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 inGait & posture Vol. 38; no. 4; pp. 912 - 917
Main Authors Lee, Paul H., Macfarlane, Duncan J., Lam, T.H.
Format Journal Article
LanguageEnglish
Published England Elsevier B.V 01.09.2013
Subjects
Online AccessGet full text
ISSN0966-6362
1879-2219
1879-2219
DOI10.1016/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.
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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Issue 4
Keywords Adherence
Participation
Physical activity
Accelerometry
Activity monitor
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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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https://dx.doi.org/10.1016/j.gaitpost.2013.04.018
https://www.ncbi.nlm.nih.gov/pubmed/23688408
https://www.proquest.com/docview/1443396640
https://www.proquest.com/docview/1500765170
Volume 38
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