Motivating physical activity among older Singaporeans : the role of fitness tracking and social context
Motivating older adults to be physically active is a significant issue, especially in countries with aging populations. As the world advances technologically, leveraging the affordances of information and communication technology (ICT) is one way to encourage older adults’ physical activity. This st...
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Format: | Thesis-Doctor of Philosophy |
Language: | English |
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Nanyang Technological University
2021
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Online Access: | https://hdl.handle.net/10356/151433 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Motivating older adults to be physically active is a significant issue, especially in countries with aging populations. As the world advances technologically, leveraging the affordances of information and communication technology (ICT) is one way to encourage older adults’ physical activity. This study applies a systematic scientific approach to finding a relationship between personalized feedback, social context, and behavior change. In a 2x2 between-group experiment, 240 participants received either a fitness tracker with a visible display or one that is blinded. Further, they participated in the experiment either by themselves or with a strong- tie dyadic partner. The first hypothesis is that personalized feedback made available on fitness trackers will lead to more physical activity because of the quantified awareness of the gap between one’s behavior and the goal. The second hypothesis is that the status of being in a dyadic condition vs. an individual condition will lead to more physical activity. I suggest that the effect of the dyad is moderated by the support of the dyadic partner and mediated by interaction with the partner. Lastly, I hypothesize that sharing fitness tracker feedback with strong-tie dyadic partners gives rise to dyad-referent feedback, magnifying the main effects of the feedback and dyadic conditions on physical activity. In addition to objectively- measured data collected from the fitness trackers, questionnaire responses were used to control for covariates and to test the proposed model in a deeper and more complete sense. Analysis of the data with structural equation modeling revealed that personalized feedback is indeed associated with higher percentages of meeting daily step counts of 7,500 and 10,000 steps. However, the effect of the dyad is associated with lower mean and median step counts, and lower percentages of meeting daily step counts of 10,000 and 15,000 steps. Dyadic support moderated the effect of the dyad in one outcome, such that when there was more support, those in the dyadic intervention reported having less sedentary time. Dyadic interaction did not mediate the effect of the dyad, nor did the feedback from fitness trackers moderate the effect of the dyad. Finally, as a secondary analysis, I carried out qualitative interviews with 22 individuals from different experimental groups. From their comments, I derived a process model explaining the mechanisms and the four effects of feedback, namely, cognition, emotion, action, and intuition. Additionally, I identified relational, individual, and situational factors within the dyad that played into positive and negative outcomes in physical activity, and into the independence of couples’ physical activity. The findings from this study elucidate how real-time personalized feedback can motivate physical activity among older adults and highlight the goal-related factors that influence this effect. It also shows that the coupled identity in older couples can impede behavior change within dyads. For older adults with set lifestyles and dyadic nomos, it may be more effective for programs to drive behavior change within individuals instead of couples. It is useful to educate them on the benefits of physical activity and provide assistance for successful mHealth adoption. |
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