Journal of Medical Internet Research (Feb 2012)

Active-Q: Validation of the Web-Based Physical Activity Questionnaire Using Doubly Labeled Water

  • Bonn, Stephanie Erika,
  • Trolle Lagerros, Ylva,
  • Christensen, Sara Elisabeth,
  • Möller, Elisabeth,
  • Wright, Antony,
  • Sjölander, Arvid,
  • Bälter, Katarina

DOI
https://doi.org/10.2196/jmir.1974
Journal volume & issue
Vol. 14, no. 1
p. e29

Abstract

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BackgroundIncreased use of the Internet provides new opportunities for collecting data in large studies. The aim of our new Web-based questionnaire, Active-Q, is to assess total physical activity and inactivity in adults. Active-Q assesses habitual activity during the past year via questions in four different domains: (1) daily occupation, (2) transportation to and from daily occupation, (3) leisure time activities, and (4) sporting activities. ObjectiveThe objective of our study is to validate Active-Q’s energy expenditure estimates using the doubly labeled water (DLW) method, and to assess the reproducibility of Active-Q by comparing the results of the questionnaire completed by the same group on two occasions. MethodsThe validity and reproducibility of Active-Q were assessed in a group of 37 individuals, aged 20 to 65 years. Active-Q was distributed via email to the participants. The total energy expenditure of the participants was assessed using DLW for 11 consecutive days. ResultsThe median time to complete Active-Q was 6.1 minutes. The majority of participants (27/37, 73%) reported that the questionnaire was “easy” or “very easy” to answer. On average, Active-Q overestimated the total daily energy expenditure by 440 kJ compared with the DLW. The Spearman correlation between the two methods was r = 0.52 (P < .001). The intraclass correlation coefficient for total energy expenditure between the results of Active-Q completed on two occasions was 0.83 (95% CI 0.73-0.93). ConclusionsActive-Q is a valid and reproducible method of assessing total energy expenditure. It is also a user-friendly method and suitable for Web-based data collection in large epidemiological studies.