Comparing GPS, Log, Survey, and Accelerometry to Measure Physical Activity

Abstract

Objectives Both self-report and objective measures have strengths and limitations for studying physical activity (PA) and travel. We explored how objectively measured global positioning system (GPS) and accelerometer data matches with travel logs and questionnaires in predicting trip duration and PA. Methods In a study of PA and travel among residents in Atlanta, GA conducted in 2008–2009, 99 participants wore GPS devices and accelerometers, and recorded all trips in a log for 5 consecutive days. Participants also completed a self-administered questionnaire on PA and travel behaviors. Results There was good agreement between GPS and log for assessment of trip duration, although log measures overestimated trip duration (concordance correlation coefficient 0.53 [0.47, 0.59]; Bland-Altman estimate 0.76 [0.16, 3.71] comparing GPS to log). Log measures underestimated light PA and overestimated moderate PA compared to accelerometry when greater than zero moderate PA was reported. Conclusions It is often not feasible to deploy accelerometry or GPS devices in population research because these devices are expensive and require technical expertise and data processing. Questionnaires and logs provide inexpensive tools to assess PA and travel with reasonable concordance with objective measures. However, they have shortcomings in evaluating the presence and amount of light and moderate PA. Future questionnaires and logs should be developed to evaluate sensitivity to light and moderate PA.

Content validity and methodological considerations in ecological momentary assessment studies on physical activity and sedentary behaviour: a systematic review

“…As stated in the inclusion criteria, all studies used EMA methodology, meaning that participants were signalled to complete assessments throughout the course of the day at random or fixed times (time-based sampling) or when exhibiting certain behaviours (event-based sampling). In this review, fourteen studies (70%) used timebased sampling [37,39,49,55,57,58,60,62,63,66,67,72], two studies (10%) used event-based sampling [54,68] and four studies (4/20: 20%) used a combination of both [52,61,64,65]. The total monitoring period duration varied from 1 day to 6 months.…”

“…Event-based sampling Of the six studies that used event-based sampling or a combination of time-and event-based sampling, three (50%) used a deviceinitiated assessment, in which the device (handheld/ smartphone) initiated the assessments in response to a behaviour or event (2 GPS, 1 mobile phone's built-in motion sensor) [52,64,65]. The other three (3/6: 50%) used a self-initiated assessment in which participants were asked to self-initiate assessments in response to specific behaviours or event [19,54,61,68]. In one of these event-based studies (17%), it was not reported whether each event had to be assessed [65].…”

“…In one study (33%), each event had to be assessed, but there was a 30min gap between the prompts to avoid excessive prompting [52]. In three studies, the self-initiated event based studies, all events had to be assessed [54,61,68].…”

“…Three studies (15%) provided some examples of the items used [58,66,67]. Five studies (25%) did not report the actual items, but only reported the construct that was measured in the EMA [49,54,55,65,68].…”

“…pilot study with experts, pilot study with users, existing EMA questionnaire, existing non-EMA questionnaire, selfmade). Only 8 (40%) of the studies reported the full source of the used items [49,55,57,58,61,64,68,69]. For example, the study of Bedard et al indicated that the items measuring affect were taken from the Positive and Negative Affect Schedule for Children, which is a non-EMA questionnaire [57].…”