Tell Me About Yourself

Xiao, Ziang; Zhou, Michelle X.; Liao, Q. Vera; Mark, Gloria; Chi, Changyan; Chen, Wenxi; Yang, Huahai

doi:10.1145/3381804

Cited by 108 publications

(39 citation statements)

References 73 publications

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“…Responses range from 0 (not at all) to 3 (nearly every day). Total scores are divided into five categories: none (0-4), mild (5-9), moderate (10-14), moderately severe (15)(16)(17)(18)(19), and severe (20+) symptoms [6].…”

Section: Mental Health Outcomesmentioning

confidence: 99%

“…Responses range from 0 (did not apply) to 3 (applied very much or most of the time). Total scores are doubled and divided into five categories: normal (0-14), mild (15)(16)(17)(18), moderate (19)(20)(21)(22)(23)(24)(25), severe (26)(27)(28)(29)(30)(31)(32)(33), and extremely severe (34+) levels of stress [7].…”

Section: Mental Health Outcomesmentioning

confidence: 99%

“…Responses range from 0 (no problem) to 4 (very severe problem). Total scores are categorized as: absence (0-7), subthreshold (8)(9)(10)(11)(12)(13)(14), moderate (15)(16)(17)(18)(19)(20)(21), and severe (22-28) insomnia [28].…”

Section: Mental Health Outcomesmentioning

confidence: 99%

“…Chatbot-driven conversational surveys could offer an alternative by automating this encouragement and interaction. Chatbots have been shown to have significantly greater engagement and higher-quality responses than typical online surveys [16,17], and the relative anonymity offered by such an approach could be of additional value to employees.…”

Section: Introductionmentioning

confidence: 99%

“…This has the potential to enhance engagement rates, using the chatbot to successfully guide and motivate users. Compared to typical online surveys, this may result in a higher level of engagement [16] and greater symptom disclosure [17]. However, to our knowledge, no system of this nature currently exists for assessing workplace mental health in Brazil.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Chatbot-Based Assessment of Employees’ Mental Health: Design Process and Pilot Implementation

Hungerbuehler¹,

Daley²,

Cavanagh³

et al. 2021

JMIR Form Res

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Background Stress, burnout, and mental health problems such as depression and anxiety are common, and can significantly impact 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 approach to achieve 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. Objective The aim of this study was to explore if a text-based chatbot is a feasible approach to engage and motivate employees to complete a workplace mental health assessment. This paper describes the design process and results of a pilot implementation. Methods A fully automated chatbot (“Viki”) was developed to evaluate employee risks of suffering from depression, anxiety, stress, insomnia, burnout, and work-related stress. Viki uses a conversation style and gamification features to enhance engagement. A cross-sectional analysis was performed to gain first insights of a pilot implementation within a small to medium–sized enterprise (120 employees). Results The response rate was 64.2% (77/120). In total, 98 employees started the assessment, 77 of whom (79%) completed it. The majority of participants scored in the mild range for anxiety (20/40, 50%) and depression (16/28, 57%), in the moderate range for stress (10/22, 46%), and at the subthreshold level for insomnia (14/20, 70%) as defined by their questionnaire scores. Conclusions 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 those of face-to-face interviews.

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