Cargando…
Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study
BACKGROUND: Self-reported mood is a valuable clinical data source regarding disease state and course in patients with mood disorders. However, validated, quick, and scalable digital self-report measures that can also detect relapse are still not available for clinical care. OBJECTIVE: In this study,...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386400/ https://www.ncbi.nlm.nih.gov/pubmed/34383689 http://dx.doi.org/10.2196/26348 |
_version_ | 1783742254184136704 |
---|---|
author | Anýž, Jiří Bakštein, Eduard Dally, Andrea Kolenič, Marián Hlinka, Jaroslav Hartmannová, Tereza Urbanová, Kateřina Correll, Christoph U Novák, Daniel Španiel, Filip |
author_facet | Anýž, Jiří Bakštein, Eduard Dally, Andrea Kolenič, Marián Hlinka, Jaroslav Hartmannová, Tereza Urbanová, Kateřina Correll, Christoph U Novák, Daniel Španiel, Filip |
author_sort | Anýž, Jiří |
collection | PubMed |
description | BACKGROUND: Self-reported mood is a valuable clinical data source regarding disease state and course in patients with mood disorders. However, validated, quick, and scalable digital self-report measures that can also detect relapse are still not available for clinical care. OBJECTIVE: In this study, we aim to validate the newly developed ASERT (Aktibipo Self-rating) questionnaire—a 10-item, mobile app–based, self-report mood questionnaire consisting of 4 depression, 4 mania, and 2 nonspecific symptom items, each with 5 possible answers. The validation data set is a subset of the ongoing observational longitudinal AKTIBIPO400 study for the long-term monitoring of mood and activity (via actigraphy) in patients with bipolar disorder (BD). Patients with confirmed BD are included and monitored with weekly ASERT questionnaires and monthly clinical scales (Montgomery-Åsberg Depression Rating Scale [MADRS] and Young Mania Rating Scale [YMRS]). METHODS: The content validity of the ASERT questionnaire was assessed using principal component analysis, and the Cronbach α was used to assess the internal consistency of each factor. The convergent validity of the depressive or manic items of the ASERT questionnaire with the MADRS and YMRS, respectively, was assessed using a linear mixed-effects model and linear correlation analyses. In addition, we investigated the capability of the ASERT questionnaire to distinguish relapse (YMRS≥15 and MADRS≥15) from a nonrelapse (interepisode) state (YMRS<15 and MADRS<15) using a logistic mixed-effects model. RESULTS: A total of 99 patients with BD were included in this study (follow-up: mean 754 days, SD 266) and completed an average of 78.1% (SD 18.3%) of the requested ASERT assessments (completion time for the 10 ASERT questions: median 24.0 seconds) across all patients in this study. The ASERT depression items were highly associated with MADRS total scores (P<.001; bootstrap). Similarly, ASERT mania items were highly associated with YMRS total scores (P<.001; bootstrap). Furthermore, the logistic mixed-effects regression model for scale-based relapse detection showed high detection accuracy in a repeated holdout validation for both depression (accuracy=85%; sensitivity=69.9%; specificity=88.4%; area under the receiver operating characteristic curve=0.880) and mania (accuracy=87.5%; sensitivity=64.9%; specificity=89.9%; area under the receiver operating characteristic curve=0.844). CONCLUSIONS: The ASERT questionnaire is a quick and acceptable mood monitoring tool that is administered via a smartphone app. The questionnaire has a good capability to detect the worsening of clinical symptoms in a long-term monitoring scenario. |
format | Online Article Text |
id | pubmed-8386400 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-83864002021-09-02 Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study Anýž, Jiří Bakštein, Eduard Dally, Andrea Kolenič, Marián Hlinka, Jaroslav Hartmannová, Tereza Urbanová, Kateřina Correll, Christoph U Novák, Daniel Španiel, Filip JMIR Ment Health Original Paper BACKGROUND: Self-reported mood is a valuable clinical data source regarding disease state and course in patients with mood disorders. However, validated, quick, and scalable digital self-report measures that can also detect relapse are still not available for clinical care. OBJECTIVE: In this study, we aim to validate the newly developed ASERT (Aktibipo Self-rating) questionnaire—a 10-item, mobile app–based, self-report mood questionnaire consisting of 4 depression, 4 mania, and 2 nonspecific symptom items, each with 5 possible answers. The validation data set is a subset of the ongoing observational longitudinal AKTIBIPO400 study for the long-term monitoring of mood and activity (via actigraphy) in patients with bipolar disorder (BD). Patients with confirmed BD are included and monitored with weekly ASERT questionnaires and monthly clinical scales (Montgomery-Åsberg Depression Rating Scale [MADRS] and Young Mania Rating Scale [YMRS]). METHODS: The content validity of the ASERT questionnaire was assessed using principal component analysis, and the Cronbach α was used to assess the internal consistency of each factor. The convergent validity of the depressive or manic items of the ASERT questionnaire with the MADRS and YMRS, respectively, was assessed using a linear mixed-effects model and linear correlation analyses. In addition, we investigated the capability of the ASERT questionnaire to distinguish relapse (YMRS≥15 and MADRS≥15) from a nonrelapse (interepisode) state (YMRS<15 and MADRS<15) using a logistic mixed-effects model. RESULTS: A total of 99 patients with BD were included in this study (follow-up: mean 754 days, SD 266) and completed an average of 78.1% (SD 18.3%) of the requested ASERT assessments (completion time for the 10 ASERT questions: median 24.0 seconds) across all patients in this study. The ASERT depression items were highly associated with MADRS total scores (P<.001; bootstrap). Similarly, ASERT mania items were highly associated with YMRS total scores (P<.001; bootstrap). Furthermore, the logistic mixed-effects regression model for scale-based relapse detection showed high detection accuracy in a repeated holdout validation for both depression (accuracy=85%; sensitivity=69.9%; specificity=88.4%; area under the receiver operating characteristic curve=0.880) and mania (accuracy=87.5%; sensitivity=64.9%; specificity=89.9%; area under the receiver operating characteristic curve=0.844). CONCLUSIONS: The ASERT questionnaire is a quick and acceptable mood monitoring tool that is administered via a smartphone app. The questionnaire has a good capability to detect the worsening of clinical symptoms in a long-term monitoring scenario. JMIR Publications 2021-08-09 /pmc/articles/PMC8386400/ /pubmed/34383689 http://dx.doi.org/10.2196/26348 Text en ©Jiří Anýž, Eduard Bakštein, Andrea Dally, Marián Kolenič, Jaroslav Hlinka, Tereza Hartmannová, Kateřina Urbanová, Christoph U Correll, Daniel Novák, Filip Španiel. Originally published in JMIR Mental Health (https://mental.jmir.org), 09.08.2021. 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 https://mental.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Anýž, Jiří Bakštein, Eduard Dally, Andrea Kolenič, Marián Hlinka, Jaroslav Hartmannová, Tereza Urbanová, Kateřina Correll, Christoph U Novák, Daniel Španiel, Filip Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title | Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title_full | Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title_fullStr | Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title_full_unstemmed | Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title_short | Validity of the Aktibipo Self-rating Questionnaire for the Digital Self-assessment of Mood and Relapse Detection in Patients With Bipolar Disorder: Instrument Validation Study |
title_sort | validity of the aktibipo self-rating questionnaire for the digital self-assessment of mood and relapse detection in patients with bipolar disorder: instrument validation study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386400/ https://www.ncbi.nlm.nih.gov/pubmed/34383689 http://dx.doi.org/10.2196/26348 |
work_keys_str_mv | AT anyzjiri validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT baksteineduard validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT dallyandrea validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT kolenicmarian validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT hlinkajaroslav validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT hartmannovatereza validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT urbanovakaterina validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT correllchristophu validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT novakdaniel validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy AT spanielfilip validityoftheaktibiposelfratingquestionnaireforthedigitalselfassessmentofmoodandrelapsedetectioninpatientswithbipolardisorderinstrumentvalidationstudy |