Literature DB >> 32116456

Secular Trends in Information Communications Technology: Access, Use, and Attitudes of Young and Older Patients With Diabetes.

Timothy L Middleton1,2, Maria I Constantino1,2, Lynda Molyneaux1,2, Turki AlMogbel1,3, Margaret McGill1,2, Dennis K Yue1,2, Stephen M Twigg1,2, Ted Wu1, Jencia Wong1,2.   

Abstract

BACKGROUND: Advances in information communications technology (ICT) provide opportunities for enhanced diabetes care. Knowledge of the more acceptable communication modalities in patients of different ages will help to inform the direction of future innovations.
METHODS: An anonymous ICT survey (examining access and use of mobile phones, computers, tablets, and the Internet and attitudes toward e-mail, Web-based consultations, and online peer-support) was conducted at the Royal Prince Alfred Hospital Diabetes Centre in Sydney, Australia. Survey deployment occurred during 4-month periods in 2012 and 2017. Respondents were stratified by current age (<40 or ≥40 years).
RESULTS: A total of 614 unselected patients (20% with type 1 diabetes, 55% with type 2 diabetes, 13% with gestational diabetes mellitus, and 12% with an undisclosed type of diabetes) completed the survey. Access to ICT increased from 89% in 2012 to 97% in 2017. The most commonly owned device was a mobile phone (87% ownership in 2017). Increase in mobile Internet usage in the <40 years of age subgroup was significant (P = 0.04). Significant increases in Internet access and smartphone feature use were observed in patients aged ≥40 years (P ≤0.001 for all). Overall use of short message service (SMS, or text messaging) was high (90 and 80% for ages <40 and ≥40 years, respectively). Use of digital applications was low, even among the young (45% in 2017). Comfort with online consultations (40%) and support groups (32%) was also low.
CONCLUSION: Access to and acceptance and use of ICT is high, especially in those <40 years of age; however, the greatest increases were seen in those aged ≥40 years. High penetrance of mobile phones and text messaging in all age-groups would suggest that innovations involving an SMS platform have the greatest potential to enhance diabetes care.
© 2019 by the American Diabetes Association.

Entities:  

Year:  2020        PMID: 32116456      PMCID: PMC7026750          DOI: 10.2337/ds18-0082

Source DB:  PubMed          Journal:  Diabetes Spectr        ISSN: 1040-9165


  13 in total

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Authors:  Marie E McDonnell
Journal:  Curr Diab Rep       Date:  2018-05-24       Impact factor: 4.810

2.  Older adults: are they ready to adopt health-related ICT?

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Review 3.  Text messaging in health care: a systematic review of impact studies.

Authors:  Valerie A Yeager; Nir Menachemi
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4.  Association of Type 1 Diabetes vs Type 2 Diabetes Diagnosed During Childhood and Adolescence With Complications During Teenage Years and Young Adulthood.

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Journal:  JAMA       Date:  2017-02-28       Impact factor: 56.272

Review 5.  Mobile phone messaging for facilitating self-management of long-term illnesses.

Authors:  Thyra de Jongh; Ipek Gurol-Urganci; Vlasta Vodopivec-Jamsek; Josip Car; Rifat Atun
Journal:  Cochrane Database Syst Rev       Date:  2012-12-12

Review 6.  Mobile phone messaging reminders for attendance at healthcare appointments.

Authors:  Ipek Gurol-Urganci; Thyra de Jongh; Vlasta Vodopivec-Jamsek; Rifat Atun; Josip Car
Journal:  Cochrane Database Syst Rev       Date:  2013-12-05

Review 7.  Mobile phone text messaging to improve medication adherence in secondary prevention of cardiovascular disease.

Authors:  Alma J Adler; Nicole Martin; Javier Mariani; Carlos D Tajer; Onikepe O Owolabi; Caroline Free; Norma C Serrano; Juan P Casas; Pablo Perel
Journal:  Cochrane Database Syst Rev       Date:  2017-04-29

8.  Baseline Characteristics and Technology Training of Underserved Adults With Type 2 Diabetes in the Mobile Diabetes Detective (MoDD) Randomized Controlled Trial.

Authors:  Elizabeth M Heitkemper; Lena Mamykina; Jonathan N Tobin; Andrea Cassells; Arlene Smaldone
Journal:  Diabetes Educ       Date:  2017-10-23       Impact factor: 2.140

9.  Predictors of eHealth usage: insights on the digital divide from the Health Information National Trends Survey 2012.

Authors:  Emily Kontos; Kelly D Blake; Wen-Ying Sylvia Chou; Abby Prestin
Journal:  J Med Internet Res       Date:  2014-07-16       Impact factor: 5.428

Review 10.  What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions.

Authors:  Sarah J Iribarren; Kenrick Cato; Louise Falzon; Patricia W Stone
Journal:  PLoS One       Date:  2017-02-02       Impact factor: 3.240

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  1 in total

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Authors:  Monica Hytiris; Daisy Johnston; Shannon Mullen; Arlene Smyth; Elizabeth Dougan; Martina Rodie; S Faisal Ahmed
Journal:  Orphanet J Rare Dis       Date:  2021-02-04       Impact factor: 4.123

  1 in total

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