{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T18:59:00Z","timestamp":1782845940620,"version":"3.54.5"},"reference-count":58,"publisher":"JMIR Publications Inc.","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The aim of this study was to understand the associations between different groups of chronic diseases and the use of different eHealth resources.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Data from the seventh survey of the Troms\u00f8 Study (Troms\u00f8 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>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).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/13116","type":"journal-article","created":{"date-parts":[[2019,9,26]],"date-time":"2019-09-26T13:37:36Z","timestamp":1569505056000},"page":"e13116","source":"Crossref","is-referenced-by-count":7,"title":["Impact of Illness on Electronic Health Use (The Seventh Troms\u00f8 Study - Part 2): Population-Based Questionnaire Study"],"prefix":"10.2196","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6349-3162","authenticated-orcid":false,"given":"Luis","family":"Marco-Ruiz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2254-3343","authenticated-orcid":false,"given":"Rolf","family":"Wynn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5689-5152","authenticated-orcid":false,"given":"Sunday Oluwafemi","family":"Oyeyemi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9525-1923","authenticated-orcid":false,"given":"Andrius","family":"Budrionis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7068-117X","authenticated-orcid":false,"given":"Kassaye Yitbarek","family":"Yigzaw","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2893-6989","authenticated-orcid":false,"given":"Johan Gustav","family":"Bellika","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2020,3,5]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2196\/13106"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.2196\/13118"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.2196\/13120"},{"key":"ref4","unstructured":"RigbyMKochSKeelingDHillPAlonsoAMaeckelbergheEEuropean Commission201301312019-11-13Developing a New Understanding of Enabling Health and Wellbeing in Europehttps:\/\/ec.europa.eu\/eip\/ageing\/library\/developing-new-understanding-enabling-health-and-wellbeing-europeharmonising-health-and_en"},{"key":"ref5","author":"Olsen, LA","year":"2007","journal-title":"The Learning Healthcare System: Workshop Summary"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1177\/107327480901600208"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.g3725"},{"key":"ref8","unstructured":"Pew Research Center201506262018-05-07Americans\u2019 Internet Access: 2000-2015http:\/\/www.pewinternet.org\/2015\/06\/26\/americans-internet-access-2000-2015\/"},{"key":"ref9","unstructured":"FoxSDugganMPew Research Center201301152019-11-15Health Online 2013https:\/\/www.pewresearch.org\/internet\/2013\/01\/15\/health-online-2013\/"},{"key":"ref10","unstructured":"Pew Research Center20130112018-05-07Majority of Adults Look Online for Health Informationhttp:\/\/www.pewresearch.org\/fact-tank\/2013\/02\/01\/majority-of-adults-look-online-for-health-information\/"},{"key":"ref11","unstructured":"SSB: Forside2018-05-08ICT Usage in Householdshttps:\/\/www.ssb.no\/statistikkbanken\/selecttable\/hovedtabellHjem.asp?KortNavnWeb=ikthus&CMSSubjectArea=teknologi-og-innovasjon&PLanguage=1&checked=true"},{"key":"ref12","unstructured":"FoxSDugganMPew Research Center20121182018-05-08Mobile Health 2012http:\/\/www.pewinternet.org\/2012\/11\/08\/mobile-health-2012\/"},{"key":"ref13","unstructured":"SmithAAndersonMPew Research Centre20180312018-05-08Social Media Use in 2018http:\/\/www.pewinternet.org\/2018\/03\/01\/social-media-use-in-2018\/"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2458-7-53"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/297416"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.5038"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1111\/j.1471-6712.2008.00662.x"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.3.2.e20"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.2297"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1001\/jama.289.18.2400"},{"issue":"4","key":"ref21","first-page":"A13","volume":"1","author":"Wagner, TH","year":"2004","journal-title":"Prev Chronic Dis"},{"key":"ref22","unstructured":"S\u00f8rensenTAndreassenHWangbergSNorwegian Centre for E-health Research20142019-11-15E-helse i Norge 2013 Prosjektrapporthttps:\/\/www.researchgate.net\/publication\/303186485_E-helse_i_Norge_2013_Prosjektrapport? 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