This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), 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.
Polish society is benefiting from growing access to the Internet, but the use of advanced e-services is still limited. The provision of Internet-based health services depends not only on the penetration of the Internet into society, but also on the acceptance of this technology by potential users.
The main objective of this study was focused on the assessment of predictors of acceptance of Internet use for provision of health services (eg, sociodemographic status, the use of information technologies, and consumption of health care services) among households in Poland.
The study was based on a secondary analysis of the dataset from the 2011 Social Diagnosis survey (a biannual survey conducted since 2001 about economic and non-economic aspects of household and individual living conditions in Poland). Analysis of the questionnaire results focused on the situations of the households included in the study. The predictors for 2 outcome variables describing the acceptance of households for Internet use for provision of a full health care service, or at least access to information and download of required forms, were assessed using multivariate logistic regression.
After excluding those households that would not consider the use of health care services or for which predictor variables assumed missing values, the final analyses were conducted on data from 8915 households. Acceptance of the use of the Internet for provision of full health care services in Polish households was significantly higher among households in urban locations with ≥ 200,000 inhabitants than among households in rural areas; it was also higher with salaried employment as the source of income than with self-employment in agriculture (odds ratio [OR] = 0.53, 95% CI 0.40 - 0.70), retirement pension (OR = 0.46, 95% CI 0.39 - 0.54), disability pension (OR = 0.48, 95% CI 0.34 - 0.68), or with several simultaneous income sources (OR = 0.66; 95% CI 0.57 - 0.79). Furthermore, acceptance of Internet-based health care was higher in households with a higher monthly net income per capita (OR = 2.11, 95% CI 1.75 - 2.53 for households from the lowest and the highest income interval), among households with > 1 child aged < 15 years (OR = 1.38, 95% CI 1.20 - 1.59), among households with at least some books (with OR = 3.33, 95% CI 2.39 - 4.64 for household with no books and those with over 500 books). Acceptance was also higher in households with a computer (OR = 1.86, 95% CI 1.35 - 2.56), Internet access (OR = 1.95, 95% CI 1.37 - 2.76), and Internet access for a longer duration (OR = 1.36, 95% CI 1.06 - 1.75 and OR = 1.81, 95% CI 1.40 - 2.33 for households with access < 1 year versus those with access for 1-5 years and > 5 years, respectively). Greater self-declared confidence in using technology was also associated with higher acceptance of the Internet for health care services (OR = 2.94, 95% CI 2.21 - 3.91 for the least confident households versus those with the highest confidence). Furthermore, recent use of health care services increased acceptance of using the Internet for at least some health-related services (OR = 1.49, 95% CI 1.16 - 1.91), but not for full provision of online health care services (OR = 1.20, 95% CI 0.92 - 1.55). Neither the hospitalization of a member of a household nor the opinion about satisfying health care needs of a household affected the degree of acceptance.
The acceptance of health care services through the Internet is higher in households from larger cities, with stable income from an employee salary, as well as with higher income levels per capita. Furthermore, general computer and Internet use in the household influenced the perception of eHealth. Paradoxically, the use of health care services or the level of satisfaction with the coverage of the household’s health needs has a limited influence on acceptance of Internet-based health care services.
Internet use has increased considerably in Poland over the past decade. The percentage of households with Internet access when Poland joined the European Union (EU) in 2004 was 26% [
User acceptance is a key condition for wide implementation of innovative information and communication technology (ICT) solutions, including eHealth [
The main goal of this study was a secondary analysis of data collected during the most recent Social Diagnosis study (2011). The scope of the study is broad and covers many areas, including household living conditions, individual quality of life, the state of civil society and economic status, the usage of new communication technology, and social exclusion. The methodology and primary analysis of the collected data was published by Czapinski et al [
The data included in the current analysis were obtained from households included in the Social Diagnosis survey in 2011. The data were collected using 2 questionnaires. The first questionnaire, covering household structure and living conditions, and the sociodemographic characteristics of its members, was completed by professional canvassers employed by the Central Statistical Office who interviewed the household representatives with the most complete knowledge of their circumstances. The second questionnaire was designed to be completed by all household members aged ≥ 16 years. The selection of households for participation in the survey was the result of a 2-level stratified sampling. It was preceded by stratification of households according to
The analysis described in this paper was conducted on data originating in the questionnaire about household circumstances. In section M of the questionnaire, the items related to the use of the Internet to accomplish specific types of services were included, such as vehicle registration, handling cases related to personal documents (eg, identity cards), and business activities. One of the items enquired about the household’s view on using the Internet to provide health-related or health care services.
The household representative answering this item could select one of 4 responses: (1) “I do not need the Internet for this service,” (2) “I would like to obtain information or download the required forms online and then proceed in the traditional way,” (3) “I would like to be able to complete the entire transaction online (including payment),” and (4) “I do not anticipate the use of such a service.” Only cases with a valid response to this item were extracted from the database containing all the data collected in 2011 and used for further analyses (12,015 of 12,386 households) [
Two outcome variables for this item were defined for the logistic regression analysis. The first outcome variable assumed the value
From the 2011 data, 14 variables were derived and included in the logistic regression procedure as predictors. The variables were selected according to their potential influence on the acceptance of the use of the Internet for health care services.
Statistical analysis was conducted using the Epi Info version 3.5.4 software (Epi Info, Centers for Disease Control and Prevention, Atlanta, GA, USA). Descriptive statistics were calculated for all variables. Logistic regression was performed in order to assess potential predictors for the acceptance of the use of the Internet for provision of health care services. All cases with missing values (1400/10,315) for any of the predictor variables included in the model were excluded from the analysis. Finally, multivariate logistic regression was calculated on the dataset of 8915 cases.
The frequencies for the categorical variables are shown in
The characteristics of households included in the multivariate logistic regression analysis (N = 8915).
Characteristic | n | % | |
|
|
|
|
|
No | 6259 | 70.21 |
|
Yes | 2656 | 29.79 |
|
|
|
|
|
No | 4895 | 54.91 |
|
Yes | 4020 | 45.09 |
|
|
|
|
|
Rural | 3549 | 39.81 |
|
Urban <20,000 | 1167 | 13.09 |
|
Urban 20,000-100,000 | 1803 | 20.22 |
|
Urban 100,000-200,000 | 611 | 6.85 |
|
Urban 200,000-500,000 | 926 | 10.39 |
|
Urban >500,000 | 859 | 9.64 |
|
|
|
|
|
Employment (wages and salaries) | 3976 | 44.60 |
|
Self-employment in agriculture | 404 | 4.53 |
|
Self-employment outside agriculture | 384 | 4.31 |
|
Retirement pension | 2499 | 28.03 |
|
Disability pension | 468 | 5.25 |
|
Non-employment source other than retirement or disability pensions | 264 | 2.96 |
|
Numerous parallel income sources | 920 | 10.32 |
|
|
|
|
|
< 700 | 2106 | 23.62 |
|
≥ 700 and < 1000 | 2284 | 25.62 |
|
≥ 1000 and < 1500 | 2101 | 23.57 |
|
≥ 1500 | 2424 | 27.19 |
|
|
|
|
|
Worsened | 2883 | 32.34 |
|
Unchanged | 5070 | 56.87 |
|
Improved | 962 | 10.79 |
|
|
|
|
|
No | 7949 | 89.16 |
|
Yes | 966 | 10.84 |
|
|
|
|
|
0 | 6075 | 68.14 |
|
1 | 1561 | 17.51 |
|
2 | 967 | 10.85 |
|
>2 | 312 | 3.50 |
|
|
|
|
|
None | 1007 | 11.30 |
|
≤ 25 | 2034 | 22.81 |
|
26-50 | 2028 | 22.75 |
|
51-100 | 1862 | 20.89 |
|
101-500 | 1505 | 16.88 |
|
>500 | 479 | 5.37 |
|
|
|
|
|
No | 3041 | 34.11 |
|
Yes | 5874 | 65.88 |
|
|
|
|
|
No | 3448 | 38.68 |
|
Yes | 5467 | 61.32 |
|
|
|
|
|
< 1 year | 3693 | 41.42 |
|
1-5 years | 2940 | 32.98 |
|
>5 years | 2282 | 25.60 |
|
|
|
|
|
Strongly disagree | 2450 | 27.48 |
|
Somewhat disagree | 2496 | 28.00 |
|
Neither agree nor disagree | 1710 | 19.18 |
|
Somewhat agree | 1922 | 21.56 |
|
Strongly agree | 337 | 3.78 |
|
|
|
|
|
No | 419 | 4.70 |
|
Yes | 8496 | 95.30 |
|
|
|
|
|
No | 6519 | 73.12 |
|
Yes | 2396 | 26.88 |
|
|
|
|
|
Worsened | 2391 | 26.82 |
|
Unchanged | 6309 | 70.77 |
|
Improved | 215 | 2.41 |
a The median and quartile values of monthly household net income per capita were calculated for the initial set of 12,015 households with valid data on the acceptance of Internet use for the provision of health services (median 1000 Polish zlotys [PLN], lower quartile 700 PLN, and upper quartile 1500 PLN). These values were used to determine 4 intervals for categorizing monthly household net income per capita. 1 PLN = US $0.31 (mid-market rate November 19, 2012).
b Yes: at least one member of the household owned a personal computer or mobile computer (eg, notebook, laptop, iPad, or tablet); no: no personal or mobile computer in a household.
c Yes: the household used health care services funded by the National Health Fund or paid out of pocket or paid by employer in past year; no: the household did not use health care services in the past year.
d Yes: at least one member of the household was admitted to hospital in past year; no: no hospitalization of members of household in past year.
Regarding computer use, 65.88% of households had a personal or mobile computer, and 61.32% had Internet access. Only 25.60% of households had Internet access for more than 5 years. Approximately one-quarter of households (25.34%, 2259/8915) felt that they were “up-to-date with modern technologies.”
Most households (95.30%) declared that their members used health care services with 26.88% having members of their household admitted to hospital in the preceding year. In the opinion of 70.77% of households, the coverage of their health needs had not changed in comparison with 2 years ago, and had improved in only 2.41% of households.
Less than half of the households (45.09%) included in the analysis accepted Internet use for full or at least partial (access to information and document download) delivery of health care services. The percentage of households expressing an opinion in favor of Internet use for complete provision of health care services was 29.79% (2656/8915).
The results of the analysis revealed that predictors of the acceptance of the use of the Internet for full provision of health care services included: monthly household income per capita, place of residence, number of children aged < 15 years, source of income, reception of aid from external sources (social care), availability of a computer (PC or mobile) in a household, Internet access and its duration, opinion about being up-to-date with modern technologies, and the number of books in the household.
The acceptance of the use of the Internet for full health care services, or for at least access to information and downloading documents, was predicted by the same variables and additionally by the use of health care services during the past year. The odds ratios (ORs), confidence intervals (CIs), and
The results of multivariate logistic regression model for factors affecting the acceptance of Internet-based health care services.
Variable | Acceptance of reception of health services by the Internet | ||||
|
Full service provision | Full service provision or only access to information and forms | |||
|
Odds ratio |
|
Odds ratio |
|
|
|
|
< .001 |
|
< .001 | |
|
Rural | 1 |
|
1 |
|
|
Urban < 20,000 | 0.92 (0.77 - 1.09) | .33 | 0.93 (0.79 - 1.09) | .36 |
|
Urban 20,000-100,000 | 1.13 (0.97 - 1.31) | .11 | 1.23 (1.06 - 1.42) | .005 |
|
Urban 100,000-200,000 | 0.96 (0.77 - 1.19) | .68 | 1.13 (0.92 - 1.40) | .24 |
|
Urban 200,000-500,000 | 1.57 (1.31 - 1.89) | < .001 | 1.63 (1.35 - 1.97) | < .001 |
|
Urban > 500,000 | 1.96 (1.61 - 2.37) | < .001 | 2.42 (1.97 - 2.97) | < .001 |
|
|
< .001 |
|
< .001 | |
|
Employment (wages and salaries) | 1 |
|
1 |
|
|
Self-employment in agriculture | 0.53 (0.40 - 0.70) | < .001 | 0.61 (0.48 - 0.78) | < .001 |
|
Self - employment outside agriculture | 0.94 (0.75 - 1.19) | .62 | 1.04 (0.81 - 1.34) | .74 |
|
Retirement pension | 0.46 (0.39 - 0.54) | < .001 | 0.47 (0.40 - 0.54) | < .001 |
|
Disability pension | 0.48 (0.34 - 0.68) | < .001 | 0.53 (0.40 - 0.71) | < .001 |
|
Non-employment source other than retirement pensions or disability payment | 1.05 (0.74 - 1.48) | .79 | 0.99 (0.72 - 1.37) | .97 |
|
Numerous parallel income sources | 0.66 (0.57 - 0.79) | < .001 | 0.70 (0.60 - 0.83) | < .001 |
|
|
< .001 |
|
< .001 | |
|
< 700 | 1 |
|
1 |
|
|
≥ 700 and < 1000 | 1.38 (1.17 - 1.63) | < .001 | 1.25 (1.08 - 1.49) | .004 |
|
≥ 1000 and < 1500 | 1.62 (1.36 - 1.94) | < .001 | 1.41 (1.19 - 1.67) | < .001 |
|
≥ 1500 | 2.11 (1.75 - 2.53) | < .001 | 1.70 (1.42 - 2.03) | < .001 |
|
|
.56 |
|
.93 | |
|
Worsened | 1 |
|
1 |
|
|
Unchanged | 0.84 (0.74 - 0.95) | .009 | 0.78 (0.69 - 0.88) | < .001 |
|
Improved | 0.98 (0.81 - 1.17) | .79 | 1.12 (0.93 - 1.36) | .23 |
|
|
.02 |
|
.045 | |
|
No | 1 |
|
1 |
|
|
Yes | 1.18 (0.97 - 1.44) | .09 | 1.14 (0.95 - 1.37) | .16 |
|
|
< .001 |
|
< .001 | |
|
0 | 1 |
|
1 |
|
|
1 | 1.38 (1.20 - 1.59) | < .001 | 1.38 (1.20 - 1.59) | < .001 |
|
2 | 1.33 (1.12 - 1.58) | .001 | 1.38 (1.16 - 1.64) | < .001 |
|
> 2 | 1.41 (1.06 - 1.88) | .018 | 1.31 (1.00 - 1.73) | .05 |
|
|
< .001 |
|
< .001 | |
|
None | 1 |
|
1 |
|
|
≤ 25 | 1.46 (1.11 - 1.92) | .007 | 1.38 (1.10 - 1.74) | .005 |
|
26-50 | 1.47 (1.12 - 1.93) | .006 | 1.59 (1.26 - 1.99) | < .001 |
|
51-100 | 1.72 (1.30 - 2.26) | < .001 | 1.91 (1.52 - 2.40) | < .001 |
|
101-500 | 2.07 (1.56 - 2.74) | < .001 | 2.36 (1.86 - 3.01) | < .001 |
|
> 500 | 3.33 (2.39 - 4.64) | < .001 | 3.46 (2.52 - 4.75) | < .001 |
|
|
< .001 |
|
< .001 | |
|
No | 1 |
|
1 |
|
|
Yes | 1.86 (1.35 - 2.56) | < .001 | 2.14 (1.66 - 2.76) | < .001 |
|
|
< .001 |
|
< .001 | |
|
No | 1 |
|
1 |
|
|
Yes | 1.95 (1.37 - 2.76) | < .001 | 1.72 (1.27 - 2.32) | < .001 |
|
|
< .001 |
|
< .001 | |
|
< 1 year | 1 |
|
1 |
|
|
1-5 years | 1.36 (1.06 - 1.75) | .02 | 1.59 (1.26 - 2.01) | < .001 |
|
> 5 years | 1.81 (1.40 - 2.33) | < .001 | 2.02 (1.58 - 2.57) | < .001 |
|
|
< .001 |
|
< .001 | |
|
Strongly disagree | 1 |
|
1 |
|
|
Rather disagree | 1.31 (1.11 - 1.55) | .002 | 1.23 (1.06 - 1.43) | .006 |
|
Neither agree nor disagree | 1.67 (1.40 - 2.00) | < .001 | 1.78 (1.52 - 2.09) | < .001 |
|
Rather agree | 1.77 (1.49 - 2.10) | < .001 | 1.73 (1.47 - 2.04) | < .001 |
|
Strongly agree | 2.94 (2.21 - 3.91) | < .001 | 2.92 (2.13 - 4.00) | < .001 |
|
|
.22 |
|
.002 | |
|
No | 1 |
|
1 |
|
|
Yes | 1.20 (0.92 - 1.55) | .18 | 1.49 (1.16 - 1.91) | .002 |
|
|
.60 |
|
.31 | |
|
No | 1 |
|
1 |
|
|
Yes | 1.05 (0.93 - 1.18) | .47 | 0.95 (0.85 - 1.07) | .41 |
|
|
.59 |
|
.95 | |
|
Worsened | 1 |
|
1 |
|
|
Unchanged | 1.00 (0.88 - 1.15) | .95 | 1.01 (0.89 - 1.14) | .92 |
|
Improved | 1.22 (0.87 - 1.70) | .25 | 1.07 (0.75 - 1.52) | .73 |
Households from urban areas with at least 200,000 inhabitants were more likely to accept the use of the Internet for health care services (for both variants of the outcome variable). In addition, households with a retirement or illness pension, farmer’s income, or several sources of income were less inclined to accept the use of the Internet for this purpose than those with an employee’s salary as the main source of income. Internet acceptance also depended on monthly household net income per capita, with growing acceptance at higher income levels (in comparison to values below the lower quartile). The OR for the outcome variable assuming acceptance of full health care services provided online were 1.38 (95% CI 1.17 - 1.63), 1.62 (95% CI 1.36 - 1.94), and 2.11 (95% CI 1.75 - 2.53), respectively for income levels.
The presence of 1 or 2 children aged < 15 years increased Internet acceptance of health care services in comparison to households without children in that age range. The values of OR for full provision of the service in the Internet were 1.38 (95% CI 1.20 - 1.59), 1.33 (95% CI 1.12 - 1.58), and 1.41 (95% CI 1.06 - 1.88) for 1, 2, and > 2 children in a household, respectively.
The reception of aid from external services, presumably from social care, was associated with both outcome variables in the general multivariate regression model. However, in the model with specified dummy variables derived from the main variables, this significant relationship was not maintained.
Households with at least some books revealed a higher acceptance of the use of the Internet for health care provision in comparison to households with no books at all. This relationship was valid for both outcome variables. Both outcome variables showed a significant association with the availability of a personal or mobile computer in a household, with OR = 1.86 (95% CI 1.35 - 2.56) and OR = 2.14 (95% CI 1.66 - 2.76) for full and at least partial acceptance of the Internet for the provision of health care services, respectively. Access to the Internet and duration of Internet access lasting at least 1 year increased the probability of acceptance of full online health care services in comparison to households without Internet access or access of less than 1 year.
Self-confidence in being up-to-date with modern technologies was associated with higher acceptance. The difference between households with the least confidence and those being less up-to-date, undecided, or confident (rather or strongly agree) was statistically significant, with the outcome variable assuming full service provided online OR = 1.31 (95% CI 1.11 - 1.55), OR = 1.67 (95% CI 1.40 - 2.00), OR = 1.77 (95% CI 1.49 - 2.10), and OR = 2.94 (95% CI 2.21 - 3.91), respectively.
The use of health care services or admission to hospital of a member of a household in the preceding year did not influence acceptance of the use of the Internet for the provision of full health care services. The use of health care services in the preceding year was related to acceptance for at least partial delivery of health care services on the Internet.
The overall acceptance of the use of the Internet for the provision of full health care services has remained at the same level since 2007 when these items were first included in the questionnaire used for assessment of Polish households as part of the Social Diagnosis study (the percentage changed only from 28.1% in 2007 to 29.1% in 2011) [
In our study, we did not analyze the actual use of eHealth services, but another survey indicates that the Internet was used to access health-related information by 23% of individuals in Poland in 2011 [
Relatively high acceptance of at least partial provision of Internet-based health care services is likely related to a general dissatisfaction with the health care system in Poland. Poland’s health care system has been undergoing a continuing process of reforms since the transition to a market economy in the early 1990s. The establishment of Regional Health Funds was one of the key changes in the late 20th century, followed by the return of a centralized funding of the health care system with the establishment of the National Health Fund in the early 21st century. Poland’s health care system is still based on public hospital services and outpatient care by private providers paid mainly from the Fund [
Most surveys reported elsewhere about the acceptance or the use of eHealth services have been related to the experience of individuals representing a whole population or selected groups, such as patients with specific disorders. Nonetheless, for at least some of the predictors resulting from the multivariate logistic regression carried out for households in Poland, corresponding findings from other surveys may be indicated.
The disparities between rural and urban areas in the use of ICT have been described previously in Poland and in other countries [
The lower acceptance of eHealth services was also revealed in households where the main income was from retirement or disability pensions. This observation illustrates the lower Internet penetration and literacy in the older strata of society, as well as lower access to modern communication technologies among people with disabilities. The relationship between the source of income and the acceptance for eHealth services is in line with general findings that professionally active people are more involved in using the Internet and computers than those who are retired or receiving disability pensions [
In our study, acceptance was consistently associated with higher household income per capita (comparison between lowest and higher quartiles). This finding is consistent with the results of studies performed in other countries [
The number of books in a household was included in the analysis in order to observe the influence the level of general literacy may have on the acceptance of the Internet as a tool for health care. Interestingly, the availability of at least some books in a household significantly affected the acceptance of using the Internet for health care services.
Our study also revealed that the factors related to ICT use in households were predictors of the acceptance of the Internet for the provision of health care services. The availability of a computer in a household, Internet access, and its duration in the household increased the level of acceptance. These findings seem to confirm the importance of the development of the information society on the acceptance of eHealth services. Similar results have been reported by other authors, both in relation to variables related to actual Internet use [
Interestingly, variables related to actual use of health care services by households had a limited impact on the acceptance of the use of the Internet for health care service provision. This was true for all 3 variables included in the logistic regression model apart from the use of health care services in the preceding year and increased acceptance of partial provision of health care on the Internet. The results of surveys performed in other countries indicate that households with at least 1 member with a high expected need for clinical services [
The surveys which focused on individual opinions also showed that predictors of Internet acceptance or use for health-related activities included age [
The assessment of acceptance levels for eHealth services is usually undertaken in relation to individual respondents. In this study, the responses registered by the canvasser were given on behalf of the whole household. Thus, the selection of potential factors which could influence the household’s acceptance of using the Internet as a tool for delivering health care services was made from the variable which could characterize household’s readiness to accept eHealth services.
The use of the concept of household acceptance in relation to eHealth services may be misleading because it is likely that not all members of a household share a common view and opinions may be diverse. On the other hand, the use of health care services usually depends on the decision of the individuals responsible for the household and their perception probably dominated in the views expressed during the canvasser interviews.
The main objective of the Social Diagnosis study was not focused on the eHealth field. Instead, it was oriented toward general issues about the household economic status and individual’s quality of life. Furthermore, the aspects of the use of ICT and the phenomenon of social divide were targeted. The strategy employed in our paper was to assess the acceptance of eHealth in Polish society using the data available from a study encompassing the whole population in a well-established and methodologically proven study.
The number of cases included in the multivariate logistic regression model presented in our paper was reduced from 12,386 to 12,015 due to missing values of key variables used to define outcome variables in the model. Furthermore, households that did not anticipate using health care services in the near future were excluded, and cases with missing values for predictors used in the model were omitted. As a result, data from 8915 households were used in the logistic regression model.
The number of missing values for outcome variables was not high (3.00%, 371/12,386), and its significance is difficult to assess due to a lack of information about potential reasons for the lack of response. The exclusion of households that did not anticipate using health care services in the near future (13.73%, 1700/12,386) was a potential source of bias in the results of the analysis. It is possible that households without sufficient levels of understanding of using the Internet for health care services provision, or those that do not accept such use, may have selected this response in order to hide their actual position. Thus, the exclusion of this group of households could suggest that a higher number of households actually accept using the Internet for this purpose. As for cases excluded from the final logistic regression model due to missing values in predictor variables (11.30%, 1400/12,386), the highest drop-out rates were related to the lack of data about monthly household net income per capita (4.28%, 530/12,386), the perception of current economic status of a household (3.17%; 393/12,386), the opinion on satisfying health care needs of a household (2.28%; 282/12,386), and hospitalizations of household members (0.99%, 123/12,386).
Interpreting missing values within these variables is difficult because of the association with the acceptance of Internet use. It is possible that households with extremely low or high monthly income rates per capita could be more prone to withholding information about their actual income. This could also be valid for the relatively high number of missing values in the variable related to the opinion of a household about its economic status in comparison to the preceding period. Assuming that the number of households with very low incomes in Poland is significantly higher than the number of households with high incomes, and because poverty is linked to a lower acceptance of ICT technologies, the relationship between income and the acceptance of the Internet for health care services is likely to be closer than shown.
As for the variables related to the opinion about satisfying health care needs of the household and hospitalization of a household member in the past year, any potential bias in the assessment of final results is not clear. These variables did not have a significant effect on the acceptance of using the Internet for health care services provision. The households that were reluctant to respond to these items could be generally dissatisfied with health care services and did not think that the Internet could provide a working solution. It is also possible that a lack of response to this item was due to the household not having used health care services extensively in the preceding period. Furthermore, hospitalization of a household member in the preceding months is likely to have resulted in focusing on the current situation instead of emerging solutions. However, the net effect of missing values within these variables is not clear.
The acceptance of health care services via the Internet was higher in households from larger cities, with stable income from an employee salary, as well as with higher income levels per capita. Furthermore, general computer and Internet use in the household influenced the perception of eHealth. Paradoxically, the use of health care services or the level of satisfaction with the coverage of the household’s health needs exerted a limited influence on acceptance of Internet-based health care.
European Union
information and communication technology
odds ratio
None declared.