<?xml version="1.0" encoding="UTF-8"?>
<ArticleSet>
  <Article>
    <Journal>
      <PublisherName></PublisherName>
      <JournalTitle>Future of Work and Digital Management Journal</JournalTitle>
      <Issn></Issn>
      <Volume>2</Volume>
      <Issue>Serial Number 4</Issue>
      <PubDate PubStatus="epublish">
        <Year>2024</Year>
        <Month>04</Month>
        <Day>01</Day>
      </PubDate>
    </Journal>
    <ArticleTitle>Digital Monitoring and Burnout: The Mediating Role of Perceived Control</ArticleTitle>
    <VernacularTitle>Digital Monitoring and Burnout: The Mediating Role of Perceived Control</VernacularTitle>
    <FirstPage>43</FirstPage>
    <LastPage>52</LastPage>
    <Language>EN</Language>
    <AuthorList>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
      <Author>
        <FirstName></FirstName>
        <LastName></LastName>
        <Affiliation></Affiliation>
      </Author>
    </AuthorList>
    <PublicationType>Journal Article</PublicationType>
    <History>
      <PubDate PubStatus="received">
        <Year>2024</Year>
        <Month>02</Month>
        <Day>21</Day>
      </PubDate>
    </History>
    <Abstract>&lt;table&gt;&#13;
&lt;tbody&gt;&#13;
&lt;tr&gt;&#13;
&lt;td&gt;&#13;
&lt;p&gt;This study aimed to investigate the relationship between digital monitoring and employee burnout, examining the mediating role of perceived control in this association. A descriptive-correlational design was employed with a sample of 285 full-time employees from various sectors. Participants completed three standardized instruments: the Electronic Monitoring and Surveillance Scale (EMSS) for digital monitoring, the Pearlin Mastery Scale (PMS) for perceived control, and the Maslach Burnout Inventory (MBI) for burnout. Data were analyzed using Pearson correlation, structural equation modeling (SEM), and mediation analysis in SPSS-27 and AMOS-24. The goodness-of-fit indices were used to evaluate the model’s fit, including χ²/df, GFI, AGFI, CFI, TLI, and RMSEA. Inferential analysis revealed that digital monitoring was positively associated with burnout (β = 0.34, p &amp;lt; .001) and negatively associated with perceived control (β = −0.31, p &amp;lt; .001). Perceived control was significantly negatively associated with burnout (β = −0.43, p &amp;lt; .001). Mediation analysis indicated a significant indirect effect of digital monitoring on burnout through perceived control (β = 0.13, p = .001), and the total effect of digital monitoring on burnout was significant (β = 0.47, p &amp;lt; .001). Model fit indices confirmed good model fit (χ²/df = 2.05, GFI = 0.94, AGFI = 0.91, CFI = 0.96, TLI = 0.95, RMSEA = 0.061). The findings suggest that digital monitoring contributes to higher levels of employee burnout both directly and indirectly by reducing perceived control. Perceived control plays a protective, mediating role and should be considered a crucial psychological factor when designing and implementing monitoring technologies in the workplace.&lt;/p&gt;&#13;
&lt;/td&gt;&#13;
&lt;/tr&gt;&#13;
&lt;/tbody&gt;&#13;
&lt;/table&gt;</Abstract>
    <ObjectList>
      <Object Type="keyword">
        <Param Name="value">Digital monitoring</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Burnout</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Perceived control</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Workplace surveillance</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Structural equation modeling</Param>
      </Object>
      <Object Type="keyword">
        <Param Name="value">Occupational stress</Param>
      </Object>
    </ObjectList>
    <ArchiveCopySource DocType="pdf">https://www.journalfwdmj.com/index.php/fwdmj/article/download/30/32</ArchiveCopySource>
  </Article>
</ArticleSet>
