||The Influence of Wearable Devices as Goal Setting for Rural Older Adults on Physical Activity and Using Behavior
||Institute of Physical Education, Health & Leisure Studies
Individualized target setting
方法與結果: 本研究將偏鄉30位高齡者隨機分成兩組，個別化組的受試者每週得到個別化的目標步數建議，通用化組則統一接收到一天一萬步的目標。受試者平均年齡為77.5歲 (範圍:61-88歲)，66.7%為女性。 在六週的介入後，個別化組的受試者在步數有顯著的上升，從每日平均4401步進步至6648步(p=0.002)，在通用化組方面，也從每日平均3102步進步至5945步(p=0.001)，達到顯著的進步。總體來說，兩組受試者的身體活動量在步數及IPAQ身體活動量表均有顯著的提升。另外，於訪談的內容發現，多數的高齡者在第一週認為穿戴式裝置不能改變他們的生活，到了第六週，認為穿戴式裝置有正面影響的高齡者有明顯增加。在手環功能測試方面，20%的高齡者在穿著手環的功能上有困難，24%的高齡者在觀看時間與距離上有困難，並且有32%的高齡者沒有辦法組裝手環，可見偏鄉高齡者使用新科技的困難。
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.
1-1 Background 1
1-2 Research purpose 3
1-3 Contributions 3
1-4 Definition of term 4
Literature Review 4
2-1 Development of activity trackers 4
2-2 Relationship between activity trackers and physical activity 7
2-3 Older adults' acceptance of wearable devices 8
2-4 Physical activity and technology use of rural older adults 10
2-5 Using goal setting on older adults 12
2-6 Chapter summary 13
3-1 Inclusion and exclusion criteria for research participants 14
3-2 A pilot study 15
3-2 Research materials 15
3-2-1 Research device: Nyftii watch 15
3-2-2 Questionnaires 16
3-2-3 Semi-structured interview 18
3-3 Research procedure 19
3-3-1 Exercise course 20
3-3-2 Functional fitness test 22
3-3-3 Activity tracker instruction course 22
3-3-4 Group assignment 24
3-4 Data analysis 25
4-2-1 Activity trackers functional test 29
4-2-2 Physical activity 30
4-2-4 Correlation between the subjective and objective ways 33
4-3 Post-intervention (six weeks, three months) 34
4-3-1 Transtheoretical model questionnaire 34
4-3-2 Day of use 35
4-3-3 IPAQ 36
4-4 Interview 36
4-4-1 Interview coding schemes 37
4-4-2 Initial interview 37
4-4-3 Midterm interview 38
4-4-4 Final interview 39
4-4-4 Post-intervention interview 42
4-4-5 Local neighborhood manager interview 43
5-1 Using conditions and barriers 44
5-2 Continuity of using 46
5-3 Change in PA 47
5-4 Goal setting 47
5-5 Factor affecting results 48
5-6 Limitations 49
Appendix1: Semi-structured interview guide 61
Appendix2: IRB No.: A-ER-106-511 63
Appendix3: IPAQ Authorization file 64
Appendix4: IPAQ 65
Appendix5: Functional fitness test norm 69
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