Cited by 175Mobile Health and mHealth ApplicationsTelemedicine and Telehealth ImplementationTechnology Use by Older Adults

Factors Influencing the Use of a Web-Based Application for Supporting the Self-Care of Patients with Type 2 Diabetes: A Longitudinal Study

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Nijland, Nicol, van Gemert-Pijnen, Julia EWC, Kelders, Saskia M, Brandenburg, Bart J, Seydel, Erwin R·2011·Journal of Medical Internet Research

Abstract

BACKGROUND: The take-up of eHealth applications in general is still rather low and user attrition is often high. Only limited information is available about the use of eHealth technologies among specific patient groups. OBJECTIVE: The aim of this study was to explore the factors that influence the initial and long-term use of a Web-based application (DiabetesCoach) for supporting the self-care of patients with type 2 diabetes. METHODS: A mixed-methods research design was used for a process analysis of the actual usage of the Web application over a 2-year period and to identify user profiles. Research instruments included log files, interviews, usability tests, and a survey. RESULTS: The DiabetesCoach was predominantly used for interactive features like online monitoring, personal data, and patient-nurse email contact. It was the continuous, personal feedback that particularly appealed to the patients; they felt more closely monitored by their nurse and encouraged to play a more active role in self-managing their disease. Despite the positive outcomes, usage of the Web application was hindered by low enrollment and nonusage attrition. The main barrier to enrollment had to do with a lack of access to the Internet (146/226, 65%). Although 68% (34/50) of the enrollees were continuous users, of whom 32% (16/50) could be defined as hardcore users (highly active), the remaining 32% (16/50) did not continue using the Web application for the full duration of the study period. Barriers to long-term use were primarily due to poor user-friendliness of the Web application (the absence of "push" factors or reminders) and selection of the "wrong" users; the well-regulated patients were not the ones who could benefit the most from system use because of a ceiling effect. Patients with a greater need for care seemed to be more engaged in long-term use; highly active users were significantly more often medication users than low/inactive users (P = .005) and had a longer diabetes duration (P = .03). CONCLUSION: Innovations in health care will diffuse more rapidly when technology is employed that is simple to use and has applicable components for interactivity. This would foresee the patients' need for continuous and personalized feedback, in particular for patients with a greater need for care. From this study several factors appear to influence increased use of eHealth technologies: (1) avoiding selective enrollment, (2) making use of participatory design methods, and (3) developing push factors for persistence. Further research should focus on the causal relationship between using the system's features and actual usage, as such a view would provide important evidence on how specific technology features can engage and captivate users.

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  • Users' adoption and long-term use of eHealth technologies remains lower than expected.

    “While such technologies can be effective [1,2], one of the main problems is that users’ adoption and long-term use remains lower than expected [3-5].”
  • The Few Touch application was equipped with neither "push" factors nor an advanced decision support system providing feedback based on accumulated data and other personal profiles.

    “The application was equipped with neither “push” factors nor an advanced decision support system providing feedback based on accumulated data and other personal profiles, which are advocated for long-term usage, according to relevant studies [62-65].”
  • Decrease in usage after gaining a sense of mastery over diabetes is in line with findings by relevant studies.

    “Decrease in usage after gaining a sense of mastery over diabetes is in line with findings by relevant studies [30,32,62].”
  • Relevant studies advocate push factors and an advanced decision support system providing feedback based on accumulated data and other personal profiles for long-term usage.

    “The application was equipped with neither “push” factors nor an advanced decision support system providing feedback based on accumulated data and other personal profiles, which are advocated for long-term usage, according to relevant studies [62-65].”

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Authors
Nijland, N., van Gemert-Pijnen, J. E., Kelders, S. M., Brandenburg, B. J., & Seydel, E. R.
Affiliations
University of Twente (NL)
Corresponding author
Nijland, Nicol
Venue
Journal of Medical Internet Research
Published
2011-09-30
Volume
13
Issue
3
Pages
e71
ISSN
1438-8871 (ISSN-L)
OpenAlex
W2101939845
Cited by
175
References
74
Citations by year
2026: 1 · 2025: 3 · 2024: 5 · 2023: 12 · 2022: 8 · 2021: 5 · 2020: 10 · 2019: 15 · 2018: 12 · 2017: 21 · 2016: 12 · 2015: 17 · 2014: 18 · 2013: 22 · 2012: 12
FWCI
32.05
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Journal of Medical Internet Research (publishedVersion, other-oa)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • University of Twente Research Information (submittedVersion, cc-by)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
  • Social Sciences › Demography › Technology Use by Older Adults
Keywords
type 2 diabetes, web application, digital health adoption, self-care, user attrition, user profiles, continuous feedback, nurse-patient communication, internet access barriers, ease of use, participatory design, diabetes duration, medication use, technology acceptance, patient engagement, personalized feedback, ceiling effect, health behavior change, diabetes self-management education
MeSH terms
Adult, Aged, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Patient Education as Topic, Patient Participation, Self Care, Social Support, User-Computer Interface, Disease Management, Internet, Access to Information, Electronic Mail, Consumer Health Information

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