Personalizing motivational strategies

Carlijn A.L. Valk; Peter Lovei; Hubert Cornelis; Yaliang Chuang; Thomas Visser; Pearl Pu; Yuan Lu

Personalizing motivational strategies

Carlijn A.L. Valk, Peter Lovei, Hubert Cornelis, Yaliang Chuang, Thomas Visser, Pearl Pu, Yuan Lu

Research output: Contribution to conference › Poster › Academic

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Abstract

Design for behaviour change (BC) has the potential to motivate older adults to increase their physical activity and enjoy the health benefits hereof. Despite this potential, there is a lack of knowledge about how to profile users, to most effectively personalize strategies, which is detrimental to the overall effectiveness of these BC solutions. Thus we conducted a random control trial in which the effects of two BC strategies, implemented in two otherwise similar mobile applications, are compared. From the statistical analysis of the measured step data and the collected survey data, we were able to create motivation profiles for BC by triangulating an individual’s contextual, behavioural and psychological factors. Here we share an overview of our approach.
In this way we aim to inform designers doing important work in the field of BC toward increased physical activity.

Original language	English
Publication status	Published - 12 Nov 2019
Event	Data Science Summit 2019: The Annual Data Science Summit Eindhoven - Frits Philips Muziekgebouw, Eindhoven, Netherlands Duration: 12 Nov 2019 → 12 Nov 2019 https://www.tue.nl/en/research/research-areas/data-science/data-science-summit-2019/

Seminar

Seminar	Data Science Summit 2019
Country/Territory	Netherlands
City	Eindhoven
Period	12/11/19 → 12/11/19
Internet address	https://www.tue.nl/en/research/research-areas/data-science/data-science-summit-2019/

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Bekker, M. M., Lu, Y., Lu, Y., Valk, C., Chuang, Y., Schoumacher, J., Damen, A. A. J. M. & Wintermans, M. C.
1/02/16 → 31/01/21
Project: Research direct

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@conference{62243248be2d49409ca89967c953399a,

title = "Personalizing motivational strategies",

abstract = "Design for behaviour change (BC) has the potential to motivate older adults to increase their physical activity and enjoy the health benefits hereof. Despite this potential, there is a lack of knowledge about how to profile users, to most effectively personalize strategies, which is detrimental to the overall effectiveness of these BC solutions. Thus we conducted a random control trial in which the effects of two BC strategies, implemented in two otherwise similar mobile applications, are compared. From the statistical analysis of the measured step data and the collected survey data, we were able to create motivation profiles for BC by triangulating an individual{\textquoteright}s contextual, behavioural and psychological factors. Here we share an overview of our approach.In this way we aim to inform designers doing important work in the field of BC toward increased physical activity.",

author = "Valk, {Carlijn A.L.} and Peter Lovei and Hubert Cornelis and Yaliang Chuang and Thomas Visser and Pearl Pu and Yuan Lu",

year = "2019",

month = nov,

day = "12",

language = "English",

note = "Data Science Summit 2019 : The Annual Data Science Summit Eindhoven ; Conference date: 12-11-2019 Through 12-11-2019",

url = "https://www.tue.nl/en/research/research-areas/data-science/data-science-summit-2019/",

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TY - CONF

T1 - Personalizing motivational strategies

AU - Valk, Carlijn A.L.

AU - Lovei, Peter

AU - Cornelis, Hubert

AU - Chuang, Yaliang

AU - Visser, Thomas

AU - Pu, Pearl

AU - Lu, Yuan

PY - 2019/11/12

Y1 - 2019/11/12

N2 - Design for behaviour change (BC) has the potential to motivate older adults to increase their physical activity and enjoy the health benefits hereof. Despite this potential, there is a lack of knowledge about how to profile users, to most effectively personalize strategies, which is detrimental to the overall effectiveness of these BC solutions. Thus we conducted a random control trial in which the effects of two BC strategies, implemented in two otherwise similar mobile applications, are compared. From the statistical analysis of the measured step data and the collected survey data, we were able to create motivation profiles for BC by triangulating an individual’s contextual, behavioural and psychological factors. Here we share an overview of our approach.In this way we aim to inform designers doing important work in the field of BC toward increased physical activity.

AB - Design for behaviour change (BC) has the potential to motivate older adults to increase their physical activity and enjoy the health benefits hereof. Despite this potential, there is a lack of knowledge about how to profile users, to most effectively personalize strategies, which is detrimental to the overall effectiveness of these BC solutions. Thus we conducted a random control trial in which the effects of two BC strategies, implemented in two otherwise similar mobile applications, are compared. From the statistical analysis of the measured step data and the collected survey data, we were able to create motivation profiles for BC by triangulating an individual’s contextual, behavioural and psychological factors. Here we share an overview of our approach.In this way we aim to inform designers doing important work in the field of BC toward increased physical activity.

M3 - Poster

T2 - Data Science Summit 2019

Y2 - 12 November 2019 through 12 November 2019

ER -

Personalizing motivational strategies

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