Barriers and facilitators to implementing the CURE stop smoking project: a qualitative study.

BACKGROUND: The Conversation, Understand, Replace, Experts and evidence-based treatment (CURE) project aims to provide a comprehensive offer of both pharmacotherapy and specialist support for tobacco dependence to all smokers admitted to hospital and after discharge. CURE was recently piloted within a single trust in Greater Manchester, with preliminary evidence suggesting this intervention may be successful in improving patient outcomes. Plans are currently underway to pilot a model based upon CURE in other sites across England. To inform implementation, we conducted a qualitative study, which aimed to identify factors influencing healthcare professionals' implementation behaviour within the pilot site. METHODS: Individual, semi-structured telephone interviews were conducted with 10 purposively sampled health professionals involved in the delivery and implementation of the CURE project pilot. Topic guides were informed by the Theoretical Domains Framework (TDF). Transcripts were analysed in line with the framework method, with data coded to TDF domains to highlight important areas of influence and then mapped to the COM-B to support future intervention development. RESULTS: Eight TDF domains were identified as important areas influencing CURE implementation; 'environmental context and resources' (physical opportunity), 'social influence' (social opportunity), 'goals', 'professional role and identity' and 'beliefs about consequences' (reflective motivation), 'reinforcement' (automatic motivation), 'skills' and 'knowledge' (psychological capability). Most domains had the potential to both hinder and/or facilitate implementation, with the exception of 'beliefs about consequences' and 'knowledge', which were highlighted as facilitators of CURE. Participants suggested that 'environmental context and resources' was the most important factor influencing implementation; with barriers most often related to challenges integrating into the wider healthcare context. CONCLUSIONS: This qualitative study identified multi-level barriers and facilitators to CURE implementation. The use of theoretical frameworks allowed for the identification of domains known to influence behaviour change, and thus can be taken forward to develop targeted interventions to support future service implementation. Future work should focus on discussing these findings with a broad range of stakeholders, to ensure resultant intervention strategies are feasible and practicable within a healthcare context. These findings complement wider evaluative work to support nationwide roll out of NHS funded tobacco dependence treatment services in acute care trusts.

Understanding the implementation strategy of a secondary care tobacco addiction treatment pathway (the CURE project) in England: a strategic behavioural analysis.

OBJECTIVES: The Conversation, Understand, Replace, Experts and evidence-based treatment (CURE) project implemented an evidence-based intervention that offers a combination of pharmacotherapy and behavioural support to tobacco-dependent inpatients. Understanding key characteristics of CURE's implementation strategy, and identifying areas for improvement, is important to support the roll-out of nationwide tobacco dependence services. This study aimed to (1) specify key characteristics of CURE's exiting implementation strategy and (2) develop theoretical-informed and stakeholder-informed recommendations to optimise wider roll-out. DESIGN AND METHODS: Data were collected via document review and secondary analysis of interviews with 10 healthcare professionals of a UK hospital. Intervention content was specified through behaviour change techniques (BCTs) and intervention functions within the Behaviour Change Wheel. A logic model was developed to specify CURE's implementation strategy and its mechanisms of impact. We explored the extent to which BCTs and intervention functions addressed the key theoretical domains influencing implementation using prespecified matrices. The development of recommendations was conducted over a two-round Delphi exercise. RESULTS: We identified six key theoretical domains of influences: 'environmental context and resources', 'goals', 'social professional role and identity', 'social influences', 'reinforcement' and 'skills'. The behavioural analysis identified 26 BCTs, 4 intervention functions and 4 policy categories present within the implementation strategy. The implementation strategy included half the relevant intervention functions and BCTs to target theoretical domains influencing CURE implementation, with many BCTs focusing on shaping knowledge. Recommendations to optimise content were developed following stakeholder engagement. CONCLUSIONS: CURE offers a strong foundation from which a tobacco dependence treatment model can be developed in England. The exiting strategy could be strengthened via the inclusion of more theoretically congruent BCTs, particularly relating to 'environmental context and resources'. The recommendations provide routes to optimisation that are both theoretically grounded and stakeholder informed. Future research should assess the feasibility/acceptability of these recommendations in the wider secondary-care context.

Barriers to and Facilitators of the Use of Digital Tools in Primary Care to Deliver Physical Activity Advice: Semistructured Interviews and Thematic Analysis.

BACKGROUND: Physical inactivity is a leading risk factor for many health conditions, including cardiovascular disease, diabetes, and cancer; therefore, increasing physical activity (PA) is a public health priority. Health care professionals (HCPs) in primary care are pivotal in addressing physical inactivity; however, few HCPs provide PA advice to patients. There can be obstacles to delivering PA advice, including lack of time, confidence, or knowledge. Digital technology has the potential to overcome obstacles and facilitate delivering PA advice. However, it is unknown if and how digital tools are used to deliver PA advice in primary care consultations and what factors influence their use. OBJECTIVE: We aimed to understand the use of digital tools to support primary care consultations and to identify the barriers to and facilitators of using these systems. METHODS: Overall, 25 semistructured interviews were conducted with primary care HCPs. Professionals were sampled based on profession (general practitioners, practice nurses, and health care assistants), prevalence of long-term conditions within their practice area, and rural-urban classification. The data were analyzed thematically to identify the influences on the use of digital tools. Themes were categorized using the COM-B (capability, opportunity, and motivation-behavior) model and the Theoretical Domains Framework to identify the barriers to and facilitators of using digital tools to support the delivery of PA advice in primary care consultations. RESULTS: The identified themes fell within 8 domains of the Theoretical Domains Framework. The most prominent influence (barrier or facilitator) within psychological capability was having the skills to use digital tools. Training in the use of digital tools was also mentioned several times. The most notable influences within physical opportunity were limited digital tools to prompt/support the provision of PA advice, time constraints, efficiency of digital tools, simplicity and ease of use of digital tools, and integration with existing systems. Other physical opportunity influences included lack of access to digital tools and technical support in the use of digital tools. Within social opportunity, a notable barrier was that digital tools reduce interpersonal communication with patients. Patient preference was also identified. Several important influences were within reflective motivation, including confidence to use digital tools, beliefs about the usefulness of digital tools, the belief that digital tools "are the way forward," beliefs related to data privacy and security concerns, and perceptions about patient capabilities. About automatic motivation, influences included familiarity and availability regarding digital tools and the fact that digital tools prompt behavior. CONCLUSIONS: A variety of influences were identified on the use of digital tools to support primary care consultations. These findings provide a foundation for designing a digital tool addressing barriers and leverages the facilitators to support PA advice provision within primary care to elicit patient behavior change and increase PA.