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User Experience and Potential Health Effects of a Conversational Agent-Based Electronic Health Intervention: Protocol for an Observational Cohort Study

Marian Z M Hurmuz, Stephanie M Jansen-Kosterink, Harm op den Akker, Hermie J Hermens

JMIR Res Protoc 2020;9(4):e16641

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Tailoring Persuasive Electronic Health Strategies for Older Adults on the Basis of Personal Motivation: Web-Based Survey Study

Although the term is often interchangeably used with personalization, we use the term tailoring as an umbrella term to cover various specific concepts, such as feedback, context awareness, or user targeting, as defined in a study by op den Akker et al [10].

Lex van Velsen, Marijke Broekhuis, Stephanie Jansen-Kosterink, Harm op den Akker

J Med Internet Res 2019;21(9):e11759

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Understanding the Acceptance of an eHealth Technology in the Early Stages of Development: An End-User Walkthrough Approach and Two Case Studies

Lex van Velsen, Mirka Evers, Cristian-Dan Bara, Harm Op den Akker, Simone Boerema, Hermie Hermens

JMIR Form Res 2018;2(1):e10474

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User Models for Personalized Physical Activity Interventions: Scoping Review

A survey of tailoring techniques used in real-time PA coaching systems published before August 2013 is presented in the study by op den Akker et al [17].The term “personalization” has multiple definitions in different domains [18].

Suparna Ghanvatkar, Atreyi Kankanhalli, Vaibhav Rajan

JMIR Mhealth Uhealth 2019;7(1):e11098

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Active Assistance Technology for Health-Related Behavior Change: An Interdisciplinary Review

Not applicable Op den Akker et al 2011 [58] PA / adults Software agent for smart phone: use machine learning to develop user model. Tailor messages to user history and current context. Prototype. Not an empirical study.

Catriona M Kennedy, John Powell, Thomas H Payne, John Ainsworth, Alan Boyd, Iain Buchan

J Med Internet Res 2012;14(3):e80

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Maximizing Potentially Avoidable Hospitalizations and Cost Savings Beyond Targeting the Most Costly Patients

11731AbstractAbstractMaximizing Potentially Avoidable Hospitalizations and Cost Savings Beyond Targeting the Most Costly PatientsHaleTimothySimonsMarianaPhD1Philips Research34 High Tech CampusEindhoven,Netherlandsmariana.simons@philips.comGolasSaraPhD2AgboolaStephenMPH, MD2op den

Mariana Simons, Sara Golas, Stephen Agboola, Jorn op den Buijs, Jennifer Felsted, Nils Fischer, Allison Orenstein

iproc 2018;4(2):e11731

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Natural Language Processing of Medical Alert Service Notes Reveals Reasons for Emergency Admissions

15225AbstractAbstractNatural Language Processing of Medical Alert Service Notes Reveals Reasons for Emergency AdmissionsBrownJulieMasculoFelipe1Philips Research34 High Tech CampusEindhovenNetherlands+31629469888felipe.masculo@philips.comhttps://orcid.org/0000-0003-3110-3478op den

Felipe Masculo, Jorn op den Buijs, Mariana Simons, Aki Harma

iproc 2019;5(1):e15225

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Analysis of the Features Important for the Effectiveness of Physical Activity–Related Apps for Recreational Sports: Expert Panel Approach

Furthermore, Op den Akker et al (2014) proposed a framework for tailoring of real-time PA coach systems [50].

Joan Dallinga, Mark Janssen, Jet van der Werf, Ruben Walravens, Steven Vos, Marije Deutekom

JMIR Mhealth Uhealth 2018;6(6):e143

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Philips Lifeline CareSage Analytics Engine: Retrospective Evaluation on Patients of Partners Healthcare at Home

Mariana Simons, Jorn op den Buijs, Linda Schertzer

iproc 2016;2(1):e8

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LEAVES (optimizing the mentaL health and resiliencE of older Adults that haVe lost thEir spouSe via blended, online therapy): Proposal for an Online Service Development and Evaluation

Lex van Velsen, Miriam Cabrita, Harm op den Akker, Lena Brandl, Joana Isaac, María Suárez, Afonso Gouveia, Nathaniel Evans, Rute Dinis de Sousa, Ana Maria Rodrigues, Helena Canhão, DELA Natura- En Levensverzekeringen NV, Marije Blok, Carlos Alcobia, Jeannette Brodbeck

JMIR Res Protoc 2020;9(9):e19344

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