The Influence of Wearable Devices as Goal Setting for Rural Older Adults on Physical Activity and Using Behavior

• Main Authors: Chia-HsuanChang, 張家萱
• Other Authors: Hsueh-wen Chow
• Format: Others
• Language: en_US
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/handle/jnrfzx

碩士 === 國立成功大學 === 體育健康與休閒研究所 === 107 === Background: Activity trackers have become a popular means to motivate people to monitor their physical activity levels and maintain regular active lifestyles. However, little attention has been paid to the effects of activity tracker use among older adults. Therefore, this study tested the activity trackers and supplied goal setting to increase physical activity (PA) for older adults who live in rural areas. Method: A total of 30 older adults living in a rural county in Taiwan wore activity trackers daily for six consecutive weeks. Participants were divided into two groups: One group were received individualized goal setting every week, as the other group were received universal goal (10000 steps daily) setting every week. The measures include activity trackers in conjunction with The International Physical Activity Questionnaire (IPAQ), use of the functional test, and a semi-structured interview. Analysis: All the data organized and imported into SPSS 18.0. Descriptive statistics applied to present the characteristics of the participants, Wilcoxon signed-rank test was adopted to examine the change in physical activity levels measured by activity trackers and IPAQ in six weeks. Mann-Whitney U test was designed to examine goal setting effects between individualized group and universal group. Spearman correlation was to be utilized to examine the relationship between objective and subjective measurement in rural elders’ physical activity level. Results: The mean age of the participants was 77.5 years (range: 61–88 years). A total of 66.7% were women. Most of the participants had little education; 30% were illiterate, and 60% had only graduated from elementary school. Among the participants, 55% did not use mobile phones. The participants showed significant increase in physical activity in terms of objective measurement from the activity tracker with the average steps. The measures indicated individual group increased their mean daily step count from 4401 to 6648 steps per day (p=0.002), while the universal group steps also changed of 3752 steps/day (range 794– 15026) in week 1 to 6297 steps/day (range 1084– 18068) in week 6 (p〈0.001). In the use of the functional test, 20% of the older adults found it difficult to wear the activity trackers. Moreover, 24% had trouble checking the total number of steps walked, 24% were unsure how to check distance travelled on the activity tracker screen, and 32% had trouble assembling the device. Although many participants stated in the interviews that wearing the activity tracker helped them check the time and motivated them to increase walking behavior, many participants had difficulty using or understanding the information related to their physical activity. Conclusion: As population aging continues, numerous health promotion campaigns and research interventions have adopted activity tracker to monitor older adults’ physical activity levels or related health information to develop future applications (e.g., in telemedicine). In this study, there is a significant increase in the amount of physical activity (steps) in the six weeks. However, we found that many older adults in rural areas of Taiwan are unfamiliar with products of such technology. Consequently, they face several obstacles when using activity trackers, such as inability to assemble and charge the device, inability to understand the on-screen information, and inconvenience due to their lifestyles (e.g., participating in agricultural work). In the future, to ensure success, interventions that involve older adults with low education levels should start with detailed instructions on how to use fitness trackers.