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

. 2019 May 29 ; 21 (5) : e13615. [epub] 20190529

Jazyk angličtina Země Kanada Médium electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid31144669
Odkazy

PubMed 31144669
PubMed Central PMC6658320
DOI 10.2196/13615
PII: v21i5e13615
Knihovny.cz E-zdroje

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.

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Ogurtsova K, da RFJD, Huang Y, Linnenkamp U, Guariguata L, Cho NH, Cavan D, Shaw JE, Makaroff LE. IDF Diabetes Atlas: global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract. 2017 Jun;128:40–50. doi: 10.1016/j.diabres.2017.03.024.S0168-8227(17)30375-3 PubMed DOI

Norwegian Institute of Public Health. [2018-06-16]. [Public Health in Norway 2018] https://www.fhi.no/globalassets/dokumenterfiler/rapporter/2018/helsetilstanden-i-norge-2018.pdf .

Jenssen TG, Tonstad S, Claudi T, Midthjell K, Cooper J. The gap between guidelines and practice in the treatment of type 2 diabetes A nationwide survey in Norway. Diabetes Res Clin Pract. 2008 May;80(2):314–20. doi: 10.1016/j.diabres.2007.12.025.S0168-8227(08)00007-7 PubMed DOI

Mouland G. [Diabetes in general practice--were treatment goals reached?] Tidsskr Nor Laegeforen. 2014 Jan 28;134(2):168–72. doi: 10.4045/tidsskr.13.0375. 3127607 PubMed DOI

Cooper JG, Claudi T, Thordarson HB, Løvaas KF, Carlsen S, Sandberg S, Thue G. Treatment of type 1 diabetes in the specialist health service--data from the Norwegian Diabetes Register for Adults. Tidsskr Nor Laegeforen. 2013 Nov 12;133(21):2257–62. doi: 10.4045/tidsskr.13.0153. 3095352 PubMed DOI

World Health Organization. [2018-06-16]. eHealth http://www.who.int/ehealth/en/

Wangberg SC, Andreassen HK, Prokosch H, Santana SMV, Sørensen T, Chronaki CE. Relations between internet use, socio-economic status (SES), social support and subjective health. Health Promot Int. 2008 Mar;23(1):70–7. doi: 10.1093/heapro/dam039. dam039 PubMed DOI

Fox S, Duggan M. Pew Internet. Washington DC: Pew Research Center; 2013. [2018-06-16]. Health Online http://www.pewinternet.org/2013/01/15/health-online-2013/

Hong YA, Cho J. Has the digital health divide widened? Trends of health-related internet use among older adults from 2003 to 2011. J Gerontol B Psychol Sci Soc Sci. 2017 Sep 1;72(5):856–63. doi: 10.1093/geronb/gbw100.gbw100 PubMed DOI

Sørensen T, Andreassen HK, Wangberg SC. Norwegian Centre for eHealth Research. 2014. [2018-06-16]. [Project report eHealth in Norway 2013] https://ehealthresearch.no/files/documents/Prosjektrapporter/NST-rapport_2014-02_e-helse_i_Norge_2013.pdf .

Hansen AH, Broz J, Claudi T, Årsand E. 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. J Med Internet Res. 2018 Nov 7;20(11):e11322. doi: 10.2196/11322. v20i11e11322 PubMed DOI PMC

[Media news] [2019-05-17]. [Share with internet access] http://medienorge.uib.no/statistikk/medium/ikt/347 .

Statistics Norway. [2019-01-31]. [Nine out of ten surf the net every day] https://www.ssb.no/teknologi-og-innovasjon/artikler-og-publikasjoner/ni-av-ti-surfer-pa-nettet-hver-dag .

Mackenbach JP. Nordic paradox, Southern miracle, Eastern disaster: persistence of inequalities in mortality in Europe. Eur J Public Health. 2017 Dec 1;27(suppl_4):14–17. doi: 10.1093/eurpub/ckx160.4430517 PubMed DOI

Grintsova O, Maier W, Mielck A. Inequalities in health care among patients with type 2 diabetes by individual socio-economic status (SES) and regional deprivation: a systematic literature review. Int J Equity Health. 2014 Jun 2;13:43. doi: 10.1186/1475-9276-13-43. 1475-9276-13-43 PubMed DOI PMC

Espelt A, Borrell C, Roskam AJ, Rodríguez-Sanz M, Stirbu I, Dalmau-Bueno A, Regidor E, Bopp M, Martikainen P, Leinsalu M, Artnik B, Rychtarikova J, Kalediene R, Dzurova D, Mackenbach J, Kunst AE. Socioeconomic inequalities in diabetes mellitus across Europe at the beginning of the 21st century. Diabetologia. 2008 Nov;51(11):1971–9. doi: 10.1007/s00125-008-1146-1. PubMed DOI

Sortsø C, Lauridsen J, Emneus M, Green A, Jensen PB. Socioeconomic inequality of diabetes patients' health care utilization in Denmark. Health Econ Rev. 2017 Dec;7(1):21. doi: 10.1186/s13561-017-0155-5. 10.1186/s13561-017-0155-5 PubMed DOI PMC

Starfield B. Pathways of influence on equity in health. Soc Sci Med. 2007 Apr;64(7):1355–62. doi: 10.1016/j.socscimed.2006.11.027.S0277-9536(06)00609-5 PubMed DOI

Whitehead M. CIEE-FLACSO. Copenhagen: World Health Organisastion (WHO) Regional Office for Europe; 1990. [2019-01-31]. The concept and principles of equity and health http://salud.ciee.flacso.org.ar/flacso/optativas/equity_and_health.pdf .

Bell AV. "I think about Oprah": social class differences in sources of health information. Qual Health Res. 2014 Apr;24(4):506–16. doi: 10.1177/1049732314524637.1049732314524637 PubMed DOI

Victora CG, Fenn B, Bryce J, Kirkwood BR. Co-coverage of preventive interventions and implications for child-survival strategies: evidence from national surveys. Lancet. 2005;366(9495):1460–6. doi: 10.1016/S0140-6736(05)67599-X.S0140-6736(05)67599-X PubMed DOI

Andreassen HK, Bujnowska-Fedak MM, Chronaki CE, Dumitru RC, Pudule I, Santana S, Voss H, Wynn R. European citizens' use of E-health services: a study of seven countries. BMC Public Health. 2007;7:53. doi: 10.1186/1471-2458-7-53. 1471-2458-7-53 PubMed DOI PMC

Li J, Theng Y, Foo S. Predictors of online health information seeking behavior: changes between 2002 and 2012. Health Informatics J. 2015 Aug 10;:804–14. doi: 10.1177/1460458215595851.1460458215595851 PubMed DOI

Buysse HE, de Moor GJ, de Maeseneer J. Introducing a telemonitoring platform for diabetic patients in primary care: will it increase the socio-digital divide? Prim Care Diabetes. 2013 Jul;7(2):119–27. doi: 10.1016/j.pcd.2012.10.085.S1751-9918(12)00208-2 PubMed DOI

Kontos E, Blake KD, Chou WS, Prestin A. Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012. J Med Internet Res. 2014;16(7):e172. doi: 10.2196/jmir.3117. v16i7e172 PubMed DOI PMC

Wangberg SC, Sørensen T, Andreassen HK. Using the internet to support exercise and diet: a stratified Norwegian survey. Med 2 0. 2015;4(2):e3. doi: 10.2196/med20.4116. v4i2e3 PubMed DOI PMC

Levine DM, Savarimuthu S, Squires A, Nicholson J, Jay M. Technology-assisted weight loss interventions in primary care: a systematic review. J Gen Intern Med. 2015 Jan;30(1):107–17. doi: 10.1007/s11606-014-2987-6. PubMed DOI PMC

Bashshur RL, Shannon GW, Smith BR, Woodward MA. The empirical evidence for the telemedicine intervention in diabetes management. Telemed J E Health. 2015 May;21(5):321–54. doi: 10.1089/tmj.2015.0029. PubMed DOI PMC

Joiner KL, Nam S, Whittemore R. Lifestyle interventions based on the diabetes prevention program delivered via eHealth: a systematic review and meta-analysis. Prev Med. 2017 Jul;100:194–207. doi: 10.1016/j.ypmed.2017.04.033. S0091-7435(17)30153-6 PubMed DOI PMC

Ministry of Health and Care Services. [2019-01-31]. The Norwegian Public Health Act https://www.regjeringen.no/globalassets/upload/hod/hoeringer-fha_fos/123.pdf .

Hansen AH, Bradway M, Broz J, Claudi T, Henriksen O, Wangberg SC, Årsand E. The use of eHealth and provider-based health services by patients with diabetes mellitus: protocol for a cross-sectional study. JMIR Res Protoc. 2016 Oct 31;5(4):e207. doi: 10.2196/resprot.6529. v5i4e207 PubMed DOI PMC

Hansen AH, Claudi T, Årsand E. Associations between the use of eHealth and out-of-hours services in people with type 1 diabetes: cross-sectional study. J Med Internet Res. 2019 Mar 21;21(3):e13465. doi: 10.2196/13465. v21i3e13465 PubMed DOI PMC

Hansen AH, Claudi T, Årsand E. Use of electronic health and its impact on doctor-visiting decisions among people with diabetes: cross-sectional study. J Med Internet Res. 2019 Apr 26;21(4):e13678. doi: 10.2196/13678. v21i4e13678 PubMed DOI PMC

Medlock S, Eslami S, Askari M, Arts DL, Sent D, de Rooij SE, Abu-Hanna A. Health information-seeking behavior of seniors who use the internet: a survey. J Med Internet Res. 2015;17(1):e10. doi: 10.2196/jmir.3749. v17i1e10 PubMed DOI PMC

The Tromsø Study Website. [2018-06-16]. http://tromsoundersokelsen.uit.no/tromso/

The Norwegian Diabetes Association. [2018-06-16]. Årsberetning 2017 https://issuu.com/knutjarle/docs/a_rsberetning_2017_ .

Merger SR, Kerner W, Stadler M, Zeyfang A, Jehle P, Müller-Korbsch M, Holl RW, DPV Initiative. German BMBF Competence Network Diabetes Mellitus Prevalence and comorbidities of double diabetes. Diabetes Res Clin Pract. 2016 Sep;119:48–56. doi: 10.1016/j.diabres.2016.06.003.S0168-8227(16)30153-X PubMed DOI

Cleland SJ, Fisher BM, Colhoun HM, Sattar N, Petrie JR. Insulin resistance in type 1 diabetes: what is 'double diabetes' and what are the risks? Diabetologia. 2013 Jul;56(7):1462–70. doi: 10.1007/s00125-013-2904-2. PubMed DOI PMC

Johnson TP, Wislar JS. Response rates and nonresponse errors in surveys. J Am Med Assoc. 2012 May 2;307(17):1805–6. doi: 10.1001/jama.2012.3532.307/17/1805 PubMed DOI

Lee C, Ramírez AS, Lewis N, Gray SW, Hornik RC. Looking beyond the Internet: examining socioeconomic inequalities in cancer information seeking among cancer patients. Health Commun. 2012;27(8):806–17. doi: 10.1080/10410236.2011.647621. PubMed DOI PMC

Zhao Y, Zhang J. Consumer health information seeking in social media: a literature review. Health Info Libr J. 2017 Dec;34(4):268–83. doi: 10.1111/hir.12192. PubMed DOI

Trawley S, Baptista S, Browne JL, Pouwer F, Speight J. The use of mobile applications among adults with type 1 and type 2 diabetes: results from the Second MILES-Australia (MILES-2) study. Diabetes Technol Ther. 2017 Dec;19(12):730–8. doi: 10.1089/dia.2017.0235. PubMed DOI

Ernsting C, Dombrowski SU, Oedekoven M, Kanzler M, Kuhlmey A, Gellert P. Using smartphones and health apps to change and manage health behaviors: a population-based survey. J Med Internet Res. 2017 Apr 5;19(4):e101. doi: 10.2196/jmir.6838. v19i4e101 PubMed DOI PMC

Elavsky S, Smahel D, Machackova H. Who are mobile app users from healthy lifestyle websites? Analysis of patterns of app use and user characteristics. Transl Behav Med. 2017 Dec;7(4):891–901. doi: 10.1007/s13142-017-0525-x. 10.1007/s13142-017-0525-x PubMed DOI PMC

Statistics Norway. [2019-02-01]. Level of education in the population https://www.ssb.no/utniv/

Bujnowska-Fedak MM. Trends in the use of the internet for health purposes in Poland. BMC Public Health. 2015;15:194. doi: 10.1186/s12889-015-1473-3. 10.1186/s12889-015-1473-3 PubMed DOI PMC

Hale TM. Is there such a thing as an online health lifestyle? Examining the relationship between social status, Internet access, and health behaviors. Information, Communication & Society. 2013 May;16(4):501–518. doi: 10.1080/1369118X.2013.777759. DOI

Halbesleben JR, Whitman MV. Evaluating survey quality in health services research: a decision framework for assessing nonresponse bias. Health Serv Res. 2013 Jun;48(3):913–30. doi: 10.1111/1475-6773.12002. PubMed DOI PMC

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