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Stephanie M Jansen-Kosterink

Biographic Data

ID2143537
NAMEStephanie M Jansen-Kosterink
GIVEN NAMESStephanie M
FAMILY NAMEJansen-Kosterink
SIGNATUREJANSEN-KOSTERINK S M
AFFILIATIONSRoessingh Research and Development
ORCID0000-0002-2095-7104
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
AUTHOR COUNT3
EDITOR COUNT0
FIRST PUBLICATION YEAR2019
LATEST PUBLICATION YEAR2025
H-INDEX0
  • Attrition of older adults in web-based health interventions

    Open Access•Marian Zm Hurmuz-Bodde, Stephanie M Jansen-Kosterink et al.•ARTICLE•Journal of Health Psychology•2025•References: 26

    To identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults. We conducted an observational cohort study. Participants completed a pre-test questionnaire and got access to an eHealth intervention, called Stranded, for 4 weeks. With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affect drop-out. Ninety older adults started usin…

  • Acceptance and Potential Impact of the eWall Platform for Health Monitoring and Promotion in Persons with a Chronic Disease or Age-Related Impairment

    Open Access•Francesco Infarinato, Stephanie M Jansen-Kosterink et al.•ARTICLE•International Journal of…•2020

    Pervasive health technologies can increase the effectiveness of personal health monitoring and training, but more user studies are necessary to understand the interest for these technologies, and how they should be designed and implemented. In the present study, we evaluated eWALL, a user-centered pervasive health technology consisting of a platform that monitors users' physical and cognitive behavior, providing feedback and motivation via an eas…

  • Identification of community-dwelling older adults at risk of frailty using the PERSSILAA screening pathway

    Open Access•Stephanie M Jansen-Kosterink, Lex Van Velsen et al.•ARTICLE•BMC Public Health•2019

    Pre-frailty is common among community-dwelling older adults. The PERSSILAA screening approach is a multi-factor, two-step screening process, potentially useful for primary prevention to identify those at risk of frailty and who will benefit most from preventive strategies

No prominent works on this page.

  • Identification of community-dwelling older adults at risk of frailty using the PERSSILAA screening pathway

    Open Access•Stephanie M Jansen-Kosterink, Lex Van Velsen et al.•ARTICLE•BMC Public Health•2019

    Pre-frailty is common among community-dwelling older adults. The PERSSILAA screening approach is a multi-factor, two-step screening process, potentially useful for primary prevention to identify those at risk of frailty and who will benefit most from preventive strategies

  • Acceptance and Potential Impact of the eWall Platform for Health Monitoring and Promotion in Persons with a Chronic Disease or Age-Related Impairment

    Open Access•Francesco Infarinato, Stephanie M Jansen-Kosterink et al.•ARTICLE•International Journal of…•2020

    Pervasive health technologies can increase the effectiveness of personal health monitoring and training, but more user studies are necessary to understand the interest for these technologies, and how they should be designed and implemented. In the present study, we evaluated eWALL, a user-centered pervasive health technology consisting of a platform that monitors users' physical and cognitive behavior, providing feedback and motivation via an eas…

  • Attrition of older adults in web-based health interventions

    Open Access•Marian Zm Hurmuz-Bodde, Stephanie M Jansen-Kosterink et al.•ARTICLE•Journal of Health Psychology•2025•References: 26

    To identify demographics and personal motivation types that predict dropping out of eHealth interventions among older adults. We conducted an observational cohort study. Participants completed a pre-test questionnaire and got access to an eHealth intervention, called Stranded, for 4 weeks. With survival and Cox-regression analyses, demographics and types of personal motivation were identified that affect drop-out. Ninety older adults started usin…

Medicine (3 works) · Public health (3 works) · Digital Mental Health Interventions (2 works) · Disease (2 works) · Gerontology (2 works) · Mobile Health and mHealth Applications (2 works) · Nursing (2 works) · Psychology (2 works) · Affect (linguistics (1 works) · Applied Psychology (1 works)

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