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Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth
Digital platforms for mental health and wellbeing purposes have become increasingly common to help users exhibiting risk behaviours (e.g. self-harming, eating-related disorders) across all ages, opening new frontiers in supporting vulnerable users. This study stems from a larger project, which explo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522450/ https://www.ncbi.nlm.nih.gov/pubmed/36196212 http://dx.doi.org/10.1007/s43545-022-00532-3 |
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author | Nichele, Elena Lavorgna, Anita Middleton, Stuart E. |
author_facet | Nichele, Elena Lavorgna, Anita Middleton, Stuart E. |
author_sort | Nichele, Elena |
collection | PubMed |
description | Digital platforms for mental health and wellbeing purposes have become increasingly common to help users exhibiting risk behaviours (e.g. self-harming, eating-related disorders) across all ages, opening new frontiers in supporting vulnerable users. This study stems from a larger project, which explores how responsible AI solutions can up-scale existing manual moderation approaches and better target interventions for young people who ask for help or engage in risk behaviours online. This research aims to better understand the challenges and needs of moderators and digital counsellors, i.e. the ‘behind the scenes’. Through this case study, the authors intend to contribute to the development of responsible AI tools that are fit for purpose and better understand the challenges. The key focus lies on Kooth.com, the UK’s leading free online confidential service offering counselling and emotional wellbeing support to young people in the UK through its online web-based and pseudo-anonymous digital platform. |
format | Online Article Text |
id | pubmed-9522450 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-95224502022-09-30 Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth Nichele, Elena Lavorgna, Anita Middleton, Stuart E. SN Soc Sci Original Paper Digital platforms for mental health and wellbeing purposes have become increasingly common to help users exhibiting risk behaviours (e.g. self-harming, eating-related disorders) across all ages, opening new frontiers in supporting vulnerable users. This study stems from a larger project, which explores how responsible AI solutions can up-scale existing manual moderation approaches and better target interventions for young people who ask for help or engage in risk behaviours online. This research aims to better understand the challenges and needs of moderators and digital counsellors, i.e. the ‘behind the scenes’. Through this case study, the authors intend to contribute to the development of responsible AI tools that are fit for purpose and better understand the challenges. The key focus lies on Kooth.com, the UK’s leading free online confidential service offering counselling and emotional wellbeing support to young people in the UK through its online web-based and pseudo-anonymous digital platform. Springer International Publishing 2022-09-29 2022 /pmc/articles/PMC9522450/ /pubmed/36196212 http://dx.doi.org/10.1007/s43545-022-00532-3 Text en © The Author(s) 2022, corrected publication, 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Nichele, Elena Lavorgna, Anita Middleton, Stuart E. Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title | Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title_full | Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title_fullStr | Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title_full_unstemmed | Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title_short | Identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible AI tools: the case study of Kooth |
title_sort | identifying key challenges and needs in digital mental health moderation practices supporting users exhibiting risk behaviours to develop responsible ai tools: the case study of kooth |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522450/ https://www.ncbi.nlm.nih.gov/pubmed/36196212 http://dx.doi.org/10.1007/s43545-022-00532-3 |
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