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An overview of the features of chatbots in mental health : a scoping review
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Abd-alrazaq, Alaa A., Alajlani, Mohannad, Alalwan, Ali Abdallah, Bewick, Bridgette M., Gardner, Peter and Househ, Mowafa (2019) An overview of the features of chatbots in mental health : a scoping review. International Journal of Medical Informatics, 132 . 103978. doi:10.1016/j.ijmedinf.2019.103978 ISSN 1386-5056.
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Official URL: https://doi.org/10.1016/j.ijmedinf.2019.103978
Abstract
Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual languages. Chatbots have the potential to be useful tools for individuals with mental disorders, especially those who are reluctant to seek mental health advice due to stigmatization. While numerous studies have been conducted about using chatbots for mental health, there is a need to systematically bring this evidence together in order to inform mental health providers and potential users about the main features of chatbots and their potential uses, and to inform future research about the main gaps of the previous literature.
Objective
We aimed to provide an overview of the features of chatbots used by individuals for their mental health as reported in the empirical literature.
Methods
Seven bibliographic databases (Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, IEEE Xplore, ACM Digital Library, and Google Scholar) were used in our search. In addition, backward and forward reference list checking of the included studies and relevant reviews was conducted. Study selection and data extraction were carried out by two reviewers independently. Extracted data were synthesised using a narrative approach. Chatbots were classified according to their purposes, platforms, response generation, dialogue initiative, input and output modalities, embodiment, and targeted disorders.
Results
Of 1039 citations retrieved, 53 unique studies were included in this review. The included studies assessed 41 different chatbots. Common uses of chatbots were: therapy (n = 17), training (n = 12), and screening (n = 10). Chatbots in most studies were rule-based (n = 49) and implemented in stand-alone software (n = 37). In 46 studies, chatbots controlled and led the conversations. While the most frequently used input modality was written language only (n = 26), the most frequently used output modality was a combination of written, spoken and visual languages (n = 28). In the majority of studies, chatbots included virtual representations (n = 44). The most common focus of chatbots was depression (n = 16) or autism (n = 10).
Conclusion
Research regarding chatbots in mental health is nascent. There are numerous chatbots that are used for various mental disorders and purposes. Healthcare providers should compare chatbots found in this review to help guide potential users to the most appropriate chatbot to support their mental health needs. More reviews are needed to summarise the evidence regarding the effectiveness and acceptability of chatbots in mental health.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
SWORD Depositor: | Library Publications Router | ||||||||
Journal or Publication Title: | International Journal of Medical Informatics | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 1386-5056 | ||||||||
Official Date: | December 2019 | ||||||||
Dates: |
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Volume: | 132 | ||||||||
Article Number: | 103978 | ||||||||
DOI: | 10.1016/j.ijmedinf.2019.103978 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Reuse Statement (publisher, data, author rights): | ** Article version: AM ** Embargo end date: 14-10-2020 ** From Elsevier via Jisc Publications Router ** History: accepted 22-09-2019; epub 14-10-2019; issue date 31-12-2019. ** Licence for AM version of this article starting on 14-10-2020: http://creativecommons.org/licenses/by-nc-nd/4.0/ | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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