Currently submitted to: JMIR Formative Research
Date Submitted: Jun 21, 2020
Open Peer Review Period: Jun 21, 2020 - Jul 17, 2020
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A chatbot-based assessment of employees' mental health: Design process and pilot implementation
Stress, burnout and mental health problems, such as depression and anxiety are common and can significantly impact on workplaces through absenteeism and reduced productivity. To address this issue, organizations must first understand the extent of the difficulties by mapping the mental health of their workforce. Online surveys are a cost-effective and scalable way to do this but typically have low response rates, in part due to a lack of interactivity. Chatbots offer one potential solution, enhancing engagement through simulated natural human conversation and use of interactive features.
To describe the design process and results of a pilot implementation of a chatbot-based assessment of employee mental health within the workplace.
A fully automated and intelligent chatbot (‘Viki’) was developed to evaluate employee risks of suffering from depression (PHQ-9), anxiety (GAD-7), stress (DASS-21), insomnia (ISI), burnout (OLBI) and work-related stressors (JSS). The chatbot uses a conversation style and gamification features including story/theme and feedback to enhance engagement. The chatbot was implemented within a small to medium-sized enterprise (SME) (N=120) in a cross-sectional study.
In total, 98 (82%) employees started the assessment, and 77 (79%) completed it. The majority of employees (54/77, 70%) reported a high risk of suffering from work-related stress. Over one-third (26/77, 34%) reported a high risk of suffering from burnout, 21 (27%) from anxiety, 14 (18%) from general stress, 12 (16%) from depression and 7 (9%) from insomnia. Depression, anxiety, and insomnia were strongly correlated with a measure of presenteeism (r between 0.8 and 0.9).
A chatbot-based workplace mental health assessment seems to be a highly engaging and effective way to collect anonymized mental health data among employees with response rates comparable to face-to-face interviews. Clinical Trial: N/A
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