Depression, anxiety and stress, comorbidity evaluation among a large sample of general adults: results from SEPAHAN study

Depression, anxiety and stress are common psychological disorders (PDs).This study aimed to assess the odds of co-occurrence of mentioned PDs in total sample and different levels of socio-demographic characteristics, specifically among a large sample of general adults.Ina cross-sectional, community-based study conducted among 4763 Iranian adults, depression and anxiety were assessed with Hospital Anxiety and Depression Scale (HADS) and stress with General Health Questionnaire (GHQ). The loglinear analysis was applied to investigate their comorbidities. Based on selected models with pair-comorbidity of anxiety with stress, depression with stress, and anxiety with depression, the results showed the odds of comorbidity between anxiety and depression (odds ratio (OR) =12.29, 95%CI: 9.58-15.80), depression and stress (OR = 7.80, 95%CI:6.55-10.18), and stress and anxiety (OR = 4.62, 95%CI:3.71-5.75). Also, ORs of pair-comorbidities were the same, except between stress and anxiety for men compared to women (adjusted-OR = 6.47, 95%CI: 4.44-9.49 versus 3.85, 95%CI:2.95-5.00) and comorbidity between stress and depression for the participants withlower than 40 years compared to others (adjusted-OR = 9.03, 95%CI: 7.17-11.36 versus 6.41, 95%CI: 4.90-8.41), p< 0.05. Stress comorbidity with depression was higher level than other pair-comorbidities. Obvious discrepancies were also observed in terms of ORs of pair-comorbidities between three mentioned disorders in different levels of SDCs.

Reliability for Multiple Reviewers by using Loglinear Models / 예방의학회지

To guarantee the inter-reviewer reliability is very important in evaluating the quality of large number of clinical research papers by multiple reviewers. We cannot find reports on statistical methods for evaluating reliability for multiple raters in clinical research field. The purpose of this paper is to introduce the statistical methods focused on kappa statistic and five kinds of loglinear models for, which can be applied when evaluating the reliability of multiple raters. We have applied these methods to the result of a project, in which seven reviewers have evaluated the quality of 33 papers with regard to four aspects of paper contents including study hypothesis, study design, study population, study method, data analysis and interpretation. Among the five loglinear models including Symmetry model, Conditional symmetry model, Quasi-symmetry model, Independence model, and Quasi-independence model, Quasi-symmetry model shows the best model of fitting. And the level of reliability among seven reviewers revealed to be acceptable as meaningful.