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P3: Living with Mental and Physical Illnesses

This mixed methods study is designed following the Medical Research Council (MRC) guidance on complex intervention development and evaluation. Our aim is to determine which patient-facing technologies (PFTs) can be effectively leveraged by patients with co-existing physical and mental multiple long-term conditions (MLTCs) to enhance self-management, improve access to care, and reduce the risk of medical escalation. Two central research questions guide our work:

  • Research question 1: Which PFTs can be utilised by patients to help manage their physical, mental, and social care needs, and better navigate access to services to reduce risk of medical escalation?
  • Research question 2: Which PFTs are acceptable and easily integrated into the lives of patients with physical and mental MLTCs that empower patients to better manage their conditions?

The study consists of two major components: a rapid evidence synthesis (umbrella review) and the co-development/feasibility testing of shortlisted PFTs.

1. Rapid evidence synthesis (umbrella review)

Objective: To comprehensively examine and synthesise the existing literature on self-management interventions that are supported by PFTs for patients with physical and mental MLTCs. This synthesis will inform the selection of candidate PFTs for further testing.

Methods: We will perform a systematic search for systematic reviews and meta-analyses focusing on self-management interventions employing PFTs. Studies will be included if they specifically address interventions for self-management in individuals living with both physical and mental MLTCs. Databases MEDLINE, EMBASE, PsycINFO, CINAHL and Cochrane Library will be searched.

Inclusion Criteria: * Population: Adults with co-existing mental and physical health conditions * Intervention: Digital technologies designed to support self-management of physical, mental and social impacts of living with MLTCs, from both clinician and patient perspective * Outcomes: Patient engagement, usability, and effectiveness in self-management.

Data extraction & synthesis: * Standardised data extraction form capturing study design, PFT functionality, reported effectiveness, and implementation barriers. * Visual mapping of evidence to illustrate PFT scalability, adaptability, and gaps in knowledge. * Stakeholder ranking: PPIE members and clinical experts will rate and rank PFTs based on feasibility, ease of integration into routine practice and potential impact.

2. Rapid Feasibility Testing

Objective: To iteratively co-develop and assess the feasibility, acceptability, and usability of the prioritised PFTs in real-world settings, ensuring that they meet the needs of patients with physical and mental MLTCs.

Methodology: Prospective observational feasibility study using a mixed-methods approach. 

  • Participant recruitment:
  • Adults aged 18+ with mental and physical MLTCs.
  • 10 participants per group for short-term feasibility testing (2-4 weeks).

  • 20 participants per group in extended feasibility trials (6-12 weeks). 

  • Intervention:

  • Wearables (e.g., BP, pulse, oxygen saturation, ECG monitoring including QTc interval).
  • Ambient sensors (e.g., sleep, fall risk monitoring).

  • Conversational AI (e.g., symptom tracking, medication experience reporting).

  • Comparator: Standard care

  • Outcome Measures:

  • Primary: Acceptability, usability, equitable uptake, engagement levels.
  • Secondary: Accuracy of data collected, impact on health outcomes.

  • Process evaluation: Semi-structured interviews with participants and healthcare professionals to explore experiences, barriers, and facilitators. 

  • Analysis:

  • Quantitative: Descriptive statistics (engagement metrics, concordance rates), comparative analysis where appropriate.

  • Qualitative: Thematic analysis of participant interviews, triangulated with usage data.

  • Iterative Testing:

  • Cyclical refinement of PFT-assisted self-management based on user feedback.
  • Technologies demonstrating high acceptability and engagement will progress to larger-scale feasibility testing.