Factors Influencing Walking and Exercise Adherence in Healthy Older Adults Using Monitoring and Interfacing Technology: Preliminary Evidence

被引:9
作者
Albergoni, Andrea [1 ,2 ,3 ,4 ]
Hettinga, Florentina J. [5 ,6 ]
Stut, Wim [7 ]
Sartor, Francesco [4 ,5 ,8 ]
机构
[1] Univ Milan, Dept Biomed Sci Hlth, I-20133 Milan, Italy
[2] Univ Genoa, Ctr Polifunz Sci Motorie, I-16132 Genoa, Italy
[3] Univ Genoa, Dept Neurosci DINOGMI, I-16148 Genoa, Italy
[4] Philips Res, Dept Patient Care & Measurements, NL-5656 AE Eindhoven, Netherlands
[5] Univ Essex, Sch Sport Rehabil & Exercise Sci, Colchester CO4 3WA, Essex, England
[6] Northumbria Univ, Dept Sport Exercise & Rehabil, Newcastle Upon Tyne NE1 8ST, Tyne & Wear, England
[7] Philips Res, Dept Chron Dis Management, NL-5656 AE Eindhoven, Netherlands
[8] Bangor Univ, Coll Hlth & Behav Sci, Bangor LL57 2EF, Gwynedd, Wales
关键词
activity pacing; wearables; profiling; FATIGUE SEVERITY SCALE; PHYSICAL-ACTIVITY; MULTIPLE-SCLEROSIS; SELF-EFFICACY; HEART-RATE; THERAPY; REPRODUCIBILITY; RECOMMENDATIONS; QUESTIONNAIRE; FATIGABILITY;
D O I
10.3390/ijerph17176142
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Background: Monitoring and interfacing technologies may increase physical activity (PA) program adherence in older adults, but they should account for aspects influencing older adults' PA behavior. This study aimed at gathering preliminary wrist-based PA adherence data in free-living and relate these to the influencing factors. Methods: Ten healthy older adults (4 females, aged 70-78 years) provided health, fatigue, activity levels, attitude towards pacing, and self-efficacy information and performed a 6 min-walk test to assess their fitness. After a baseline week they followed a two-week walking and exercise intervention. Participants saw their progress via a purposely designed mobile application. Results: Walking and exercise adherence did not increase during the intervention (p= 0.38,p= 0.65). Self-efficacy decreased (p= 0.024). The baseline physical component of the Short Form Health Survey was the most predictive variable of walking adherence. Baseline perceived risk of over-activity and resting heart rate (HRrest) were the most predictive variables of exercise adherence. When the latter two were used to cluster participants according to their exercise adherence, the fitness gap between exercise-adherent and non-adherent increased after the intervention (p= 0.004). Conclusions: Risk of over-activity and HR(rest)profiled short-term exercise adherence in older adults. If confirmed in a larger and longer study, these could personalize interventions aimed at increasing adherence.
引用
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页码:1 / 18
页数:17
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