Unraveling the Work-Related Distress Profiles of Election Officers in Yogyakarta: Lessons Learned from the 2019 General Election

Rizqi Nur'aini A'yuninnisa; Acintya Ratna Priwati; Ramadhan Dwi Marvianto; Fuad Hamsyah; Faturochman Faturochman

doi:10.22146/jpsi.89858

Unraveling the Work-Related Distress Profiles of Election Officers in Yogyakarta: Lessons Learned from the 2019 General Election

Rizqi Nur'aini A'yuninnisa, Acintya Ratna Priwati, Ramadhan Dwi Marvianto, Fuad Hamsyah, Faturochman Faturochman

(Submitted 16 October 2023)

(Published 28 December 2023)

Abstract

Drawing from the 2019 electoral incident, this study seeks to comprehend election officials’ working context, providing insights for the forthcoming 2024 general election (Pemilu). Specifically, this study investigates the working conditions of election officials during Indonesia's 2019 general election by examining their job demands, job resources, psychological and physical stress responses. Utilizing the job demands-resources (JD-R) model, the study evaluated the job demands, job resources, psychological and physical stress responses of 212 election officials in Yogyakarta Province using part of The New Brief Job Stress Questionnaire (NBJSQ). Latent Class Analysis revealed three distinct class profiles among the 2019 election officials based on their JD-R model scores, which included job demands, job resources, psychological and physical stress responses. The majority of participants fell into class 2, characterized by high job demands and job resources but low stress reactions. In contrast, class 1 had low job demands and job resources but a high level of stress, while class 3 exhibited high job demands, low job resources, and low stress. These results indicate that high job demand and job resources can potentially lead to work-related stress, although this relationship is influenced by the specific context and nature of job demands and job resources.

Keywords

National election (Pemilu) 2019; job demands; job resources; work-related stress; latent class analysis

Full Text: PDF

DOI: 10.22146/jpsi.89858

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