Efficacy of a theory-based behavioural intervention to increase physical activity in an at-risk group in primary care (ProActive UK): a randomised trial
ABSTRACT Declining physical activity is associated with a rising burden of global disease. Efforts to reverse this trend have not been successful. We aimed to assess the efficacy of a facilitated behavioural intervention to increase the physical activity of sedentary individuals at familial risk of diabetes.
We enrolled 365 sedentary adults who had a parental history of type 2 diabetes. They were recruited from either diabetes or family history registers at 20 general practice clinics in the UK. Eligible participants were randomly assigned to one of two intervention groups, or to a comparison group. All participants were posted a brief advice leaflet. One intervention group was offered a 1-year behaviour-change programme, to be delivered by trained facilitators in participants' homes, and the other the same programme by telephone. The programme was designed to alter behavioural determinants, as defined by the theory of planned behaviour, and to teach behaviour-change strategies. The principal outcome at 1 year was daytime physical activity, which was objectively measured as a ratio to resting energy expenditure. Analysis was by intention to treat. This study is registered as ISRCTN61323766.
Of 365 patients, we analysed primary endpoints for 321 (88%) for whom we had data after 1 year of follow-up. At 1 year, the physical-activity ratio of participants who received the intervention, by either delivery route, did not differ from the ratio in those who were given a brief advice leaflet. The mean difference in daytime physical-activity ratio, adjusted for baseline, was -0.04 (95% CI -0.16 to 0.08). The physical-activity ratio did not differ between participants who were delivered the intervention face-to-face or by telephone (mean difference -0.05; 95% CI -0.19 to 0.10).
A facilitated theory-based behavioural intervention was no more effective than an advice leaflet for promotion of physical activity in an at-risk group; therefore health-care providers should remain cautious about commissioning behavioural programmes into individual preventive health-care services.
Full-textDOI: · Available from: Ulf Ekelund, Jun 16, 2015
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ABSTRACT: Web-based interventions for physical activity offer several advantages over face-to-face, print-and telephone-based interventions and are scalable and potentially cost-effective. Recent reviews of web-based interventions in adults show that they have positive but small effects on physical activity but identify a number of limitations including a reliance on self-report measures of outcome. This trial used an objective measure of physical activity to assess the effectiveness of three minimal contact interventions: 1) A multi-component web-based intervention incorporating objective monitoring and graphical feedback of physical activity; 2) A version of the first intervention that consisted only of objective monitoring plus web-based graphical feedback; and 3) Self-monitoring of physical activity using a paper diary. Get Moving is an individually randomised controlled trial with allocation of 488 participants to one of three interventions or to a no-intervention control group. Participants are physically inactive working adults aged 18-65 years. They attended a baseline assessment session at which anthropometric, biological and questionnaire measures were taken and they completed a treadmill exercise test. They then wore a combined movement and heart rate monitor for six days and nights before being randomised to one of the four trial arms. The baseline measures were repeated at the follow-up assessment which took place approximately 12 weeks post-randomisation, conducted by staff blind to group allocation. Participants wore the movement and heart rate monitor for six days and nights before this. The co-primary outcomes are: physical activity energy expenditure measured using individually calibrated combined heart-rate and movement data; and cardiorespiratory fitness measured using a sub-maximal treadmill exercise test. Strengths of the trial include the use of an objective measure of physical activity, a measure of cardiorespiratory fitness, relatively large sample size and the use of robust methods of randomisation, allocation concealment and blinding to outcome assessment. Get Moving will contribute to the evidence base on minimal contact interventions for increasing physical activity. The interventions could be implemented in other settings such as primary care. ISRCTN31844443 . Registered 18 June 2010.BMC Public Health 03/2015; 15(1):296. DOI:10.1186/s12889-015-1654-0 · 2.32 Impact Factor
- Review of General Psychology 01/2015; 19(1):69-95. DOI:10.1037/gpr0000029 · 1.78 Impact Factor
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ABSTRACT: Missing data are common in medical research, which can lead to a loss in statistical power and potentially biased results if not handled appropriately. Multiple imputation (MI) is a statistical method, widely adopted in practice, for dealing with missing data. Many academic journals now emphasise the importance of reporting information regarding missing data and proposed guidelines for documenting the application of MI have been published. This review evaluated the reporting of missing data, the application of MI including the details provided regarding the imputation model, and the frequency of sensitivity analyses within the MI framework in medical research articles. A systematic review of articles published in the Lancet and New England Journal of Medicine between January 2008 and December 2013 in which MI was implemented was carried out. We identified 103 papers that used MI, with the number of papers increasing from 11 in 2008 to 26 in 2013. Nearly half of the papers specified the proportion of complete cases or the proportion with missing data by each variable. In the majority of the articles (86%) the imputed variables were specified. Of the 38 papers (37%) that stated the method of imputation, 20 used chained equations, 8 used multivariate normal imputation, and 10 used alternative methods. Very few articles (9%) detailed how they handled non-normally distributed variables during imputation. Thirty-nine papers (38%) stated the variables included in the imputation model. Less than half of the papers (46%) reported the number of imputations, and only two papers compared the distribution of imputed and observed data. Sixty-six papers presented the results from MI as a secondary analysis. Only three articles carried out a sensitivity analysis following MI to assess departures from the missing at random assumption, with details of the sensitivity analyses only provided by one article. This review outlined deficiencies in the documenting of missing data and the details provided about imputation. Furthermore, only a few articles performed sensitivity analyses following MI even though this is strongly recommended in guidelines. Authors are encouraged to follow the available guidelines and provide information on missing data and the imputation process.BMC Medical Research Methodology 12/2015; 15(1):30. DOI:10.1186/s12874-015-0022-1 · 2.17 Impact Factor