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Personal Health Data in Healthcare - Important Factors Considered by Health Students A Qualitative Study

Groeneveld, (Sjors) (Phd); Ouden, (Marjolein) (Lector); Bin Noon, G. (Gaya) (Extern); Figeys, M. (Mathieu) (Extern); Gemert-Pijnen, L. (Lisette) van (Extern); Verdaasdonk, R.M. (Rudolf) (Extern); Pelegrini Morita, P. (Plinio) (Extern); Esmail, S. (Shariff) (Extern); Os-Medendorp, H. (Harmieke ) van (Extern)

Background/Objectives: Digital technologies and data-driven approaches are rapidly transforming healthcare practice and enabling more personalized and preventive care. As personal health data becomes increasingly embedded in healthcare systems, understanding how future healthcare professionals interpret …

2026-06-16AlgemeenArtikel

Predicting Emotional Exhaustion with Multimodal Sensor Data During Return‑to‑Work Trajectories

Berkemeier, Lea; Kamphuis, Wim; Oldenhuis, Hilbrand (Digital Transformation); Kok, Robin N; Verdaasdonk, Ruud; van Gemert-Pijnen, Lisette

Purpose: Emotional exhaustion is a core component of burnout and impacts return-to-work trajectories following sick leave due to burnout or stress. Previous research identified links between emotional exhaustion and sleep, physical activity, mobility, and smartphone usage, yet little is known about how …

2026-04-22Mens & Maatschappij; …Artikel

Understanding the Factors that Influence the Implementation of AI-Driven Lifestyle Monitoring in Long-Term Care for Older Adults

S.W.M. Groeneveld; T. Dekkers; J.E.W.C. van Gemert-Pijnen; R.M. Verdaasdonk; T.J. Verveda; R. Witteveen; Harmieke van Os‑Medendorp (Lector); M.E.M. den Ouden

AI-driven lifestyle monitoring systems collect data from ambient, motion, contact, light, and physiological sensors placed in the home, enabling AI algorithms to identify daily routines and detect deviations to support older adults "aging in place." Despite its potential to support several challenges …

2025-10-03GezondheidArtikel

Essential competencies of nurses working with AI-driven lifestyle monitoring in long-term care: A modified Delphi study

Groeneveld, (Sjors) (Onderzoeker); Gemert-Pijnen, J.E.W.C. (Lisette) van (Extern); Os-Medendorp, (Harmieke) van (Extern); Dekkers, (Tessa ) (Extern); Verdaasdonk, R.M. (Ruud) (Extern); Houwelingen, T. (Thijs) van; Ouden, M.E.M. (Marjolein) den (Lector)

As more and more older adults prefer to stay in their homes as they age, thereandapos;s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace …

2025-03-12AlgemeenArtikel

Essential competencies of nurses working with AI-driven lifestyle monitoring in long-term care

S.W.M. Groeneveld; Harmieke van Os‑Medendorp (Lector); J.E.W.C. van Gemert-Pijnen; R.M. Verdaasdonk; C.T.M. van Houwelingen; T. Dekkers; M.E.M. den Ouden

As more and more older adults prefer to stay in their homes as they age, there’s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace nurses …

2025-03-01GezondheidArtikel

Essential competencies of nurses working with AI-driven lifestyle monitoring in long-term care

Sjors Groeneveld (Onderzoeker); Harmieke van Os-Medendorp (Onderzoeker); Lisette van Gemert-Pijnen (Onderzoeker); Ruud Verdaasdonk (Onderzoeker); Thijs van Houwelingen (Onderzoeker); Tessa Dekkers (Onderzoeker); Marjolein den Ouden (Onderzoeker)

Background: As more and more older adults prefer to stay in their homes as they age, there’s a need for technology to support this. A relevant technology is Artificial Intelligence (AI)-driven lifestyle monitoring, utilizing data from sensors placed in the home. This technology is not intended to replace …

2025GezondheidArtikel

The Cooperation Between Nurses and a New Digital Colleague “AI-Driven Lifestyle Monitoring” in Long-Term Care for Older Adults

Sjors Groeneveld; Gaya Bin Noon; Marjolein E.M. den Ouden; Harmieke van Os‑Medendorp (Lector); J.E.W.C. van Gemert-Pijnen; Rudolf M Verdaasdonk; Plinio Pelegrini Morita

Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in …

2024-05-23GezondheidArtikel

The Cooperation Between Nurses and a New Digital Colleague “AI-Driven Lifestyle Monitoring” in Long-Term Care for Older Adults: Viewpoint

Groeneveld, (Sjors) (Onderzoeker); Bin Noon, (Gaya) (Extern); Ouden, (Marjolein) den (Lector); Os-Medendorp, (Harmieke) van (Extern); Gemert-Pijnen, (Lisette) van (Extern); Verdaasdonk, (Rudolf) (Extern); Morita, (Plinio) (Extern)

2024-05-23AlgemeenArtikel

Preferences for coaching strategies in a personalized virtual coach for emotional eaters

Dol, Aranka (New Business & Ict); van Strien, Tatjana; Velthuijsen, Hugo (New Business & Ict); van Gemert-Pijnen, Lisette; Bode, Christina

Objectives: Emotional eating is recognized as a potential contributor to weight gain. Emotional eaters often hide their problems because of feelings of shame about their behavior, making it challenging to provide them with the necessary support. The introduction of a virtual coach might offer a potential …

2023-11-16ICT & Media; …Artikel

Virtual coaching for emotional eaters

Dol, Aranka (New Business & Ict); van Gemert-Pijnen, Lisette; Bode, Christina; Velthuijsen, Hugo

Obesity is a complex problem worldwide. This chronic condition has many different causes. One of them is emotional eating. In about 40% of overweight people, emotional eating plays a major role. Emotional eating is the tendency to (over)eat in response to negative emotions such as stress or irritability. …

2023-11-13ICT & Media; …Proefschrift

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