Factors associated with participant compliance in studies using accelerometers
•We investigated factors associated with accelerometer compliance.•Participants wore the accelerometer on average for 13.9h in a 24-h day.•Those with full-time job, healthier, and older participants tended to comply.•These results provide details for sample size calculation for accelerometer studies...
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Published in | Gait & posture Vol. 38; no. 4; pp. 912 - 917 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier B.V
01.09.2013
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Subjects | |
Online Access | Get full text |
ISSN | 0966-6362 1879-2219 1879-2219 |
DOI | 10.1016/j.gaitpost.2013.04.018 |
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Abstract | •We investigated factors associated with accelerometer compliance.•Participants wore the accelerometer on average for 13.9h in a 24-h day.•Those with full-time job, healthier, and older participants tended to comply.•These results provide details for sample size calculation for accelerometer studies.
Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009–January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance. |
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AbstractList | Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009-January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance.Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009-January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance. Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009-January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance. Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6 A- 13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009aJanuary 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9 h in a 24-h day. No significant difference was found between males and females (p = 0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p < 0.001), those with full-time job (p < 0.01), with tertiary education (p < 0.01), non-smokers (p < 0.01) and with high self-reported health (p < 0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance. •We investigated factors associated with accelerometer compliance.•Participants wore the accelerometer on average for 13.9h in a 24-h day.•Those with full-time job, healthier, and older participants tended to comply.•These results provide details for sample size calculation for accelerometer studies. Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the researchers but many do not. We investigated a range of demographic factors associated with participant compliance in obtaining analyzable accelerometer data. A total of 3601 participants (aged 47.6±13.1 years, 44.6% male) were included. They were asked to wear an accelerometer (ActiGraph) for four consecutive days after completing a household survey during March 2009–January 2011 in Hong Kong. Participants wore the accelerometer on average for 13.9h in a 24-h day. No significant difference was found between males and females (p=0.38). Using log-linear regression, it was found that older participants (0.5% more wearing hours for each year of age, p<0.001), those with full-time job (p<0.01), with tertiary education (p<0.01), non-smokers (p<0.01) and with high self-reported health (p<0.05) wore the accelerometer for more hours. These results provide details for estimating compliance rates for samples with different characteristics and thus sample size calculation to account for participant compliance. Highlights • We investigated factors associated with accelerometer compliance. • Participants wore the accelerometer on average for 13.9 h in a 24-h day. • Those with full-time job, healthier, and older participants tended to comply. • These results provide details for sample size calculation for accelerometer studies. |
Author | Macfarlane, Duncan J. Lam, T.H. Lee, Paul H. |
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Snippet | •We investigated factors associated with accelerometer compliance.•Participants wore the accelerometer on average for 13.9h in a 24-h day.•Those with full-time... Highlights • We investigated factors associated with accelerometer compliance. • Participants wore the accelerometer on average for 13.9 h in a 24-h day. •... Participant compliance is an important issue in studies using accelerometers. Some participants wear the accelerometer for the duration specified by the... |
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SubjectTerms | Accelerometry Accelerometry - statistics & numerical data Activity monitor Adherence Adult Age Factors Cohort Studies Educational Status Employment - statistics & numerical data Female Health Status Hong Kong - epidemiology Humans Linear Models Male Middle Aged Monitoring, Ambulatory - statistics & numerical data Motor Activity Orthopedics Participation Patient Compliance - statistics & numerical data Physical activity Self Report Sex Factors Smoking - epidemiology Time Factors |
Title | Factors associated with participant compliance in studies using accelerometers |
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