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Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial
BACKGROUND: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. OBJECTIVE: To assess (i) accep...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453320/ https://www.ncbi.nlm.nih.gov/pubmed/32788150 http://dx.doi.org/10.2196/17019 |
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author | Lewis, Shon Ainsworth, John Sanders, Caroline Stockton-Powdrell, Charlotte Machin, Matthew Whelan, Pauline Hopkins, Richard He, Zhimin Applegate, Eve Drake, Richard Bamford, Charlie Roberts, Chris Wykes, Til |
author_facet | Lewis, Shon Ainsworth, John Sanders, Caroline Stockton-Powdrell, Charlotte Machin, Matthew Whelan, Pauline Hopkins, Richard He, Zhimin Applegate, Eve Drake, Richard Bamford, Charlie Roberts, Chris Wykes, Til |
author_sort | Lewis, Shon |
collection | PubMed |
description | BACKGROUND: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. OBJECTIVE: To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse. METHODS: The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team. RESULTS: Of 181 eligible patients, 81 (45%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33% of alerts) of 84% (30/36}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff. CONCLUSIONS: The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse. TRIAL REGISTRATION: ISRCTN Registry ISRCTN88145142; http://www.isrctn.com/ISRCTN88145142 |
format | Online Article Text |
id | pubmed-7453320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-74533202020-08-31 Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial Lewis, Shon Ainsworth, John Sanders, Caroline Stockton-Powdrell, Charlotte Machin, Matthew Whelan, Pauline Hopkins, Richard He, Zhimin Applegate, Eve Drake, Richard Bamford, Charlie Roberts, Chris Wykes, Til J Med Internet Res Original Paper BACKGROUND: Improving recovery from acute symptoms and preventing relapse are two significant challenges in severe mental illness. We developed a personalized smartphone-based app to monitor symptoms in real time and validated its acceptance, reliability, and validity. OBJECTIVE: To assess (i) acceptability of continuous monitoring to SMI patients and health professionals over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; and (iii) the feasibility of detecting early warning signs of relapse. METHODS: The active symptom monitoring smartphone app was built into an end-to-end system in two NHS Trusts to enable real-time symptom self-monitoring and detection by the clinical team of early signs of relapse in people with severe mental illness. We conducted an open randomized controlled trial of active symptom monitoring compared to usual management to assess: (i) acceptability and safety of continuous monitoring over 3 months; (ii) impact of active self-monitoring on positive psychotic symptoms assessed at 6 and 12 weeks; (iii) feasibility of detecting early warning signs of relapse communicated to the healthcare staff via an app streaming data to the electronic health record. Eligible participants with a Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) diagnosis of schizophrenia and related disorders, and a history of relapse within the previous two years were enrolled from an early intervention team and a community mental health team. RESULTS: Of 181 eligible patients, 81 (45%) consented and were randomized to either active symptom monitoring or management as usual. At 12 weeks, 90% (33/36) of those in the active monitoring group continued to use the system and exhibited an adherence rate (defined as responding to >33% of alerts) of 84% (30/36}. Active symptom monitoring was associated with no difference on the empowerment scale in comparison to the usual management group at 12 weeks. The pre-planned intent-to-treat analysis of the primary outcome, a positive score on the Positive and Negative Syndrome Scale (PANSS) scale, showed a significant reduction in the active symptom monitoring group over 12 weeks in the early intervention center. Alerts for personalized early warning signs of relapse were built into the workflows of both NHS Trusts, and 100% of health professional staff used the system in a new digital workflow. Qualitative analyses supported the acceptability of the system to participants and staff. CONCLUSIONS: The active smartphone monitoring system is feasible and was accepted by users in a 3-month study of people with severe mental illness, with surprisingly high levels of adherence. App use was associated with psychotic symptom improvement in recent-onset participants, but not those with longstanding illness, supporting the notion of improved self-management. When built into clinical management workflows to enable personalized alerts of symptom deterioration, the app has demonstrated utility in promoting earlier intervention for relapse. TRIAL REGISTRATION: ISRCTN Registry ISRCTN88145142; http://www.isrctn.com/ISRCTN88145142 JMIR Publications 2020-08-13 /pmc/articles/PMC7453320/ /pubmed/32788150 http://dx.doi.org/10.2196/17019 Text en ©Shon Lewis, John Ainsworth, Caroline Sanders, Charlotte Stockton-Powdrell, Matthew Machin, Pauline Whelan, Richard Hopkins, Zhimin He, Eve Applegate, Richard Drake, Charlie Bamford, Chris Roberts, Til Wykes. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.08.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Lewis, Shon Ainsworth, John Sanders, Caroline Stockton-Powdrell, Charlotte Machin, Matthew Whelan, Pauline Hopkins, Richard He, Zhimin Applegate, Eve Drake, Richard Bamford, Charlie Roberts, Chris Wykes, Til Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title | Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title_full | Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title_fullStr | Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title_full_unstemmed | Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title_short | Smartphone-Enhanced Symptom Management In Psychosis: Open, Randomized Controlled Trial |
title_sort | smartphone-enhanced symptom management in psychosis: open, randomized controlled trial |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7453320/ https://www.ncbi.nlm.nih.gov/pubmed/32788150 http://dx.doi.org/10.2196/17019 |
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