Although there are many studies explored count models in epidemiology and public health area, it is the first study to utilize count regression models to fit the intensity of the adverse outcomes in schizophrenia patients [23–26]. Moreover, it is crucially important to select the best-fitted model for the data since there is no model fitted well for all data. Here, we used four count regression models to investigate influencing factors associated with the number of adverse outcomes in schizophrenia patients and to compare the goodness-of-fit. In our study, over 99% of schizophrenia patients have reported no adverse outcomes in 2020. Traditional Poisson regression had the worst fit to this study data for all types of outcomes because of the overdispersion and excess zeros. To solve the zero-inflated phenomenon, the ZIP model was used and provided a considerable improvement over Poisson regression. To deal with the overdispersion problem, the NB model was used and fitted the data better than the Poisson model, but cannot solve the zero-inflated phenomenon. The ZINB model can account for both overdispersion and the excess zeroes but provided a similar fit compared to the NB model because of no zero-inflated phenomenon with the NB model in fitting aggressiveness without police dispatch intensity. Therefore, the NB model was selected to be the simplest and first choice to fit the number of aggressiveness without police dispatch, and the ZINB model was preferred for the other two events intensity.
Investigation of influencing factors for adverse outcomes is of benefit to intervention and prevention of schizophrenia. In our study, a wide range of sociodemographic and clinical factors were assessed.
Our finding indicated that younger age increased the risk of all outcomes, including aggressiveness with police dispatch or violent crime, aggressiveness without police dispatch, and self-harm or suicide attempts. These results are consistent with the results of other studies that have explored risk factors with binominal response[10, 11, 27, 28]. Males increased the number of adverse events that violence against others and consistent findings were found in other studies. However, the association between gender and self-harm or suicide attempts was mixed and inconclusive in previous studies[30–32], we found that males decreased the intensity of self-harm or suicide attempts.
In addition, our findings revealed that having adverse outcomes history significantly decreases the likelihood of all three outcomes. It is contrary to the finding of previous studies[14, 30, 33, 34]. It is worth noting that the schizophrenia patients in our study were participants in basic public health services in China. They receive regular follow-up and intervention by community doctors. Patients who had adverse outcomes history had higher risk assessments and received more frequent follow-up. In addition, their psychiatrists may adjust drug doses or modify treatment regimens according to their condition. Therefore, having adverse outcomes history may decrease the number of adverse events because of the above intervention. It needs further researches to explore the relationship between such intervention and adverse outcomes intensity.
On the other hand, results from our study showed that many risk factors were not shared across the different types of adverse outcomes. It suggests that it is distinct for mechanism between violence and self-harm or suicide attempts, and customized tools in risk assessment and intervention for specific events are necessary. For example, educational level, employment status, and medical history were related to violence against others but not self-harm and suicide attempts. Our findings were in concordance with the results of previous studies that unemployment status and low educational level were risk factors for violence [16, 35, 36]. The previous studies indicated that having medical history increases the risk of violence. However, our study found an inverse relationship with a medical history and aggressiveness with police dispatch or violent crime. The possible reasons may be similar to the association between adverse outcomes history and violence. Having medical history may increase the risk of adverse effects [37–39]. Once patients having an adverse effect, he or she may be assessed to be unstable patient and received more intensive follow-up and symptomatic treatment. Those interventions may contribute to decreasing the violence intensity.
Having a family history of mental disease increased the risk of self-harm or suicide attempts but did not affect violence. The previous research also found that family history of mental disease was the risk factor of self-harm or suicide attempts[12, 40–42], but it was rarely found in terms of violence. This finding support that self-harm or suicide attempts are affected by genetic factors[44, 45]. Although previous studies found that earlier age of illness onset was a risk factor of violence and suicide, we founded that adult-onset schizophrenia increases the risk of aggressiveness without police dispatch and the risk of self-harm or suicide attempts. This is in line with results from some previous studies and suggests that adult-onset patients are more unbearable with the disease and have more passive aggressive personality disorder traits compared with early-onset patients [30, 46, 47]. Further studies are warranted to evaluate this relationship between these events intensity and age of illness onset.
In our study, patients who had a longer duration of illness were more likely to aggressiveness without police dispatch, but not to aggressiveness with police dispatch or violent crime, and to self-harm or suicide attempts. However, schizophrenia patients with a history of severe violence or with suicide attempts had a longer duration of illness in other studies[31, 32, 48]. It is possible that with a longer duration of illness, caregivers, as well as community doctors, gained a greater awareness of severer outcomes, such as and suicide attempts and severer violence. Further studies are needed to clarify the relationship between the duration of illness and different types of adverse outcomes.
In addition, the residential type was another individual influencing factor of aggressiveness without police dispatch, and living in rural was a protective factor. A possible explanation is that rural schizophrenia patients are much willing to receive basic public health services and have better access to primary medical institutions in China, which may contribute to achieving effective control and decreasing the risk of violence[49, 50]. The different treatment of schizophrenia between urban and rural areas may be another possible explanation. A previous study in China found that rural patients were more likely to receive anticholinergics compared to urban patients . Similarly, poverty was an individual protective factor for aggressiveness with police dispatch or violent crime. This may be attributed to the higher rate of receiving follow-ups regularly and increasing demand and utilization of health services among poverty patients[49, 52].
In our study, some factors were not significantly associated with the number of adverse outcomes. For instance, psychosis treatment status showed insignificantly associate with the number of these outcomes. It may be too few psychosis untreated patients to have enough power to find the differences. Other factors, such as marital status, register type were not related to the number of adverse outcomes. It may be attributed to the different statistical analysis methods. In the count regression model of our study, the exponentiated regression coefficient of the count model is the ratio of expected counts instead of the odds ratio in the logistic regression model. In other words, the exponentiated coefficient represents the IRR for each unit change in the predictor, while the other predictors in the model are held constant. Another possible reason for the non-significance is the differences in the definition of these adverse outcomes and the research population. Further studies should assess the impact of varying covariates on the intensity of these events among schizophrenia patients.
Several limitations should be noted. First, the inclusion criteria of patients may introduce selection bias, but the demographics distribution of our study sample was similar to that of the schizophrenia patients followed up in 2020. Secondly, the correlation between covariates was not considered in our study, but the correlation cannot have a significant influence on the results of our study. Finally, our results were limited due to the lack of variables that may contribute to adverse outcomes, including antipsychotic drugs, drug adherence, drug abuse, parental abuse, and clinical symptoms.