ABSTRACT
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.
ABSTRACT
BACKGROUND: National Health Service Health Checks were introduced in 2009 to reduce cardiovascular disease (CVD) risks and events. Since then, national evaluations have highlighted the need to maximise the programme's impact by improving coverage and outputs. To address these challenges it is important to understand the extent to which positive behaviours are influenced across the NHS Health Check pathway and encourage the promotion or minimisation of behavioural facilitators and barriers respectively. This study applied behavioural science frameworks to: i) identify behaviours and actors relevant to uptake, delivery and follow up of NHS Health Checks and influences on these behaviours and; ii) signpost to example intervention content. METHODS: A systematic review of studies reporting behaviours related to NHS Health Check-related behaviours of patients, health care professionals (HCPs) and commissioners. Influences on behaviours were coded using theory-based models: COM-B and Theoretical Domains Framework (TDF). Potential intervention types and behaviour change techniques (BCTs) were suggested to target key influences. RESULTS: We identified 37 studies reporting nine behaviours and influences for eight of these. The most frequently identified influences were physical opportunity including HCPs having space and time to deliver NHS Health Checks and patients having money to adhere to recommendations to change diet and physical activity. Other key influences were motivational, such as beliefs about consequences about the value of NHS Health Checks and behaviour change, and social, such as influences of others on behaviour change. The following techniques are suggested for websites or smartphone apps: Adding objects to the environment, e.g. provide HCPs with electronic schedules to guide timely delivery of Health Checks to target physical opportunity, Social support (unspecified), e.g. include text suggesting patients to ask a colleague to agree in advance to join them in taking the 'healthy option' lunch at work; Information about health consequences, e.g. quotes and/or videos from patients talking about the health benefits of changes they have made. CONCLUSIONS: Through the application of behavioural science we identified key behaviours and their influences which informed recommendations for intervention content. To ascertain the extent to which this reflects existing interventions we recommend a review of relevant evidence.
