Background Individuals living with long-term physical health conditions frequently experience co-occurring mental health problems. This comorbidity has a significant impact on an individual’s levels of emotional distress, health outcomes, and associated health care utilization. As health care services struggle to meet demand and care increasingly moves to the community, digital tools are being promoted to support patients to self-manage their health. One such technology is the autonomous virtual agent (chatbot, conversational agent), which uses artificial intelligence (AI) to process the user’s written or spoken natural language and then to select or construct the corresponding appropriate responses. Objective This study aimed to co-design the content, functionality, and interface modalities of an autonomous virtual agent to support self-management for patients with an exemplar long-term condition (LTC; chronic pulmonary obstructive disease [COPD]) and then to assess the acceptability and system content. Methods We conducted 2 co-design workshops and a proof-of-concept implementation of an autonomous virtual agent with natural language processing capabilities. This implementation formed the basis for video-based scenario testing of acceptability with adults with a diagnosis of COPD and health professionals involved in their care. Results Adults (n=6) with a diagnosis of COPD and health professionals (n=5) specified 4 priority self-management scenarios for which they would like to receive support: at the time of diagnosis ( information provision ), during acute exacerbations ( crisis support ), during periods of low mood ( emotional support ), and for general self-management ( motivation ). From the scenario testing, 12 additional adults with COPD felt the system to be both acceptable and engaging, particularly with regard to internet-of-things capabilities. They felt the system would be particularly useful for individuals living alone. Conclusions Patients did not explicitly separate mental and physical health needs, although the content they developed for the virtual agent had a clear psychological approach. Supported self-management delivered via an autonomous virtual agent was acceptable to the participants. A co-design process has allowed the research team to identify key design principles, content, and functionality to underpin an autonomous agent for delivering self-management support to older adults living with COPD and potentially other LTCs.

Background: Malignant pleural effusion (MPE) is a common, serious problem predominantly seen in metastatic lung and breast cancer and malignant pleural mesothelioma. Recurrence of malignant pleural effusion is common, and symptoms significantly impair people's daily lives. Numerous treatment options exist, yet choosing the most suitable depends on many factors and making decisions can be challenging in pressured, time-sensitive clinical environments. Clinicians identified a need to develop a decision support tool. This paper reports the process of coproducing an initial prototype tool. Methods: Creative co-design methods were used. Three pleural teams from three disparate clinical sites in the UK were involved. To overcome the geographical distance between sites and the ill-health of service users, novel distributed methods of creative co-design were used. Local workshops were designed and structured, including video clips of activities. These were run on each site with clinicians, patients and carers. A joint national workshop was then conducted with representatives from all stakeholder groups to consider the findings and outputs from local meetings. The design team worked with participants to develop outputs, including patient timelines and personas. These were used as the basis to develop and test prototype ideas. Results: Key messages from the workshops informed prototype development. These messages were as follows. Understanding and managing the pleural effusion was the priority for patients, not their overall cancer journey. Preferred methods for receiving information were varied but visual and graphic approaches were favoured. The main influences on people's decisions about their MPE treatment were personal aspects of their lives, for example, how active they are, what support they have at home. The findings informed the development of a first prototype/service visualisation (a video representing a web-based support tool) to help people identify personal priorities and to guide shared treatment decisions.

Background: Co-production, co-creation and co-design are increasingly used in healthcare research knowledge mobilisation. These methods have grown in popularity and the broad range of approaches are often used without any formal evaluation. The challenges to using these approaches are well reported yet there is little evidence on how to overcome them or how they work. This study evaluates ‘creative co-design’, a design-led, solutions-focused process developed specifically as a means to mobilise knowledge in healthcare.<br />Aims and objectives: To investigate the impact of creative co-design on the knowledge mobilisation process. To understand how it impacts on the application of research knowledge in routine clinical practice.<br />Methods: Semi-structured interviews were carried out with 20 participants from 14 projects. Data were analysed using the Framework approach. A workshop involving the first 10 participants was held prior to the final interviews and analysis.<br />Findings: The findings indicate that creative co-design successfully facilitates knowledge mobilisation in healthcare. This is represented by three interconnected themes: creative and visual; design-led; and creating the right conditions.<br />Discussion and conclusions: The themes highlight how the approach supports engagement and creates a safe space for knowledge sharing and synthesis in a non-hierarchical environment. This study contributes important insights into how creative co-design can mobilise knowledge in healthcare. Further evaluation is warranted to help it develop into a recognised and effective method for research implementation and service improvement.<br /><br /><br />Key messages<br /><ul><li>Creative co-design was perceived to be a successful knowledge mobilisation approach.</li><br /><li>Creative and visual tools enhanced engagement and innovation.</li><br /><li>Involving a designer was key and is recommended in co-production projects.</li><br /><li>Creating a safe space balanced power and voice.</li><br /></ul>

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Background: Safety-netting in primary care may help diagnose cancer earlier, but it is unclear what the format and content of an acceptable safety-netting intervention would be. This project aimed to co-design a safety-netting intervention with and for primary care patients and staff. Aim: This work sought to address 1) how would a safety-netting intervention be implemented in practice? 2) if and how a safety-netting intervention would be acceptable to all stakeholders? Design and setting: Patient representatives, GPs and Nurse Practitioners were invited to a series of co-design workshops. Patients who had and had not received a diagnosis of cancer, and primary care practices took part in separate focus groups. Method: Three workshops using creative co-design processes developed the format and content of the intervention prototype. The COM-B Framework underpinned five focus groups to establish views on capability, opportunity, and motivation to use the intervention to assist with prototype refinement. Results: Workshops and focus groups suggested the intervention format and content should incorporate visual and written communication specifying clear timelines for monitoring symptoms and when to present back; be available in paper and electronic forms linked to existing computer systems; be able to be delivered within a ten minute consultation. Intervention use themes included, ‘Building confidence through partnership’, ‘Using familiar and current procedures and systems’ and ‘Seeing value’. Conclusion: The Shared Safety Net Action Plan (SSNAP) – a safety-netting intervention to assist the timely diagnosis of cancer in primary care, was successfully co-designed with and for patients and primary care staff.

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BACKGROUND Individuals living with long-term physical health conditions frequently experience co-occurring mental health problems. This comorbidity has a significant impact on an individual’s levels of emotional distress, health outcomes, and associated health care utilization. As health care services struggle to meet demand and care increasingly moves to the community, digital tools are being promoted to support patients to self-manage their health. One such technology is the autonomous virtual agent (chatbot, conversational agent), which uses artificial intelligence (AI) to process the user’s written or spoken natural language and then to select or construct the corresponding appropriate responses. OBJECTIVE This study aimed to co-design the content, functionality, and interface modalities of an autonomous virtual agent to support self-management for patients with an exemplar long-term condition (LTC; chronic pulmonary obstructive disease [COPD]) and then to assess the acceptability and system content. METHODS We conducted 2 co-design workshops and a proof-of-concept implementation of an autonomous virtual agent with natural language processing capabilities. This implementation formed the basis for video-based scenario testing of acceptability with adults with a diagnosis of COPD and health professionals involved in their care. RESULTS Adults (n=6) with a diagnosis of COPD and health professionals (n=5) specified 4 priority self-management scenarios for which they would like to receive support: at the time of diagnosis (information provision), during acute exacerbations (crisis support), during periods of low mood (emotional support), and for general self-management (motivation). From the scenario testing, 12 additional adults with COPD felt the system to be both acceptable and engaging, particularly with regard to internet-of-things capabilities. They felt the system would be particularly useful for individuals living alone. CONCLUSIONS Patients did not explicitly separate mental and physical health needs, although the content they developed for the virtual agent had a clear psychological approach. Supported self-management delivered via an autonomous virtual agent was acceptable to the participants. A co-design process has allowed the research team to identify key design principles, content, and functionality to underpin an autonomous agent for delivering self-management support to older adults living with COPD and potentially other LTCs.

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