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Article: ReMind, a smartphone application for psychotic relapse prediction: A longitudinal study protocol

TitleReMind, a smartphone application for psychotic relapse prediction: A longitudinal study protocol
Authors
Keywordsapp
mhealth
psychosis
relapse
smartphone
Issue Date2020
PublisherWiley-Blackwell Publishing Asia. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1751-7893
Citation
Early Intervention in Psychiatry, 2020, Epub 2020-12-23 How to Cite?
AbstractBackground: Psychotic disorders are associated with a high rate of relapse. In addition to medication non-adherence, some psychosocial factors have been found to be predictive of relapse (e.g., poor premorbid adjustment, high expressed emotion and substance misuse). Impairments in cognitive functions including general memory functioning, set shifting, attention, processing speed and working memory have also been indicative of a subsequent psychotic episode. As clinical appointments do not always allow for timely or accurate detection of these early warning signs, the ReMind app is developed to explore potential relapse predictors and enhance the process of relapse monitoring. Aim: The ReMind app aims (1) to assess whether verbal or visual working memory predicts psychotic relapse in 1 year and (2) to determine whether social factors such as stressful life events, level of expressed emotion and medication adherence also predict relapse in 1 year. Methods: This is a one-year prospective follow-up study involving 176 remitted patients diagnosed with schizophrenia or non-affective psychoses. Monthly relapse predictor assessments will be conducted via ReMind throughout the one-year study duration. These assessments include neurocognitive tasks and psychosocial questionnaires. Results: Recruitment began in August 2017 and is still ongoing. Preliminary user feedback suggested an overall positive experience with the app. Conclusion: The ReMind app presents a step forward to the identification and sensitive detection of reliable psychosis relapse predictors. With its anticipated success, it may offer an alternative means of monitoring relapse for the Chinese-speaking population in the future.
Persistent Identifierhttp://hdl.handle.net/10722/295524
ISSN
2021 Impact Factor: 2.721
2020 SCImago Journal Rankings: 1.087
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorHui, CLM-
dc.contributor.authorLam, BST-
dc.contributor.authorWong, AKH-
dc.contributor.authorTao, TJ-
dc.contributor.authorHo, ECN-
dc.contributor.authorSuen, YN-
dc.contributor.authorLee, EHM-
dc.contributor.authorChan, KW-
dc.contributor.authorChang, WC-
dc.contributor.authorChong, CSY-
dc.contributor.authorSiu, CMW-
dc.contributor.authorLo, TL-
dc.contributor.authorChen, EYH-
dc.date.accessioned2021-01-25T11:16:06Z-
dc.date.available2021-01-25T11:16:06Z-
dc.date.issued2020-
dc.identifier.citationEarly Intervention in Psychiatry, 2020, Epub 2020-12-23-
dc.identifier.issn1751-7885-
dc.identifier.urihttp://hdl.handle.net/10722/295524-
dc.description.abstractBackground: Psychotic disorders are associated with a high rate of relapse. In addition to medication non-adherence, some psychosocial factors have been found to be predictive of relapse (e.g., poor premorbid adjustment, high expressed emotion and substance misuse). Impairments in cognitive functions including general memory functioning, set shifting, attention, processing speed and working memory have also been indicative of a subsequent psychotic episode. As clinical appointments do not always allow for timely or accurate detection of these early warning signs, the ReMind app is developed to explore potential relapse predictors and enhance the process of relapse monitoring. Aim: The ReMind app aims (1) to assess whether verbal or visual working memory predicts psychotic relapse in 1 year and (2) to determine whether social factors such as stressful life events, level of expressed emotion and medication adherence also predict relapse in 1 year. Methods: This is a one-year prospective follow-up study involving 176 remitted patients diagnosed with schizophrenia or non-affective psychoses. Monthly relapse predictor assessments will be conducted via ReMind throughout the one-year study duration. These assessments include neurocognitive tasks and psychosocial questionnaires. Results: Recruitment began in August 2017 and is still ongoing. Preliminary user feedback suggested an overall positive experience with the app. Conclusion: The ReMind app presents a step forward to the identification and sensitive detection of reliable psychosis relapse predictors. With its anticipated success, it may offer an alternative means of monitoring relapse for the Chinese-speaking population in the future.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing Asia. The Journal's web site is located at http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1751-7893-
dc.relation.ispartofEarly Intervention in Psychiatry-
dc.rightsSubmitted (preprint) Version This is the pre-peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. Accepted (peer-reviewed) Version This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.-
dc.subjectapp-
dc.subjectmhealth-
dc.subjectpsychosis-
dc.subjectrelapse-
dc.subjectsmartphone-
dc.titleReMind, a smartphone application for psychotic relapse prediction: A longitudinal study protocol-
dc.typeArticle-
dc.identifier.emailHui, CLM: christyh@hku.hk-
dc.identifier.emailTao, TJ: tjunchen@hku.hk-
dc.identifier.emailHo, ECN: eliseho@hku.hk-
dc.identifier.emailSuen, YN: suenyn@hku.hk-
dc.identifier.emailLee, EHM: edwinlhm@hku.hk-
dc.identifier.emailChan, KW: kwsherry@hku.hk-
dc.identifier.emailChang, WC: changwc@hku.hk-
dc.identifier.emailSiu, CMW: smw732@hku.hk-
dc.identifier.emailLo, TL: lotl@hku.hk-
dc.identifier.emailChen, EYH: eyhchen@hku.hk-
dc.identifier.authorityHui, CLM=rp01993-
dc.identifier.authoritySuen, YN=rp02481-
dc.identifier.authorityLee, EHM=rp01575-
dc.identifier.authorityChan, KW=rp00539-
dc.identifier.authorityChang, WC=rp01465-
dc.identifier.authorityChen, EYH=rp00392-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/eip.13108-
dc.identifier.pmid33369162-
dc.identifier.scopuseid_2-s2.0-85099519719-
dc.identifier.hkuros320996-
dc.identifier.volumeEpub 2020-12-23-
dc.identifier.isiWOS:000601208900001-
dc.publisher.placeUnited States-

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