Evaluating the impact of mental workload on drillers' risk perception using wearable eye-tracking technology.

Drilling accidents can lead to substantial financial losses, reputational damage, and even pose serious threats to human life. Existing research indicates that most drilling incidents are related to human factors, but the influence of mental workload on drillers' risk perception in well control rema...

Full description

Bibliographic Details
Published in:Behaviour & Information Technology Vol. 45; no. 11; pp. 2660 - 2680
Main Authors: Hao, Su, Jiaxin, Jiang, Siping, Fan, Jian, Wang, Ruiying, Xie, Lifei, Xu, Xiaoqin, Wang, Xin, Qing, Yuqi, Song
Format: pictorial research tables/charts Journal Article
Published: Taylor & Francis Ltd Jul2026
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=195034169&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 195034169
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        0144929X
        B6Q
      jtl: Behaviour & Information Technology
      issn: 0144929X
      maglogo: Y
    pubinfo:
      dt: Jul2026
      vid: 45
      iid: 11
      pid: 377
      pub: Taylor & Francis Ltd
      place: Philadelphia, Pennsylvania
    artinfo:
      ui:
        195034169
        189448020
        195034169
        195034169
        10.1080/0144929X.2025.2590088
        195034169
      ppf: 2660
      ppct: 20
      formats:
      tig:
        atl: Evaluating the impact of mental workload on drillers' risk perception using wearable eye-tracking technology.
      aug:
        au:
          Hao, Su
          Jiaxin, Jiang
          Siping, Fan
          Jian, Wang
          Ruiying, Xie
          Lifei, Xu
          Xiaoqin, Wang
          Xin, Qing
          Yuqi, Song
        affil: School of Economics and Management, Southwest Petroleum University, Chengdu, People's Republic of China
      sug:
        subj:
          Blue Collar Workers Psychosocial Factors
          Attitude to Risk Evaluation
          Workload
          Mental Health
          Eye Movement Measurements
          Wearable Sensors Utilization
          Cognition Evaluation
          Human
          Female
          Male
          Young Adult
          Adult
          Middle Age
          Field Studies
          Reaction Time
          Validity
          Attention
          Paired T-Tests
          Task Performance and Analysis
          Wilcoxon Signed Rank Test
          Multiple Linear Regression
          Data Analysis Software
          Descriptive Statistics
          Funding Source
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Female
          Male
      ab: Drilling accidents can lead to substantial financial losses, reputational damage, and even pose serious threats to human life. Existing research indicates that most drilling incidents are related to human factors, but the influence of mental workload on drillers' risk perception in well control remains underexplored. To address this gap, the present study employed a Sustained Attention to Response Task (SART) paradigm and eye-tracking technology to investigate the effects of cognitive load. A total of 48 drilling workers participated in simulated monitoring tasks under low and high workload conditions. The results demonstrated that eye-tracking indicators – including fixation, saccade, and pupil diameter measures – accurately reflect variations in mental workload. Furthermore, analysis of task performance and fixation entropy revealed that increased mental workload significantly impairs drillers' ability to perceive well control risks. These findings not only support the broader application of eye-tracking technology in the oil drilling industry, but more importantly, provide a solid foundation for developing effective safety interventions and attention-guided training strategies to reduce drilling-related accidents.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N