AimTo explore the association(s) between demographic factors, socioeconomic status (SES), social capital, health-related quality of life (HRQoL), and mental health among residents of Tehran, Iran.MethodsThe pooled data (n = 31 519) were extracted from a population-based survey Urban Health Equity Assessment and Response Tool-2 (Urban HEART-2) conducted in Tehran in 2011. Mental health, social capital, and HRQoL were assessed using the 28-item General Health Questionnaire (GHQ-28), social capital questionnaire, and Short-Form Health Survey (SF-12), respectively. The study used a multistage sampling method. Social capital, HRQoL, and SES were considered as latent variables. The association between these latent variables, demographic factors, and mental health was determined by structural-equation modeling (SEM).ResultsThe mean age and mental health score were 44.48 ± 15.87 years and 23.33 ± 11.10 (range, 0-84), respectively. The prevalence of mental disorders was 41.76% (95% confidence interval 41.21-42.30). The SEM model showed that age was directly associated with social capital (P = 0.016) and mental health (P = 0.001). Sex was indirectly related to mental health through social capital (P = 0.018). SES, HRQoL, and social capital were associated both directly and indirectly with mental health status.ConclusionThis study suggests that changes in social capital and SES can lead to positive changes in mental health status and that individual and contextual determinants influence HRQoL and mental health.

Background:Drug abuse is a chronic and enduring phenomenon, which is among the important challenging public health problems. One of the main aspects in drug abuse is the relapse.Objectives:The aims of this study were to estimate the time to relapse (survival rate) and to evaluate some of its associated variables by survival analysis.Patients and Methods:This research was conducted in four addiction treatment centers on 140 self-referred addicts in Ilam city, Iran, in 2012. Cluster sampling method was used for selecting the samples and data were collected by interview and referring to the subjects’ records. The gathered data were analyzed through the life table, Kaplan-Meier analysis, log rank test, and Cox regression.Results:The relapse rate was 30.42%, mean and median of the time to relapse (survival time) were 27.40 ± 1.63 months (CI 95%: 24.19 - 30.60) and 25 ± 2.25 months (CI 95%: 22.5 - 27.5), respectively. In the first six months, the cumulative survival rate was 83%, while in the 24th month it was 46% and the following time was consistent. Job status (OR = 2.64), marital status (OR = 1.55), family size (OR = 1.20) and age (OR = 0.23) were statistically significant in Cox regression model.Conclusions:In the initial treatment, it seems necessary to supervise and monitor the treatment process through staff in addiction treatment centers together with the company of the addicts’ families to reduce relapse rate.

Wristband bar-code medication scanning can decrease the ME in hospital setting. Since the patient's safety is the main goal of the World Health Organization, it is recommended that a unique patient identification barcode should be used with name, medical record number, and bar-coded financial number.

Background: Patients' escape from hospital imposes a significant cost to patients as well as the health system. Besides, for these patients, exposure to adverse events (such as suicide, self-harm, violence and harm to hospital reputation) are more likely to occur compared to others. The present study aimed to determine the characteristics of the absconding patients in a general hospital through a case-control design in Shiraz, Iran. Methods: This case-control study was conducted on 413 absconded patients as case and 413 patients as control in a large general hospital in Shiraz, southern Iran. In this study, data on the case and control patients was collected from the medical records using a standard checklist in the period of 2011-3. Then, the data were analyzed using descriptive and analytical statistics, through SPSS 16. Results: The finding showed that 413 patients absconded (0.50%) and mean of age in case group was 40.98 ± 16.31 years. In univariate analysis, variables of gender [Odds Ratio (OR)= 2], ward (OR= 1.22), insurance status (OR= 0.41), job status (OR= 0.34) and residence expenditure were significant. However, in multivariate analysis significant variables were age (OR adj = 0.13), gender (OR adj = 2.15), self-employment/unemployed (OR adj = 0.47), emergency/admission (OR adj = 2.14), internal/admission (OR adj = 3.16), insurance status (OR adj = 4.49) and residence expenditure (OR adj = 1.15). Conclusion: Characteristics such as middle age, male gender, no insurance coverage, inability to afford hospital expenditures and admission in emergency department make patients more likely abscond from the hospital. Therefore, it may be necessary to focus efforts on high-risk groups and increase insurance coverage in the country to prevent absconding from hospital.