Predicting elders’ cognitive flexibility from their language use

1063

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nan

Abstract

AbstractThis study recruited 51 elders aged 53-74 to discuss their daily activities in focus groups. The transcribed discourse was analyzed using the Chinese version of LIWC (Lin et al., 2020; Pennebaker et al., 2015) for cognitive complexity and dynamic language as well as content words related to elders’ daily activities. The interruption behavior during the conversation was also coded and analyzed. After controlling for education, gender and age, the results showed that cognitive flexibility performance was accompanied by the increasing adoption of dynamic language, insight words and family words. These findings serve as the basis for predicting elders’ cognitive flexibility through their daily language use.

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�� 51� 53-74�� LIWC2015 �� (��2020; Pennebaker et al., 2015) �� Abstract Increasing research efforts are directed towards the relationship between cognitive decline and language use. However, few of them had focused specifically on how language use is related to cognitive flexibility. This study recruited 51 elders aged 53-74 to discuss their daily activities in focus groups. The transcribed discourse was analyzed using the Chinese version of LIWC (Lin et al., 2020; Pennebaker et al., 2015) for cognitive complexity and dynamic language as well as content words related to elders’ daily activities. The interruption behavior during conversation was also analyzed. The results showed that, after controlling for education, gender and age, cognitive flexibility performance was accompanied by the increasing adoption of dynamic language, insight words and family words. These findings serve as the basis for the prediction of elders’ cognitive flexibility through their daily language use. �� Keywords: language use, cognitive flexibility, elders 1 �� (cognitive frailty) (Kelaiditi et al ., 2013; Panza et al., 2015)�� (Lumsden et al., 2016 ; Siraly et al., 2015)�� (literacy)�� (Mild Cognitive Impairment, MCI)�� (dementia) (Martínez-Nicolás et al., 2021)�� Predicting elders’ cognitive flexibility from their language use �� Man-Ying Wang �� Department of Psychology Soochow University �� 70 � mywang.scu@gmail.com �� Yu-An Ko �� Department of Psychology Soochow University �� 70 � Kelen850408@gmail.com �� Chin-Lan Huang �� Department of Humanities & Social Sciences National Taiwan University of Science and Technology �� 4 � 43 � chinlanhuang@gmail.com �� Jyun-Hong Chen �� Department of Psychology Soochow University �� 70 � chinlanhuang@gmail.com �� Te-Tien Ting �� Department of Data Science Soochow University �� 70 � tetien@scu.edu.tw The 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021) Taoyuan, Taiwan, October 15-16, 2021. The Association for Computational Linguistics and Chinese Language Processing 132 ��(cognitive flexibility) �� (executive function)�� (Buitenweg et al., 2012)�� (Logue & Gould, 2014; Martyr & Clare, 2012)�� LIWC �� 2 � �� (speech)�� vs.��(Mild Cognitive Impairment, MCI) �� (Alzheimer’s Disease)�� AI � ��(Dodge et al., 2015; Konig et al., 2018)�� ? Dodge ��(2015)�� (��)�� MCI �� (��)�� MCI �� Asgari ��(2017)� � LIWC2001 �� MCI ��(vs.�� )��(�� Polsinelli � � (2020) �� 102 ��(�� 75.8 �) ��(�� ) �� LIWC �� (analytic)�� (Diamond, 2013)�� (Hülür, Ram, Willis, Schaie, & Gerstorf, 2016) � Polsinelli �� /��/�� Polsinelli�� (�� 12 �� 30 ��)�� LIWC�Linguistic Inquiry and Word Count �� Pennebaker �� (��)�� (� arrive, car, go) (Newman et al., 2003)�� (function words)��(Simmons et al., 2005)�LIWC �� (Weaver, 2017)�� (Tausczik & Pennebaker, 2010)�� (Graesser, McNamara, Louwerse, & Cai, 2004)� �� (Hartley, Pennebaker, & Fox, 2003)� � � � � …

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Publication Details

Paper ID:: 1063
Year:: 2021
Publication:: TIPSTER
Publication Type:: conf
DOI:: nan

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