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Background Patients who suffer from different diseases may use different electronic health (eHealth) resources. Thus, those who plan eHealth interventions should take into account which eHealth resources are used most frequently by patients that suffer from different diseases. Objective The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources. Methods Data from the seventh survey of the Tromsø Study (Tromsø 7) were analyzed to determine how different diseases influence the use of different eHealth resources. Specifically, the eHealth resources considered were use of apps, search engines, video services, and social media. The analysis contained data from 21,083 participants in the age group older than 40 years. A total of 15,585 (15,585/21,083; 73.92%) participants reported to have suffered some disease, 10,604 (10,604/21,083; 50.29%) participants reported to have used some kind of eHealth resource in the last year, and 7854 (7854/21,083; 37.25%) participants reported to have used some kind of eHealth resource in the last year and suffered (or had suffered) from some kind of specified disease. Logistic regression was used to determine which diseases significantly predicted the use of each eHealth resource. Results The use of apps was increased among those individuals that (had) suffered from psychological problems (odds ratio [OR] 1.39, 95% CI 1.23-1.56) and cardiovascular diseases (OR 1.12, 95% CI 1.01-1.24) and those part-time workers that (had) suffered from any of the diseases classified as others (OR 2.08, 95% CI 1.35-3.32). The use of search engines for accessing health information increased among individuals who suffered from psychological problems (OR 1.39, 95% CI 1.25-1.55), cancer (OR 1.26, 95% CI 1.11-1.44), or any of the diseases classified as other diseases (OR 1.27, 95% CI 1.13-1.42). Regarding video services, their use for accessing health information was more likely when the participant was a man (OR 1.31, 95% CI 1.13-1.53), (had) suffered from psychological problems (OR 1.70, 95% CI 1.43-2.01), or (had) suffered from other diseases (OR 1.43, 95% CI 1.20-1.71). The factors associated with an increase in the use of social media for accessing health information were as follows: (had) suffered from psychological problems (OR 1.65, 95% CI 1.42-1.91), working part time (OR 1.35, 95% CI 0.62-2.63), receiving disability benefits (OR 1.42, 95% CI 1.14-1.76), having received an upper secondary school education (OR 1.20, 95% CI 1.03-1.38), being a man with a high household income (OR 1.67, 95% CI 1.07-2.60), suffering from cardiovascular diseases and having a high household income (OR 3.39, 95% CI 1.62-8.16), and suffering from respiratory diseases while being retired (OR 1.95, 95% CI 1.28-2.97). Conclusions Our findings show that different diseases are currently associated with the use of different eHealth resources. This knowledge is useful for those who plan eHealth interventions as they can take into account which type of eHealth resource may be used for gaining the attention of the different user groups.

Background Parents seek trustworthy information online to promote healthy eating for their toddlers. Such information must be perceived as relevant and easy to implement and use. Objective The objectives of this study were to conduct a process evaluation of the electronic health (eHealth) intervention (Food4toddlers) targeting food environment, parental feeding practices, and toddlers’ diet and to examine possible differences in these areas according to education and family composition. Methods A 2-armed randomized controlled trial, including 298 parent–toddler dyads from Norway, was conducted in 2017. In total, 148 parents in the intervention group received access to an intervention website for 6 months. Data on website usage were retrieved from the learning management platform used (NEO). Participants’ satisfaction with the intervention was asked for in a postintervention questionnaire. Chi-square and t tests were used to examine differences in usage and satisfaction between education and family composition groups. Results Most participants were mothers (144/148, 97.2%), lived in two-adult households (148/148, 100%), and were born in Norway (132/148, 89.1%). Mean parental age was 31.5 years (SD 4.2). More than 87.8% (129/147) had a university education degree and 56.5% (83/147) had over 4 years of university education. Most (128/148, 86.5%) intervention participants entered the website at least once (mean days of access 7.4 [SD 7.1]). Most parents reported the website as appropriate to the child’s age (71/83, 86%) and self-explanatory (79/83, 95%) and appreciated the interface (52/83, 63%) and layout (46/83, 55%). In total, 61% (51/83) stated that they learned something new from the intervention. Parents with over 4 years of university education and in 1-child households used the intervention website more than those with 4 years or less of university education (8.4 vs 5.9 days in total, P=.04) and households with more than 1 child (8.3 vs 5.8 days in total, P=.04), respectively. Conclusions The Food4toddlers intervention website was found to be relevant by most participants in the intervention group, although usage of the website differed according to educational level and family composition. For eHealth interventions to be effective, intervention materials such as websites must be used by the target group. Our results highlight the need to include users from different groups when developing interventions. Trial Registration ISRCTN Registry ISRCTN92980420; http://www.isrctn.com/ISRCTN92980420

The following article, Hansen, A.H., Brož, J., Claudi, T. & Årsand, E. (2018). Relations between the use of electronic health and the use of general practitioner and somatic specialist visits in patients with type 1 diabetes: Cross-sectional study. Journal of Medical Internet Research, 20(11), can be accessed at https://doi.org/10.2196/11322. 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 of great value. However, little is known about the association between the use of eHealth and provider-based health care services among people with diabetes. Objective: The objective of this study was to investigate the use of 4 different eHealth platforms (apps, search engines, video services, and social media sites) and associations with the use of provider-based health care visits among people diagnosed with type 1 diabetes mellitus (T1DM). Methods: We used email survey data collected from 1250 members of the Norwegian Diabetes Association (aged 18 to 89 years) in 2018. Eligible for analyses were the 523 respondents with T1DM. Using descriptive statistics, we estimated the use of eHealth and the use of general practitioners (GPs) and somatic specialist outpatient services. By logistic regressions, we studied the associations between the use of these provider-based health services and the use of eHealth, adjusted for gender, age, education, and self-rated health. Results: Of the sample of 523 people with T1DM, 90.7% (441/486) had visited a GP once or more, and 61.0% (289/474) had visited specialist services during the previous year. Internet search engines (such as Google) were used for health purposes sometimes or often by 84.0% (431/513), apps by 55.4% (285/514), social media (such as Facebook) by 45.2% (232/513), and video services (such as YouTube) by 23.3% (118/506). Participants aged from 18 to 39 years used all forms of eHealth more than people aged 40 years and older, with the exception of social media. The use of search engines was positively associated with the use of somatic specialist services (odds ratio 2.43, 95% CI 1.33-4.45). GP visits were not associated with any kind of eHealth use. Conclusions: eHealth services are now widely used for health support and health information by people with T1DM, primarily in the form of search engines but often in the form of apps and social media as well. We found a positive association between the use of search engines and specialist visits and that people with T1DM are frequent users of eHealth, GPs, and specialist services. We found no evidence that eHealth reduces the use of provider-based health care; these services seem to be additional rather than alternative. Future research should focus on how health care services can meet and adapt to the high prevalence of eHealth use. Our results also indicate that many patients with T1DM do not visit specialist clinics once a year as recommended. This raises questions about collaboration in health care services and needs to be followed up in future research.

Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 30.05.2017. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). Background: Adequate self-management is the cornerstone of type 2 diabetes treatment, as people make the majority of daily treatment measures and health decisions. The increasing prevalence of type 2 diabetes mellitus (T2DM) and the complexity of diabetes self-management demonstrate the need for innovative and effective ways to deliver self-management support. eHealth interventions are promoted worldwide and hold a great potential in future health care for people with chronic diseases such as T2DM. However, many eHealth interventions face high dropout rates. This led to our interest in the experiences of participants who dropped out of an eHealth intervention for adults with T2DM, based on the Guided Self-Determination (GSD) counseling method. Objective: In this study, we aimed to explore experiences with an eHealth intervention based on GSD in general practice from the perspective of those who dropped out and to understand their reasons for dropping out. To the best of our knowledge, no previous qualitative study has focused on participants who withdrew from an eHealth self-management support intervention for adults with T2DM. Methods: A qualitative design based on telephone interviews was used to collect data. The sample comprised 12 adults with type 2 diabetes who dropped out of an eHealth intervention. Data were collected in 2016 and subjected to qualitative content analysis. Results: We identified one overall theme: “Losing motivation for intervention participation.” This theme was illustrated by four categories related to the participants’ experiences of the eHealth intervention: (1) frustrating technology, (2) perceiving the content as irrelevant and incomprehensible, (3) choosing other activities and perspectives, and (4) lacking face-to-face encounters. Conclusions: Our findings indicate that the eHealth intervention based on GSD without face-to-face encounters with nurses reduced participants’ motivation for engagement in the intervention. To maintain motivation, our study points to the importance of combining eHealth with regular face-to-face consultations. Our study also shows that the perceived benefit of the GSD eHealth intervention intertwined with choosing to focus on other matters in complex daily lives are critical aspects in motivation for such interventions. This indicates the importance of giving potential participants tailored information about the aim, the content, and the effort needed to remain engaged in complex interventions so that eligible participants are recruited. Finally, motivation for engagement in the eHealth intervention was influenced by the technology used in this study. It seems important to facilitate more user-friendly but high-security eHealth technology. Our findings have implications for improving the eHealth intervention and to inform researchers and health care providers who are organizing eHealth interventions focusing on self-management support in order to reduce dropout rates.