Predicting Workers' Stress: Application of a High-Performance Algorithm Using Working-Style Characteristics.

ABSTRACT:

Background

Work characteristics, such as teleworking rate, have been studied in relation to stress. However, the use of work-related data to improve a high-performance stress prediction model that suits an individual's lifestyle has not been evaluated.

Objective

This study aims to develop a novel, high-performance algorithm to predict an employee's stress among a group of employees with similar working characteristics.

Methods

This prospective observational study evaluated participants' responses to web‑based questionnaires, including attendance records and data collected using a wearable device. Data spanning 12 weeks (between January 17, 2022, and April 10, 2022) were collected from 194 Shionogi Group employees. Participants wore the Fitbit Charge 4 wearable device,

SUBMITTER: Iwamoto H 

PROVIDER: S-EPMC11329844 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature