<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="chan-etal-2025-prompt">
    <titleInfo>
        <title>Prompt Engineering for Capturing Dynamic Mental Health Self States from Social Media Posts</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Callum</namePart>
        <namePart type="family">Chan</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Sunveer</namePart>
        <namePart type="family">Khunkhun</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Diana</namePart>
        <namePart type="family">Inkpen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Juan</namePart>
        <namePart type="given">Antonio</namePart>
        <namePart type="family">Lossio-Ventura</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-05</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025)</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Ayah</namePart>
            <namePart type="family">Zirikly</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Andrew</namePart>
            <namePart type="family">Yates</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Bart</namePart>
            <namePart type="family">Desmet</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Molly</namePart>
            <namePart type="family">Ireland</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Steven</namePart>
            <namePart type="family">Bedrick</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sean</namePart>
            <namePart type="family">MacAvaney</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Kfir</namePart>
            <namePart type="family">Bar</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Yaakov</namePart>
            <namePart type="family">Ophir</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Albuquerque, New Mexico</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-226-8</identifier>
    </relatedItem>
    <abstract>With the advent of modern Computational Linguistic techniques and the growing societal mental health crisis, we contribute to the field of Clinical Psychology by participating in the CLPsych 2025 shared task. This paper describes the methods and results obtained by the uOttawa team’s submission (which included a researcher from the National Institutes of Health in the USA, in addition to three researchers from the University of Ottawa, Canada). The task consists of four subtasks focused on modeling longitudinal changes in social media users’ mental states and generating accurate summaries of these dynamic self-states. Through prompt engineering of a modern large language model (Llama-3.3-70B-Instruct), the uOttawa team placed first, sixth, fifth, and second, respectively, for each subtask, amongst the other submissions. This work demonstrates the capacity of modern large language models to recognize nuances in the analysis of mental states and to generate summaries through carefully crafted prompting.</abstract>
    <identifier type="citekey">chan-etal-2025-prompt</identifier>
    <identifier type="doi">10.18653/v1/2025.clpsych-1.22</identifier>
    <location>
        <url>https://aclanthology.org/2025.clpsych-1.22/</url>
    </location>
    <part>
        <date>2025-05</date>
        <extent unit="page">
            <start>256</start>
            <end>267</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T Prompt Engineering for Capturing Dynamic Mental Health Self States from Social Media Posts
%A Chan, Callum
%A Khunkhun, Sunveer
%A Inkpen, Diana
%A Lossio-Ventura, Juan Antonio
%Y Zirikly, Ayah
%Y Yates, Andrew
%Y Desmet, Bart
%Y Ireland, Molly
%Y Bedrick, Steven
%Y MacAvaney, Sean
%Y Bar, Kfir
%Y Ophir, Yaakov
%S Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025)
%D 2025
%8 May
%I Association for Computational Linguistics
%C Albuquerque, New Mexico
%@ 979-8-89176-226-8
%F chan-etal-2025-prompt
%X With the advent of modern Computational Linguistic techniques and the growing societal mental health crisis, we contribute to the field of Clinical Psychology by participating in the CLPsych 2025 shared task. This paper describes the methods and results obtained by the uOttawa team’s submission (which included a researcher from the National Institutes of Health in the USA, in addition to three researchers from the University of Ottawa, Canada). The task consists of four subtasks focused on modeling longitudinal changes in social media users’ mental states and generating accurate summaries of these dynamic self-states. Through prompt engineering of a modern large language model (Llama-3.3-70B-Instruct), the uOttawa team placed first, sixth, fifth, and second, respectively, for each subtask, amongst the other submissions. This work demonstrates the capacity of modern large language models to recognize nuances in the analysis of mental states and to generate summaries through carefully crafted prompting.
%R 10.18653/v1/2025.clpsych-1.22
%U https://aclanthology.org/2025.clpsych-1.22/
%U https://doi.org/10.18653/v1/2025.clpsych-1.22
%P 256-267

Markdown (Informal)

[Prompt Engineering for Capturing Dynamic Mental Health Self States from Social Media Posts](https://aclanthology.org/2025.clpsych-1.22/) (Chan et al., CLPsych 2025)

• Prompt Engineering for Capturing Dynamic Mental Health Self States from Social Media Posts (Chan et al., CLPsych 2025)

ACL

• Callum Chan, Sunveer Khunkhun, Diana Inkpen, and Juan Antonio Lossio-Ventura. 2025. Prompt Engineering for Capturing Dynamic Mental Health Self States from Social Media Posts. In Proceedings of the 10th Workshop on Computational Linguistics and Clinical Psychology (CLPsych 2025), pages 256–267, Albuquerque, New Mexico. Association for Computational Linguistics.