@inproceedings{lynn-etal-2018-clpsych,
title = "{CLP}sych 2018 Shared Task: Predicting Current and Future Psychological Health from Childhood Essays",
author = "Lynn, Veronica and
Goodman, Alissa and
Niederhoffer, Kate and
Loveys, Kate and
Resnik, Philip and
Schwartz, H. Andrew",
editor = "Loveys, Kate and
Niederhoffer, Kate and
Prud{'}hommeaux, Emily and
Resnik, Rebecca and
Resnik, Philip",
booktitle = "Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic",
month = jun,
year = "2018",
address = "New Orleans, LA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W18-0604",
doi = "10.18653/v1/W18-0604",
pages = "37--46",
abstract = "We describe the shared task for the CLPsych 2018 workshop, which focused on predicting current and future psychological health from an essay authored in childhood. Language-based predictions of a person{'}s current health have the potential to supplement traditional psychological assessment such as questionnaires, improving intake risk measurement and monitoring. Predictions of future psychological health can aid with both early detection and the development of preventative care. Research into the mental health trajectory of people, beginning from their childhood, has thus far been an area of little work within the NLP community. This shared task represents one of the first attempts to evaluate the use of early language to predict future health; this has the potential to support a wide variety of clinical health care tasks, from early assessment of lifetime risk for mental health problems, to optimal timing for targeted interventions aimed at both prevention and treatment.",
}
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%0 Conference Proceedings
%T CLPsych 2018 Shared Task: Predicting Current and Future Psychological Health from Childhood Essays
%A Lynn, Veronica
%A Goodman, Alissa
%A Niederhoffer, Kate
%A Loveys, Kate
%A Resnik, Philip
%A Schwartz, H. Andrew
%Y Loveys, Kate
%Y Niederhoffer, Kate
%Y Prud’hommeaux, Emily
%Y Resnik, Rebecca
%Y Resnik, Philip
%S Proceedings of the Fifth Workshop on Computational Linguistics and Clinical Psychology: From Keyboard to Clinic
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, LA
%F lynn-etal-2018-clpsych
%X We describe the shared task for the CLPsych 2018 workshop, which focused on predicting current and future psychological health from an essay authored in childhood. Language-based predictions of a person’s current health have the potential to supplement traditional psychological assessment such as questionnaires, improving intake risk measurement and monitoring. Predictions of future psychological health can aid with both early detection and the development of preventative care. Research into the mental health trajectory of people, beginning from their childhood, has thus far been an area of little work within the NLP community. This shared task represents one of the first attempts to evaluate the use of early language to predict future health; this has the potential to support a wide variety of clinical health care tasks, from early assessment of lifetime risk for mental health problems, to optimal timing for targeted interventions aimed at both prevention and treatment.
%R 10.18653/v1/W18-0604
%U https://aclanthology.org/W18-0604
%U https://doi.org/10.18653/v1/W18-0604
%P 37-46
Markdown (Informal)
[CLPsych 2018 Shared Task: Predicting Current and Future Psychological Health from Childhood Essays](https://aclanthology.org/W18-0604) (Lynn et al., CLPsych 2018)
ACL