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Electronic health (eHealth) services may help people obtain information and manage their health, and they are gaining attention as technology improves, and as traditional health services are placed under increasing strain. We present findings from the first representative, large-scale, population-based study of eHealth use in Norway.
The objectives of this study were to examine the use of eHealth in a population above 40 years of age, the predictors of eHealth use, and the predictors of taking action following the use of these eHealth services.
Data were collected through a questionnaire given to participants in the seventh survey of the Tromsø Study (Tromsø 7). The study involved a representative sample of the Norwegian population aged above 40 years old. A subset of the more extensive questionnaire was explicitly related to eHealth use. Data were analyzed using logistic regression analyses.
Approximately half (52.7%; 9752/18,497) of the respondents had used some form of eHealth services during the last year. About 58% (5624/9698) of the participants who had responded to a question about taking some type of action based on information gained from using eHealth services had done so. The variables of being a woman (OR 1.58; 95% CI 1.47-1.68), of younger age (40-49 year age group: OR 4.28, 95% CI 3.63-5.04), with a higher education (tertiary/long: OR 3.77, 95% CI 3.40-4.19), and a higher income (>1 million kr [US $100,000]: OR 2.19, 95% CI 1.77-2.70) all positively predicted the use of eHealth services. Not living with a spouse (OR 1.14, 95% CI 1.04-1.25), having seen a general practitioner (GP) in the last year (OR 1.66, 95% CI 1.53-1.80), and having had some disease (such as heart disease, cancer, asthma, etc; OR 1.29, 95% CI 1.18-1.41) also positively predicted eHealth use. Self-rated health status did not significantly influence eHealth use. Taking some action following eHealth use was predicted with the variables of being a woman (OR 1.16, 95% CI 1.07-1.27), being younger (40-49 year age group: OR 1.72, 95% CI 1.34-2.22), having a higher education (tertiary/long: OR 1.65, 95% CI 1.42-1.92), having seen a GP in the last year (OR 1.58, 95% CI 1.41-1.77), and having ever had a disease (such as heart disease, cancer or asthma; OR 1.26, 95% CI 1.14-1.39).
eHealth appears to be an essential supplement to traditional health services for those aged above 40 years old, and especially so for the more resourceful. Being a woman, being younger, having higher education, having had a disease, and having seen a GP in the last year all positively predicted using the internet to get health information and taking some action based on this information.
Online resources, including the use of search engines, social media, apps, and online video services, are becoming increasingly important for people in their everyday lives [
Electronic health (eHealth) is the use of Information and Communication Technology, such as the internet, to enable or improve health care [
The aging population in many Western countries is likely to increase demands on health services. An increasing number of people with chronic illnesses are likely to stretch the capacity of health services further, and as many as 45% of US adults have one or more chronic illnesses [
It remains unclear how eHealth influences traditional health service use in Norway, whether eHealth tools and services can replace traditional services or whether eHealth tools and services should be added to existing health service use [
While prior studies have suggested that there are social divisions in the use of the internet for health purposes, many of these have been based on web-panels and other samples that might not have been fully representative of the general population [
In the United States, at least two larger studies have used representative samples: the Health Information National Trends Survey (HINTS) study [
Nordic countries, especially the subarctic regions, are sparsely populated, and access to specialist health services may be limited in rural areas. eHealth services could be particularly relevant for stakeholders and policymakers in sparsely populated, rural, and remote areas [
The seventh, population-based Tromsø Study included a questionnaire about the use of eHealth. In a series of four papers, we explore data from this questionnaire and how the use of eHealth related to a range of other variables that were measured in the Tromsø Study. In the first paper (this paper), we present our main findings regarding the characteristics of the participants and their use of eHealth. In the present study, we examined the use of eHealth in the population above 40 years of age, predictors of eHealth use, and predictors of participants acting following their use of eHealth services. In the second paper [
The Tromsø Study is a population-based, longitudinal health study conducted by the University of Tromsø in cooperation with several other Norwegian public agencies [
As part of a more extensive questionnaire on health and illness (in total more than 300 questions), the participants completed a questionnaire with data about their use of different types of eHealth services. The following question was asked:
How often during the last year have you used the following Internet-services for information and advice on health and disease issues: Applications (‘Apps’) for smart phone or tablet?, Search engines (like Google)?, Social media (like Facebook)?, Video services (like YouTube)?
For each item, it was possible to respond either “never,” “once,” “a few times,” or “often.” Those who responded that they had used at least one of the services were subsequently asked the following question:
If you during the last year have used Internet-services for information and advice on health and disease issues, based on the information you found on the Internet: Have you decided to go to the doctor?, Have you decided not to go the doctor?, Have you discussed the information with a doctor?, Have you changed your medication without consulting a doctor?, Have you been unsure whether the treatment you have received is correct?, Have you decided to seek out complementary or alternative treatment?, Have you made lifestyle changes?, Have you felt anxiety?, Have you felt reassured?, Have you felt more knowledgeable?, Have you felt more confused?
For each of the items, it was possible to respond either “never,” “once,” “a few times,” or “often.”
The questions and their respective response options are also available online at the Tromsø Study website [
Variables obtained from the Tromsø 7 questionnaire included gender, age, education, occupation/work status, household income, whether the participant had seen a GP in the last year, assessment of own health, living status with a spouse, self-reported diseases, and use of the internet for finding health information. We excluded participants who had missing information on the use of the internet for health information searching (through search engines, social media, apps, or video services; n=384), and those with missing information on any of the other variables: gender, age, education, occupation, household income, GP consultation, assessment of own health, living status with spouse, and self-reported diseases (n=2202). The final analytical sample consisted of 18,497 participants (9138 men and 9359 women).
We also carried out separate analyses, including those who took health decisions (acted or not acted) following information gathering from online services (search engines, social media, apps, or video services). This subcohort included 9698 participants (4243 men and 5455 women), who had given information on these variables.
Information on the use of the internet for health and participants' self-reported diseases was taken from the Tromsø 7 questionnaires. Self-reported disease conditions included: high blood pressure, heart attack, heart failure, atrial fibrillation, angina, stroke, diabetes, kidney disease, bronchitis, asthma, cancer, rheumatoid arthritis, arthrosis, migraine, psychological problems, and chronic pain. The options on these questions were “no,” or “yes,” or “yes, previously.”
The information on those (n=9698) who completed questions regarding the effect of using internet resources for health information or advice (through search engines, social media, health apps, or video services) was used in the subcohort analyses. The responses included in the present analyses were: if they had decided to visit (or not visit) the doctor, discussed information found online with a doctor, changed medication without consulting a doctor, if they had been unsure about whether the treatment they had received was correct, if they had made lifestyle changes, and if they had sought alternative or complementary treatment. The options were “never,” “once,” “a few times,” or “often.”
We performed multivariable logistic regression analysis with the use of the internet for health information as the dichotomous dependent variable, and gender, age, education, occupation/work status, household income, GP consultation, assessment of own health, living status with spouse, and self-reported diseases as the independent variables. The use of the internet for health information was dichotomized into never/ever by grouping those who had never used any of the resources (search engines, social media, health apps, or video services) as never, and those who had used at least one of the resources for health advice as ever. Similarly, we grouped participants who never had any of the disease conditions as never, and those participants who previously or currently had at least one condition as ever. Age was grouped into four groups: 40-49, 50-59, 60-69, and 70 years old and older. Education was grouped into four groups: primary or partly secondary education (up to 10 years of school), upper secondary education (minimum of three years), short tertiary education (college or university for less than four years), and long tertiary education (college or university for four years or more). Occupation/work status was categorized into works full time, works part-time, unemployed, housekeeper, retired, student/in military service, on disability benefit or work assessment allowance, and on family income supplement. Household income in kr per annum: less than 250,000 (<US $25,000), 250,000-450,000 (US $25,000-$45,000), 451,000-750,000 (US $45,100-$75,000), 751,000-1,000,000 (US $75,100-$100,000), and more than 1,000,000 (>US $100,000). Living status with a spouse and consultation with the GP (during the last year) were either yes or no. Assessment of own health was either very bad, bad, neither good nor bad, good, or excellent.
We checked for possible interactions between education and occupation/work status, education and income, and occupation/work status and disease condition. We further explored the relationship between the use of the internet for health information and the independent variables stratified by disease conditions (never/ever).
All
All participants gave written informed consent. The Regional Committee for Medical and Health Research Ethics approved the study (REK Nord, reference 2014/940).
Regarding age, about 60% (11,036/18,497) of the participants were within the 40-59 years old age range. Only about 15% (2759/18,497) were 70 years old or older (see
For education, occupation/work status, and income, about half of the participants had tertiary education while the other half had either primary or secondary school education. The respondents were mostly in full time employment (60%; 11,188/18,497) or retired (21%; 3886/18,497). About half (51%; 9474/18,497) earned more than 750,000 kr (US $75,000) per annum, while less than 5% (890/18,497) earned 250,000 (US $25,000) or less.
A clear majority of the respondents (77.3%; 14,305/18,497) stated they were living with a spouse. As for health and psychological variables, most of the participants (80%; 14,781/18,497) had had at least one appointment with their GP during the last year, even though 70% (12,901/18,497) rated their health as excellent or good. About 73% (13,552/18,497) had had at least one of the diseases of interest in this study (see
One of the main findings of this study was that 52.7% (9752/18,497) of the respondents in the last year had used at least one eHealth service (ie, search engine, social media, apps, or video services) to get information and advice about health and illness (see
In the multivariable analyses, we found that women had 1.58 times the odds of using internet resources (at least one of these: search engine, social media, apps, or video services) for health information when compared to men (OR 1.58, 95% CI 1.47-1.68). Also, educational level and household income positively predicted the use of the internet for health information searching. Those who had a long tertiary education had 3.77 times the odds of using internet resources to look for health information compared to those who only had primary or partly secondary school education (OR 3.77, 95% CI 3.40-4.19). Similarly, those who earned the most were significantly at increased odds of using internet resources (OR 2.19, 95% CI 1.77-2.70) when compared to those who earned the least. Occupation or work status did not predict the use of internet resources for health information. However, those on disability benefits and other family welfare benefits had 1.71 times the odds of using the internet for health information when compared to those who worked full time (OR 1.71, 95% CI 1.05-2.78).
In regard to living with a spouse, those participants had 0.88 times the odds of using the internet for health information when compared to those who were not living with a spouse (OR 0.88, 95%CI 0.80-0.97). We also found that those who had consulted their GP in the last year had 1.66 times the odds of using internet resources for health information compared to those who had not consulted their GP. Similarly, those who had ever had at least one of the diseases of interest were at increased odds of using the internet for health information (OR 1.29, 95% CI 1.18-1.41). Intriguingly, assessment of own health did not predict the use of internet resources for health information searching (see
About 58% (5624/9696) of those who answered this question took some form of action after having obtained information about health and illness on the internet (see
In the multivariable analyses of the subcohort (n=9698) who made health decisions following use of the internet for health information searching, we found that similar to the use of internet resources for health information, the odds of making health-related decisions following use decreased with age. Those aged 70 years old and above had nearly half the odds of making health-related decisions/actions when compared to those that were 40-49 years old (OR 0.58, 95% CI 0.45-0.75). Also, we found that women had 1.16 times the odds of making health-related decisions following the use of internet resources when compared to men (OR 1.16, 95% CI 1.07-1.27).
Regarding education and income, educational level positively predicted making health-related decisions following the use of internet resources for health information. Those with a long tertiary education had 1.65 times the odds of making health-related decisions following use when compared to those who had primary or partly secondary school education (OR 1.65, 95% CI 1.42-1.92). However, household income did not significantly predict health-related decision-making following the use of internet resources.
Unlike in the use of the internet for health information, not living with a spouse did not significantly predict health-related decision-making following the use of internet resources. Additionally, those who had consulted their GP in the last year (OR 1.58, 95% CI 1.41-1.77) and those who had had at least one of the diseases of interest (OR 1.26, 95% CI 1.41-1.39) had increased odds of taking health actions following internet resources use (see
We found that approximately half of the respondents had used some form of eHealth during the last year. This figure is lower than what has been suggested in some prior studies [
Younger age was a significant positive predictor of eHealth use, in line with the findings of several prior studies [
Some prior studies have suggested higher rates of use in the older age groups than we did in the present study [
We also found that being a woman was a significant predictor of use, in line with previous findings [
We found that having a higher education positively predicted the use of eHealth. Higher education has also previously been shown to predict eHealth use [
A review study has found that patients’ engagement with digital health decreases with higher age and lower health literacy [
While loneliness is known to increase the risk of death [
Health and psychological variables have, to varying degrees, been found to predict health-related internet use [
The finding that about 6/10 acted based on information gained from using eHealth services suggests that health information on the internet plays a surprisingly important role in people’s decision-making processes regarding their health care. The action taken included deciding to see a doctor or not to see a doctor. It is not surprising that health information may help people make such a decision, and many people probably search for health information online to get a basis for deciding whether they need professional help or not.
Other actions taken were discussing the information with a doctor, changing medication without talking with a doctor, deciding to see an alternative practitioner, or changing lifestyle. Prior studies have suggested that many patients obtain information from the internet that they want to discuss with their doctor [
Many of the same variables were of importance to acting on the information as to accessing it in the first place, and being a woman, being of younger age, having higher education, having seen a GP in the last year, and having ever had an illness all predicted taking some form of action. Searching for information and acting on this information are qualitatively different processes. However, both behaviors are determined by many of the same variables. Household income was not a predictor of acting on the information, possibly because health care is covered by national insurance in Norway. Thus, searching for information and acting on this information were predicted by mostly the same variables.
eHealth was associated with the use of traditional health services (ie, having seen the GP during the last year). It is possible that using online health information may increase traditional health service consumption. We know that health-related information on the internet, on social media, and video services may be wrong, misleading, or biased [
We have found that higher age, being male, and having lower education, not having an illness, and not having seen a GP in the last year were associated with a lower use of eHealth services. We do not know why some subgroups used the internet less for health purposes. We suggest that a lower degree of engagement in health, in general, might explain some of the differences in eHealth use. Furthermore, some may not access eHealth services because they are unaware of the service [
This is the first representative, large-scale, population-based study of eHealth use in Norway. We have given a representative picture of the use of eHealth in a population 40 years old and older, predictors of eHealth use, and predictors of taking action following the use of eHealth services. There are important differences in the organization and funding of health care in the United States, Norway, and much of Europe. Despite these differences, lower age, female gender, higher educational level, and having a chronic illness seemed to predict increased eHealth use both in the United States and in Norway.
There are some central limitations to this study. There might be a self-selection bias because not everyone who was invited chose to participate. As this study was based on cross-sectional data obtained from questionnaires, there is a possibility of recall bias (ie, that participants either underestimated or overestimated their use of eHealth or their actions taken). However, the validity and reproducibility of self-reported (ie, recalled) findings from the Tromsø Study have been reported as quite high and of sufficient quality for epidemiological research [
About half of respondents used some form of eHealth in the last year, and about 6/10 of this half used the information to take some form of action. The use of eHealth was associated with the use of traditional health services. This study has provided new knowledge about the importance of the internet, social media, apps, and online videos for health information and how this information impacts patients and the general public. While one might hope that eHealth services can benefit those most in need, the present study suggests that it is those with the most resources, the highly educated and well-off, that consume eHealth services the most. Being in poor health did not predict the use of online health information. Clinicians should be aware that many patients above 40 years of age use eHealth to find information about health and illness, and that they also often act on this information [
Study tables.
complementary and alternative medicine
electronic health
European Union
general practitioner
Health Information National Trends Survey
seventh survey of the Tromsø Study
We thank the organizers, management, and the technical staff of Tromsø 7 for their valuable work in preparing and collecting the data. Above all, we thank the residents of Tromsø. Their willingness to participate is fundamental to our research. This research was made possible by a grant from the Research Council of Norway to the Norwegian Centre for eHealth Research, University Hospital of North Norway, Grant No 248150/O70, and by UiT The Arctic University of Norway. The publication charges for this article have been funded by a grant from the Publication Fund of UiT The Arctic University of Norway.
None declared.