WeChat is the most popular social media platform in mainland China, with over 1 billion active users. Although social media is widely used in professional healthcare education in western countries,...

Research on social work practice is essential for developing an indigenized base of knowledge. In China, while social work education has grown rapidly, much of what is taught – and many social work priorities in research and practice – is influenced by rapidly changing national government policies. This policy environment creates both opportunities and challenges to building an infrastructure to support research on social work practice. This article reviews the context and challenges related to developing research on social work practice in mainland China, and the important role for social work education to support this development.

Approximately 65 million children in mainland China are left behind in rural areas while their parents work in the cities. Research has highlighted their health needs. However, current research on interventions for this population is unknown. The purpose of this study was to systematically review existing health service interventions for left-behind children in China. The study team identified interventions for left-behind children by conducting a comprehensive search of major academic databases for Chinese and English research. Articles were retained in the study if they were original empirical intervention studies that target health and related well-being outcomes of left-behind children. A total of eighteen unique studies met inclusion criteria. The majority of them demonstrated positive outcomes using various modalities, including education, sport and nutrition guidance and nursing services. However, the shortcomings in research design and intervention limit their replication. Intervention research for left-behind children shows an enormous gap in the knowledge about this at-risk group. Of the existing programs identified, we observe considerable promise for interventions based on inter-disciplinary approaches to services. We provide additional recommendations for conducting future research and for building collaborative relationships with social workers to better serve the needs of children.

The present study examined the types of drugs likely to be used by bullies, victims, and bully/victims. Participants comprise African American adolescents from three high schools, one youth church group, two community youth programs, and four public venues in low-income communities in Chicago’s Southside. A series of logistic regression analyses and latent class analyses were employed. Victims are likely to use alcohol, marijuana, and lean/krokodil. Bullies were likely to use alcohol and marijuana. Bully/victims were not at risk of any of the substances. Our LCA findings revealed a lower occurrence of substance use among victims although 30% used alcohol and marijuana; more than half of bullies showed high levels of alcohol, marijuana, and lean/krokodil use; a diverse pattern of drug use was shown among bully/victims although their lean/krokodil and crack/cocaine use was higher than other subgroups of bullying. The drugs of choice for African American bullies, victims, or bully/victims are variable.

Purpose: While social work case management faces ongoing challenges with practice inefficiency, the emergence of artificial intelligence (AI) presents an innovative solution. This systematic review examines how AI is applied in social work case management. Method: A comprehensive search was conducted across databases for studies published after 2000. Empirical studies on AI-assisted social work case management were included in the review. Results : From 11,022 identified studies, eight met the inclusion criteria and were reviewed. The results indicated that the most commonly used AI techniques were machine learning and natural language processing. They were utilized in decision-making procedures, client identification, intervention classification, risk prevention, and service monitoring. Seven studies demonstrated effective outcomes. Discussion : Though AI applications in social work case management remain in the early development stages, this review reveals growing interest and promising potential benefits. These findings contribute to advancing AI-assisted social work case management on a global scale.

Improving mental well-being is essential for social workers. Self-care services are often facilitated to enhance it, but there is limited research exploring their characteristics and effectiveness. We conducted a systematic review of self-care interventions targeting the mental well-being of social workers. A comprehensive search of four English and one Chinese databases yielded 2969 studies for initial screening. Fourteen eligible studies were finally included and reviewed. The results underscored mindfulness as prevalent and effective, with social work students being the main service recipients. Although with limitations, the findings inform future research and self-care services for social workers.