Causes of dental caries from the perspectives of adolescents: a qualitative study

Objective: Various factors affect dental caries and impact the patterns of dental care. A few studies have been conducted to identify these factors from the perspectives of students. This study aimed to explore factors influencing dental caries from students' perspectives

Methods: A qualitative design using content analysis approach was conducted to collect the perspectives of 18 Iranian students who were studying in 8 guidance schools. They were chosen through purposive sampling. Semi- structured private interviews and focus groups were held for data gathering. The tape-recorded interviews were transcribed verbatim and analyzed using an inductive content analysis approach. In order to support the validity and rigor of the data, different trustworthiness criteria such as acceptability, confirm ability and transferability were considered

Results: During data analysis, four main categories were developed: [difficult conditions of care], [disability in caring], [uncontrollability of dental caries] and [intangible sense of the factors causing dental caries]. The participants more emphasized their own experiences about having insufficient dental-oral care, not paying attention to oral health, dental fear and the lack of both knowledge and competency regarding this issue

Conclusion: The findings of this study revealed factors influencing dental caries from students' perspectives and emphasized the roles of individual, parent, dentist and community in this respect

The findings of this study can be considered to be a valuable basis to design oral health interventions. However, more studies are required to improve our understanding of dental fear and denote barriers and social beliefs pertinent to oral health in different groups of students

Prognostic factors in gastric cancer using log-normal censored regression model.

Background & objectives: Gastric cancer is one of the most common cancers in the world. It is rarely detected early, and the prognosis remains poor. Cox proportional hazard model is used to examine the relationship between survival and covariates. Parametric survival models such as log normal regression model can also be used for this analysis. We used log normal regression model in this study to evaluate prognostic factors in gastric cancer and compared with Cox model. Methods: We retrospectively studied the 746 patients diagnosed with gastric cancer admitted in a referral hospital in Tehran, Iran, from February 2003 through January 2007. Age at diagnosis, sex, extent of wall penetration, histology type, tumour grade, tumour size, pathologic stage, lymph node metastasis and presence of metastasis were entered into a log normal model. Hazard rate (HR) was employed to interpret the risk of death and the results were compared with Cox regression. The AIC (Akaike Information Criterion) was employed to compare the efficiency of models. Results: Univariate analysis indicated that with increasing age the risk of death increased significantly in both log normal and Cox models. Patients with grater tumour size were also in higher risk of death followed by those with poorly differentiated and moderately differentiated in tumour grade and advanced pathologic stage. The presence of metastasis was significant prognostic factor only in log normal analysis. In final multivariate model, age was still a significant prognostic factor in Cox regression but it was not significant in log normal model. Presence of metastasis followed by histology type were other prognostic features found significant in log normal results. Based on AIC, log normal model performed better than Cox. Interpretation & conclusion: Our results suggest that early detection of patients in younger age and in primary stages and grade of tumour could be important to decrease the risk of death in patients with gastric cancer. Comparison between Cox and log normal models indicated that log normal regression model can be a useful statistical model to find prognostic factors instead of Cox.

Comparing Cox regression and parametric models for survival of patients with gastric carcinoma.

BACKGROUND: Researchers in medical sciences often tend to prefer Cox semi-parametric instead of parametric models for survival analysis because of fewer assumptions but under certain circumstances, parametric models give more precise estimates. The objective of this study was to compare two survival regression methods - Cox regression and parametric models - in patients with gastric adenocarcinomas who registered at Taleghani hospital, Tehran. METHODS: We retrospectively studied 746 cases from February 2003 through January 2007. Gender, age at diagnosis, family history of cancer, tumor size and pathologic distant of metastasis were selected as potential prognostic factors and entered into the parametric and semi parametric models. Weibull, exponential and lognormal regression were performed as parametric models with the Akaike Information Criterion (AIC) and standardized of parameter estimates to compare the efficiency of models. RESULTS: The survival results from both Cox and Parametric models showed that patients who were older than 45 years at diagnosis had an increased risk for death, followed by greater tumor size and presence of pathologic distant metastasis. CONCLUSION: In multivariate analysis Cox and Exponential are similar. Although it seems that there may not be a single model that is substantially better than others, in univariate analysis the data strongly supported the log normal regression among parametric models and it can be lead to more precise results as an alternative to Cox.