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Considerable effort has been directed to offering online health information and services aimed at the general population. Such efforts potentially support people to obtain improved health outcomes. However, when health information and services are moved online, issues of equality need to be considered. In this study, we focus on the general population and take as a point of departure how health statuses (physical functioning, social functioning, mental health, perceived health, and physical pain) are linked to internet access (spanning internet attitude, material access, internet skills, and health-related internet use).
This study aims to reveal to what extent (1) internet access is important for online health outcomes, (2) different health statuses are important for obtaining internet access and outcomes, and (3) age and education moderate the contribution of health statuses to internet access.
A sequence of 2 online surveys drawing upon a sample collected in the Netherlands was used, and a data set with 1730 respondents over the age of 18 years was obtained.
Internet attitude contributes positively to material access, internet skills, and health outcomes and negatively to health-related internet use. Material access contributes positively to internet skills and health-related internet use and outcomes. Internet skills contribute positively to health-related internet use and outcomes. Physical functioning contributes positively to internet attitude, material access, and internet skills but negatively to internet health use. Social functioning contributes negatively to internet attitude and positively to internet skills and internet health use. Mental health contributes positively to internet attitude and negatively to material access and internet health use. Perceived health positively contributes to material access, internet skills, and internet health use. Physical pain contributes positively to internet attitude and material access and indirectly to internet skills and internet health use. Finally, most contributions are moderated by age (<65 and ≥65 years) and education (low and high).
To make online health care attainable for the general population, interventions should focus simultaneously on internet attitude, material access, internet skills, and internet health use. However, issues of equality need to be considered. In this respect, digital inequality research benefits from considering health as a predictor of all 4 access stages. Furthermore, studies should go beyond single self-reported measures of health. Physical functioning, social functioning, mental health, perceived health, and physical pain all show unique contributions to the different internet access stages. Further complicating this issue, online health-related interventions for people with different health statuses should also consider age and the educational level of attainment.
The World Health Organization (WHO) stresses that public health is an important topic on policy agendas in most Western countries. Considerable effort is directed to offering health information and services aimed at the general population online. Such efforts potentially support people in improved outcomes regarding their knowledge of health issues, health communication with professionals, decision-making about health issues, proper use of health services, and improved ways of taking care of themselves [
Resources and appropriation theory considers internet access as a process of appropriation following attitude, material access, skills, and use [
Prior research has revealed that internet attitude directly affects material access, the development of internet skills, and internet use [
Hypothesis 1 (H1): Internet attitude is positively associated with (1) material access, (2) internet skills, (3) health-related internet use, and (4) health outcomes.
H2: Material access is positively associated with (1) internet skills, (2) health-related internet use, and (3) health outcomes.
H3: Internet skills are positively associated with (1) health-related internet use and (2) health outcomes.
H4: Health-related internet use is positively associated with health outcomes.
For the second goal of this paper, we focus on a range of health statuses pertaining to general functioning and well-being among the general population [
H5: Physical functioning is associated with (1) internet attitude, (2) material access, (3) internet skills, and (4) health-related internet use.
H6: Social functioning is associated with (1) internet attitude, (2) material access, (3) internet skills, and (4) health-related internet use.
H7: Mental health is associated with (1) internet attitude, (2) material access, (3) internet skills, and (4) health-related internet use.
H8: Health perceptions are associated with (1) internet attitude, (2) material access, (3) internet skills, and (4) health-related internet use.
H9: Pain is associated with (1) internet attitude, (2) material access, (3) internet skills, and (4) health-related internet use.
Conceptual model and hypotheses.
The conceptual model in
This study used online surveys and drew upon a sample collected in the Netherlands. To obtain a representative sample of the population, we used PanelClix, a professional organization for market research. Members of the panel receive a small incentive for every survey they complete. In the Netherlands, 98% of the population uses the internet, closely representing the general population in terms of sociodemographic composition. We aimed to obtain a data set with approximately 1700 respondents over the age of 18 years. Eventually, this resulted in the collection of 1730 responses in a 2-wave study, both conducted over a 1-week period. The survey in the first wave (April 2020; n=2227) was specifically designed to gather background variables, including the different health statuses that are the topic of interest in this contribution. The survey furthermore included questions related to COVID-19. The average time required to complete this survey was 15-20 minutes. The survey in the second wave (November 2020; n=1730, 77.7%) was administered among respondents of the first wave and involved questions around the different internet access stages, including internet motivation, material access, internet skills, internet health use, and health outcomes. The reason for administering a second survey among respondents of the first wave was a practical one: as the background variables were already collected, more space was available for questions related to internet access. Of the respondents of the first survey, 1730 (77.7%) completed the second survey. The average time required to complete this second survey was 20 minutes. During the first wave, 3 amendments to the sampling frame were made to ensure the representativeness of the Dutch population. Accordingly, the analyses revealed that respondents’ gender, age, and formal education largely matched official census data. This was also the case for the sample that resulted from the second wave. See
Both online surveys followed Mahon’s [
Characteristics of the study sample (N=1730).
Characteristics | Participants, n (%) | |
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Male | 871 (50.3) |
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Female | 859 (49.7) |
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18-34 | 397 (22.9) |
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35-49 | 412 (23.8) |
50-64 | 502 (29.0) | |
≥65 | 419 (24.2) | |
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No diploma, primary or lower secondary diploma | 516 (29.8) |
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Secondary diploma | 602 (34.8) |
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Higher diploma | 612 (35.4) |
To comply with requirements on privacy, collected data were anonymized by stripping IP addresses from the data set before the data files were saved to the researcher’s computer.
The measures for the 5 considered health statuses were adapted from the Dutch version of the Medical Outcomes Study (MOS) Short-Form General Health Survey (SF-20) [
Gender was included as a dichotomous variable, and age was directly asked. Data on education were collected by degree. These were subsequently divided into 2 groups of low (ie, no diploma or primary or [lower] secondary education diploma) and high (ie, college and university) educational level attained.
Items, descriptive statistics, and internal consistency (Cronbach α) for internet attitude, internet skills, health-related internet use, and health-related internet outcomes.
Items | Mean (SD) | |
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Technologies, such as the internet and mobile phones, make life easier. | 4.29 (0.83) |
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I feel that people pressure me to be constantly connected (recoded). | 4.03 (1.23) |
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There are many things on the internet that are good for people like me. | 3.89 (0.85) |
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I know how to upload files. | 3.16 (1.07) |
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I know how to adjust privacy settings. | 3.54 (1.04) |
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I know how to use my smartphone as a hotspot. | 4.11 (1.55) |
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I know how to check whether the information I find online is true. | 3.33 (1.21) |
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I find it easy to decide what the best keywords are. | 4.17 (1.02) |
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I know how to figure out whether a website can be trusted. | 3.71 (1.22) |
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I know how to store photos, documents, or other files in the cloud (eg, Google Drive, iCloud). | 3.76 (1.41) |
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I know how to keep track of the costs of mobile app use. | 4.17 (1.41) |
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I know how to change with whom I share content (eg, friends, friends of friends, or the public). | 4.28 (1.13) |
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I know how to block messages from people I do not want to have anything to do with anymore. | 4.16 (1.14) |
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I know what pictures of me or others I can share online. | 4.23 (1.11) |
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I know how to turn off my location on a smartphone. | 3.24 (1.19) |
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I know how to reach people with my digital creations. | 3.66 (1.37) |
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I know how to create videos or selfies to which others will react positively. | 4.18 (1.32) |
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I know how to create digital materials to express my ideas. | 3.60 (1.35) |
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I know how to block unwanted popup messages or ads. | 3.59 (1.38) |
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I know how to post homemade videos or music online. | 3.64 (1.46) |
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I know how to make basic changes to the content that others have produced. | 3.48 (1.38) |
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I know which (copy) rights apply to online material. | 3.57 (1.29) |
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I know how to increase the number of followers of my profile on social media. | 3.45 (2.05) |
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Finding information about your health or medical care | 2.60 (1.02) |
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Contacting a physician or medical specialist | 1.94 (0.98) |
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Talking to others about your personal health | 1.91 (1.23) |
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Participating in an online training or health program | 1.76 (1.18) |
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Finding information or watching videos about improving your fitness/health | 2.05 (1.27) |
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Using an app to check your health status or treatment | 1.96 (1.33) |
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The way the last advice, program, or app you used affected your health | 2.04 (1.56) |
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The feeling about your fitness/health that online information gives you | 2.23 (1.59) |
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The latest online health information or online advice that you applied | 3.03 (2.03) |
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The way you have adapted your behavior based on online health information | 2.11 (1.53) |
aA 5-point agreement scale ranging from “strongly disagree” to “strongly agree.”
bA 5-point truth scale ranging from “not at all true of me” to “very true of me.”
cA 6-point frequency scale ranging from “never” to “multiple times a day.”
dA 5-point satisfaction scale ranging from “very dissatisfied” to “very satisfied.”
Items, descriptive statistics, and internal consistency (Cronbach α) for health state variables.
Items | Mean (SD) | |
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Vigorous activities, such as lifting heavy objects, running, or participating in strenuous sports | 1.57 (0.50) |
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Moderate activities, such as moving a table or carrying groceries | 1.77 (0.42) |
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Walking uphill or climbing a few steps without resting | 1.74 (0.44) |
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Bending or lifting or stooping | 1.73 (0.44) |
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Walking 1 block | 1.83 (0.38) |
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Eating, dressing, bathing, or using the toilet | 1.89 (0.31) |
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My health regularly limits me in social activities (eg, visiting friends or family)—recoded. | 3.81 (1.16) |
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I regularly feel depressed and gloomy (recoded). | 3.43 (1.05) |
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I am often so sad that nothing can cheer me up (recoded). | 3.60 (0.87) |
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I am regularly nervous (recoded). | 3.65 (1.10) |
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I usually feel calm and composed. | 3.66 (0.84) |
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I feel happy most of the time. | 4.05 (1.01) |
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I am a little sick (recoded). | 3.72 (1.18) |
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I am as healthy as anyone I know. | 3.22 (1.04) |
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My health is excellent. | 3.28 (1.06) |
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I have been feeling bad lately (recoded). | 3.73 (1.05) |
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Have you experienced any physical pain in the past 4 weeks? | 3.67 (1.26) |
aDid your health condition limit you in any of the following activities last year? If so, for how long? Yes, longer than 3 months/Yes, less than 3 months/No → transposed to No (1)/Yes (2).
bA 5-point agreement scale ranging from “strongly disagree” to “strongly agree.”
cA 5-point scale ranging from “heavy pain” to “no pain.”
To test the first hypothesized relationships, we applied path analysis with Amos 23 (IBM Corporation). To obtain a comprehensive model fit, we included the suggested indices by Hair et al [
To test the hypothesized relationships, we started by examining the basic assumptions of path analysis. Normality, kurtosis, and skewness did not differ significantly from acceptable criteria, and there were no outliers or multicollinearity beyond what would theoretically be expected. The structural model with coefficients and variances explained is presented in
The first hypotheses concerning the internet access stages and outcomes (H1-H4) are supported, with the exception of H1c. Internet attitude has a negative direct path to internet health use, and the total effect is 0. For the other hypotheses, all direct and indirect paths are positive and significant. See
For the second set of hypotheses (concerning the health statuses), first
Structural model with path coefficients. Note: Path coefficients are significant at
Significant direct, indirect, and total effects (standardizes regression weights and significance).
Path | Direct effects | Indirect effects | Total effects | |||
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β | β | β | |||
Internet attitude → health outcome | .05 | .01 | .03 | .01 | .08 | .01 |
Material access → health outcome | .04 | .04 | .16 | .01 | .20 | .01 |
Internet skills → health outcome | .10 | .01 | .13 | .03 | .23 | .01 |
Internet health use → health outcome | .45 | .02 | N/Aa | N/A | .45 | .02 |
Internet attitude → material access | .14 | .02 | N/A | N/A | .14 | .02 |
Internet attitude → digital skills | .11 | .01 | .05 | .01 | .16 | .01 |
Internet attitude → internet health use | –.07 | .03 | .07 | .01 | .00 | .50 |
Material access → internet skills | .35 | .02 | N/A | N/A | .35 | .01 |
Material access → internet health use | .18 | .01 | .10 | .01 | .28 | .01 |
Internet skills → internet health use | .30 | .04 | N/A | N/A | .30 | .01 |
Physical functioning → internet attitude | .18 | .02 | N/A | N/A | .18 | .02 |
Physical functioning → material access | .13 | .01 | .03 | .01 | .16 | .02 |
Physical functioning → internet skills | .10 | .01 | .08 | .01 | .18 | .01 |
Physical functioning → internet health use | –.09 | .01 | .07 | .01 | –.02 | .62 |
Physical functioning → health outcomes | N/A | N/A | .03 | .12 | .03 | .12 |
Social functioning → internet attitude | –.09 | .01 | N/A | N/A | –.09 | .01 |
Social functioning → material access | .02 | .49 | –.01 | .01 | .01 | .77 |
Social functioning → internet skills | .08 | .03 | –.01 | .66 | .07 | .09 |
Social functioning → internet health use | .10 | .01 | .03 | .07 | .13 | .01 |
Social functioning → health outcomes | N/A | N/A | .06 | .02 | .06 | .02 |
Mental health → internet attitude | .11 | .02 | N/A | N/A | .11 | .02 |
Mental health → material access | –.09 | .02 | .02 | .01 | –.07 | .02 |
Mental health → internet skills | .01 | .80 | –.02 | .26 | –.01 | .74 |
Mental health → internet health use | –.22 | .01 | –.02 | .05 | –.24 | .01 |
Mental health → health outcomes | N/A | N/A | –.11 | .02 | –.11 | .02 |
Perceived health → internet attitude | –.04 | .36 | N/A | N/A | –.04 | .36 |
Perceived health → material access | .14 | .02 | –.01 | .31 | .13 | .02 |
Perceived health → internet skills | .10 | .03 | .04 | .01 | .14 | .02 |
Perceived health → internet health use | .17 | .01 | .07 | .02 | .24 | .02 |
Perceived health → health outcomes | N/A | N/A | .12 | .02 | .12 | .02 |
Physical pain → internet attitude | –.10 | .01 | N/A | N/A | .10 | .01 |
Physical pain → material access | –.07 | .01 | –.01 | .02 | –.08 | .01 |
Physical pain → internet skills | –.01 | .65 | –.04 | .01 | –.05 | .09 |
Physical pain → internet health use | –.02 | .65 | –.03 | .03 | –.05 | .19 |
Physical pain → health outcomes | N/A | N/A | –.04 | .02 | –.04 | .02 |
a N/A: not applicable.
We tested for the significance of the
Concerning age and internet access,
For education and internet access,
Direct path coefficient comparisons for age and education.
Path | Age<65 years | Age≥65 years | Low education level | High education level | ||||
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β | β | β | β | ||||
Internet attitude → health outcome | .06 | .01 | .03 | .46 | .03 | .27 | .08 | .02 |
Material access → health outcome | .04 | .18 | –.00 | .93 | .05 | .06 | –.01 | .74 |
Internet skills → health outcome | .04 | .12 | .11 | .02 | .07 | .01 | .12 | <.001 |
Internet health use → health outcome | .46 | <.001 | .42 | <.001 | .45 | <.001 | .48 | <.001 |
Internet attitude → material access | .13 | <.001 | .24 | <.001 | .21 | <.001 | .13 | .002 |
Internet attitude → internet skills | .11 | <.001 | .14 | .003 | .14 | <.001 | .01 | .77 |
Internet attitude → internet health use | –.08 | .003 | .08 | .10 | –.05 | .06 | –.07 | .08 |
Material access → internet skills | .28 | <.001 | .31 | <.001 | .36 | <.001 | .29 | <.001 |
Material access → internet health use | .16 | <.001 | .15 | .002 | .16 | <.001 | .21 | <.001 |
Internet skills → internet health use | .26 | <.001 | .23 | <.001 | .30 | <.001 | .25 | <.001 |
Physical functioning → internet attitude | .18 | <.001 | .19 | .01 | .21 | <.001 | .10 | .04 |
Physical functioning → material access | .08 | .03 | .13 | .08 | .10 | .01 | .16 | <.001 |
Physical functioning → internet skills | .08 | .01 | .02 | .80 | .10 | .01 | .10 | .04 |
Physical functioning → internet health use | –.10 | .003 | –.11 | .10 | –.08 | .04 | –.11 | .02 |
Social functioning → internet attitude | –.13 | <.001 | .03 | .68 | –.00 | .94 | –.25 | <.001 |
Social functioning → internet access | .05 | .21 | –.08 | .24 | –.06 | .15 | .19 | <.001 |
Social functioning → internet skills | .07 | .04 | .13 | .07 | .10 | .01 | .06 | .31 |
Social functioning → internet health use | .11 | .002 | .01 | .91 | .10 | .01 | .08 | .12 |
Mental health → internet attitude | .17 | <.001 | –.03 | .64 | .10 | .01 | .14 | .003 |
Mental health → material access | –.10 | .002 | .14 | .01 | –.08 | .02 | –.12 | .01 |
Mental health → internet skills | .01 | .71 | .12 | .02 | –.03 | .33 | .09 | .06 |
Mental health → internet health use | –.21 | <.001 | –.16 | .004 | –.21 | <.001 | –.22 | <.001 |
Perceived health → internet attitude | –.10 | .03 | .08 | .31 | –.04 | .45 | –.06 | .34 |
Perceived health → material access | .19 | <.001 | –.11 | .02 | .08 | .10 | .24 | <.001 |
Perceived health → internet skills | .12 | .01 | .08 | .26 | .11 | .01 | .09 | .16 |
Perceived health → internet health use | .18 | <.001 | .10 | .20 | .15 | <.001 | .20 | <.001 |
Physical pain → internet attitude | –.09 | .01 | –.12 | .04 | –.10 | .01 | –.11 | .02 |
Physical pain → material access | –.09 | .01 | –.03 | .59 | –.04 | .22 | –.13 | .01 |
Physical pain → internet skills | –.01 | .71 | –.00 | .94 | –.01 | .78 | –.02 | .63 |
Physical pain → internet health use | –.00 | .99 | –.11 | .05 | –.01 | .78 | –.04 | .44 |
This paper aimed to provide a comprehensive view of digital inequality in relation to different health statuses among the Dutch population. The study’s first goal was to reveal to what extent the process of internet access is important to obtain health outcomes. Internet attitude increases the likelihood of improving material access, the development of internet skills, and internet health use, suggesting that making online health apps attractive for larger segments of the population is an important objective. Material access, considered in this study as the diversity of the devices used, is highly relevant, as it has significant relationships with internet skills and internet health use. Individuals with different devices to connect to the internet everywhere and at all times of the day have more opportunities to develop internet skills and use online health apps. Internet skills are, in turn, required to use online health apps. The sequential nature of the access stages does not suggest that improving material access will automatically result in better internet skills or that a high level of internet skills will automatically result in a large variety of health-related internet use; all stages are, however, necessary conditions. The results furthermore revealed that all 4 access stages directly contribute to obtaining positive health outcomes, suggesting that to make online health care attainable for the general population, interventions should focus
The second goal of this paper was to reveal to what extent different health statuses among the general population relate to the internet access stages and thus to internet health outcomes. The results confirmed that digital inequality research would benefit from considering health as a predictor of internet attitude, material access, internet skills, internet health use, and health outcomes. However, a general conclusion is that we should go beyond single self-reported measures of health, as different health statuses among the general population make unique contributions to the different internet access stages:
Physical functioning contributes to internet attitude, material access, and internet skills, likely because physical limitations impact the process of taking up or learning how to use technologies (eg, in the case of smaller tablets or smartphones) [
Better social functioning contributes to better material access and higher levels of internet skills. The importance of social bonds to use technology has long been established [
Concerning mental health, the results revealed a positive contribution to internet attitude but a negative contribution to material access. An explanation might be that those suffering from mental health issues are more likely to experience excessive internet use, which is supported by the use of multiple devices to provide instant access at all times [
People who perceive their health as higher have greater levels of material access and internet skills. A possible explanation might be that higher health perceptions foster social interactions that are supported by material access and higher levels of internet skills in the case of online social networking. The higher use of online health information and services among those with higher health perceptions seems to be inconsistent with prior research [
Like poor physical functioning, physical pain negatively affects internet attitude and material access, suggesting that physical pain limits the use of certain devices and the process of learning how to use the internet.
In relation to our third goal, the general conclusion is that the contributions of the health statuses to the internet access stages differ for age and education. The main findings concerning age are that for seniors:
internet attitude plays a more important role in obtaining material access than for those aged under 65 years. An important reason for seniors not to go online is a less favorable attitude toward the internet [
mental health plays a larger role in obtaining material access and developing internet skills. This suggests that seniors with mental health issues have a relatively high need for support, a worthwhile finding as online health interventions can reduce their mental health problems [
perceived poor health hinders material access, suggesting that seniors who believe they are in poor health consider this as a barrier to interact with computer devices. This is a missed opportunity, as smartphones, tablets, or laptops might also be used as tools to enhance their perceived health [
The main findings concerning education are that for those with
internet attitude plays a larger role in obtaining material access, consistent with prior research that showed that education positively affects internet attitude [
physical functioning is relatively important for developing a favorable internet attitude. This might be explained by the fact that lower-educated individuals are more likely to suffer from limitations in physical functioning [
social functioning plays a relatively important role in the development of internet skills and the use of online health information and services. Unfortunately, lower-educated individuals are less likely to perceive higher levels of support in relation to health [
perceived health is relatively important for the development of internet skills. This suggests that lower-educated people who believe they are in poor health are more in need for skills training to make use of online health information and services as compared to their higher-educated counterparts.
A few limitations should be noted. The first is the study’s cross-sectional design, which did not allow confirmation of causal inferences about the association between health statuses and internet access. Furthermore, we focused on the general population, and the baseline status of the different health statuses varied slightly. Effects might have been stronger when targeting more people with serious conditions in relation to the 5 health statuses, although that was not the purpose of this study. Finally, we encourage further qualitative research to focus on the barriers and facilitators for people with different health statuses when using the internet to support their health needs.
To obtain positive health outcomes and make online health care attainable for the general population, interventions should focus simultaneously on internet attitude, material access, internet skills, and internet health apps. However, issues of equality need to be considered and digital inequality research would benefit from considering health as a predictor of all 4 internet access stages and health outcomes. Furthermore, studies among the general population should go beyond single self-reported measures of health as physical functioning, social functioning, mental health, perceived health, and physical pain all demonstrated unique contributions to the internet access stages. The general conclusion is that different health statuses affect internet access stages in different ways and, consequently, the health-related opportunities that the internet offers. Further complicating this issue is that such influence is moderated by age and education.
comparative fit index
root mean square error of approximation
standardized root mean residual
Tucker-Lewis index
None declared.