This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
The internet has enabled convenient and efficient health information searching which is valuable for individuals with chronic conditions requiring some level of self-management. However, there is little research evaluating what factors may impact the use of the internet for health-related tasks for specific clinical populations, such as individuals with inflammatory bowel diseases.
Our goal was to investigate the factors that influence internet use in acquiring health information by individuals with inflammatory bowel diseases. Specifically, we identified factors associated with internet searching behavior and using the internet for completing health-related tasks.
We used 2016 National Health Interview Survey weighted data to develop logistic regression models to predict the likelihood that individuals with inflammatory bowel diseases would use the internet for 2 types of tasks: seeking health information through online searches and using the internet to perform health-related tasks including scheduling appointments and emailing care providers.
2016 National Health Interview Survey weighted data include more than 3 million weighted adult respondents with inflammatory bowel diseases (approximately 1.29% of adults in the weighted data set). Our results suggest that approximately 66.3% of those with inflammatory bowel diseases reported using the internet at least once a day, and approximately 14.7% reported being dissatisfied with their current health care. About 62.3% of those with inflammatory bowel diseases reported that they had looked up health information online, 16.3% of those with inflammatory bowel diseases reported that they had scheduled an appointment with a health care provider online, and 21.6% reported having used a computer to communicate with a health provider by email. We found that women who were self-regulating their care were more likely to look up health information online than others. Both middle-aged and older adults with inflammatory bowel diseases who were unsatisfied with their current health care were less likely to look up health information online. Frequent internet users who were worried about medical costs were more likely to look up health information online. Similarly, the results from our statistical models suggest that individuals with inflammatory bowel diseases who were frequent internet users were more likely to use the internet for specific health-related tasks. Additionally, women with inflammatory bowel diseases who reported being married were less likely to use the internet for specific health-related tasks.
For those with inflammatory bowel diseases, there are additional socioeconomic and behavioral factors that impact the use of the internet for health information and health-related tasks. Future research should evaluate how these factors moderate the use of the internet and identify how online resources can support clinical populations in ways that improve access to information, support health self-management, and subsequently improve health outcomes.
The internet is seen as a reliable alternative source of health information [
Individuals with chronic diseases are a unique user population in terms of their potential use of online health information in self-management of their health. The prevalence of chronic diseases is high in the United States; Ward et al [
To ensure the effectiveness of the internet related to health information, the US Department of Health and Human Services [
Crohn disease and ulcerative colitis are collectively referred to as inflammatory bowel disease (IBD) [
Generally, the majority of studies related to IBD focus on its pathology and medical treatment. Although some studies have focused on the diagnosis of IBD [
The overall objective of this study was to investigate the factors that influence the use of the internet to acquire health information for individuals with IBD. We examined 2 types of internet-related activities: searching the internet for health information and using the internet for health-related tasks such as scheduling appointments with health care providers and communicating with a health care provider by email. We evaluated a number of potential factors that might impact how an individual with IBD uses the internet for health information. Previous research has shown that a number of factors impact internet usage for health information in general populations including: gender [
The National Health Interview Survey (NHIS), which is conducted by the National Center for Health Statistics, covers broad health topics [
This study focused on the behaviors and experiences, during the year preceding the interview, of adult individuals who reported having IBD (ULCCOLEV). The dependent variables in this study were related to internet usage: (1) individuals searching for health information on the internet (HIT1A), (2) individuals using the internet to schedule appointments with health care providers (HIT3A), and (3) individuals using the internet to communicate with health care providers via email (HIT4A). All dependent variables were recoded as binary variables (1, they reported that they had done the activity in the previous 12 months; 0; they had not).
Demographic variables such as sex (SEX) and age (AGE_P) were used in the analysis. The age variable was recoded into 3 groups: younger adults (18-35 years old), middle-age adults (36-55 years old), and older adults (older than 55). We recoded marriage status (R_MARITL) as a binary variable (1, married; 0, not married) where not married included never married, divorced, widowed, separated, as well as preferred not to answer and nonresponses. Parental status (PAR_STAT) of participants was recoded as being a parent of a child or not a parent of a child. Work status (DOINGLWA) of participants was recoded as employed or not employed.
It is possible that individuals with multiple chronic conditions may use the internet differently than those with a single chronic condition because of the complexity of managing multiple conditions. It is possible that they may receive conflicting medical advice for diverse chronic conditions [
Other variables that may impact an individual’s online information searching behaviors were also included in the analysis such as socioeconomic considerations, the level of satisfaction with health care services, and internet usage frequency. Whether the respondent reported having trouble finding a care provider in the previous 12 months (APRVTRYR) was recoded as reported trouble in finding a care provider and reported no trouble in finding a care provider. The respondents who reported being worried about paying medical bills (AWORPAY) were recoded as worried and not worried, with the former category including those who were very worried and those who were somewhat worried. A new variable was created to indicate whether participants were self-regulating care in a number of possible ways. This self-regulating care included whether the respondents reported doing at least one of the following actions: skipping medication doses (ARX12_1), taking less medicine (ARX12_2), delaying filling a prescription (ARX12_3), asking a doctor for less expensive medication (ARX12_4), and using alternative therapies (ARX12_6). A binary variable was created to identify whether the participants reported having seen or talked to a general practitioner in the prior year (AHCSYR9). A variable was also created to determine whether the participants tried to purchase health insurance directly in the prior 3 years by combining the 2 relevant variables of “Tried to purchase health insurance directly” (AINDINS2) and “Purchased health insurance directly” (AINDPRCH). The satisfaction of participants in their health care (ASISATHC) was recoded as satisfied and not satisfied, with the satisfied category including those who reported being very or somewhat satisfied with their health care services. A variable was created identifying frequent internet users based on the respondent’s frequency of internet usage (AWEBOFNO and AWEBOFTP). Frequent internet users were identified as such if the internet was used at least once a day (ie, at least 7 times per week) and were classified as not frequent internet users otherwise.
The data were analyzed using R (version 3.5.0). Specifically, the svyglm function (Survey package; version 3.34) [
After applying the data weights, the sample size of individuals who reported having IBD was 3,155,477 (approximately 1.29% of all the adults in the weighted data set); approximately 64.4% (2,032,022) of the respondents were female, the average age of the respondents was 52.8 (SE 0.87) years, and approximately 49.9% of the respondents (1,575,168) reported being married. Approximately 80.7% (2,544,995/3,155,477) of the respondents reported having seen or talked to a general practitioner in the previous year, with very few (273,977/3,155,477, 8.7%) reporting having trouble finding a provider in the previous 12 months, although 14.7% (464,376/3,155,477) reported being dissatisfied with their health care. Approximately 42.6% (1,344,253/3,155,477) and 41.2% (1,288,836/3,155,477) of the respondents also reported having hypertension or high cholesterol, respectively, which were the 2 highest prevalences of comorbidities examined for individuals who had IBD. More than half of the respondents (1,965,639/3,155,477, 62.3%) reported looking up health information online, and approximately 66.3% (2,090,505/3,155,477) reported being frequent internet users, using it at least daily. In terms of the health-related tasks, 16.3% (515,253/3,155,477) of those with IBD reported scheduling an appointment with a health care provide online, and 21.6% (680,872/3,155,477) reported having used computer to communicate with a health provider by email. The complete demographic information of the respondents is in
The characteristics of the sample of survey respondents who reported having IBD.
Variable | Weighted, n (%) | ||
|
|
||
|
Younger adults (18-35 years old) | 454,950 (14.4) | |
|
Middle age adults (36-55 years old) | 1,159,430 (36.7) | |
|
Older adults (>55 years old) | 1,541,097 (48.8) | |
|
|
||
|
Male | 1,123,455 (35.6) | |
|
Female | 2,032,022 (64.4) | |
Married | 1,575,168 (49.9) | ||
Employed | 1,548,101 (49.1) | ||
Has at least one child | 670,310 (21.2) | ||
Looked up health information online | 1,965,639 (62.3) | ||
Used computers to schedule an appointment with a health care provider | 515,253 (16.3) | ||
Used computer to communicate with a health care provider by email | 680,872 (21.6) | ||
Reported having hypertension | 1,344,253 (42.6) | ||
Reported having high cholesterol | 1,298,836 (41.2) | ||
Reported having coronary heart disease | 320,715 (10.2) | ||
Reported having asthma | 636,538 (20.2) | ||
Reported having cancer | 491,356 (15.6) | ||
Reported having diabetes | 564,795 (17.9) | ||
Reported having chronic/long-term liver conditions | 127,679 (4.0) | ||
Reported having trouble in finding a provider in the previous 12 months | 273,977 (8.7) | ||
Reported being worried about paying medical bills | 1,732,203 (54.9) | ||
Reported multiple types of self-regulating care | 1,192,446 (37.9) | ||
Reported having seen or talked to a general doctor in the previous year | 2,544,995 (80.7) | ||
Reported trying to purchase health insurance directly in the previous 3 years | 426,541 (13.5) | ||
Reported being unsatisfied with their health care | 464,376 (14.7) | ||
Used the internet frequently (at least daily usage) | 2,090,505 (66.3) | ||
Reported being worried about medical costs | 1,618,723 (51.3) |
A binary logit model was created to evaluate how individuals with IBD use the internet for information seeking (
Both middle-aged and older women were less likely to look up health information online compared to others (adjusted OR 0.07, 99% CI 0.004 to 0.96 and adjusted OR 0.02, 99% CI 0.001 to 0.29, respectively). Women with IBD who reported self-regulating care were more likely to look up health information online than others (adjusted OR 9.87, 99% CI 1.49 to 65.37). Both middle-aged (36-55 years old) and older (over 55 years old) adults who were married were more likely to look up health information online (adjusted OR 22.20, 99% CI 1.46 to 336.97 and adjusted OR 23.81, 99% CI 1.75 to 327.01, respectively). Both middle-aged and older adults who were unsatisfied with their current health care were less likely to look up health information online (adjusted OR 0.03, 99% CI 0.002 to 0.58 and 0.03, 99% CI 0.001 to 0.71, respectively). Individuals who were employed and were unsatisfied with their current health care were less likely to look up health information online (adjusted OR 0.07, 99% CI 0.007 to 0.62). Additionally, frequent internet users who were worried about the medical costs of an illness/accident were more likely to look up health information online (adjusted OR 12.18, 99% CI 2.08 to 72.24).
Binary logit model for the likelihood of looking up health information on internet.
Parameter | Estimate | 99% CI | SE | Adjusted ORa | 99% CI | ||
Intercept | –2.95 | (–4.91, –0.99) | 0.76 | –3.87 | <.001 | 0.05 | (0.007, 0.37) |
Female | 3.08 | (0.75, 5.42) | 0.91 | 3.40 | .001 | 21.76 | (2.12, 225.88) |
Middle-aged adults | 0.98 | (–1.11, 3.08) | 0.81 | 1.21 | .228 | —b |
|
Older adults | 1.43 | (–0.59, 3.44) | 0.78 | 1.83 | .068 | — |
|
Married | –2.72 | (–5.03, –0.42) | 0.90 | –3.04 | .002 | 0.07 | (0.007, 0.66) |
Employed | 0.95 | (–0.06, 1.95) | 0.39 | 2.42 | .016 | — |
|
Had asthma | 1.09 | (0.16, 2.02) | 0.36 | 3.02 | .003 | 2.97 | (1.17, 7.54) |
Self-regulating care | –1.30 | (–2.72, 0.13) | 0.55 | –2.34 | .019 | — |
|
Unsatisfied with health care | 4.15 | (1.08, 7.22) | 1.19 | 3.49 | .001 | 63.52 | (2.94, 1366.49) |
Worried about medical costs of illness/accident | –1.30 | (-2.57, -0.02) | 0.50 | –2.62 | .009 | 0.27 | (0.08, 0.98) |
Frequent internet users | 2.60 | (1.47, 3.73) | 0.44 | 5.92 | <.001 | 13.42 | (4.35, 41.68) |
Female × middle-aged adults | –2.72 | (–5.40, –0.04) | 1.04 | –2.62 | .009 | 0.07 | (0.004, 0.96) |
Female × older adults | –3.91 | (–6.59, –1.23) | 1.04 | –3.76 | <.001 | 0.02 | (0.001, 0.29) |
Female × self-regulating care | 2.29 | (0.40, 4.18) | 0.73 | 3.12 | .002 | 9.87 | (1.49, 65.37) |
Middle-aged adults × married | 3.10 | (0.38, 5.82) | 1.06 | 2.93 | .004 | 22.20 | (1.46, 336.97) |
Older adults × married | 3.17 | (0.56, 5.79) | 1.01 | 3.13 | .002 | 23.81 | (1.75, 327.01 |
Middle-aged adults × unsatisfied with health care | –3.51 | (–6.47, –0.55) | 1.15 | –3.06 | .002 | 0.03 | (0.002, 0.58) |
Older adults × unsatisfied with health care | –3.48 | (–6.61, –0.34) | 1.22 | –2.86 | .004 | 0.03 | (0.001, 0.71) |
Employed × unsatisfied with health care | –2.72 | (–4.97, –0.48) | 0.87 | –3.12 | .002 | 0.07 | (0.007, 0.62) |
Worried about medical costs of illness/accident × frequent internet users | 2.50 | (0.73, 4.28) | 0.69 | 3.64 | <.001 | 12.18 | (2.08, 72.24) |
aOR: odds ratio.
bNo statistically significant differences were found at α=.01.
A binary logistic regression model was created to predict the likelihood that an individual with IBD used a computer to schedule an appointment with their care provider (see
Binary logit model for the likelihood of using the internet to schedule an appointment with a health care provider.
Parameter | Estimate | 99% CI | SE | t value | Adjusted ORa | 99% CI | |
Intercept | –5.82 | (–8.23, –3.42) | 0.93 | –6.24 | <.001 | 0.003 | (<0.001,0.03) |
Female | 1.84 | (–0.12, 3.79) | 0.76 | 2.42 | .016 | —b | — |
Married | 2.10 | (0.09, 4.11) | 0.78 | 2.69 | .007 | 8.17 | (1.09,60.95) |
Self-regulating care | 0.96 | (0.05, 1.87) | 0.35 | 2.72 | .007 | 2.61 | (1.05,6.49) |
Frequent internet users | 2.72 | (1.27, 4.17) | 0.56 | 4.82 | <.001 | 15.18 | (3.56,64.72) |
Female × married | –2.60 | (–4.92, –0.29) | 0.90 | –2.90 | .004 | 0.07 | (0.007,0.75) |
aOR: odds ratio.
bNo statistically significant differences was found at α=.01.
A binary logistic regression model was created to predict the likelihood that an individual with IBD used email to communicate with their care provider (see
Binary logit model for the likelihood of emailing a health care provider.
Parameter | Estimate | 99% CI | SE | t value | Adjusted ORa | 99% CI | |
Intercept | –4.02 | (–5.60, –2.43) | 0.61 | -6.54 | <.001 | 0.02 | (0.003,0.09) |
Female | 1.36 | (–0.10, 2.83) | 0.57 | 2.41 | .017 | —b | — |
Married | 1.42 | (–0.07, 2.91) | 0.58 | 2.45 | .014 | — | — |
Frequent internet users | 2.13 | (1.17, 3.08) | 0.37 | 5.75 | <.001 | 8.41 | (3.22,21.76) |
Female × married | –1.88 | (–3.69, –0.07) | 0.70 | –2.67 | .008 | 0.15 | (0.02,0.93) |
aOR: odds ratio.
bNo statistically significant difference was found at α=.01.
Our study examined the use of the internet by individuals with IBD to seek health information and to perform health-related activities. The population of interest was examined because these chronic conditions are often self-managed [
In general, previous studies [
As the literature suggests, individuals in poor health tend to use the internet more frequently than healthy individuals to look up health information [
Those who reported self-regulating their care were more likely to use the internet to schedule appointments with health care providers. Additionally, women who self-regulated their care were more likely to look up health information on the internet. This may relate to the fact that those who self-regulated care may utilize these online resources as part of their self-regulating behaviors, for example, searching for suggestions to support self-regulating their care through self-medicating [
Identifying factors that might impact the use of the internet for health-related tasks and health information searching can identify demographic and specific issues that might lead to targeted interventions and an examination of how online information is designed for and presented to these populations. According to Kittler et al [
As expected, frequent internet users were shown to be more likely to use the internet to seek health information, schedule an appointment, and email health providers. In this study, we categorized frequent internet users as individuals who used the internet at least daily, yet many people currently use the internet on a more constant basis, and this variable may not capture differences between daily users and more constant users of the internet. Future research should more specifically examine the impact of internet usage frequency on how individuals with IBD use the internet for health care related activities. It would also be interesting to examine the frequency of internet use as a continuous variable and how that would impact the estimates of using the internet for health care tasks for those with IBD.
There are several limitations of this study that should be addressed in future research. The focus of the NHIS survey was not specifically related to the use of the internet for health care–related tasks, nor was it specifically focused on individuals with IBD. Future work could specifically focus on this clinical population and on specific internet-related tasks. Additionally, with the frequent changes to health IT and in the adoption of health technology, it is possible that this survey did not capture some of the specific uses of technology for health-related purposes or possible technologies (eg, smartphones and health-related apps). There may also be other factors that influence the use of the internet for health-related activities that were not captured by the survey, and thus, were not included in this analysis. For example, some insurance companies require that their customers refill their medications online, a situation not captured by the survey. Nor were socioeconomic variables related to internet access included. Additionally, there are other factors that may impact the use of the internet in conducting health-related tasks (eg, mental health comorbidities, cognitive abilities, health literacy skills [
In addition, to facilitate this analysis, most of the survey responses were categorized into binary variables that combined some answers with nonanswers and “I don’t know” responses. For example, internet use was transformed into a binary variable of frequent internet use versus infrequent internet use. These dichotomized variables may impact the findings associated with specific variables. Thus, future research could also examine the variables on a broader continuum in order to identify any additional nuances in the data. Additionally, future research should use different methods to identify why some relationships between variables were significant and also to identify the underlying causes so that future information strategies account for these differences and leverage what we know about the individuals with IBD and their internet health-related behaviors.
As the use of health information technology increases and evolves, it is critical to understand what specific clinical groups are using these resources, how they are doing so, and how those resources can best support health care self-management and disease prevention. This study examined using the internet for health information seeking tasks by individuals with IBD. As expected, frequent internet users were more likely to use the internet for health-related tasks. Our study demonstrates there are a number of factors and complex subgroups that impact the likelihood of individuals with IBD using the internet for information seeking. Future research should further investigate how these factors and groups (eg, women trying to self-regulate care) use the internet for health information and how the use of the internet shapes self-management of their health. Future research should also attempt to identify information design strategies and specific health-related task strategies for this population. In addition, human factors studies should be conducted to identify if and how online resources can support these populations in ways that improve access to information and health outcomes.
inflammatory bowel disease
odds ratio
National Health Interview Survey
The authors would like to thank Xiaoxia Li for her assistance with the preliminary data analysis for this manuscript. The authors would also like to thank the EASt lab for their feedback on a previous version of this paper.
Both authors contributed equally to the manuscript.
None declared.