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Towards a chatbot for digital counselling

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TLDR
The aim of this paper is to outline the design of a chatbot to be used within mental health counselling, able to provide initial counselling, and lead users into the correct services or self-help information.
Abstract
The aim of this paper is to outline the design of a chatbot to be used within mental health counselling. One of the main causes of the burden of disease worldwide is mental health problems. Mental health contributes to 28% of the total burden of disease, compared to 16% each for cancer and heart disease in the UK. Stress, anxiety or depression accounted for 15.8 million days of sickness absence across the UK in 2016. By 2020, the gap between the demand for mental health care and the resources the National Health Service (NHS) can provide is likely to widen, therefore providers are increasingly needing to find more cost-effective ways to deliver mental health care. Digital Interventions have been created to help with these issues, for example anxiety, stress and depression. Chatbots can be incorporated into digital interventions, or used as standalone interventions. Chatbots can be a more interactive experience for the user to receive information, or complete diagnostic tools, or to even be used for counselling. A demo chatbot was created using interactive emoji’s and GIFs to improve the user experience when searching for online self-help tips. This chatbot will be further developed and incorporated into a full web based programme for mental health in the workplace. It is envisaged that the chatbot will be able to provide initial counselling, and lead users into the correct services or self-help information.

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Citations
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Securing Our Future Health: Taking a Long-Term View. The Health Service in 2022

Wanless D
TL;DR: The Wanless Report concludes that in order to meet peopleâ?Ts expectations and to deliver the highest quality over the next 20 years, the UK will need to devote more resources to health care and that this must be matched by reform to ensure that these resources are used effectively.
Journal ArticleDOI

Using Health Chatbots for Behavior Change: A Mapping Study

TL;DR: This study conducts a mapping study to survey the landscape of health chatbots along three research questions: What illnesses are chatbots tackling?
Proceedings ArticleDOI

Comparing Data from Chatbot and Web Surveys: Effects of Platform and Conversational Style on Survey Response Quality

TL;DR: It was found that the participants in the chatbot survey, as compared to those in the web survey, were more likely to produce differentiated responses and were less likely to satisfice; the chat bot survey thus resulted in higher-quality data.
Proceedings ArticleDOI

Usability testing of a healthcare chatbot: Can we use conventional methods to assess conversational user interfaces?

TL;DR: Usability test outcomes confirm what is already known about chatbots - that they are highly usable but conventional methods for assessing usability and user experience may not be as accurate when applied to chatbots.
References
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Journal ArticleDOI

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

Theo Vos, +778 more
- 16 Sep 2017 - 
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
Book

Computer Power and Human Reason

TL;DR: The book mentions some important concerns which are obscured by harsh and sometimes shrill accusations against the Artificial Intelligence research community, but it seems to me that the personal attacks distract and mislead the reader from more valuable abstract points.
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