Alison L. Marshall
The aim of this study was to determine if feedback on step counts from a pedometer encourages participants to increase walking.
Randomly recruited older adults (n = 105) were asked to wear a pedometer for 2 wk. Half the participants were asked to monitor and record daily step counts during week 1 (feedback), then seal the pedometer shut during week 2 (no feedback). Half completed the study in reverse order. Self-reported walking was assessed via telephone interviews.
Significantly more steps were recorded per day (approximately 400 steps per day) when participants (n = 103, 63% women; mean BMI 25 ± 4) monitored their daily step count [t (102) = –2.30, P = 0.02)] compared to the no feedback condition. There was no statistically significant difference in self-reported walking (P = 0.31) between feedback conditions.
The difference in daily step counts observed between conditions, while statistically significant, may not be considered clinically significant. Further, the non-significant difference in self-reported walking between conditions suggests that feedback on daily step counts from a pedometer does not encourage participants to increase their walking.
Kate Giles and Alison L. Marshall
One- to two-week test–retest reliability and construct validity (against pedometer step counts) of the CHAMPS physical activity questionnaire were evaluated in older Australian adults.
Participants (n = 100, age >65 years) were invited to complete CHAMPS by mail. Spearman correlation coefficients are reported for physical activity constructs time (min/wk) and sessions per week for walking, moderate-, and vigorous-intensity activity and total physical activity. Correct classification of participants as meeting physical activity recommendations was assessed using percent agreement and kappa statistics.
Seventy-three participants completed CHAMPS at T1; 54 provided repeat data (T2). Sixty percent of the participants provided complete data. Good to excellent test– retest reliability was observed for all the physical activity constructs (r
s = .70 to .89 for sessions/wk and r
s = .65 to .75 for min/wk). Agreement between proportions classified as meeting recommendations at T1 and T2 was good (79%; kappa = 0.55). Fair to low validity coefficients were observed between steps and T1 CHAMPS walking and total activity sessions/wk (r
s = .57 and r
s = .52), and min/wk (r
s = .40 and r
s = .21).
Mailed self-complete CHAMPS data provided reliable and valid estimates of physical activity in older Australian adults. Observed measurement coefficients were comparable to those reported in previous evaluations of CHAMPS. Further work is required to identify strategies to prevent data loss.
Marina M. Reeves, Alison L. Marshall, Neville Owen, Elisabeth A.H. Winkler and Elizabeth G. Eakin
We compared the responsiveness to change (prepost intervention) of 3 commonly-used self-report measures of physical activity.
In a cluster-randomized trial of a telephone-delivered intervention with primary care patients, physical activity was assessed at baseline and 4 months (n = 381) using the 31-item CHAMPS questionnaire; the 6-item Active Australia Questionnaire (AAQ); and, 2 walking for exercise items from the US National Health Interview Survey (USNHIS). Responsiveness to change was calculated for frequency (sessions/week) and duration (MET·minutes/week) of walking and moderate-to-vigorous intensity physical activity.
The greatest responsiveness for walking frequency was found with the USNHIS (0.45, 95% CI: 0.19, 0.72) and AAQ (0.43, 95% CI: 0.19, 0.67), and for walking duration with the USNHIS (0.27, 95%CI 0.13, 0.41) and CHAMPS (0.24, 95% CI: 0.12, 0.36). For moderate-to-vigorous activity, responsiveness for frequency was slightly higher for the AAQ (0.50, 95% CI: 0.30, 0.69); for duration it was slightly higher for CHAMPS (0.32, 95% CI: 0.17, 0.47).
In broad-reach trials, brief self-report measures (USNHIS and AAQ) are useful for their comparability to population physical activity estimates and low respondent burden. These measures can be used without a loss in responsiveness to change relative to a more detailed self-report measure (CHAMPS).
Ross E. Andersen, Adrian E. Bauman, Shawn C. Franckowiak, Sue M. Reilley and Alison L. Marshall
This intervention promoted stair use among people attending the American College of Sports Medicine (ACSM) annual meeting.
All attendees using the stairs or escalators in the main lobby were unobtrusively observed for 3 days and coded for activity choices to get to the second floor. During day 2, a prominent sign stating “Be a role model. Use the stairs!” encouraged point-of-choice decisions favoring stairs over the escalator. The sign was removed on day 3.
16,978 observations were made. Stair use increased from 22.0% on day 1 to 29.3% and 26.8% on days 2 and 3, respectively (P values < .001). Active choices (stair use or walk up escalator) increased from 28.3% on day 1 to 40.1% and 40.2% on subsequent days. Analyses were similar after adjustment for gender, estimated age category, and race.
Relatively few conference attendees were persuaded to model stair-use behavior. Health professionals should be encouraged to be “active living” role models.
Dori E. Rosenberg, Fiona C. Bull, Alison L. Marshall, James F. Sallis and Adrian E. Bauman
This study explored definitions of sedentary behavior and examined the relationship between sitting time and physical inactivity using the sitting items from the International Physical Activity Questionnaire (IPAQ).
Participants (N = 289, 44.6% male, mean age = 35.93) from 3 countries completed self-administered long- and short-IPAQ sitting items. Participants wore accelero-meters; were classified as inactive (no leisure-time activity), insufficiently active, or meeting recommendations; and were classified into tertiles of sitting behavior.
Reliability of sitting time was acceptable for men and women. Correlations between total sitting and accelerometer counts/min <100 were significant for both long (r = .33) and short (r = .34) forms. There was no agreement between tertiles of sitting and the inactivity category (kappa = .02, P = .68).
Sedentary behavior should be explicitly measured in population surveillance and research instead of being defined by lack of physical activity.