Work readiness during COVID-19 among taxibike online drivers in Samarinda, Indonesia

Setyowati, Dina Lusiana; Paramita, Swandari; Ifroh, Riza Hayati; Asrianti, Tanti; Fitriani, Efi; Rahman, Wahnadita

doi:10.11591/ijphs.v10i3.20870

Cited by 4 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These cases were mainly contracted at community places. Likewise, studies by Setyowati et al [31] found that the impact of COVID-19 on the informal business sector, including online motorcycle taxi drivers, affects efforts to control the spread of the disease. Kshirsagar et al [32] highlight the pandemic's impact on workplace learning and businesses, while Furuse et al [33] identified 22 probable primary case-patients for the clusters, most of whom were 20-39 years of age and presymptomatic or asymptomatic at virus transmission.…”

Section: Discussionmentioning

confidence: 99%

Data modeling COVID-19 patients in Thailand: data mining techniques

Pansayta,

Chansanam

2023

IJPHS

View full text Add to dashboard Cite

This study aimed to investigate the characteristics of COVID-19 patients in Thailand and develop a data model for analyzing these characteristics. A total of 1,888,941 cases from the Thailand Department of Disease Control website from January 12, 2020, to October 29, 2021, were analyzed, and 20,110 cases were selected for further analysis. The two-step cluster analysis method was used to cluster the data according to four variables: nationality, occupation, patient type, and risk groups. The results showed the presence of three groups of COVID-19 patients. Group 1 consisted of 5,883 workers in trade and service occupations who had contact with the public and were either Thai nationals or from abroad. Group 2 was the largest cluster, consisting of 7,420 migrant workers classified as foreigners and working in industrial settings. Group 3 consisted of 6,870 cases of indirect transmission, with individuals in this group infected through close contact with family members or individuals in the first two groups. This clustering approach offers valuable insights for pandemic management, aiding in identifying high-risk groups and developing tailored interventions. In future outbreaks with similar characteristics, such as airborne transmission, contact infection, or super spreader events, our model can serve as a valuable tool for devising effective management plans and countermeasures. In conclusion, this study emphasizes the significance of cluster analysis in understanding the dynamics of COVID-19 transmission and highlights its potential for informing effective pandemic management strategies. It also outlines promising avenues for further research to enhance our knowledge of COVID-19's impact on specific populations and inform future public health efforts.

show abstract

Section: Discussionmentioning

confidence: 99%

Data modeling COVID-19 patients in Thailand: data mining techniques

Pansayta,

Chansanam

2023

IJPHS

View full text Add to dashboard Cite

show abstract

“…Drivers who slept less than that time will feel less refreshed and are more at risk of experiencing fatigue at work Quamilla and Martiana (2022). The amount of sleep duration is needed so that it can be useful for optimizing the performance of online motorcycle taxi drivers (Setyowati et al, 2021). Several factors could influence sleep duration, including the length of work, which causes online taxi bike drivers to need more sleep (Manuel and Wirawan, 2020).…”

Section: Discussionmentioning

confidence: 99%

Relationship Between Work Duration, Length of Work, and Sleep Duration With Work Fatigue Among Online Taxi Bike Drivers in Greater Jakarta

Surury,

Aisya Alawiyah,

Fitri Anggraeni

et al. 2024

J Vocat Heal Stud

View full text Add to dashboard Cite

Background: Online taxi bike drivers were part of the road users vulnerable to accidents due to a demand that required online taxi bike drivers to work on the highway. Work duration, length of work, and sleep duration could cause the fatigue experienced by online taxi bike drivers. Purpose: See the strength of the relationship between work duration, length of work, sleep duration and work fatigue among online taxi bike drivers in Greater Jakarta. Method: This study was observational with a cross-sectional design involving as many as 52 online taxi bike drivers selected by non-probability sampling from online taxi bike drivers in Greater Jakarta from the end of November 2022 to early December 2022. Result: The majority of respondents (84.6%) were under 40 years old, male (92.3%), worked more than eight hours a day (55.8%), had experience as online taxi bike drivers for more than 3 years (73.1%), sleep duration less than 8 hours (78.8%), and there were 36 online taxi bike drivers (69.2%) reported experiencing high-very high levels of fatigue. The work duration is significantly related to work fatigue (p-value = 0.002). Also, there was no significant relationship between the length of work (p-value = 0.268) and sleep duration (p-value = 0.058) with work fatigue. Conclusion: There was a significant relationship between work duration and work fatigue, and there was no significant relationship between the length of work and sleep duration with work fatigue. The taxi drivers with work duration >8 hours, length of work >3 years, and sleep duration <8 hours had higher risk factors for work fatigue. If a taxi bike driver works more than 8 hours daily, it is advisable to compensate with adequate rest.

show abstract

“…The fast-paced advancement of information technology has left a considerable imprint on every individual within society, extending its influence even to healthcare [1]. The COVID-19 pandemic that has spread worldwide has affected various aspects of life, including social structure, economics, and education [2], [3]. The use of technology is an alternative to continue carrying out life activities according to established health protocols to prevent the chain of transmission of the coronavirus.…”

Section: Introductionmentioning

confidence: 99%

Analysis of digital literacy development to improve skills, competence, and self-confidence in students

Budi,

Putri

2024

IJPHS

View full text Add to dashboard Cite

Education is an essential aspect of human resource development. Additional learning facilities in the form of patient acceptance digital literacy are needed to improve students' skills and competencies before carrying out work practices. This study aimed to analyze the need for developing digital literacy in patient admission applications in health services. This investigation adopts a qualitative research methodology characterized by an exploratory perspective. Data gathering encompassed conducting interviews, observations, and reviewing documentary materials. Digital literacy patient acceptance of applications needs to be developed immediately to support the preparation for practical work activities. Things that need to be designed to create digital literacy are the function features provided, the display of the dashboard menu, and the material the participants must master. This research was successful in helping to collect the data needed to develop digital literacy in patient admission applications in health services. This research is expected to offer insights that can be valuable for future studies focused on enhancing digital literacy through characteristics, interfaces, and learning materials.

show abstract

Work readiness during COVID-19 among taxibike online drivers in Samarinda, Indonesia

Cited by 4 publications

References 16 publications

Data modeling COVID-19 patients in Thailand: data mining techniques

Data modeling COVID-19 patients in Thailand: data mining techniques

Relationship Between Work Duration, Length of Work, and Sleep Duration With Work Fatigue Among Online Taxi Bike Drivers in Greater Jakarta

Analysis of digital literacy development to improve skills, competence, and self-confidence in students

Contact Info

Product

Resources

About