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Development of a Mobile App for Occupational Stress Screening Among Female Workers: Protocol for an Exploratory
Dini Widianti1,2, Zwasta Pribadi Mahardhika1, Robiana Modjo2
1Faculty of Medicine, YARSI University, Jakarta Pusat, Indonesia.
Background:
Occupational safety hazards include physical, chemical, ergonomic, biological, and psychological hazards. Technological innovation in screening for occupational stress, especially among female workers, is needed to improve their health and productivity.
Objective:
This research is being conducted to obtain a prediction model of work stress through a questionnaire instrument that includes stressors and symptoms based on the transactional model, as well as measurement of work stress through a mobile app that can be used anywhere.
Methods:
The research is conducted in 3 stages: qualitative research, quantitative research (cross-sectional), and mobile app development. Data were collected from companies located in Jakarta, Indonesia. The sample was chosen based on purposive sampling. For the quantitative research (n=430), logistic regression analysis was used.
Results:
We are developing a work stress screening instrument for female workers, which includes stressors and symptoms based on the transactional model, in the form of a digital platform so that female workers can undertake the examination anywhere without interfering with working hours or home duties. This research was funded in January 2024 and qualitative data collection began in February 2024. Quantitative data were obtained in March 2024; the number of respondents in the qualitative stage was 6, and in the quantitative stage it was 430. The work stress screening app is in the development stage and will be launched at the same time as the data collection is performed so we can examine the respondents' perspectives on the use of the app.
Conclusions:
This study analyzes the prediction of work stress to help female workers screen for work stress. Workers who are detected as experiencing work stress will be educated using an algorithm programmed in the app.
International Registered Report Identifier (Irrid):
PRR1-10.2196/55874.
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