Psychosis is a severe mental health problem. Symptoms of psychosis include hallucinations (e.g. hearing voices that others cannot hear) and delusions (unusual, often troubling beliefs). People who experience psychosis often have times when their symptoms are relatively stable. At other times, their symptoms may increase and become much more problematic (a 'relapse'). Helping people with psychosis to stay well (preventing relapses) is an important and time-consuming challenge for mental health services.

Smartphones and other digital technologies are now widespread. This offers a solution to help tackle the overwhelming demand on services and to enable people with psychosis to access mental health support when they need it most (e.g. when relapsing). Research shows that people with psychosis are often willing to report their symptoms using a smartphone app. Apps like this can alert health professionals when someone needs extra support, but can be burdensome to use long-term. The investigators want to make a system that is less burdensome and is personalised to users' needs and experiences (a 'complex digital remote monitoring system'). Recent research shows that information gathered routinely by individuals' smartphones (e.g. GPS, step count) might help predict relapses of psychosis. The investigators want to use this method in a complex digital remote monitoring system. First, the investigators need to know what people with psychosis and mental health staff think about this idea.

The investigators will interview around sixty adults with psychosis and around forty staff, recruited from UK mental health services (Manchester, Glasgow, Edinburgh, Cardiff, London, Sussex). These one-off, audio-recorded interviews will last up to 60 minutes. The interviewer will ask about participants' views on complex digital remote monitoring. The investigators will then systematically analyse the interviews. Findings will inform the design of the investigators' own complex digital remote monitoring system and future digital tools designed by other researchers. NIHR and Wellcome are funding this study.

SERVICE USER PARTICIPANTS

Inclusion Criteria:

• Clinical diagnosis of schizophrenia spectrum disorder (ICD10 F20-29) OR meets the early Intervention for Psychosis Service entry criteria, operationally defined using the Positive and Negative Syndrome Scale (PANSS) and/or the psychosis transition criteria of the Comprehensive Assessment of At-Risk Mental States (CAARMS).
• In contact with mental health services
• Over 16 years of age
• Ability to give informed consent

Exclusion Criteria:

• Not sufficiently stable to take part in an interview
• Not sufficiently fluent in English to take part in an interview

STAFF PARTICIPANTS

Inclusion Criteria:

• Work within an adult NHS service providing mental health support to people who experience psychosis / severe mental health problems
• Ability to give informed consent

Exclusion Criteria:

- Not sufficiently fluent in English to take part in an interview

Participants are drawn from two populations: people with lived experience of schizophrenia spectrum psychosis who are in contact with secondary care mental health services and mental health staff who work in such services. Participants from both groups will be recruited from secondary care mental health services in six geographical locations: Manchester, Glasgow, Edinburgh, Cardiff, Sussex and London.

We will obtain opt in consent from participants to share their data with other researchers for secondary analysis in future related research studies. Participants will be fully informed of this before consenting. The de-identified dataset will be stored on a secure server at the University of Manchester for up to 20 years and then destroyed.

Researchers wishing to use the data for secondary analysis will be required to make a formal request to the study publication committee and chief investigator, including a statement of the specific research question they wish to address. In all cases, access will be given at the CI and publication committee's discretion. Approved researchers will be furnished with the de-identified dataset by the CI (or delegated individual). Files will be securely transferred to the approved researcher, who will sign a written agreement stating that they will not share the dataset with others.