O b j e c t i v e s: The aim of study was to investigate the association between anxiety, depression, stress and determinants of quality of life among Iranian students. M e t h o d s: The questionnaires were completed by 275 students. The random sampling was conducted in two phases, the stratified sampling which some classes were selected among different classes of faculty of health and at the second phase, in each class the number of students who had the requirements to enter in the study were selected randomly. the logistic regression to find out the association between demographic characteristics with the quality of life was run and according to the normality status of the distribution of data the parametric or non-parametric tests were used. R e s u l t s: In the univariable model, the students that were living in their own homes had the odds of 2.18 times more than the others to have a higher quality of life level (95% CI: 1.07–4.45). In the multi variable model the anxiety and stress were significantly related to the quality of life and for increasing each 1 unit in the amount of anxiety and stress the odds of a better quality of life decreases 0.19 and 0.03 respectively. Even after adjusting for other covariates – in the multivariable model – both anxiety and stress were associated with the quality of life. C o n c l u s i o n: It is useful for the universities to understand different aspects of the students’ lives which are under the influence of stress, anxiety and depression, and also determining the resources from which they are originated.
Objectives: Relapse is very much associated with the management of disorder during the treatment, but also many other factors could trigger it. The aim of this study was to explore classes and patterns of relapse risk in patients with schizophrenia of Razi Hospital. Methods: Using random sampling techniques, we recruited 300 participants with a diagnosis of schizophrenia in Razi hospital of Tehran (Iran) between January and May 2017 in a cross -sectional survey. We used latent class analysis (LCA) to establish a baseline model of risk profiles and to identify the optimal number of latent classes, and we used ordinal regression to identify factors associated with class membership. Results: Three classes of multiple relapse risk were identified. LCA showed that, overall, 52%, 22% and 26% of participants with schizophrenia were divided into class 1, class 2 and class 3, respectively. Compared to members in the lowest -risk class (reference group), the highest -risk class members had higher odds of being the age of disorder onset under 25 (OR = 1.4; CI: 1.42–2.33). Participants with schizophrenia who were unemployed were more likely to categorize in the highest -risk class than members of the low -risk class (OR = 2.5; CI: 1.44–4.1). Also, female patients were more likely to belong to members of the high -risk class than members of the low -risk class (OR = 2.22; CI: 1.74–7.64). Conclusion: These findings emphasize the importance of having targeted prevention programs for all domains of Age of onset, female and unemployed related. So, current study suggested that interventions should focus on these risk factors. Furthermore, Increasing the Job opportunities for participants with schizophrenia is warranted so as to prevent of schizophrenia disorder.