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Identifying psychological resilience in Chinese migrant youth through multidisciplinary language pattern decoding

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  • Li, Sijia
  • Lu, Shuang
  • Ni, Shiguang
  • Peng, Kaiping

Abstract

China's four decades of rural-to-urban labor migration has created 36 million migrant youth, who encounter more adversity than their urban peers due to educational and socioeconomic exclusion. This study focuses on the psychological resilience of these migrant youth since it indicates the ability or success to cope with adversity. We examine psychological resilience indicators based on migrant youth language patterns extracted in a multidisciplinary way. Our research questions are: whether Chinese migrant youths' language patterns indicate their resilience-related characteristics, and how effectively can three language analysis approaches (user-defined dictionary, feature extraction, and word co-occurrence) identify these indicators, which may be further applied as machine learning features for psychological resilience level estimation. Students in a middle school for migrant youth in Shenzhen, China were recruited as initial participants, and their resilience levels were rated by the Chinese version of Connor-Davidson Resilience Scale. These youth then wrote one week of diary entries. The high- (n = 37) and low-resilience (n = 45) participants' writings were analyzed through the three language analysis approaches. The results suggest that Chinese migrant youth in this study present distinctive language patterns that closely relate to resilience indicators (positive emotion, self-efficacy, self-esteem, and positive affect), which can be further employed in differentiating resilience level (high vs. low) as machine learning features with satisfactory prediction accuracy. Our findings suggest a new interdisciplinary approach for effective psychological resilience identification among migrant youth in China and other high-risk youth populations.

Suggested Citation

  • Li, Sijia & Lu, Shuang & Ni, Shiguang & Peng, Kaiping, 2019. "Identifying psychological resilience in Chinese migrant youth through multidisciplinary language pattern decoding," Children and Youth Services Review, Elsevier, vol. 107(C).
    • Handle: RePEc:eee:cysrev:v:107:y:2019:i:c:s0190740919306747
    DOI: 10.1016/j.childyouth.2019.104506
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    References listed on IDEAS

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    4. Metzler, Marilyn & Merrick, Melissa T. & Klevens, Joanne & Ports, Katie A. & Ford, Derek C., 2017. "Adverse childhood experiences and life opportunities: Shifting the narrative," Children and Youth Services Review, Elsevier, vol. 72(C), pages 141-149.
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    Cited by:

    1. Ma, Gaoming & Wu, Qiaobing, 2020. "Cultural capital in migration: Academic achievements of Chinese migrant children in urban public schools," Children and Youth Services Review, Elsevier, vol. 116(C).
    2. Yuwen Lyu & Julian Chun-Chung Chow & Ji-Jen Hwang & Zhi Li & Cheng Ren & Jungui Xie, 2022. "Psychological Well-Being of Left-Behind Children in China: Text Mining of the Social Media Website Zhihu," IJERPH, MDPI, vol. 19(4), pages 1-13, February.
    3. Cheng, Zhiming & Wang, Ben Zhe & Jiang, Zhou & Taksa, Lucy & Tani, Massimiliano, 2020. "English Skills and Early Labour Market Integration: Evidence from Humanitarian Migrants in Australia," GLO Discussion Paper Series 672, Global Labor Organization (GLO).
    4. Yang, Fan & Liu, Xiaoli, 2020. "Grandparenting styles, childhood food insecurity, and depression among Chinese rural left-behind children: A structural equation model," Children and Youth Services Review, Elsevier, vol. 119(C).
    5. Cheng, Zhiming & Wang, Ben Zhe & Jiang, Zhou & Taksa, Lucy & Tani, Massimiliano, 2020. "English Skills and Early Labour Market Integration of Humanitarian Migrants," IZA Discussion Papers 13728, Institute of Labor Economics (IZA).

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