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Artha, Dian Parama
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Nursing Public Health

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Individual characteristics, psychosocial factors, and sleep quality with work fatigue among technical service employees in the National Electricity Company, Bantul Artha, Dian Parama; Surono, Agus; Pribadi, Ari Prayogo
BKM Public Health and Community Medicine Vol 40 No 08 (2024)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/bkm.v40i08.12749

Abstract

Purpose: This study aims to determine the relationship between individual characteristic factors, psychosocial factors, and sleep quality on work fatigue among Yantek employees at National Electricity Company (PLN), Unit (ULP) Bantul. Methods: The method used in this study is a quantitative method with a cross-sectional design. The population in this study used a total sample of 55. The research instruments used the IFRC, COPSOQ III, and PSQI. Data analysis uses univariate tests, chi-square tests, and field observations. Results: Work fatigue among Yantek employees was categorized as mild in 47.27%, moderate in 40%, and severe in 12.73%. There was a significant relationship between individual characteristics such as age (<0.001), water consumption (0.004), smoking status (0.008), exercise habits (0.005), shift work (0.003), and work duration (<0.001). There was a significant relationship between psychosocial factors and work fatigue in the demand domain in the workplace (0.003), content and job organization (0.003), interpersonal relationships and leadership (0.007), and individual and job interactions (0.003). There was a significant relationship between sleep quality (p = 0.001) and work fatigue. Conclusion: Individual characteristics were associated with work fatigue. Psychosocial factors were associated with work fatigue. Sleep quality also had a significant relationship with work fatigue.
Overview of Chatbot Usage on Mental Health: A Scoping Review Permatasari, Ririn Indah; Artha, Dian Parama; Wiratama, Bayu Satria; Wulandari, Hanifah
BKM Public Health and Community Medicine The 12th UGM Public Health Symposium
Publisher : Universitas Gadjah Mada

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Abstract

Purpose: Mental disorders are the second leading global health burden among adolescents (15-19 years) and the third among adults (20-39 years). One approach to mitigate the medical and socio-economic impacts of mental disorders is the use of digital health technology, including chatbots. Methods: This study aimed to map mental health chatbot technology use through a scoping review. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extensions for Scoping Reviews (PRISMA-ScR) guidelines and involved PubMed, Scopus, ScienceDirect, and Google Scholar searches. The studies were categorized by type of usage, including acceptability, effectiveness, usability, adoption, and features. Study selection was assisted by Rayyan, and data extraction used a narrative approach. Results: Out of 172 research articles, 21 met the inclusion criteria and evaluated the use of mental health chatbots. Most chatbots were standalone applications (10/21). Adults (11/21) and university students (6/21) were the primary populations for testing chatbot usage. The most common mental health issues targeted by chatbots were anxiety, depression, and stress, although the focus was generally ideal for a range of mental health conditions. Conclusion: Numerous chatbots have been used for various mental health disorders, serving multiple purposes such as prevention, training, and therapy. Most applications combine these functions. Further research is needed to understand the changes that occur following mental health chatbot interventions.
Co-Authors Agus Surono Ari Prayogo Pribadi Bayu Satria Wiratama Permatasari, Ririn Indah Wulandari, Hanifah