Substance use, psychiatric symptoms, personal mastery, and social support among COVID-19 long haulers: A compensatory model

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Abstract

Background Substance use has become a critical health concern during the COVID-19 pandemic, and emerging attention has been paid to people with the persistent symptoms of COVID-19 (COVID-19 long haulers) due to their high vulnerability. However, scant research has investigated their substance use and relevant psychosocial factors. The current study was to (1) examine substance use behaviors (i.e., legal drug use, illicit drug use, and non-medical use of prescription drugs); and (2) assessed their associations with psychiatric symptoms (i.e., depression, anxiety, and post-traumatic stress disorder) and psychosocial factors (i.e., personal mastery and social support) among COVID-19 long haulers. Methods In January–March 2022, 460 COVID-19 long haulers (50% female), with an average age of 32, completed online surveys regarding their demographics, substance use, psychiatric symptoms, and psychosocial factors. Results In the past three months, the most commonly used or non-medically used substances were tobacco (82%) for legal drugs, cocaine (53%) for illicit drugs, and prescription opioids (67%) for prescription drugs. Structural equation modeling suggested that psychiatric symptoms were positively associated with substance use behaviors (βs = 0.38 to .68, ps < 0.001), while psychosocial factors were negatively associated with substance use behaviors (βs = -0.61 to -0.43, ps < 0.001). Conclusion Substance use is common in COVID-19 long haulers and psychiatric symptoms are the risk factors. Personal mastery and social support appear to offer protection offsetting the psychiatric influences. Substance use prevention and mental health services for COVID-19 long haulers should attend to personal mastery and social support.

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APA

Tam, C. C., Qiao, S., Garrett, C., Zhang, R., Aghaei, A., Aggarwal, A., … Li, X. (2023). Substance use, psychiatric symptoms, personal mastery, and social support among COVID-19 long haulers: A compensatory model. PLoS ONE, 18(8 August). https://doi.org/10.1371/journal.pone.0289413

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