Calibration of self-report tools for physical activity research: the Physical Activity Questionnaire (PAQ)

Abstract

BackgroundThe utility of self-report measures of physical activity (PA) in youth can be greatly enhanced by calibrating self-report output against objectively measured PA data.This study demonstrates the potential of calibrating self-report output against objectively measured physical activity (PA) in youth by using a commonly used self-report tool called the Physical Activity Questionnaire (PAQ).MethodsA total of 148 participants (grades 4 through 12) from 9 schools (during the 2009–2010 school year) wore an Actigraph accelerometer for 7 days and then completed the PAQ. Multiple linear regression modeling was used on 70% of the available sample to develop a calibration equation and this was cross validated on an independent sample of participants (30% of sample).ResultsA calibration model with age, gender, and PAQ scores explained 40% of the variance in values for the percentage of time in moderate-to-vigorous PA (%MVPA) measured from the accelerometers (%MVPA = 14.56 - (sex*0.98) - (0.84*age) + (1.01*PAQ)). When tested on an independent, hold-out sample, the model estimated %MVPA values that were highly correlated with the recorded accelerometer values (r = .63) and there was no significant difference between the estimated and recorded activity values (mean diff. = 25.3 ± 18.1 min; p = .17).ConclusionsThese results suggest that the calibrated PAQ may be a valid alternative tool to activity monitoring instruments for estimating %MVPA in groups of youth.

Is self-reported time spent sedentary and in physical activity differentially biased by age, gender, body mass index, and low-back pain?

“…An attractive option is to correct for self-report bias in a calibration procedure and use the corrected exposure values for further analyses. Calibration, or exposure modeling, is an established method for correcting self-reported information in the field of nutritional and body composition (41,42) and in occupational hygiene (43)(44)(45), and it is becoming increasingly popular in the field of physical activity (46)(47)(48)(49), even in an occupational context (50)(51)(52). The present study contributes to the development of effective models for estimating "true" sedentary time and time in MVPA by identifying a number of factors that may, in addition to the self-reported exposure in its own right, influence the extent of self-report bias, and that may, therefore, be candidates for inclusion in calibration models.…”

Gender and school-stage associations with health-related behaviours and health-related quality of life in Spanish children

“…Respondents are asked to recall the frequency and type of physical activity they have engaged in on each of the seven days prior to completing the questionnaire. Validation studies have found the PAQ-C to be highly reliable (Saint-Maurice, Welk, Beyler, Bartee, & Heelan, 2014).…”

Prediction of objectively measured physical activity and sedentariness among blue-collar work using survey questionnaires

“…Explicit prediction models have been proposed before to predict time spent sedentary and in physical activity (23)(24)(25), but these studies have not developed models for exposures at work, which may show associations with self-reported predictors other than leisure time exposures. A few previous studies have, indeed, developed prediction models for time spent sedentary and in physical activity specifically at work (26)(27)(28)(29)(30).…”