Assessing a WeChat-based Integrative Family Intervention (WIFI) for Schizophrenia

The study aims to test both the effectiveness and implementation strategy of a WeChat-based integrative family intervention (WIFI) to support family caregiving of schizophrenia in China.

The investigators will conduct a type 2 hybrid effectiveness-implementation study to test both the effect of and the implementation process of a WeChat-based integrative family intervention (WIFI) program. The program will include three core components: 1) psycho-education through WeChat Official Account (WOA), 2) peer support through WeChat chat group, and 3) professional support through WeChat video chat. A rigorous stepped wedge cluster randomized trial will be used to evaluate the implementation, effectiveness, and cost of the WIFI program. The WIFI program will be implemented in 12 communities affiliated with the Changsha psychiatric hospital through the free medicine delivery process in the 686 Program. 20 families of schizophrenia will be selected from each community. The 12 communities will be randomized to one of four fixed sequences every two months during an 8-month intervention period in four clusters of 3 communities each. All clusters will receive the usual financial benefit of the Reward Policy as the control condition, and then successively and in random order, will cross over to the WIFI program at 2-month intervals until the study ends. Outcomes will be assessed for both family caregivers and the family member with schizophrenia. Family caregivers will be assessed for their knowledge and skills about caregiving, social support and coping, perceived stigma, caregiver burden, family functioning, positive feelings, and psychological distress. Schizophrenia individuals will be assessed for their symptoms and functioning, quality of life, recovery and re-hospitalization. Cost data such as costs of the intervention, health care utilization, and costs associated with lost productivity will also be collected. In addition, the investigators will collect process data including fidelity and quality of program implementation as well as users' attitudes will also be collected. Treatment effects will be estimated using generalized linear maximum likelihood mixed modeling (GLMM) with clusters as a random effect and time as a fixed effect. Cost-effectiveness analysis will be performed from the societal perspective using incremental cost effectiveness ratios (ICERs). Qualitative analysis will use the grounded theory approach and immersion-crystallization process. All statistical analyses will be conducted according to the intention-to-treat principle.