Dataset Information

Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study.

ABSTRACT: BACKGROUND:The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes. OBJECTIVE:The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and the association with socioeconomic status (SES) among people diagnosed with type 1 and type 2 diabetes mellitus (T1D and T2D, respectively). METHODS:We used email survey data from 1250 members of the Norwegian Diabetes Association (aged 18-89 years), collected in 2018. Eligible for analyses were the 1063 respondents having T1D (n=523) and T2D (n=545). 5 respondents reported having both diabetes types and thus entered into both groups. Using descriptive statistics, we estimated the use of the different types of eHealth. By logistic regressions, we studied the associations between the use of these types of eHealth and SES (education and household income), adjusted for gender, age, and self-rated health. RESULTS:We found that 87.0% (447/514) of people with T1D and 77.7% (421/542) of people with T2D had used 1 or more forms of eHealth sometimes or often during the previous year. The proportion of people using search engines was the largest in both diagnostic groups, followed by apps, social media, and video services. We found a strong association between a high level of education and the use of search engines, whereas there were no educational differences for the use of apps, social media, or video services. In both diagnostic groups, high income was associated with the use of apps. In people with T1D, lower income was associated with the use of video services. CONCLUSIONS:This paper indicates a digital divide among people with diabetes in Norway, with consequences that may contribute to sustaining and shaping inequalities in health outcomes. The strong relationship between higher education and the use of search engines, along with the finding that the use of apps, social media, and video services was not associated with education, indicates that adequate communication strategies for audiences with varying education levels should be a focus in future efforts to reduce inequalities in health outcomes.

SUBMITTER: Hansen AH

PROVIDER: S-EPMC6658320 | biostudies-other | 2019 May

REPOSITORIES: biostudies-other

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Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study.

Hansen Anne Helen AH Bradway Meghan M Broz Jan J Claudi Tor T Henriksen Øystein Ø Wangberg Silje C SC Årsand Eirik E

Journal of medical Internet research 20190529 5

<h4>Background</h4>The prevalence of diabetes and the use of electronic health (eHealth) are increasing. People with diabetes need frequent monitoring and follow-up of health parameters, and eHealth services can be highly valuable. However, little is known about the use of eHealth in different socioeconomic groups among people with diabetes.<h4>Objective</h4>The aim of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media s ...[more]

PMID: 31144669

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Project description:BACKGROUND:Despite the increasing prevalence of diabetes and the increasing use of eHealth, little is known about the association between provider-based health services and eHealth among people with diabetes. This is the second study in a project exploring the associations between the use of eHealth and the use of provider-based health services. OBJECTIVE:The objective of this study was to investigate which eHealth services are used among out-of-hours (OOH) visitors with type 1 diabetes (T1D), and whether the use of eHealth (eg, apps, search engines, video services, and social media) was associated with the use of OOH services. We also wanted to investigate associations between anxiety, reassurance, and change in doctor-seeking behavior because of health information acquired from the Internet, and the use of OOH services. METHODS:We used data from a 2018 email survey of members of the Norwegian Diabetes Association (18-89 years old). Respondents with T1D were eligible for analyses. Using descriptive statistics, we estimated the use of OOH services and eHealth. Using logistic regressions, we studied the associations between the use of OOH services and the use of eHealth, as well as associations between the use of OOH services and reported consequences of using Internet-based health information. RESULTS:In the sample of 523 people with T1D (mean age 47 years), 26.7% (129/484) visited OOH services once or more during the previous year. Among the OOH visitors, search engines were used for health purposes by 86.7% (111/128), apps (health apps in general) by 63.6% (82/129), social media by 45.3% (58/128), and video services by 28.4% (36/127). The use of OOH services was positively associated with self-reported anxiety/depression (odds ratio [OR] 4.53, 95% CI 1.43-14.32) and with the use of apps (OR 1.73, 95% CI 1.05-2.85), but not with other types of eHealth. Those who had felt anxious based on information from the Internet were more likely to visit OOH services compared with those who had not felt anxious (OR 2.38, 95% CI 1.50-3.78). People who had decided to consult a doctor based on information from the Internet were more likely to visit OOH services (OR 2.76, 95% CI 1.64-4.66), compared to those who had not made such an Internet-based decision. CONCLUSIONS:People with T1D were frequent users of OOH services, and the OOH visitors were frequent users of eHealth. The use of OOH services was positively associated with the use of health apps, with self-reported anxiety/depression, and with feeling anxious based on information from the Internet. Likewise, deciding to consult a doctor based on information from the Internet was positively associated with OOH visits. The use of eHealth seems to have a significant impact on people with T1D.

Project description:BackgroundUnderstanding how people with diabetes seek online health information and use health applications is important to ensure these electronic tools are successfully supporting patient self-care. Furthermore, identifying the relationship between patient mobile eHealth literacy (mobile eHL) and diabetes outcomes can have far-reaching utility, for example, in the design of targeted interventions to address mobile eHL limitations. However, only limited studies have explored the impact of mobile eHL in a population with diabetes.ObjectiveThis study aims to present data about online information-seeking behavior and mobile health (mHealth) app usage, investigate the factors related to mobile eHL in Taiwanese patients with type 2 diabetes, and flesh out the relationship between eHealth literacy (eHL), mobile health literacy (mHL), and health outcomes.MethodsSubjects were recruited from January 2017 to December 2017 in the outpatient departments of 3 hospitals in Taiwan. A total of 249 Taiwanese patients with diabetes voluntarily completed a cross-sectional survey assessing sociodemographic characteristics; diabetes status; knowledge and skills of computers, the internet, and mobile apps; mobile eHL; and patient outcomes (self-care behaviors, self-rated health, HbA1c). Structural equation modeling analyses examined the model fit of mobile eHL scores and the interrelationships between latent constructs and observable variables.ResultsOf the 249 patients with diabetes, 67% (164/249) reported they had searched for online diabetes information. The participants with smartphones had owned them for an average of 6.5 years and used them for an average of 4.5 (SD 3.81) hours per day. Only 1.6% (4/249) of the patients used health apps. Some demographic factors affecting mobile eHL included age, education, and duration of type 2 diabetes. Mobile eHL was related to self-care behaviors as well as knowledge and skills of computers, the internet, and mobile technology, but only had a weak, indirect effect on self-rated health. The final model had adequate goodness-of-fit indexes: chi-square (83)=149.572, P<.001; comparative fit index (CFI)=0.925; root mean square of approximation (RMSEA)=0.057 (90% CI 004-006); chi-square/df=1.082. Mobile eHL had a weak, indirect effect on self-rated health through the variables of knowledge with skills.ConclusionsOur study reveals that although people with diabetes who rated their health conditions as moderate were confident in using mobile eHealth and technology, few adopted these tools in their daily lives. The study found that mobile eHL had a direct effect on self-care behavior as well as knowledge and skills of computers, the internet, and mobile technology, and had an indirect effect on health outcomes (glycemic control and self-rated health status). Information about this population's experiences and the role mobile eHL plays in them can spur necessary mobile eHealth patient education.

Project description:BackgroundThe magnitude of socioeconomic health inequalities differs across age groups. It is less clear whether socioeconomic health inequalities differ across age groups by other factors that are known to affect the relation between socioeconomic position and health, like the indicator of socioeconomic position, the health outcome, gender, and as to whether socioeconomic health inequalities are measured in absolute or in relative terms. The aim is to investigate whether absolute and relative socioeconomic health inequalities differ across age groups by indicator of socioeconomic position, health outcome and gender.MethodsThe study sample was derived from the baseline measurement of the LifeLines Cohort Study and consisted of 95,432 participants. Socioeconomic position was measured as educational level and household income. Physical and mental health were measured with the RAND-36. Age concerned eleven 5-years age groups. Absolute inequalities were examined by comparing means. Relative inequalities were examined by comparing Gini-coefficients. Analyses were performed for both health outcomes by both educational level and household income. Analyses were performed for all age groups, and stratified by gender.ResultsAbsolute and relative socioeconomic health inequalities differed across age groups by indicator of socioeconomic position, health outcome, and gender. Absolute inequalities were most pronounced for mental health by household income. They were larger in younger than older age groups. Relative inequalities were most pronounced for physical health by educational level. Gini-coefficients were largest in young age groups and smallest in older age groups.ConclusionsAbsolute and relative socioeconomic health inequalities differed cross-sectionally across age groups by indicator of socioeconomic position, health outcome and gender. Researchers should critically consider the implications of choosing a specific age group, in addition to the indicator of socioeconomic position and health outcome, as findings on socioeconomic health inequalities may differ between them.

Project description:BackgroundLow back pain is an important public health issue across the world. However, it is unclear whether socioeconomic status (SES) is associated with low back pain. This study determines an association between SES and low back pain among older people.MethodsWe used cross-sectional data derived from the year 2013 across 30 Japanese municipalities. The survey was conducted between October 2013 to December 2013. Functionally independent community-dwelling older adults aged 65 and above (n?=?26,037) were eligible for the study. Multilevel Poisson regression analysis with a robust variance estimator was used to examine the association between SES and low back pain. Self-reported low back pain in the past year was used as a dependent variable. Educational attainment, past occupation, equivalized household income, wealth, and subjective economic situation represented SES and were separately analyzed as independent variables, adjusted for covariates including age and sex.ResultsThe prevalence of low back pain was 63.4%. Overall, lower SES were more likely to suffer from low back pain compared with that for the highest. First, as for the educational attainment, the prevalence ratio (PR) (95% credible interval (CI)) for the lowest level was 1.07 (1.02-1.12). Second, as for the past occupation, the PR (95% CI) for the blue-collared workers compared with professionals was 1.06 (1.01-1.11). Third, as for the equalized household income, the PRs (95% CI) for lower middle and the lowest income levels were 1.08 (1.02-1.13) and 1.16 (1.10-1.23), respectively. Fourth, as for the wealth, the PRs (95% CI) for lower middle and the lowest wealth levels were 1.11 (1.04-1.19) and 1.18 (1.11-1.27), respectively. Fifth, as for the subjective economic situation, the PRs (95% CI) for lower middle and the lowest financial conditions were 1.18 (1.10-1.26) and 1.32 (1.22-1.44), respectively.ConclusionsSignificant socioeconomic inequalities were observed in low back pain among older individuals in Japan. Policymakers and clinicians must understand the nature of these inequalities.

Project description:Type 2 diabetes (T2D) is a rising global epidemic with lower socioeconomic groups being more affected. Considering specific population subgroups to examine prevalence and socioeconomic inequalities in T2D is rare. Moreover, using one indicator to depict socioeconomic inequalities in health is a common practice despite evidence on differences in what different socioeconomic indicators ought to measure. This study has two aims: 1. Examine the prevalence of T2D in employed individuals, nonworking spouses and pensioners. 2. Examine socioeconomic inequalities in T2D in the three population subgroups and determine the explanatory power of income, education and occupation in employed individuals and nonworking spouses. This study is based on claims data from a statutory health insurance provider in Lower Saxony, Germany. T2D prevalence in the period between 2013 and 2017 was examined in employed individuals, nonworking spouses and pensioners. Multivariate logistic regression analysis was applied to examine socioeconomic inequalities in T2D in the three population subgroups. Explanatory power of the three socioeconomic indicators was determined by deviance analysis. Results showed that T2D prevalence was four times higher in male nonworking spouses (24.2%) and 2.6 times higher in female nonworking spouses (12.7%) compared to employed men (6.4%) and women (4.7%) respectively, while it accounted for 40% of men and 36% of women in pensioners. T2D inequalities emerged for all three socioeconomic indicators and were observed in the three subgroups. School education had the highest explanatory power in employed men and women and male nonworking spouses. Nonworking spouses are an important target group in T2D prevention interventions. The three socioeconomic indicators have independent effects and differ in their explanatory power where low school education appears to be a major risk factor. It can be discussed that health literacy and the associated health behavior play a role in mediating the association between school education and T2D.

Dataset Information

Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study.

Publications

Inequalities in the Use of eHealth Between Socioeconomic Groups Among Patients With Type 1 and Type 2 Diabetes: Cross-Sectional Study.

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