Behaviour change techniques to change the postnatal eating and physical activity behaviours of women who are obese: a qualitative study

2015 ◽  
Vol 123 (2) ◽  
pp. 279-284 ◽  
Author(s):  
DM Smith ◽  
W Taylor ◽  
T Lavender
Author(s):  
Coral L. Hanson ◽  
Emily J. Oliver ◽  
Caroline J. Dodd-Reynolds ◽  
Alice Pearsons ◽  
Paul Kelly

Abstract Background Physical Activity Referral Schemes (PARS), including exercise referral schemes, are a popular approach to health improvement, but understanding of effectiveness is limited by considerable heterogeneity in reporting and evaluation. We aimed to gain consensus for a PARS taxonomy as a comprehensive method for reporting and recording of such schemes. Methods We invited 62 experts from PARS policy, research and practice to complete a modified Delphi study. In round one, participants rated the need for a PARS taxonomy, the suitability of three proposed classification levels and commented on proposed elements. In round two, participants rated proposed taxonomy elements on an 11-point Likert scale. Elements scoring a median of ≥7, indicating high agreement, were included in the final taxonomy. Results Of those invited, 47 (75.8%) participated in round one, with high retention in round two (n = 43; 91.5%). 42 were UK-based, meaning the resultant taxonomy has been scrutinised for fit to the UK context only. The study gained consensus for a three-level taxonomy: Level 1: PARS classification (primary classification, provider, setting, conditions accepted [have or at risk of], activity type and funding). Level 2: scheme characteristics (staff structure, staff qualifications, behaviour change theories, behaviour change techniques, referral source, referrers, referral process, scheme duration, session frequency, session length, session times, session type, exit routes, action in case of non-attendance, baseline assessment, exit assessment, feedback to referrer and exclusion criteria) and Level 3: participant measures (demographics, monitoring and evaluation, and measures of change). Conclusion Using a modified Delphi method, this study developed UK-based consensus on a PARS classification taxonomy. We encourage PARS practitioners and public health colleagues, especially those working with similar service models internationally, to test, refine and use this taxonomy to inform policy and practice.


2011 ◽  
Vol 26 (11) ◽  
pp. 1479-1498 ◽  
Author(s):  
Susan Michie ◽  
Stefanie Ashford ◽  
Falko F. Sniehotta ◽  
Stephan U. Dombrowski ◽  
Alex Bishop ◽  
...  

2016 ◽  
Vol 17 (1) ◽  
pp. 34-42 ◽  
Author(s):  
Shamala Thilarajah ◽  
Ross A Clark ◽  
Gavin Williams

Stroke is a leading cause of disability worldwide, with approximately one third of people left with permanent deficits impacting on their function. This may contribute to a physically inactive lifestyle and further associated health issues. Current research suggests that people after stroke are not meeting the recommended levels of physical activity, and are less active than people with other chronic illnesses. Thus, it is important to understand how to support people after stroke to uptake and maintain physical activity. Wearable sensors and mobile health (mHealth) technologies are a potential platform to measure and promote physical activity. Some of these technologies may incorporate behaviour change techniques such as real-time feedback. Although wearable activity trackers and smartphone technology are widely available, the feasibility and applicability of these technologies for people after stroke is unclear. This article reviews the devices available for assessment of physical activity in stroke and discusses the potential for advances in technology to promote physical activity in this population.


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