A systematic review of passive data for remote monitoring in psychosis and schizophrenia
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 aimed to summarise how studies processed and analysed data collected through digital devices. In total, 203 articles colle...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01451-2 |
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| author | Siân Bladon Emily Eisner Sandra Bucci Anuoluwapo Oluwatayo Glen P. Martin Matthew Sperrin John Ainsworth Sophie Faulkner |
| author_facet | Siân Bladon Emily Eisner Sandra Bucci Anuoluwapo Oluwatayo Glen P. Martin Matthew Sperrin John Ainsworth Sophie Faulkner |
| author_sort | Siân Bladon |
| collection | DOAJ |
| description | 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 aimed to summarise how studies processed and analysed data collected through digital devices. In total, 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). Thirty studies assessed data quality and another 69 applied data quantity thresholds. Mixed effects models were used in 21 studies and 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 the standardisation of methods and reporting in this area of research. |
| format | Article |
| id | doaj-art-bf00fb8d40b74b589ac3286c35448513 |
| institution | Kabale University |
| issn | 2398-6352 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Digital Medicine |
| spelling | doaj-art-bf00fb8d40b74b589ac3286c354485132025-02-02T12:43:46ZengNature Portfolionpj Digital Medicine2398-63522025-01-018111310.1038/s41746-025-01451-2A systematic review of passive data for remote monitoring in psychosis and schizophreniaSiân Bladon0Emily Eisner1Sandra Bucci2Anuoluwapo Oluwatayo3Glen P. Martin4Matthew Sperrin5John Ainsworth6Sophie Faulkner7Centre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of ManchesterDivision of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of ManchesterDivision of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of ManchesterDivision of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of ManchesterCentre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of ManchesterCentre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of ManchesterCentre for Health Informatics, Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of ManchesterDivision of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of ManchesterAbstract 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 aimed to summarise how studies processed and analysed data collected through digital devices. In total, 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). Thirty studies assessed data quality and another 69 applied data quantity thresholds. Mixed effects models were used in 21 studies and 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 the standardisation of methods and reporting in this area of research.https://doi.org/10.1038/s41746-025-01451-2 |
| spellingShingle | Siân Bladon Emily Eisner Sandra Bucci Anuoluwapo Oluwatayo Glen P. Martin Matthew Sperrin John Ainsworth Sophie Faulkner A systematic review of passive data for remote monitoring in psychosis and schizophrenia npj Digital Medicine |
| title | A systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| title_full | A systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| title_fullStr | A systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| title_full_unstemmed | A systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| title_short | A systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| title_sort | systematic review of passive data for remote monitoring in psychosis and schizophrenia |
| url | https://doi.org/10.1038/s41746-025-01451-2 |
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