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A Call Center Model for Online Mental Health Support

Authors:
Tim Rens de Boer
Saskia Mérelle
Sandjai Bhulai
Rob van der Mei

Keywords: call center models; queueing; mental health; helplines; data analytics; forecasting

Abstract:
Helplines for mental healthcare differ from other call centers in various aspects. Many agents are volunteers, the conversations are often more complex and emotional, and many helplines use a triage system. In this paper, we first propose a call center model that includes the specifics of online mental health helplines, including features such as a triage system for chats and service times consisting of a warm-up, conversation, and wrap-up cool-down periods. The model is validated using a trace-driven simulation based on real-life (anonymous) data provided by 113 Suicide Prevention. The results show that the model can simulate the waiting-time performance of the helpline accurately. Second, we focus on forecasting the number of chats and telephone calls. Our results show that (Seasonal) Autoregressive Integrated Moving Average ((S)ARIMA) models trained on historical data perform better than other models in the case of short-term forecasting (five weeks or less ahead), while using linear regression works best for long-term forecasts (longer than five weeks).

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2022

Publication date: July 24, 2022

Published in: conference

ISBN: 978-1-68558-019-3

Location: Nice, France

Dates: from July 24, 2022 to July 28, 2022