differences in the prevalence of diabetes in the United States, it is vital to understand the factors that predict the use of the internet to seek health information among US adults with diabetes. In addition, with the reported disproportionate racial prevalence of diabetes in the United States, it is essential to investigate whether there is a racial or ethnic disparity in internet health information seeking. Knowing this information is critical for improving diabetes health education and communication, support systems, and quality of life of adults with diabetes in the United States. This study examines the factors associated with internet health information seeking and racial disparity in internet health information seeking among US adults with diabetes.
This cross-sectional study uses data from the Health Information National Trends Survey (HINTS). HINTS is a national representative survey that collects data from the US noninstitutionalized adult population [
To identify our study population, we pooled and combined data from 4 administrations of HINTS: 2017 (version 5, cycle 1, N=3285), 2018 (version 5, cycle 2, N=3504), 2019 (version 5, cycle 3, N=3374), and 2020 (version 5, cycle 4, N=3865). This study focused on investigating internet health information seeking among the adult population with diabetes. We selected respondents who answered “Yes” to the question “Has a doctor or other health professional ever told you that you had diabetes or high blood sugar?” A total of 2903 respondents met the inclusion criteria for this study (655/3285, 19.94%, in 2017; 714/3504, 20.38%, in 2018; 717/3374, 21.25%, in 2019; and 817/3865, 21.14%, in 2020).
This study was approved as exempt by the institutional review board of the University of Alabama because no human participants were involved.
Our dependent variable, internet health information–seeking behavior, was defined on the basis of the respondents’ report on whether they had in the past 12 months used a computer, smartphone, or other electronic means to look for health or medical information for themselves (yes or no). We excluded invalid or missing responses (52/2903, 1.79%) in our final analyses because the percentage was very small.
The primary predictor variables of interest in this study included sociodemographic information: race and ethnicity (non-Hispanic White, non-Hispanic Black, and other), sex (male and female), age group (18-44 years, 45-64 years, and ≥65 years), education level (less than high school, high school graduate, some college, and college graduate or higher), occupation (employed and unemployed), household income (<US $50,000, US $50,000 to <US $75,000, and ≥US $75,000), residency (urban and rural), and marital status (married, divorced, widowed, single, or never been married). Other covariates included were frequency of visits to health care providers (≤1 time, 2-4 times, and ≥5 times), insurance type (private, public, mixed, no insurance, and other), quality of care (excellent or very good, good, and fair or poor), general health (excellent or very good, good or fair, and poor), ability to take care of one’s health (completely or very confident, somewhat confident, and a little or not confident at all). We also examined the respondents’ level of trust in the different sources of information (medical professionals, internet, social network, traditional media, and organizations). The trust scores were reverse coded: 4=a lot, 3=some, 2=a little, and 1=or not at all. Medical professionals as a source of information was scored using only 1 question: “From a doctor?” The social network score was based on the mean of 2 questions: “From family or friends?” and “From religious organizations or leaders?” The internet score was based on 1 question: “Internet?” The traditional media score was based on the mean of 2 questions: “From radio?” and “From television?” The newspapers and magazines score was based on 1 question: “From newspapers or magazines?” The trust in organizations score was based on the mean of 2 questions: “From government health agencies?” and “From charitable organizations?”
We used descriptive analyses to summarize the frequencies and unweighted and weighted proportions of respondents grouped by sociodemographic characteristics. The weighted proportions were generated using the survey’s weighting variables to generalize the results to the US population. We calculated the trust score using the original survey questions and estimated the mean trust scores for the different sources of information. Multivariable logistic regression models were created to explore the association between the independent variables and health information–seeking behaviors. A total of 2 multiple logistic regression models were constructed to determine the impact of variables of interest with covariates (model 1) and without covariates (model 2). Jackknife replicate weights were used to provide bias-corrected variance estimates [
The weighted and unweighted estimates of the characteristics of interest are summarized in
Sample characteristics of respondents with diabetes, of Health Information National Trends Survey, 2017 to 2020 (N=2903).
Variable | Value, n | Unweighted estimates (%) | Weighted estimates (%) | ||||
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Non-Hispanic White | 1744 | 60.08 | 65.96 | |||
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Non-Hispanic Black | 638 | 22 | 16.8 | |||
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Other | 521 | 17.9 | 17.3 | |||
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Male | 1336 | 46.88 | 48.91 | |||
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Female | 1514 | 53.12 | 51.09 | |||
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18 to 44 | 306 | 10.5 | 17.8 | |||
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45 to 64 | 1134 | 39.06 | 48.96 | |||
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≥65 | 1463 | 50.40 | 33.25 | |||
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Less than high school | 337 | 11.9 | 13.8 | |||
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High school graduate | 682 | 24.1 | 28.5 | |||
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Some college | 908 | 32.1 | 37.8 | |||
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College graduate or higher | 904 | 31.9 | 19.9 | |||
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Urban | 2519 | 86.77 | 84.84 | |||
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Rural | 384 | 13.2 | 15.2 | |||
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Married | 1426 | 50.46 | 57.38 | |||
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Divorced | 575 | 20.3 | 12.1 | |||
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Widowed | 433 | 15.3 | 8.6 | |||
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Single or never been married | 392 | 13.9 | 21.9 | |||
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<50,000 | 1460 | 56.85 | 54.02 | |||
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50,000 to <75,000 | 429 | 16.7 | 17.4 | |||
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≥75,000 | 679 | 26.4 | 28.6 |
Mean scores of trust in health information sources stratified by race and ethnicity group.
Comparison of characteristics between Health Information National Trends Survey (2017 to 2020) respondents who reported that they searched the internet for health information and those who did not search the internet for health information (N=2903).
Variable | Searched the internet for health information, n (%) | |||||||
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Yes (n=1793) | No (n=1110) |
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<.001 | |||||||
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18 to 44 | 226 (12.6) | 80 (7.21) |
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||||
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45 to 64 | 798 (44.51) | 336 (30.27) |
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≥65 | 769 (42.89) | 694 (62.52) |
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.41 | |||||||
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Non-Hispanic White | 1118 (62.35) | 626 (56.4) |
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Non-Hispanic Black | 354 (19.74) | 284 (25.59) |
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Other | 321 (17.9) | 200 (18.02) |
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<.001 | |||||||
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Less than high school | 106 (6) | 231 (21.73) |
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High school graduate | 316 (17.87) | 366 (34.43) |
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Some college | 616 (34.84) | 292 (27.47) |
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College graduate or higher | 730 (41.29) | 174 (16.37) |
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.01 | |||||||
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Employed | 355 (19.8) | 104 (9.37) |
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Unemployed | 1438 (80.2) | 1006 (90.63) |
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<.001 | |||||||
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<50,000 | 789 (48.02) | 671 (72.54) |
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50,000 to <75,000 | 300 (18.26) | 129 (13.95) |
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≥75,000 | 554 (33.72) | 125 (13.51) |
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.03 | |||||||
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Male | 810 (45.79) | 526 (48.66) |
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Female | 959 (54.21) | 555 (51.34) |
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.15 | |||||||
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Urban | 1595 (88.96) | 924 (83.24) |
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Rural | 198 (11.04) | 186 (16.76) |
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<.001 | |||||||
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Married | 998 (56.51) | 428 (40.38) |
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Divorced | 334 (18.91) | 241 (22.73) |
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Widowed | 180 (10.19) | 253 (23.87) |
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Single or never been married | 254 (14.38) | 138 (13.02) |
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.001 | |||||||
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Private | 566 (31.57) | 173 (15.59) |
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Public | 546 (30.45) | 521 (46.94) |
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Mixed | 540 (30.12) | 333 (30) |
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Other | 39 (2.18) | 20 (1.8) |
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No insurance | 102 (5.69) | 63 (5.68) |
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.60 | |||||||
|
Excellent or very good | 1224 (73.82) | 729 (75.86) |
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Good | 331 (19.96) | 164 (17.07) |
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Fair or poor | 103 (6.21) | 68 (7.08) |
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.29 | |||||||
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Excellent or very good | 479 (26.88) | 272 (24.66) |
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Good | 1215 (68.18) | 746 (67.63) |
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Fair or poor | 88 (4.94) | 85 (7.71) |
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.05 | |||||||
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Completely or very confident | 1071 (59.87) | 691 (62.7) |
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Somewhat confident | 579 (32.36) | 304 (27.59) |
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||||
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A little or not confident at all | 139 (7.77) | 107 (9.71) |
|
The 2 models we created to examine the factors that predict the use of the internet to seek health information in participants who reported that they had diabetes are presented in
Model 2 presents the effect of the main predictor variables of interest without the covariates. In this model, only education level, age group, and household income level remained the main predictors of use of the internet to search for health information among persons who reported that they had diabetes. In models 1 and 2, race and ethnicity, occupation, sex, marital status, and urbanity were not significantly associated with using the internet to search for health information among respondents who have diabetes (
Odds ratios (ORs) and 95% CIs of respondents seeking health information by multiple logistic regression model.
Variable | Model 1, OR (95% CI) | Model 2, OR (95% CI) | |||
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Less than high school (reference) | —a | — | ||
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High school graduate | 0.82 (0.61-1.10) | 0.82 (0.60-1.10) | ||
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Some college | 1.44 (1.10-1.88)b | 1.45 (1.12-1.86)b | ||
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College graduate or higher | 2.50 (1.79-3.50)b | 2.76 (2.04-3.74)b | ||
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|||||
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Employed (reference) | — | — | ||
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Unemployed | 0.99 (0.73-1.33) | 0.98 (0.79-1.23) | ||
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18 to 44 (reference) | — | — | ||
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45 to 64 | 0.88 (0.63-1.22) | 0.94 (0.72-1.22) | ||
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≥65 | 0.46 (0.34-0.63)b | 0.46 (0.35-0.60)b | ||
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<50,000 (reference) | — | — | ||
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50,000 to <75,000 | 0.82 (0.63-1.08) | 0.88 (0.69-1.11) | ||
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≥75,000 | 1.43 (1.03-1.99)b | 1.41 (1.07-1.87)b | ||
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Urban (reference) | — | — | ||
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Rural | 0.77 (0.59-1.00) | 0.81 (0.65-1.02) | ||
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|||||
|
Married (reference) | — | — | ||
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Divorced | 0.85 (0.61-1.19) | 0.87 (0.66-1.15) | ||
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Widowed | 0.85 (0.59-1.22) | 0.89 (0.62-1.27) | ||
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Single, never been married | 0.92 (0.58-1.44) | 0.87 (0.58-1.30) | ||
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Male (reference) | — | — | ||
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Female | 1.12 (0.94-1.34) | 1.15 (0.99-1.34) | ||
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Non-Hispanic White (reference) | — | — | ||
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Non-Hispanic Black | 1.12 (0.79-1.59) | 1.05 (0.80-1.39) | ||
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Other | 0.95 (0.61-1.46) | 0.92 (0.67-1.26) | ||
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|||||
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Private (reference) | — | N/Ac | ||
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Public | 0.88 (0.54-1.45) | N/A | ||
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Mixed | 1.25 (0.79-2.00) | N/A | ||
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Other | 0.54 (0.15-1.98) | N/A | ||
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No insurance | 1.40 (0.55-3.54) | N/A | ||
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|||||
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≤1 time (reference) | — | N/A | ||
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2 to 4 times | 0.88 (0.63-1.22) | N/A | ||
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≥5 times | 1.52 (1.11-2.10)b | N/A | ||
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|||||
|
Excellent or very good (reference) | — | N/A | ||
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Good | 1.16 (0.80-1.69) | N/A | ||
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Fair or poor | 1.02 (0.68-1.52) | N/A | ||
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|||||
|
Excellent or very good (reference) | — | N/A | ||
|
Good or fair | 1.06 (0.82-1.37) | N/A | ||
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Poor | 0.70 (0.43-1.14) | N/A | ||
|
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|
Completely or very confident (reference) | — | N/A | ||
|
Somewhat confident | 1.21 (0.89-1.64) | N/A | ||
|
A little or not confident at all | 0.97 (0.62-1.52) | N/A |
aReference level for corresponding predictors.
b
CN/A: not applicable (variables were included in model 1 only).
Odds ratios (ORs) and 95% CIs of respondents seeking health information on the internet by race and ethnicity group.
Variable | Model 1: non-Hispanic White, OR (95% CI) | Model 2: non-Hispanic Black, OR (95% CI) | Model 3: other, OR (95% CI) | |
|
||||
|
Less than high school (reference) | —a | — | — |
|
High school graduate | 0.70 (0.49-1.01) | 1.23 (0.58-2.61) | 0.57 (0.20-1.58) |
|
Some college | 1.31 (0.95-1.79) | 1.36 (0.76-2.45) | 4.73 (2.23-10.01)b |
|
College graduate or higher | 2.77 (1.93-3.96)b | 1.72 (0.73-4.03) | 2.10 (0.53-8.26) |
|
||||
|
Employed (reference) | — | — | — |
|
Unemployed | 0.97 (0.69-1.36) | 0.90 (0.50-1.63) | 0.70 (0.35-1.41) |
|
||||
|
18 to 44 (reference) | — | — | — |
|
45 to 64 | 0.81 (0.52-1.26) | 1.05 (0.46-2.39) | 1.33 (0.49-3.59) |
|
≥65 | 0.53 (0.34-0.82)b | 0.32 (0.14-0.72)b | 0.30 (0.09-1.04) |
|
||||
|
<50,000 (reference) | — | — | — |
|
50,000 to <75,000 | 0.93 (0.64-1.36) | 0.74 (0.36-1.53) | 0.35 (0.18-0.70)b |
|
≥75,000 | 1.47 (0.97-2.24) | 2.42 (1.09-5.38)b | 1.37 (0.74-2.53) |
|
||||
|
Male (reference) | — | — | — |
|
Female | 1.06 (0.85-1.33) | 1.18 (0.74-1.88) | 1.95 (0.90-4.22) |
|
||||
|
≤1 time (reference) | — | — | — |
|
2 to 4 times | 1.03 (0.67-1.56) | 0.62 (0.33-1.17) | 0.85 (0.30-2.37) |
|
≥5 times | 1.87 (1.25-2.80)b | 0.84 (0.42-1.66) | 1.48 (0.46-4.74) |
|
||||
|
Private (reference) | — | — | — |
|
Public | 0.71 (0.37-1.37) | 0.69 (0.36-1.33) | 2.76 (0.50-15.09) |
|
Mixed | 1.00 (0.53-1.89) | 1.77 (0.68-4.59) | 1.24 (0.29-5.36) |
|
Other | 0.53 (0.12-2.43) | 1.63 (0.27-9.88) | 0.06 (0.01-0.52)b |
|
No insurance | 2.63 (1.19-5.81)b | 0.42 (0.07-2.57) | 2.67 (0.52-13.69) |
|
||||
|
Urban (reference) | — | — | — |
|
Rural | 0.91 (0.68-1.20) | 0.40 (0.25-0.66)b | 0.22 (0.06-0.77)b |
|
||||
|
Married (reference) | — | — | — |
|
Divorced | 1.02 (0.70-1.47) | 0.69 (0.38-1.24) | 1.25 (0.38-4.14) |
|
Widowed | 0.93 (0.58-1.49) | 1.28 (0.66-2.45) | 0.22 (0.07-0.70)b |
|
Single or never been married | 0.76 (0.45-1.29) | 1.24 (0.62-2.48) | 0.68 (0.21-2.24) |
|
||||
|
Excellent or very good (reference) | — | — | — |
|
Good | 1.11 (0.70-1.74) | 1.64 (0.75-3.58) | 0.70 (0.23-2.16) |
|
Fair or poor | 1.27 (0.69-2.32) | 0.58 (0.25-1.35) | 0.90 (0.18-4.43) |
|
||||
|
Excellent or very good (reference) | — | — | — |
|
Good | 0.92 (0.68-1.24) | 1.22 (0.63-2.36) | 1.51 (0.54-4.27) |
|
Fair or poor | 0.71 (0.40-1.26) | 1.35 (0.35-5.13) | 0.29 (0.05-1.82) |
|
||||
|
Completely or very confident (reference) | — | — | — |
|
Somewhat confident | 1.27 (0.86-1.87) | 1.46 (0.69-3.09) | 1.10 (0.41-2.93) |
|
A little or not confident at all | 0.82 (0.50-1.36) | 0.76 (0.21-2.71) | 3.16 (0.52-19.41) |
aReference level for corresponding predictors.
b
Diabetes self-management skills refer to the tasks the patient must carry out to manage or reduce the impact of diabetes on their health status and daily living. The internet is a popular platform where individuals with chronic medical conditions obtain information or opinions to improve their health conditions. This cross-sectional study examined the factors associated with internet health information–seeking behavior among US adults with diabetes. We found that approximately two-thirds of the individuals who reported that they are living with diabetes seek personal health information using the internet. Standard features of the US adults with diabetes who seek internet health information include non-Hispanic White race, some college or graduate-level education, unemployment, being married, women, and living in urban areas. The significant predictors of internet use for health information are education level, age, household income, and frequency of visits to health care provider. Our results show that persons with college graduate–level education or higher have 2.5 times higher odds of seeking health information from the internet than individuals with less than high school education. People with diabetes who frequently visit health care providers (≥5 times per year) are 1.5 times more likely to seek health information from the internet than those who see their provider once or not at all in a year. Older age groups (≥65 years) are significantly less likely to use the internet for health information than younger age groups. We observed inconsistencies, by race, in the factors associated with internet health information seeking among US adults with diabetes. The main predictors of internet health information seeking among non-Hispanic White individuals are college graduate education or higher degree, younger age, no insurance, and higher frequency of visits to health care providers. By contrast, among non-Hispanic Black individuals, the main predictors are higher household income, residency, and age of patients.
The ever-growing availability of the internet increases its utility for accessing health information, especially among people with chronic medical conditions. Even so, health care professionals remain the most trusted source of health information and are trailed by internet sources. As in most studies, we observed that the trust in health information sources among US adults with diabetes was higher for health care professionals than for internet sources [
Contrary to our findings of a large proportion of US adults with diabetes seeking internet health information, Kalanzi et al [
Individual characteristics (eg, income, sex, race and ethnicity, age, and education) influence internet health information–seeking behaviors, regardless of the types of illnesses [
Overall, our study showed a significant association between higher internet use for health information and higher education levels in all race categories. We did not find any significant association between the race of a person living with diabetes and internet health information–seeking behavior. However, we observed inconsistency in the predictors of internet health information seeking across racial groups of adults living with diabetes. Although no association was observed between insurance types and internet use among the Hispanic and non-Hispanic Black individuals with diabetes, our results show that non-Hispanic White individuals with diabetes who have no insurance are significantly more likely to use the internet for health information than non-Hispanic White individuals with private insurance. Previous reports of the association between internet use and insurance status are mixed. Research mostly shows that people with private insurance are more likely to use the internet to seek health information, which could be attributed to their socioeconomic status [
In comparison, among non-Hispanic Black individuals with diabetes, the main significant predictors of internet health information seeking include higher household income and living in an urban area. Notably, our study explored the difference in the effects of the predictor on internet health information seeking stratified by race and ethnicity among US adults with diabetes. We were unable to compare our data with any similar studies. However, studies have shown a vast racial divide in internet health information–seeking behavior [
The findings from our study add significantly to the literature; however, the study is not without limitations. First, the data used in this study, HINTS data, are self-report secondary survey data. Therefore, there may be issues with validity and bias in the information collected in this survey. For example, the identification of persons with diabetes is based on the information provided by the respondents. We could not verify this information by using clinical data to determine whether diabetes was diagnosed clinically in these respondents. In addition, the response to our dependent variable could have been overreported or underreported. Second, the HINTS data are cross-sectional data. We could not ascertain the trend in internet information seeking in this population and examine any behavior change during the study period. Third, our analytical approach may be subject to robustness issues related to sample sizes. The small sample size of non-Hispanic Black and other race strata compared with the non-Hispanic White group could have affected our findings in this study. Our pooled approach and use of jackknife weights in our analyses helped minimize potential sampling biases and enhance the generalizability of our results. Even with these limitations, the nationwide sampling approach of the survey data is a great strength of this study.
Our study provides insights into the predictors of internet health information–seeking behavior of US adults living with diabetes. Seeking internet health information is common among adults living with diabetes. To improve the self-management and quality of life of individuals living with diabetes, it is crucial for health care providers to educate patients about reliable and verifiable internet health information sources.
Health Information National Trends Survey
odds ratio
None declared.