Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers
Objective. This study examines factors predicting self-reported voice symptoms in call center workers. Methods. Multivariate analysis and predictive modeling assess personal, work-related, acoustic, and behavioral factors. Generalized Linear Models (GLMs) and Receiver Operating Characteristic (RO...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | Spanish |
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Fundación Universitaria María Cano
2024-01-01
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| Series: | Revista de Investigación e Innovación en Ciencias de la Salud |
| Subjects: | |
| Online Access: | https://riics.info/index.php/RCMC/article/view/240 |
| _version_ | 1827369229707378688 |
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| author | Adrián Castillo-Allendes Lady Catherine Cantor-Cutiva Eduardo Fuentes-López Eric J. Hunter |
| author_facet | Adrián Castillo-Allendes Lady Catherine Cantor-Cutiva Eduardo Fuentes-López Eric J. Hunter |
| author_sort | Adrián Castillo-Allendes |
| collection | DOAJ |
| description |
Objective. This study examines factors predicting self-reported voice symptoms in call center workers.
Methods. Multivariate analysis and predictive modeling assess personal, work-related, acoustic, and behavioral factors. Generalized Linear Models (GLMs) and Receiver Operating Characteristic (ROC) curves are employed.
Results. Age and sleep patterns impacted voice quality and effort, while workplace factors influenced symptom perception. Unhealthy vocal behaviors related to tense voice and increased effort, while hydration was protective. Voice acoustics showed diagnostic potential, supported by ROC data. These findings emphasize voice symptom complexity in call center professionals, necessitating comprehensive assessment.
Limitations. This study recognizes its limitations, including a moderate-sized convenience sample and reliance on PROM metrics. Future research should incorporate more objective measures in addition to self-reports and acoustic analysis.
Value. This research provides novel insights into the interplay of personal, occupational, and voice-related factors in developing voice symptoms among call center workers. Predictive modeling enhances risk assessment and understanding of individual susceptibility to voice disorders.
Conclusion. Results show associations between various factors and self-reported voice symptoms. Protective factors include sleeping more than six hours and consistent hydration, whereas risk factors include working conditions, such as location and behaviors like smoking. Diagnostic models indicate good accuracy for some voice symptom PROMs, emphasizing the need for comprehensive models considering work factors, vocal behaviors, and acoustic parameters to understand voice issues complexity.
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| first_indexed | 2024-03-08T09:43:13Z |
| format | Article |
| id | doaj.art-e67b85cc60b94b8d8ab55e7bc5df9452 |
| institution | Directory Open Access Journal |
| issn | 2665-2056 |
| language | Spanish |
| last_indexed | 2024-03-08T09:43:13Z |
| publishDate | 2024-01-01 |
| publisher | Fundación Universitaria María Cano |
| record_format | Article |
| series | Revista de Investigación e Innovación en Ciencias de la Salud |
| spelling | doaj.art-e67b85cc60b94b8d8ab55e7bc5df94522024-01-30T03:44:37ZspaFundación Universitaria María CanoRevista de Investigación e Innovación en Ciencias de la Salud2665-20562024-01-016110.46634/riics.240Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call CentersAdrián Castillo-Allendes0Lady Catherine Cantor-Cutiva1Eduardo Fuentes-López2Eric J. Hunter3Department of Communicative Sciences and Disorders; Michigan State University; East Lansing; Michigan; United States. / Department of Communication Sciences and Disorders; The University of Iowa; Iowa City; United StatesDepartment of Communication Sciences and Disorders; The University of Iowa; Iowa City; United StaDepartment of Health Sciences; School of Medicine; Pontificia Universidad Católica de Chile; Santiago; ChileDepartment of Communication Sciences and Disorders; The University of Iowa; Iowa City; United States Objective. This study examines factors predicting self-reported voice symptoms in call center workers. Methods. Multivariate analysis and predictive modeling assess personal, work-related, acoustic, and behavioral factors. Generalized Linear Models (GLMs) and Receiver Operating Characteristic (ROC) curves are employed. Results. Age and sleep patterns impacted voice quality and effort, while workplace factors influenced symptom perception. Unhealthy vocal behaviors related to tense voice and increased effort, while hydration was protective. Voice acoustics showed diagnostic potential, supported by ROC data. These findings emphasize voice symptom complexity in call center professionals, necessitating comprehensive assessment. Limitations. This study recognizes its limitations, including a moderate-sized convenience sample and reliance on PROM metrics. Future research should incorporate more objective measures in addition to self-reports and acoustic analysis. Value. This research provides novel insights into the interplay of personal, occupational, and voice-related factors in developing voice symptoms among call center workers. Predictive modeling enhances risk assessment and understanding of individual susceptibility to voice disorders. Conclusion. Results show associations between various factors and self-reported voice symptoms. Protective factors include sleeping more than six hours and consistent hydration, whereas risk factors include working conditions, such as location and behaviors like smoking. Diagnostic models indicate good accuracy for some voice symptom PROMs, emphasizing the need for comprehensive models considering work factors, vocal behaviors, and acoustic parameters to understand voice issues complexity. https://riics.info/index.php/RCMC/article/view/240Voice symptomscall center workerspredictive factorsoccupational healthself-reported measures |
| spellingShingle | Adrián Castillo-Allendes Lady Catherine Cantor-Cutiva Eduardo Fuentes-López Eric J. Hunter Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers Revista de Investigación e Innovación en Ciencias de la Salud Voice symptoms call center workers predictive factors occupational health self-reported measures |
| title | Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers |
| title_full | Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers |
| title_fullStr | Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers |
| title_full_unstemmed | Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers |
| title_short | Behind the Headset: Predictive Accuracy of Patient-Reported Outcome Measures for Voice Symptoms in Call Centers |
| title_sort | behind the headset predictive accuracy of patient reported outcome measures for voice symptoms in call centers |
| topic | Voice symptoms call center workers predictive factors occupational health self-reported measures |
| url | https://riics.info/index.php/RCMC/article/view/240 |
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