@inproceedings{du-etal-2026-maps,
title = "{MAPS}: Robot-Mediated Multimodal Mental Health Screening for {C}hinese Adolescents",
author = "Du, Zhicheng and
Liu, Yang and
Chen, Zheng and
Deng, Zhuo and
Xie, Zhaotian and
Xi, Wenji and
Yuan, Xi and
Liang, Zhen and
Yu, Dongmei and
Yan, Chenggang and
Ji, Jiansong and
Qin, Peiwu and
Chen, Zhenglin and
Ma, Lan",
editor = "Wang, Zimu and
Jiang, Yiwen and
Shen, Yaling and
Zhao, Xiangyu and
Fong, Stephanie and
Sun, Xin and
Zhou, Yi and
Ji, Shaoxiong and
Desimone, Robert and
Nelson, Barnaby and
Dwyer, Dominic and
Ge, Zongyuan",
booktitle = "Proceedings of the 1st Workshop on Multimodal, Multilingual, and Multicultural Mental Health and Psychotherapy ({M}ulti{P}syche)",
month = nov,
year = "2026",
address = "Hengqin, Zhuhai, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.multipsyche-1.7/",
pages = "69--79",
ISBN = "979-8-89176-448-4",
abstract = "We present an initial study of robot-mediated multimodal mental-health screening for Chinese adolescents aged 12{--}15. MAPS (Multimodal Adolescent Psychological Screening) combines facial, acoustic, textual, and remotely estimated physiological signals collected through a standardized protocol of questionnaires, emotionally evocative tasks, and question answering. From 3,783 participants, 968 records were retained after consent, completeness, and quality-control filtering. We introduce GAME (Generalized Model with Attention and Multimodal EmbraceNet), a fusion model combining eight unimodal representations with relation-graph and attention features. Separate models are trained for 12 questionnaire- and expert-derived screening targets. Stratified 10-fold cross-validation yields 73.04{--}92.77{\%} accuracy and 71.32{--}91.06{\%} weighted F1. Feature ablations and descriptive contribution analyses suggest that representation use varies across targets. This initial study connects a portable interaction protocol with task-specific multimodal modeling in a Chinese school setting and provides a basis for further research on screening-label prediction. Future work will expand data collection, refine the fusion and training procedures, and evaluate generalization and screening utility through external and clinically supervised validation."
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<abstract>We present an initial study of robot-mediated multimodal mental-health screening for Chinese adolescents aged 12–15. MAPS (Multimodal Adolescent Psychological Screening) combines facial, acoustic, textual, and remotely estimated physiological signals collected through a standardized protocol of questionnaires, emotionally evocative tasks, and question answering. From 3,783 participants, 968 records were retained after consent, completeness, and quality-control filtering. We introduce GAME (Generalized Model with Attention and Multimodal EmbraceNet), a fusion model combining eight unimodal representations with relation-graph and attention features. Separate models are trained for 12 questionnaire- and expert-derived screening targets. Stratified 10-fold cross-validation yields 73.04–92.77% accuracy and 71.32–91.06% weighted F1. Feature ablations and descriptive contribution analyses suggest that representation use varies across targets. This initial study connects a portable interaction protocol with task-specific multimodal modeling in a Chinese school setting and provides a basis for further research on screening-label prediction. Future work will expand data collection, refine the fusion and training procedures, and evaluate generalization and screening utility through external and clinically supervised validation.</abstract>
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%0 Conference Proceedings
%T MAPS: Robot-Mediated Multimodal Mental Health Screening for Chinese Adolescents
%A Du, Zhicheng
%A Liu, Yang
%A Chen, Zheng
%A Deng, Zhuo
%A Xie, Zhaotian
%A Xi, Wenji
%A Yuan, Xi
%A Liang, Zhen
%A Yu, Dongmei
%A Yan, Chenggang
%A Ji, Jiansong
%A Qin, Peiwu
%A Chen, Zhenglin
%A Ma, Lan
%Y Wang, Zimu
%Y Jiang, Yiwen
%Y Shen, Yaling
%Y Zhao, Xiangyu
%Y Fong, Stephanie
%Y Sun, Xin
%Y Zhou, Yi
%Y Ji, Shaoxiong
%Y Desimone, Robert
%Y Nelson, Barnaby
%Y Dwyer, Dominic
%Y Ge, Zongyuan
%S Proceedings of the 1st Workshop on Multimodal, Multilingual, and Multicultural Mental Health and Psychotherapy (MultiPsyche)
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, Zhuhai, China
%@ 979-8-89176-448-4
%F du-etal-2026-maps
%X We present an initial study of robot-mediated multimodal mental-health screening for Chinese adolescents aged 12–15. MAPS (Multimodal Adolescent Psychological Screening) combines facial, acoustic, textual, and remotely estimated physiological signals collected through a standardized protocol of questionnaires, emotionally evocative tasks, and question answering. From 3,783 participants, 968 records were retained after consent, completeness, and quality-control filtering. We introduce GAME (Generalized Model with Attention and Multimodal EmbraceNet), a fusion model combining eight unimodal representations with relation-graph and attention features. Separate models are trained for 12 questionnaire- and expert-derived screening targets. Stratified 10-fold cross-validation yields 73.04–92.77% accuracy and 71.32–91.06% weighted F1. Feature ablations and descriptive contribution analyses suggest that representation use varies across targets. This initial study connects a portable interaction protocol with task-specific multimodal modeling in a Chinese school setting and provides a basis for further research on screening-label prediction. Future work will expand data collection, refine the fusion and training procedures, and evaluate generalization and screening utility through external and clinically supervised validation.
%U https://aclanthology.org/2026.multipsyche-1.7/
%P 69-79
Markdown (Informal)
[MAPS: Robot-Mediated Multimodal Mental Health Screening for Chinese Adolescents](https://aclanthology.org/2026.multipsyche-1.7/) (Du et al., MultiPsyche 2026)
ACL
- Zhicheng Du, Yang Liu, Zheng Chen, Zhuo Deng, Zhaotian Xie, Wenji Xi, Xi Yuan, Zhen Liang, Dongmei Yu, Chenggang Yan, Jiansong Ji, Peiwu Qin, Zhenglin Chen, and Lan Ma. 2026. MAPS: Robot-Mediated Multimodal Mental Health Screening for Chinese Adolescents. In Proceedings of the 1st Workshop on Multimodal, Multilingual, and Multicultural Mental Health and Psychotherapy (MultiPsyche), pages 69–79, Hengqin, Zhuhai, China. Association for Computational Linguistics.