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Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study

BACKGROUND: Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants’ self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowle...

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Autores principales: Goltermann, Janik, Emden, Daniel, Leehr, Elisabeth Johanna, Dohm, Katharina, Redlich, Ronny, Dannlowski, Udo, Hahn, Tim, Opel, Nils
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837996/
https://www.ncbi.nlm.nih.gov/pubmed/33433392
http://dx.doi.org/10.2196/24333
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author Goltermann, Janik
Emden, Daniel
Leehr, Elisabeth Johanna
Dohm, Katharina
Redlich, Ronny
Dannlowski, Udo
Hahn, Tim
Opel, Nils
author_facet Goltermann, Janik
Emden, Daniel
Leehr, Elisabeth Johanna
Dohm, Katharina
Redlich, Ronny
Dannlowski, Udo
Hahn, Tim
Opel, Nils
author_sort Goltermann, Janik
collection PubMed
description BACKGROUND: Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants’ self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowledge about their psychometric properties, especially their validity. OBJECTIVE: The goal of this study is to systematically investigate the validity of smartphone-administered assessments of self-reported affective symptoms using the Remote Monitoring Application in Psychiatry (ReMAP). METHODS: The ReMAP app was distributed to 173 adult participants of ongoing, longitudinal psychiatric phenotyping studies, including healthy control participants, as well as patients with affective disorders and anxiety disorders; the mean age of the sample was 30.14 years (SD 11.92). The Beck Depression Inventory (BDI) and single-item mood and sleep information were assessed via the ReMAP app and validated with non–smartphone-based BDI scores and clinician-rated depression severity using the Hamilton Depression Rating Scale (HDRS). RESULTS: We found overall high comparability between smartphone-based and non–smartphone-based BDI scores (intraclass correlation coefficient=0.921; P<.001). Smartphone-based BDI scores further correlated with non–smartphone-based HDRS ratings of depression severity in a subsample (r=0.783; P<.001; n=51). Higher agreement between smartphone-based and non–smartphone-based assessments was found among affective disorder patients as compared to healthy controls and anxiety disorder patients. Highly comparable agreement between delivery formats was found across age and gender groups. Similarly, smartphone-based single-item self-ratings of mood correlated with BDI sum scores (r=–0.538; P<.001; n=168), while smartphone-based single-item sleep duration correlated with the sleep item of the BDI (r=–0.310; P<.001; n=166). CONCLUSIONS: These findings demonstrate that smartphone-based monitoring of depressive symptoms via the ReMAP app provides valid assessments of depressive symptomatology and, therefore, represents a useful tool for prospective digital phenotyping in affective disorder patients in clinical and research applications.
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spelling pubmed-78379962021-01-29 Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study Goltermann, Janik Emden, Daniel Leehr, Elisabeth Johanna Dohm, Katharina Redlich, Ronny Dannlowski, Udo Hahn, Tim Opel, Nils JMIR Ment Health Original Paper BACKGROUND: Smartphone-based symptom monitoring has gained increased attention in psychiatric research as a cost-efficient tool for prospective and ecologically valid assessments based on participants’ self-reports. However, a meaningful interpretation of smartphone-based assessments requires knowledge about their psychometric properties, especially their validity. OBJECTIVE: The goal of this study is to systematically investigate the validity of smartphone-administered assessments of self-reported affective symptoms using the Remote Monitoring Application in Psychiatry (ReMAP). METHODS: The ReMAP app was distributed to 173 adult participants of ongoing, longitudinal psychiatric phenotyping studies, including healthy control participants, as well as patients with affective disorders and anxiety disorders; the mean age of the sample was 30.14 years (SD 11.92). The Beck Depression Inventory (BDI) and single-item mood and sleep information were assessed via the ReMAP app and validated with non–smartphone-based BDI scores and clinician-rated depression severity using the Hamilton Depression Rating Scale (HDRS). RESULTS: We found overall high comparability between smartphone-based and non–smartphone-based BDI scores (intraclass correlation coefficient=0.921; P<.001). Smartphone-based BDI scores further correlated with non–smartphone-based HDRS ratings of depression severity in a subsample (r=0.783; P<.001; n=51). Higher agreement between smartphone-based and non–smartphone-based assessments was found among affective disorder patients as compared to healthy controls and anxiety disorder patients. Highly comparable agreement between delivery formats was found across age and gender groups. Similarly, smartphone-based single-item self-ratings of mood correlated with BDI sum scores (r=–0.538; P<.001; n=168), while smartphone-based single-item sleep duration correlated with the sleep item of the BDI (r=–0.310; P<.001; n=166). CONCLUSIONS: These findings demonstrate that smartphone-based monitoring of depressive symptoms via the ReMAP app provides valid assessments of depressive symptomatology and, therefore, represents a useful tool for prospective digital phenotyping in affective disorder patients in clinical and research applications. JMIR Publications 2021-01-12 /pmc/articles/PMC7837996/ /pubmed/33433392 http://dx.doi.org/10.2196/24333 Text en ©Janik Goltermann, Daniel Emden, Elisabeth Johanna Leehr, Katharina Dohm, Ronny Redlich, Udo Dannlowski, Tim Hahn, Nils Opel. Originally published in JMIR Mental Health (http://mental.jmir.org), 12.01.2021. 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 JMIR Mental Health, is properly cited. The complete bibliographic information, a link to the original publication on http://mental.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Goltermann, Janik
Emden, Daniel
Leehr, Elisabeth Johanna
Dohm, Katharina
Redlich, Ronny
Dannlowski, Udo
Hahn, Tim
Opel, Nils
Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title_full Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title_fullStr Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title_full_unstemmed Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title_short Smartphone-Based Self-Reports of Depressive Symptoms Using the Remote Monitoring Application in Psychiatry (ReMAP): Interformat Validation Study
title_sort smartphone-based self-reports of depressive symptoms using the remote monitoring application in psychiatry (remap): interformat validation study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837996/
https://www.ncbi.nlm.nih.gov/pubmed/33433392
http://dx.doi.org/10.2196/24333
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