BackgroundManagement of cardiovascular risk factors includes commitment from patients to adhere to prescribed medications and adopt healthy lifestyles. Unfortunately many fail to take up and maintain the four key healthy behaviours (not smoking, having a balanced diet, limiting alcohol consumption and being more active). Five factors (beliefs, knowledge, transport and other costs, emotions, and friends and family support) are known to predict uptake of lifestyle behaviour change. The key factors influencing maintenance of healthy lifestyles are not known but would be helpful to support the development of relapse prevention programmes for this population. Our review aimed to clarify the main patient perceived factors thought to influence maintenance of changed healthy lifestyles.MethodsWe performed a systematic review of qualitative observational studies and applied the principles of content synthesis and thematic analysis to extract reported factors (barriers and facilitators) considered by individuals to be influential in maintaining changed healthy lifestyle behaviours. Factors were then organised into an existing framework of higher order categories which was followed by an analysis of the interrelationships between factors to identify key themes.ResultsTwenty two studies met our inclusion criteria. Participants reported barriers and facilitators within 13 categories, the majority of which were facilitators. The most commonly reported influences were those relating to social support (whether provided formally or informally), beliefs (about the self or the causes and management of poor health, and the value of maintaining lifestyle behaviours), and other psychological factors (including attitude, thinking and coping styles, and problem solving skills). Physical activity was the most commonly investigated behaviour in four categories, but overall, the main barriers and facilitators were related to a range of behaviours. Through analysis of the interrelationships between factors within categories, ‘social support’, ‘education and knowledge’, and ‘beliefs and emotions’ were all considered key themes.ConclusionsOur review suggests that for the most part, factors that influence lifestyle change are also important for maintaining healthy behaviours. This indicates that addressing these barriers and facilitators within lifestyle support programmes would also be of value in the longer-term.

Reducing risk of a cardiovascular event involves adopting healthier lifestyles. Community-based active lifestyle schemes offer support, but problems with uptake, completion and evaluation are common. We report the engagement and experiences of older adults referred to a scheme in England. Data transcribed from a focus group or individual interviews were analysed using thematic framework analysis. Participants reported an increased awareness of health difficulties with age, and described attendance-related psychological benefits, including an increased sense of responsibility for change and having had negative beliefs about age, health and change challenged. Some physical benefits (including reduced weight and blood pressure) were also reported. Those who attended most consistently were more likely to report caring responsibilities and describe positive social and relational outcomes, but were not more likely to report marked physical benefits. We recommend several changes to ensure that schemes meet their objectives and the needs of those referred. Age-related, health and lifestyle beliefs do not prohibit change but influence attendance and so should be addressed. Outcomes should be publicised, and structured, fixed-term programmes, incorporating relapse-prevention strategies, should be delivered to a closed group at flexible times. Active follow-up of non-attenders and improved data collection are also recommended. These should reduce the risk of schemes providing social support at the expense of intended health benefits.

This article reports the development of natural history and active treatment benchmarks for psychological treatments of chronic pain. The benchmarks were derived from randomized controlled trials (RCTs) reported in a published meta-analysis. In two preliminary studies we surveyed small samples of active clinicians working in U.K. pain management programs. Study 1 assessed the fit between routine clinical treatment and the selected RCTs. In study 2 Delphi methodology was used to determine a set of outcome domains to be used in the development of benchmarks. In study 3 we extracted data from a set of RCTs where both pre- and post-treatment data were reported. Measures were allocated to 1 of 5 outcome domains (cognitive coping and appraisal, pain experience, pain behavior, emotional functioning, and physical functioning). Pre-treatment to post-treatment effect sizes (Cohen's d) were computed and, where necessary, aggregated within trial so that each trial contributed a single estimate to outcome domain. Effect size (ES) benchmarks were computed for all trials and those trials with an explicit cognitive behavior therapy protocol. In no case did the ES estimates for the untreated control deviate from 0. The average ES across outcome domains for the treatment arms was approximately 0.35. These benchmarks may be used to assess the effectiveness of routine clinical treatments for chronic pain. The application of these data and the limitations of the study are discussed.

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