Abstract
There is increasing use of digital tools to monitor people with psychosis and schizophrenia remotely, but using this type of data is challenging. This systematic review aims to summarise how studies processed and analysed data collected through digital devices. 203 articles collecting passive data through smartphones or wearable devices, from participants with psychosis or schizophrenia were included in the review. Accelerometers were the most common device (n = 115 studies), followed by smartphones (n = 46). The most commonly derived features were sleep duration (n = 50) and time spent sedentary (n = 41). 30 studies
assessed data quality, and another 69 applied data quantity thresholds. Mixed effects models were used in 21 studies, time-series and machine learning methods were used in 18 studies. Reporting of methods to process and analyse data was inconsistent, highlighting a need to improve standardisation of methods and reporting in this area of research.
assessed data quality, and another 69 applied data quantity thresholds. Mixed effects models were used in 21 studies, time-series and machine learning methods were used in 18 studies. Reporting of methods to process and analyse data was inconsistent, highlighting a need to improve standardisation of methods and reporting in this area of research.
Original language | English |
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Journal | npj Digital Medicine |
Publication status | Accepted/In press - 13 Jan 2025 |