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Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study

BACKGROUND: Less than 10% of the individuals seeking behavioral health care receive measurement-based care (MBC). Technology has the potential to implement MBC in a secure and efficient manner. To test this idea, a mobile health (mHealth) platform was developed with the goal of making MBC easier to...

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Autores principales: Lynch, William, Platt, Michael L, Pardes, Adam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8663615/
https://www.ncbi.nlm.nih.gov/pubmed/34757319
http://dx.doi.org/10.2196/30313
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author Lynch, William
Platt, Michael L
Pardes, Adam
author_facet Lynch, William
Platt, Michael L
Pardes, Adam
author_sort Lynch, William
collection PubMed
description BACKGROUND: Less than 10% of the individuals seeking behavioral health care receive measurement-based care (MBC). Technology has the potential to implement MBC in a secure and efficient manner. To test this idea, a mobile health (mHealth) platform was developed with the goal of making MBC easier to deliver by clinicians and more accessible to patients within integrated behavioral health care. Data from over 3000 users of the mHealth platform were used to develop an output severity score, a robust screening measure for depression and anxiety. OBJECTIVE: The aim of this study is to compare severity scores with scores from validated assessments for depression and anxiety and scores from clinician review to evaluate the potential added value of this new measure. METHODS: The severity score uses patient-reported and passively collected data related to behavioral health on an mHealth platform. An artificial intelligence–derived algorithm was developed that condenses behavioral health data into a single, quantifiable measure for longitudinal tracking of an individual’s depression and anxiety symptoms. Linear regression and Bland-Altman analyses were used to evaluate the relationships and differences between severity scores and Personal Health Questionnaire-9 (PHQ-9) or Generalized Anxiety Disorder-7 (GAD-7) scores from over 35,000 mHealth platform users. The severity score was also compared with a review by a panel of expert clinicians for a subset of 250 individuals. RESULTS: Linear regression results showed a strong correlation between the severity score and PHQ-9 (r=0.74; P<.001) and GAD-7 (r=0.80; P<.001) changes. A strong positive correlation was also found between the severity score and expert panel clinical review (r=0.80-0.84; P<.001). However, Bland-Altman analysis and the evaluation of outliers on regression analysis showed that the severity score was significantly different from the PHQ-9. CONCLUSIONS: Clinicians can reliably use the mHealth severity score as a proxy measure for screening and monitoring behavioral health symptoms longitudinally. The severity score may identify at-risk individuals who are not identified by the PHQ-9. Further research is warranted to evaluate the sensitivity and specificity of the severity score.
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spelling pubmed-86636152022-01-05 Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study Lynch, William Platt, Michael L Pardes, Adam JMIR Form Res Original Paper BACKGROUND: Less than 10% of the individuals seeking behavioral health care receive measurement-based care (MBC). Technology has the potential to implement MBC in a secure and efficient manner. To test this idea, a mobile health (mHealth) platform was developed with the goal of making MBC easier to deliver by clinicians and more accessible to patients within integrated behavioral health care. Data from over 3000 users of the mHealth platform were used to develop an output severity score, a robust screening measure for depression and anxiety. OBJECTIVE: The aim of this study is to compare severity scores with scores from validated assessments for depression and anxiety and scores from clinician review to evaluate the potential added value of this new measure. METHODS: The severity score uses patient-reported and passively collected data related to behavioral health on an mHealth platform. An artificial intelligence–derived algorithm was developed that condenses behavioral health data into a single, quantifiable measure for longitudinal tracking of an individual’s depression and anxiety symptoms. Linear regression and Bland-Altman analyses were used to evaluate the relationships and differences between severity scores and Personal Health Questionnaire-9 (PHQ-9) or Generalized Anxiety Disorder-7 (GAD-7) scores from over 35,000 mHealth platform users. The severity score was also compared with a review by a panel of expert clinicians for a subset of 250 individuals. RESULTS: Linear regression results showed a strong correlation between the severity score and PHQ-9 (r=0.74; P<.001) and GAD-7 (r=0.80; P<.001) changes. A strong positive correlation was also found between the severity score and expert panel clinical review (r=0.80-0.84; P<.001). However, Bland-Altman analysis and the evaluation of outliers on regression analysis showed that the severity score was significantly different from the PHQ-9. CONCLUSIONS: Clinicians can reliably use the mHealth severity score as a proxy measure for screening and monitoring behavioral health symptoms longitudinally. The severity score may identify at-risk individuals who are not identified by the PHQ-9. Further research is warranted to evaluate the sensitivity and specificity of the severity score. JMIR Publications 2021-11-10 /pmc/articles/PMC8663615/ /pubmed/34757319 http://dx.doi.org/10.2196/30313 Text en ©William Lynch, Michael L Platt, Adam Pardes. Originally published in JMIR Formative Research (https://formative.jmir.org), 10.11.2021. 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 Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Lynch, William
Platt, Michael L
Pardes, Adam
Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title_full Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title_fullStr Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title_full_unstemmed Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title_short Development of a Severity Score and Comparison With Validated Measures for Depression and Anxiety: Validation Study
title_sort development of a severity score and comparison with validated measures for depression and anxiety: validation study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8663615/
https://www.ncbi.nlm.nih.gov/pubmed/34757319
http://dx.doi.org/10.2196/30313
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