Recommendations to improve the accuracy of estimates of physical activity derived from self report.
ABSTRACT Assessment of physical activity using self-report has the potential for measurement error that can lead to incorrect inferences about physical activity behaviors and bias study results.
To provide recommendations to improve the accuracy of physical activity derived from self report.
We provide an overview of presentations and a compilation of perspectives shared by the authors of this paper and workgroup members.
We identified a conceptual framework for reducing errors using physical activity self-report questionnaires. The framework identifies 6 steps to reduce error: 1) identifying the need to measure physical activity, 2) selecting an instrument, 3) collecting data, 4) analyzing data, 5) developing a summary score, and 6) interpreting data. Underlying the first 4 steps are behavioral parameters of type, intensity, frequency, and duration of physical activities performed, activity domains, and the location where activities are performed. We identified ways to reduce measurement error at each step and made recommendations for practitioners, researchers, and organizational units to reduce error in questionnaire assessment of physical activity.
Self-report measures of physical activity have a prominent role in research and practice settings. Measurement error may be reduced by applying the framework discussed in this paper.
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ABSTRACT: Risk factors associated with many chronic diseases can be improved through regular physical activity. This study investigated whether cross-sectional associations between physical activity, assessed by the Exercise Vital Sign (EVS), and cardiometabolic risk factors can be detected in clinical settings. We used electronic records from Kaiser Permanente Southern California members (N = 622,897) to examine the association of EVS category with blood pressure, fasting glucose, random glucose, and glycosylated hemoglobin. Adults aged 18 years or older with at least 3 EVS measures between April 2010 and December 2012, without comorbid conditions, and not taking antihypertension or glucose-lowering medications were included. We compared consistently inactive (EVS = 0 min/wk for every measure) with consistently active (EVS ≥150 min/wk) and irregularly active (EVS 1-149 min/wk or not meeting the consistently active or inactive criteria) patients. Separate linear regression analyses were conducted controlling for age, sex, race/ethnicity, body mass index, and smoking status. Consistently active women had lower systolic (-4.60 mm Hg; 95% confidence interval [CI], -4.70 to -4.44) and diastolic (-3.28 mm Hg; 95% CI, -3.40 to -3.17) blood pressure than inactive women. Active men had lower diastolic blood pressure than inactive men. Consistently active patients (women, -5.27 mg/dL [95% CI, -5.56 to -4.97]; men, -1.45 mg/dL [95% CI, -1.75 to -1.16] and irregularly active patients (women, -4.57 mg/dL [95% CI, -4.80 to -4.34]; men, -0.42 mg/dL [95% CI, -0.66 to -0.19]) had lower fasting glucose than consistently inactive patients. Consistently active and irregularly active men and women also had favorable random glucose and HbA1c compared with consistently inactive patients. Routine clinical physical activity assessment may give health care providers additional information about their patients' cardiometabolic risk factors.Preventing chronic disease 01/2014; 11:E219. · 1.96 Impact Factor
- European Review of Aging and Physical Activity 10/2014; 11(2):133-139. · 0.81 Impact Factor
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ABSTRACT: Physical activity (PA) is a behavior that involves bodily movements resulting in energy expenditure. When assessing PA, the goal is to identify the frequency, duration, intensity, and types of behaviors performed during a period of time. Self-report measures of PA include administration of questionnaires and completion of detailed diaries and/or brief logs. Direct measures include motion sensors such as accelerometers, pedometers, heart-rate monitors, and multiple-sensor devices. The PA assessment period can range from a few hours to a lifetime depending on the tools used. Considerations when selecting a PA tool should include the literacy requirements of a tool, the purpose for assessing PA, the recall or time period to measure, the validity evidence of an assessment tool for the populations measured, and the generalizability of the results to diverse populations.Progress in Cardiovascular Diseases 10/2014; 57(4). · 2.44 Impact Factor