Increasing physical activity and healthy diet in outpatients with mental disorders: a randomized-controlled evaluation of two psychological interventions

This study reviewed previous studies to explore the effect of season, and consequently weather, on levels of physical activity. Thirty-seven primary studies (published 1980-2006) representing a total of 291883 participants (140482 male and 152085 female) from eight different countries are described, and the effect of season on moderate levels of physical activity is considered. Upon review of the evidence, it appears that levels of physical activity vary with seasonality, and the ensuing effect of poor or extreme weather has been identified as a barrier to participation in physical activity among various populations. Therefore, previous studies that did not recognize the effect of weather and season on physical activity may, in fact, be poor representations of this behaviour. Future physical activity interventions should consider how weather promotes or hinders such behaviour. Providing indoor opportunities during the cold and wet months may foster regular physical activity behaviours year round.

Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies.

Little is known about the effectiveness of strategies to enable people to achieve an increase in their physical activity. To assess the effects of interventions for promoting physical activity in adults aged 16 years and older, not living in an institution. We searched CENTRAL (Issue 4, 2001), MEDLINE, EMBASE, CINAHL, PsychLIT, BIDS ISI, SPORTDISCUS, SIGLE, SCISEARCH (from earliest date available to December 2001) and reference lists of articles. Randomised, controlled, trials comparing different interventions to encourage sedentary adults not living in an institution to become physically active. Studies required a minimum of six months follow up from the start of the intervention to the collection of final data and either used an intention to treat analysis or, failing that, had no more than 20% loss to follow up. At least two reviewers independently assessed each study quality and extracted data. Study authors were contacted for additional information where necessary. Standardised mean differences and 95% confidence intervals were calculated for continuous measures of self reported physical activity and cardio-respiratory fitness. For studies with dichotomous outcomes, odds ratios and 95% confidence intervals were calculated. The effect of interventions on self reported physical activity (11 studies; 3940 participants) was positive and moderate, with a pooled standardised mean difference of 0.31 (95% CI 0.12 to 0.50), as was the effect on cardio-respiratory fitness (7 studies; 1406 participants) pooled SMD 0.4 (95% CI 0.09 to 0.70). The effect of interventions in achieving a predetermined threshold of physical activity (6 studies; 2313 participants) was not significant with an odds ratio of 1.30 (95% CI 0.87 to 1.95). There was significant heterogeneity in the reported effects as well as heterogeneity in characteristics of the interventions. The heterogeneity in reported effects was reduced in higher quality studies, when physical activity was self-directed with some professional guidance and when there was on-going professional support. Our review suggests that physical activity interventions have a moderate effect on self reported physical activity and cardio-respiratory fitness, but not on achieving a predetermined level of physical activity. Due to the clinical and statistical heterogeneity of the studies, only limited conclusions can be drawn about the effectiveness of individual components of the interventions. Future studies should provide greater detail of the components of interventions.