Forecasting call and chat volumes at online helplines for mental health
Bibliographic Data
| ID | 15368172 |
|---|---|
| Authors | Tim Rens de Boer (Centrum Wiskunde & Informatica, corresponding author), Saskia Mérelle (0000-0003-1748-7700, GGD Amsterdam), Sandjai Bhulai (0000-0003-1124-8821, Vrije Universiteit Amsterdam), Renske Gilissen (0000-0002-8009-6326, GGD Amsterdam), Rob van der Mei (0000-0002-5685-5310, Vrije Universiteit Amsterdam) |
| Year | 2023 |
| Volume | 23 |
| Issue | 1 |
| Pages | 984-984 |
| Publication date | 2023-05-26 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Public Health (JOURNAL) |
| Journal identifiers | ISSN: 1471-2458 • E-ISSN: 1471-2458 |
| Publisher | BioMed Central (PUBLISHER • GB) |
| DOI | 10.1186/s12889-023-15887-2 |
| PMID | 37237378 |
| OpenAlex | W4378470539 |
| Language | EN |
| References cited | 14 |
(S)ARIMA models can best be used to forecast the number of daily chats and phone calls with a MAPE of less than 10 in short-term forecasting. These models perform better than other models showing that the number of arrivals depends on historical data. These forecasts can be used as support for planning the number of counselors needed. Furthermore, the questionnaire data show that the workload experienced by senior counselors is more dependent on the number of chat arrivals and less on the number of available agents, showing the value of insight into the arrival process of conversations
Helpfulness · Hotline · Internet privacy · Mental health · Phone · Psychiatry · Public health · Staffing · Telecommunications · Workload · Applied Psychology · Computer Science · Digital Mental Health Interventions · Health disparities and outcomes · Medicine · Mental Health Research Topics · Nursing · Psychology · Social Psychology
| Highly cited | No |
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