Abstract
BackgroundMeaningful improvement in physical activity among control group participants in lifestyle intervention trials is not an uncommon finding, and may be partly explained by participant characteristics. This study investigated which baseline demographic, health and behavioural characteristics were predictive of successful improvement in physical activity in usual care group participants recruited into a telephone-delivered physical activity and diet intervention trial, and descriptively compared these characteristics with those that were predictive of improvement among intervention group participants.MethodsData come from the Logan Healthy Living Program, a primary care-based, cluster-randomized controlled trial of a physical activity and diet intervention. Multivariable logistic regression models examined variables predictive of an improvement of at least 60 minutes per week of moderate-to-vigorous intensity physical activity among usual care (n = 166) and intervention group (n = 175) participants.ResultsBaseline variables predictive of a meaningful change in physical activity were different for the usual care and intervention groups. Being retired and completing secondary school (but no further education) were predictive of physical activity improvement for usual care group participants, whereas only baseline level of physical activity was predictive of improvement for intervention group participants. Higher body mass index and being unmarried may also be predictors of physical activity improvement for usual care participants.ConclusionThis is the first study to examine differences in predictors of physical activity improvement between intervention group and control group participants enrolled in a physical activity intervention trial. While further empirical research is necessary to confirm findings, results suggest that participants with certain socio-demographic characteristics may respond favourably to minimal intensity interventions akin to the treatment delivered to participants in a usual care group. In future physical activity intervention trials, it may be possible to screen participants for baseline characteristics in order to target minimal-intensity interventions to those most likely to benefit. (Australian Clinical Trials Registry, http://www.anzctr.org.au/default.aspx, ACTRN012607000195459)
Highlights
Meaningful improvement in physical activity among control group participants in lifestyle intervention trials is not an uncommon finding, and may be partly explained by participant characteristics
Within the usual care (UC) group, participants who were excluded from the main analyses (n = 40) differed from the included sample (n = 166) with respect to income and Body mass index (BMI), with more excluded UC participants reporting ‘don’t know’ or refusing to answer questions about household income (30.0% [n = 12] of excluded vs. 13.3% [n = 22] of included, p = 0.043), and being in the obese BMI category (62.5% [n = 25] of excluded vs. 39.8% [n = 66] of included, p = 0.008)
This study found that certain socio-demographic characteristics consistently predicted an increase in physical activity of 60 minutes or more per week among participants allocated to the usual care arm of a physical activity and diet intervention trial
Summary
Meaningful improvement in physical activity among control group participants in lifestyle intervention trials is not an uncommon finding, and may be partly explained by participant characteristics. A number of potential explanations for control group improvements have been posited, including: the Hawthorne effect (where participants improve in the experimental variable being tested due to awareness of being observed) [14,15,16]; social desirability bias (the propensity to report behaviour that is compatible with social norms) [17,18,19]; regression to the mean (a problem associated with intra-participant variation and measurement error, which may occur in trials using pre- and post-intervention measurements, when behavioural screening is employed to select an inactive sample) [20,21,22]; the effects of measurement (when measurement is sufficient to produce a change in behaviour in the absence of a formal intervention) [16,23]; or, the recruitment of a highly motivated volunteer sample
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