A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity
Abstract Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of th...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-11-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-46075-2 |
| _version_ | 1797636904465727488 |
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| author | Ahnjili Zhuparris Ghobad Maleki Liesbeth van Londen Ingrid Koopmans Vincent Aalten Iris E. Yocarini Vasileios Exadaktylos Albert van Hemert Adam Cohen Pim Gal Robert-Jan Doll Geert Jan Groeneveld Gabriël Jacobs Wessel Kraaij |
| author_facet | Ahnjili Zhuparris Ghobad Maleki Liesbeth van Londen Ingrid Koopmans Vincent Aalten Iris E. Yocarini Vasileios Exadaktylos Albert van Hemert Adam Cohen Pim Gal Robert-Jan Doll Geert Jan Groeneveld Gabriël Jacobs Wessel Kraaij |
| author_sort | Ahnjili Zhuparris |
| collection | DOAJ |
| description | Abstract Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of this study is to identify the correlations between remotely monitored self-reported assessments and objectively measured activities with depression severity assessments often applied in clinical trials. 30 unipolar depressed patients and 29 age- and gender-matched healthy controls were enrolled in this study. Each participant’s daily physiological, physical, and social activity were monitored using a smartphone-based application (CHDR MORE™) for 3 weeks continuously. Self-reported depression anxiety stress scale-21 (DASS-21) and positive and negative affect schedule (PANAS) were administered via smartphone weekly and daily respectively. The structured interview guide for the Hamilton depression scale and inventory of depressive symptomatology–clinical rated (SIGHD-IDSC) was administered in-clinic weekly. Nested cross-validated linear mixed-effects models were used to identify the correlation between the CHDR MORE™ features with the weekly in-clinic SIGHD-IDSC scores. The SIGHD-IDSC regression model demonstrated an explained variance (R2) of 0.80, and a Root Mean Square Error (RMSE) of ± 15 points. The SIGHD-IDSC total scores were positively correlated with the DASS and mean steps-per-minute, and negatively correlated with the travel duration. Unobtrusive, remotely monitored behavior and self-reported outcomes are correlated with depression severity. While these features cannot replace the SIGHD-IDSC for estimating depression severity, it can serve as a complementary approach for assessing depression and drug effects outside the clinic. |
| first_indexed | 2024-03-11T12:40:46Z |
| format | Article |
| id | doaj.art-7fc77d26e65c4a94b6761c3ca90e1519 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-11T12:40:46Z |
| publishDate | 2023-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-7fc77d26e65c4a94b6761c3ca90e15192023-11-05T12:18:05ZengNature PortfolioScientific Reports2045-23222023-11-0113111410.1038/s41598-023-46075-2A smartphone- and wearable-based biomarker for the estimation of unipolar depression severityAhnjili Zhuparris0Ghobad Maleki1Liesbeth van Londen2Ingrid Koopmans3Vincent Aalten4Iris E. Yocarini5Vasileios Exadaktylos6Albert van Hemert7Adam Cohen8Pim Gal9Robert-Jan Doll10Geert Jan Groeneveld11Gabriël Jacobs12Wessel Kraaij13Centre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Transparant Centre for Mental Health CareCentre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Leiden Institute of Advanced Computer Science (LIACS), Leiden UniversityCentre for Human Drug Research (CHDR)Leiden University Medical Centre (LUMC), Leiden UniversityCentre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Centre for Human Drug Research (CHDR)Leiden Institute of Advanced Computer Science (LIACS), Leiden UniversityAbstract Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of this study is to identify the correlations between remotely monitored self-reported assessments and objectively measured activities with depression severity assessments often applied in clinical trials. 30 unipolar depressed patients and 29 age- and gender-matched healthy controls were enrolled in this study. Each participant’s daily physiological, physical, and social activity were monitored using a smartphone-based application (CHDR MORE™) for 3 weeks continuously. Self-reported depression anxiety stress scale-21 (DASS-21) and positive and negative affect schedule (PANAS) were administered via smartphone weekly and daily respectively. The structured interview guide for the Hamilton depression scale and inventory of depressive symptomatology–clinical rated (SIGHD-IDSC) was administered in-clinic weekly. Nested cross-validated linear mixed-effects models were used to identify the correlation between the CHDR MORE™ features with the weekly in-clinic SIGHD-IDSC scores. The SIGHD-IDSC regression model demonstrated an explained variance (R2) of 0.80, and a Root Mean Square Error (RMSE) of ± 15 points. The SIGHD-IDSC total scores were positively correlated with the DASS and mean steps-per-minute, and negatively correlated with the travel duration. Unobtrusive, remotely monitored behavior and self-reported outcomes are correlated with depression severity. While these features cannot replace the SIGHD-IDSC for estimating depression severity, it can serve as a complementary approach for assessing depression and drug effects outside the clinic.https://doi.org/10.1038/s41598-023-46075-2 |
| spellingShingle | Ahnjili Zhuparris Ghobad Maleki Liesbeth van Londen Ingrid Koopmans Vincent Aalten Iris E. Yocarini Vasileios Exadaktylos Albert van Hemert Adam Cohen Pim Gal Robert-Jan Doll Geert Jan Groeneveld Gabriël Jacobs Wessel Kraaij A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity Scientific Reports |
| title | A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity |
| title_full | A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity |
| title_fullStr | A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity |
| title_full_unstemmed | A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity |
| title_short | A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity |
| title_sort | smartphone and wearable based biomarker for the estimation of unipolar depression severity |
| url | https://doi.org/10.1038/s41598-023-46075-2 |
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