Karlijn Sporrel
Biographic Data
| ID | 7943770 |
|---|---|
| NAME | Karlijn Sporrel |
| GIVEN NAMES | Karlijn |
| FAMILY NAME | Sporrel |
| SIGNATURE | SPORREL K |
| AFFILIATIONS | Utrecht University |
| ORCID | 0000-0002-2757-8553 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
The social impact of community sports in disadvantaged neighbourhoods
In this article, we argue for the use of the concept of ‘public familiarity’ in research on community development through community sports to broaden our perspective on its social effects. Public familiarity is defined as a feeling of ease in local spaces, enabled by the capacity to know what to expect and who and when to trust or distrust, developed by some level of acquaintance, however superficial and fluid. The aims of this pilot study are to…
What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…
A Focus Group Study Among Inactive Adults Regarding the Perceptions of a Theory-Based Physical Activity App
Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the…
The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…
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What Are Good Situations for Running? A Machine Learning Study Using Mobile and Geographical Data
Running is a popular form of physical activity. Personal, social, and environmental determinants influence the engagement of the individual. To get insight in the relation between running behavior and external situations for different types of users, we carried out an extensive data mining study on large-scale datasets. We combined 4 years of historical running data (collected by a mobile exercise application from over 10K participants) with weat…
A Focus Group Study Among Inactive Adults Regarding the Perceptions of a Theory-Based Physical Activity App
Background: Despite the increasing attention for the positive effects of physical activity (PA), nearly half of the Dutch citizens do not meet the national PA guidelines. A promising method for increasing PA are mobile exercise applications (apps), especially if they are embedded with theoretically supported persuasive strategies (e.g., goal setting and feedback) that align with the needs and wishes of the user. In addition, it is argued that the…
The Design and Development of a Personalized Leisure Time Physical Activity Application Based on Behavior Change Theories, End-User Perceptions, and Principles From Empirical Data Mining
Introduction: Many adults do not reach the recommended physical activity (PA) guidelines, which can lead to serious health problems. A promising method to increase PA is the use of smartphone PA applications. However, despite the development and evaluation of multiple PA apps, it remains unclear how to develop and design engaging and effective PA apps. Furthermore, little is known on ways to harness the potential of artificial intelligence for de…
Reinforcement Learning to Send Reminders at Right Moments in Smartphone Exercise Application
Just-in-time adaptive intervention (JITAI) has gained attention recently and previous studies have indicated that it is an effective strategy in the field of mobile healthcare intervention. Identifying the right moment for the intervention is a crucial component. In this paper the reinforcement learning (RL) technique has been used in a smartphone exercise application to promote physical activity. This RL model determines the 'right' time to deli…
The social impact of community sports in disadvantaged neighbourhoods
In this article, we argue for the use of the concept of ‘public familiarity’ in research on community development through community sports to broaden our perspective on its social effects. Public familiarity is defined as a feeling of ease in local spaces, enabled by the capacity to know what to expect and who and when to trust or distrust, developed by some level of acquaintance, however superficial and fluid. The aims of this pilot study are to…
Psychology (4 works) · Computer Science (3 works) · Focus group (3 works) · Mobile Health and mHealth Applications (3 works) · Physical Activity and Health (3 works) · Applied Psychology (2 works) · Artificial Intelligence (2 works) · Human–computer interaction (2 works) · Perception (2 works) · Social Psychology (2 works)