Universidad de Burgos RIUBU Principal Default Universidad de Burgos RIUBU Principal Default
  • español
  • English
  • français
  • Deutsch
  • português (Brasil)
  • italiano
Universidad de Burgos RIUBU Principal Default
  • Ayuda
  • Contattaci
  • Manda Feedback
  • Acceso abierto
    • Archivar en RIUBU
    • Acuerdos editoriales para la publicación en acceso abierto
    • Controla tus derechos, facilita el acceso abierto
    • Sobre el acceso abierto y la UBU
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    • español
    • English
    • français
    • Deutsch
    • português (Brasil)
    • italiano
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Ricerca

    Tutto RIUBUArchivi & CollezioniData di pubblicazioneAutoriTitoliSoggettiQuesta CollezioneData di pubblicazioneAutoriTitoliSoggetti

    My Account

    LoginRegistrazione

    Statistiche

    Ver Estadísticas de uso

    Compartir

    Mostra Item 
    •   RIUBU Home
    • E-Prints
    • Untitled
    • Untitled
    • Untitled
    • Mostra Item
    •   RIUBU Home
    • E-Prints
    • Untitled
    • Untitled
    • Untitled
    • Mostra Item

    Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10259/8294

    Título
    How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hypoacusia
    Autor
    Barrero Ahedo, Jesús P.Autoridad UBU Orcid
    García Herrero, SusanaAutoridad UBU Orcid
    Mariscal Saldaña, Miguel ÁngelAutoridad UBU Orcid
    Gutierrez, J. M.
    Publicado en
    Safety Science. 2018, V. 110, Part A, p. 1-12
    Editorial
    Elsevier
    Fecha de publicación
    2018-12
    ISSN
    0925-7535
    DOI
    10.1016/j.ssci.2018.07.011
    Abstract
    In this research we identify the main factors believed to trigger occupational hypoacusia in an effort to increase our knowledge of how this occupational disease occurs and develops. With this goal in mind, we have gathered various demographic/personal, occupational and non-occupational data from a heterogeneous sample of 1418 workers. The data selected include the noise levels to which the individuals in the sample are exposed. This entailed taking measurements at their respective jobs, as well as doing an objective assessment of their hearing ability, which required administering medical hearing tests. Lastly, the workers completed a survey on various habits and other factors deemed to be influential, and on the respondents’ own perception of their hearing. Bayesian networks were used to obtain the conditioned probability of developing hypoacusia based on the data collected from the sample. Specifically, for this study we used the general network created by the relationships between all of the factors associated with developing hypoacusia in order to analyze the influence individually and by grouping three specific variables: activity sector, noise level and time on the job. This work yielded a considerable database that can be used to conduct a multitude of analyses intended to study and predict the hearing acuity of the working population under different scenarios. Specifically, in the case at hand, the Bayesian network obtained indicates that the three factors analyzed influence the hearing of the individuals, though to different extents. The least influential factor involves the sector of activity, followed by the noise level on the job, which varies noticeably in favor of better hearing for workers in jobs whose noise levels are rated as low. Finally, we deemed time on the job (which is also related to age), as the most influential factor as it exhibits the largest differences among its potential states, with workers whose time on the job is rated as low or medium exhibiting the best likelihood of having good hearing.
    Materia
    Organización del trabajo
    Methods engineering
    Gestión de empresas
    Industrial management
    Salud pública
    Public health
    URI
    http://hdl.handle.net/10259/8294
    Versión del editor
    https://doi.org/10.1016/j.ssci.2018.07.011
    Aparece en las colecciones
    • Untitled
    • Untitled
    Attribution-NonCommercial-NoDerivatives 4.0 Internacional
    Documento(s) sujeto(s) a una licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional
    Files in questo item
    Nombre:
    Barrero-ss_2018.pdf
    Tamaño:
    1.043Mb
    Formato:
    Adobe PDF
    Thumbnail
    Mostra/Apri

    Métricas

    Citas

    Ver estadísticas de uso

    Exportar

    RISMendeleyRefworksZotero
    • edm
    • marc
    • xoai
    • qdc
    • ore
    • ese
    • dim
    • uketd_dc
    • oai_dc
    • etdms
    • rdf
    • mods
    • mets
    • didl
    • premis
    Mostra tutti i dati dell'item

    Universidad de Burgos

    Powered by MIT's. DSpace software, Version 5.10