A longitudinal investigation of mental health outcomes after the Henan floods in China: Examining predictors of resilience trajectories

Abstract

A heavy rainstorm struck Henan, China, in July 2021. Previous studies have indicated that natural disasters have a wide range of psychological sequelae, but little research has been done on the psychological effects of floods specifically. This study aimed to track the mental health trajectories of flood victims over time and identify associated protective and risk factors. People living in the areas most impacted by the flood (N = 376) were surveyed at four different time points: 3 weeks, 1 month, 2 months, and 3 months post-flood. Latent growth mixture modeling was utilized to delineate longitudinal patterns of depression, anxiety, and posttraumatic stress disorder (PTSD). Least absolute shrinkage and selection operator logistic regression, a supervised machine-learning approach, was employed to discern predictors among 49 assessed variables at both contextual and personal levels. Results revealed three classes of PTSD (resilience, recovery, moderate symptoms) and anxiety (resilience, chronicity, recovery) trajectories, along with two classes of depression trajectories (resilience, chronicity). Key factors predicting resilience in mental health included personality traits, media consumption habits, pre-existing health conditions at the individual level, and asset loss and ongoing adversities at the contextual level. In spite of the widespread impact of the flood, most victims displayed resilience in the face of adversity. Identifying critical factors across various psychological symptoms offers valuable insights for both pre-disaster preparation and post-disaster trans-diagnostic psychological interventions.

Keywords

flood / mental health / natural disaster / resilience / trajectories

References

[1] Berg, K. C., Peterson, C. B., Crosby, R. D., Cao, L., Crow, S. J., Engel, S. G., & Wonderlich, S. A. (2014). Relationship between daily affect and overeating-only, loss of control eating-only, and binge eating episodes in obese adults. Psychiatry Research, 215(1), 185–191.

[2] Blevins, C. A., Weathers, F. W., Davis, M. T., Witte, T. K., & Domino, J. L. (2015). The posttraumatic stress disorder checklist for DSM-5 (PCL-5): Development and initial psychometric evaluation. Journal of Traumatic Stress, 28(6), 489–498.

[3] Bonanno, G. A., Brewin, C. R., Kaniasty, K., & Greca, A. M. (2010). Weighing the costs of disaster: Consequences, risks, and resilience in individuals, families, and communities. Psychological Science in the Public Interest, 11(1), 1–49.

[4] Bonanno, G. A., Ho, S. M. Y., Chan, J. C. K., Kwong, R. S. Y., Cheung, C. K. Y., Wong, C. P. Y., & Wong, V. C. W. (2008). Psychological resilience and dysfunction among hospitalized survivors of the SARS epidemic in Hong Kong: A latent class approach. Health Psychology, 27(5), 659–667.

[5] Bonanno, G. A., Romero, S. A., & Klein, S. I. (2015). The temporal elements of psychological resilience: An integrative framework for the study of individuals, families, and communities. Psychological Inquiry, 26(2), 139–169.

[6] Chen, S., Bagrodia, R., Pfeffer, C. C., Meli, L., & Bonanno, G. A. (2020). Anxiety and resilience in the face of natural disasters associated with climate change: A review and methodological critique. Journal of Anxiety Disorders, 76, 102297.

[7] Chen, S., Bi, K., Sun, P., & Bonanno, G. A. (2022). Psychopathology and resilience following strict COVID-19 lockdowns in Hubei, China: Examining person-and context-level predictors for longitudinal trajectories. The American Psychologist, 77(2), 262–275.

[8] Connor, K. M., & Davidson, J. R. T. (2003). Development of a new resilience scale: The Connor-Davidson resilience scale (CD-RISC). Depression and Anxiety, 18(2), 76–82.

[9] Dar, K. A., Iqbal, N., Prakash, A., & Paul, M. A. (2018). PTSD and depression in adult survivors of flood fury in Kashmir: The payoffs of social support. Psychiatry Research, 261, 449–455.

[10] Everly, G. S., Jr., & Lating, J. M. (2021). Psychological first aid (PFA) and disasters. International Review of Psychiatry, 33(8), 718–727.

[11] Fernandez, C. A., Vicente, B., Marshall, B. D., Koenen, K. C., Arheart, K. L., Kohn, R., Saldivia, S., & Buka, S. L. (2017). Longitudinal course of disaster-related PTSD among a prospective sample of adult Chilean natural disaster survivors. International Journal of Epidemiology, 46(2), 440–452.

[12] Galatzer-Levy, I. R., Huang, S. H., & Bonanno, G. A. (2018). Trajectories of resilience and dysfunction following potential trauma: A review and statistical evaluation. Clinical Psychology Review, 63(9), 41–55.

[13] Gero, K., Aida, J., Shirai, K., Kondo, K., & Kawachi, I. (2021). Dispositional optimism and disaster resilience: A natural experiment from the 2011 great East Japan earthquake and tsunami. Social Science & Medicine, 273(1982), 113777.

[14] Gosling, S. D., Rentfrow, P. J., & Swann, W. B. (2003). A very brief measure of the big-five personality domains. Journal of Research in Personality, 37(6), 504–528.

[15] He, X., Li, C., Qian, J., Cui, H., & Wu, W. (2010). Reliability and validity of the generalized anxiety scale in general hospitals. Shanghai Archives of Psychiatry, 22(4), 200–203.

[16] Hu, S., Tan, H., Cofie, R., Zhou, J., Yang, T., Tang, X., & Liu, A. (2015). Recovery from post-traumatic stress disorder after a flood in China: A 13-year follow-up and its prediction by degree of collective action. BMC Public Health, 15, 615.

[17] Javanmard, A., & Montanari, A. (2018). Debiasing the lasso: Optimal sample size for gaussian designs. The Annals of Statistics, 46(6A), 2593–2622.

[18] Kaiser, T., Herzog, P., Voderholzer, U., & Brakemeier, E. L. (2021). Unraveling the comorbidity of depression and anxiety in a large inpatient sample: Network analysis to examine bridge symptoms. Depression and Anxiety, 38(3), 307–317.

[19] Kino, S., Aida, J., Kondo, K., & Kawachi, I. (2021). Persistent mental health impacts of disaster. Five-year follow-up after the 2011 great east Japan earthquake and tsunami: Iwanuma study. Journal of Psychiatric Research, 136, 452–459.

[20] Kopala-Sibley, D. C., Kotov, R., Bromet, E. J., Carlson, G. A., Danzig, A. P., Black, S. R., & Klein, D. N. (2016). Personality diatheses and hurricane Sandy: Effects on post-disaster depression. Psychological Medicine, 46(4), 865–875.

[21] Kroenke, K., Spitzer, R. L., & Williams, J. B. W. (2001). The PHQ-9: Validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613.

[22] Lai, B. S., La Greca, A. M., Brincks, A., Colgan, C. A., D’Amico, M. P., Lowe, S., & Kelley, M. L. (2021). Trajectories of posttraumatic stress in youths after natural disasters. JAMA Network Open, 4(2), e2036682.

[23] Li, J. (2013). Reliability and validity test of the Chinese version of the 10-item big five personality inventory (TIPI-C). China Journal of Health Psychology, 21(11), 1688–1692.

[24] Liang, Y., Zhao, Y., Ji, W., Bian, X., & Xi, J. (2023). Latent profiles of psychological status among populations cumulatively exposed to a flood and the recurrence of the COVID-19 pandemic in China. International Journal of Disaster Risk Reduction: IJDRR, 85, 103520.

[25] Liang, Y., Zhou, Y., & Liu, Z. (2021). Consistencies and differences in posttraumatic stress disorder and depression trajectories from the Wenchuan earthquake among children over a 4-year period. Journal of Affective Disorders, 279, 9–16.

[26] Lin, L. Y., Sidani, J. E., Shensa, A., Radovic, A., Miller, E., Colditz, J. B., Hoffman, B. L., Giles, L. M., & Primack, B. A. (2016). Association between social media use and depression among U.S. young adults. Depression and Anxiety, 33(4), 323–331.

[27] Liu, S. R., Davis, E. P., Palma, A. M., Sandman, C. A., & Glynn, L. M. (2022). The acute and persisting impact of COVID-19 on trajectories of adolescent depression: Sex differences and social connectedness. Journal of Affective Disorders, 299, 246–255.

[28] Mason, V., Andrews, H., & Upton, D. (2010). The psychological impact of exposure to floods. Psychology, Health & Medicine, 15(1), 61–73.

[29] Mughal, M. K., Giallo, R., Arshad, M., Arnold, P. D., Bright, K., Charrois, E. M., Rai, B., Wajid, A., & Kingston, D. (2023). Trajectories of maternal depressive symptoms from pregnancy to 11 years postpartum: Findings from avon longitudinal study of parents and children (ALSPAC) cohort. Journal of Affective Disorders, 328, 191–199.

[30] Muthén, L. K., & Muthén, B. O. (2017). Mplus User’s Guide (8th ed.). Muthén & Muthén.

[31] Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling, 14(4), 535–569.

[32] R Core Team. (2023). R: A language and environment for statistical computing. R Foundation for Statistical Computing.

[33] Sakuma, A., Ueda, I., Shoji, W., Tomita, H., Matsuoka, H., & Matsumoto, K. (2020). Trajectories for post-traumatic stress disorder symptoms among local disaster recovery workers following the great east Japan earthquake: Group-based trajectory modeling. Journal of Affective Disorders, 274, 742–751.

[34] Sasaki, Y., Tsuji, T., Koyama, S., Tani, Y., Saito, T., Kondo, K., Kawachi, I., & Aida, J. (2020). Neighborhood ties reduced depressive symptoms in older disaster survivors: Iwanuma study, a natural experiment. International Journal of Environmental Research and Public Health, 17(1), 337.

[35] Spitzer, R. L., Kroenke, K., Williams, J. B. W., & Löwe, B. (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166(10), 1092–1097.

[36] Tang, B., Deng, Q., Glik, D., Dong, J., & Zhang, L. (2017). A meta-analysis of risk factors for post-traumatic stress disorder (PTSD) in adults and children after earthquakes. International Journal of Environmental Research and Public Health, 14(12), 1537.

[37] Tang, B., Liu, X., Liu, Y., Xue, C., & Zhang, L. (2014). A meta-analysis of risk factors for depression in adults and children after natural disasters. BMC Public Health, 14, 623.

[38] Ungar, M. (2019). Designing resilience research: Using multiple methods to investigate risk exposure, promotive and protective processes, and contextually relevant outcomes for children and youth. Child Abuse & Neglect, 96, 104098.

[39] Van Heel, M., Bijttebier, P., Colpin, H., Goossens, L., Van Den Noortgate, W., Verschueren, K., & Van Leeuwen, K. (2020). Perspective taking, empathic concern, agreeableness, and parental support: Transactional associations across adolescence. Journal of Adolescence, 85, 21–31.

[40] Yu, X., & Zhang, J. (2007). Factor analysis and psychometric evaluation of the Connor-Davidson resilience scale (CD-RISC). Social Behavior and Personality, 35(1), 19–30.

[41] Zhang, N., Yang, S., & Jia, P. (2022). Cultivating resilience during the COVID-19 pandemic: A socioecological perspective. Annual Review of Psychology, 73, 575–598.

[42] Zhao, N., & Zhou, G. (2020). Social media use and mental health during the COVID-19 pandemic: Moderator role of disaster stressor and mediator role of negative affect. Applied Psychology. Health and Well-Being, 12(4), 1019–1038.

[43] Zhen, R., Quan, L., & Zhou, X. (2020). Co-occurring patterns of post-traumatic stress disorder and depression among flood victims: A latent profile analysis. Journal of Health Psychology, 25(10–11), 1543–1555.

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2024 The Author(s). PsyCh Journal published by Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.