Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring
The research described in this article is a continuation of work on a computational model of quality of life (QoL) satisfaction. In the proposed approach, overall life satisfaction is aggregated to personal life satisfaction (PLUS). The model described in the article is based on well-known and commo...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/23/9214 |
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| author | Piotr Prokopowicz Dariusz Mikołajewski Emilia Mikołajewska |
| author_facet | Piotr Prokopowicz Dariusz Mikołajewski Emilia Mikołajewska |
| author_sort | Piotr Prokopowicz |
| collection | DOAJ |
| description | The research described in this article is a continuation of work on a computational model of quality of life (QoL) satisfaction. In the proposed approach, overall life satisfaction is aggregated to personal life satisfaction (PLUS). The model described in the article is based on well-known and commonly used clinimetric scales (e.g., in psychiatry, psychology and physiotherapy). The simultaneous use of multiple scales, and the complexity of describing the quality of life with them, require complex fuzzy computational solutions. The aim of the study is twofold: (1) To develop a fuzzy model that allows for the detection of changes in life satisfaction scores (data on the influence of the COVID-19 pandemic and the war in the neighboring country were used). (2) To develop more detailed guidelines than the existing ones for further similar research on more advanced intelligent systems with computational models which allow for sensing, detecting and evaluating the psychical state. We are concerned with developing practical solutions with higher scientific and clinical utility for both small datasets and big data to use in remote patient monitoring. Two exemplary groups of specialists at risk of occupational burnout were assessed three times at different intervals in terms of life satisfaction. The aforementioned assessment was made on Polish citizens because the specific data could be gathered: before and during the pandemic and during the war in Ukraine (a neighboring country). That has a higher potential for presenting a better analysis and reflection on the practical application of the model. A research group (physiotherapists, n = 20) and a reference group (IT professionals, n = 20) participated in the study. Four clinimetric scales were used for assessment: the Perceived Stress Scale (PSS10), the Maslach Burnout Scale (MBI), the Satisfaction with Life Scale (SWLS), and the Nordic Musculoskeletal Questionnaire (NMQ). The assessment was complemented by statistical analyses and fuzzy models based on a hierarchical fuzzy system. Although several models for understanding changes in life satisfaction scores have been previously investigated, the novelty of this study lies in the use of data from three consecutive time points for the same individuals and the way they are analyzed, based on fuzzy logic. In addition, the new hierarchical structure of the model used in the study provides flexibility and transparency in the process of remotely monitoring changes in people’s mental well-being and a quick response to observed changes. The aforementioned computational approach was used for the first time. |
| first_indexed | 2024-03-09T17:33:08Z |
| format | Article |
| id | doaj.art-b7c4c53cb61b423b844195803cc8224b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T17:33:08Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-b7c4c53cb61b423b844195803cc8224b2023-11-24T12:10:26ZengMDPI AGSensors1424-82202022-11-012223921410.3390/s22239214Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health MonitoringPiotr Prokopowicz0Dariusz Mikołajewski1Emilia Mikołajewska2Institute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, PolandInstitute of Computer Science, Kazimierz Wielki University, 85-064 Bydgoszcz, PolandFaculty of Health Sciences, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 87-100 Toruń, PolandThe research described in this article is a continuation of work on a computational model of quality of life (QoL) satisfaction. In the proposed approach, overall life satisfaction is aggregated to personal life satisfaction (PLUS). The model described in the article is based on well-known and commonly used clinimetric scales (e.g., in psychiatry, psychology and physiotherapy). The simultaneous use of multiple scales, and the complexity of describing the quality of life with them, require complex fuzzy computational solutions. The aim of the study is twofold: (1) To develop a fuzzy model that allows for the detection of changes in life satisfaction scores (data on the influence of the COVID-19 pandemic and the war in the neighboring country were used). (2) To develop more detailed guidelines than the existing ones for further similar research on more advanced intelligent systems with computational models which allow for sensing, detecting and evaluating the psychical state. We are concerned with developing practical solutions with higher scientific and clinical utility for both small datasets and big data to use in remote patient monitoring. Two exemplary groups of specialists at risk of occupational burnout were assessed three times at different intervals in terms of life satisfaction. The aforementioned assessment was made on Polish citizens because the specific data could be gathered: before and during the pandemic and during the war in Ukraine (a neighboring country). That has a higher potential for presenting a better analysis and reflection on the practical application of the model. A research group (physiotherapists, n = 20) and a reference group (IT professionals, n = 20) participated in the study. Four clinimetric scales were used for assessment: the Perceived Stress Scale (PSS10), the Maslach Burnout Scale (MBI), the Satisfaction with Life Scale (SWLS), and the Nordic Musculoskeletal Questionnaire (NMQ). The assessment was complemented by statistical analyses and fuzzy models based on a hierarchical fuzzy system. Although several models for understanding changes in life satisfaction scores have been previously investigated, the novelty of this study lies in the use of data from three consecutive time points for the same individuals and the way they are analyzed, based on fuzzy logic. In addition, the new hierarchical structure of the model used in the study provides flexibility and transparency in the process of remotely monitoring changes in people’s mental well-being and a quick response to observed changes. The aforementioned computational approach was used for the first time.https://www.mdpi.com/1424-8220/22/23/9214intelligent systemscomputational modelfuzzy logicremote monitoringquality of lifelife satisfaction |
| spellingShingle | Piotr Prokopowicz Dariusz Mikołajewski Emilia Mikołajewska Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring Sensors intelligent systems computational model fuzzy logic remote monitoring quality of life life satisfaction |
| title | Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring |
| title_full | Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring |
| title_fullStr | Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring |
| title_full_unstemmed | Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring |
| title_short | Intelligent System for Detecting Deterioration of Life Satisfaction as Tool for Remote Mental-Health Monitoring |
| title_sort | intelligent system for detecting deterioration of life satisfaction as tool for remote mental health monitoring |
| topic | intelligent systems computational model fuzzy logic remote monitoring quality of life life satisfaction |
| url | https://www.mdpi.com/1424-8220/22/23/9214 |
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