PURPOSE: This study aimed to assess the factor structure of the Persian version of posttraumatic growth inventory (P-PTGI). METHODS: Participants included 272 Iranian people of Azari ethnicity (111 women and 161 men), aged between 21 and 91 years (mean 52.65 years), who were diagnosed with cancer and were referred to the oncology department of the university hospital. The P-PTGI was assessed to determine the construct validity, using various indices of confirmatory factor analysis and standardized lambda coefficient, followed by further assessment of the discriminant and convergent validities by using the structural equation model. LISREL 8.8 for Windows and SPSS were used for data analysis. RESULTS: The calculated values of comparative fit index, incremental fit index, normed fit index, and non-normed fit index > .90 and the values of standardized root-mean-square residual < .08 indicate an acceptable fit for the original PTGI. Considering that the values of average variance extracted (.52–.74) were greater than the square of correlation coefficients between the five dimensions of P-PTGI, discriminant validity was approved. Convergent validity was confirmed through a high value of standardized lambda coefficient (.52–.92) between the items and their related factors. CONCLUSIONS: This study revealed that P-PTGI has an acceptable validity and reliability for posttraumatic growth assessment in Iranian cancer patients and its factor structure is similar to that of the original form developed by Tedeschi and Calhoun.
Female ; Humans ; Reproducibility of Results ; Statistics as Topic

Objectives: Access to maternal and neonatal care services (MNCS) is an important goal of health policy in developing countries. In this study, we proposed a 3-level hierarchical location-allocation model to maximize the coverage of MNCS providers in Iran. Methods: First, the necessary criteria for designing an MNCS network were explored. Birth data, including gestational age and birth weight, were collected from the data bank of the Iranian Maternal and Neonatal Network national registry based on 3 service levels (I, II, and III). Vehicular travel times between the points of demand and MNCS providers were considered. Alternative MNCS were mapped in some cities to reduce access difficulties. Results: It was found that 130, 121, and 86 MNCS providers were needed to respond to level I, II, and III demands, respectively, in 373 cities. Service level III was not available in 39 cities within the determined travel time, which led to an increased average travel time of 173 minutes to the nearest MNCS provider. Conclusions This study revealed inequalities in the distribution of MNCS providers. Management of the distribution of MNCS providers can be used to enhance spatial access to health services and reduce the risk of neonatal mortality and morbidity. This method may provide a sustainable healthcare solution at the policy and decision-making level for regional, or even universal, healthcare networks.