Health care is becoming more patient-centered and, as a result, patients' experiences of care and assessment of satisfaction are taken more seriously. Patient satisfaction inluences treatment cooperation, and better cooperation leads to healthier patients in the long term. This generalization clearly applies in the dental school clinic setting. Furthermore, dental school clinics' administrators and clinicians should know about the dimensions of their patient satisfaction in order to provide the highest quality of care. The aim of this study was to review studies published between 1980 and March 2014 to identify the dimensions used to measure patients' satisfaction when they receive services in dental school clinics. The PubMed database was used to access published studies using patient satisfaction surveys in dental school clinics, and the dimensions used in these surveys were then categorized. Through several stages of searching in PubMed, the authors selected 41 articles from a total of 730; after further critical appraisal, nine articles were retained. Five dimensions included in patient surveys were identiied: quality, interaction, access, environment, and cost. Determining the dimensions used in patient satisfaction surveys in dental school clinics can assist academic dental institutions in providing the highest quality of care.
Background and Aim. The aim of this study is to assess the cortical bone thickness and interradicular distance between posterior maxillary teeth using cone beam computed tomography (CBCT). Methods and Materials. Cone beam computed tomography records of 35 patients (70 quadrants) from maxilla were evaluated. The images were analyzed using the NNT viewer software (version 23). The measurements were made on axial sections at 2, 4, 6, and 8 mm from CEJ. The optimal sites were defined in terms of mesiodistal palatal or buccal interradicular distance, alveolar cortical bone thickness, and palatal or buccal safe depth of the bone for miniscrew insertion. Descriptive statistics, paired t-test, and repeated measure ANOVA were used to analyze the data. Results. The mean buccal interradicular distance was the lowest between first and second molar (2.44 mm) and the highest between first and second premolar (3.28 mm). The mean palatal interradicular distance was the lowest between first and second premolar (3.64 mm) and the highest between second premolar and first molar (5.30 mm). The mean buccal safe depth was the lowest between canine and first premolar (1.96 mm) and the highest between first and second molar (2.61 mm). The mean palatal safe depth was the lowest between second premolar and first molar (3.35 mm) and the highest between first and second molar (3.56 mm). The thinnest and thickest buccal cortical thicknesses were detected on canine and first molar (1.04 mm) and on the second premolar and second molar (1.56 mm). Conclusion. The quantity and quality of the maxillary alveolar process is an important factor to decide where to insert the orthodontic miniscrews, necessitating careful preoperative evaluation.
Background Increasing social welfare and reducing poverty are to ensure the well-being of all classes of a society. Cities and villages are distinguished by cultural and economic disparities. The purpose of this study was to develop and present a comprehensive model on welfare and wealth components and their relationship with each other, as well as determining the contributing factors and variables affecting them by presenting a comprehensive model. Methods The components of wealth and welfare were determined based on the national data comprising 19261 rural and 18701 urban household participants. Initially, the conceptual model was drawn. Later, observed and latent variables of the model were analyzed and tested using AMOS software, in two exploratory and confirmatory factor analyses. Finally, the Structural Equation Modeling was used to analyze the data and investigate the causal relationship of latent variables. Results The findings showed that the factors generating wealth in the urban initiate from education and lead to employment and then into income and ultimately provide wealth and welfare. Plus, there is no separation between the concept of welfare and wealth in urban society. However, land ownership is the prerequisite for wealth and welfare issues in a rural community. Moreover, wealth and welfare are two distinct phenomena in rural areas. Conclusions The results of this study would provide the clear hints for effective policy making to resolve deprivation and poverty in Iranian rural and urban populations, prioritizing education for urban and land ownership for rural areas.
Background: Socioeconomic status (SES) is a criterion consisting of several components that encompass socioeconomic and cultural dimensions. This study aimed to design and develop a methodological guideline for calculating a single summary index (SSI) using the contributing variables of SES in a family unit. Methods: The data consisted of 18700 urban and 19200 rural households. Effective components of SES were extracted using two-step factor analysis and the structural equational modeling (SEM) method for both populations separately with AMOS software. Then, in order to customize and validate the weight of each component, the analytic hierarchy process (AHP) method was performed by a panel of experts. Finally, the SES index computational tool was developed as an SSI using all effective components by Excel software. Statistical analysis was done with SPSS software version 21. Results: In rural areas, the four wealth components of education, job, income, and family size were recognized as effective socioeconomic factors. Yet, in urban areas, family size was disregarded as an effective factor. In both rural and urban communities the three welfare components of appropriate nutrition, appropriate home appliance, and appropriate housing were similarly effective. The SES of rural population had a homogeneous distribution, while urban population did not follow a particular trend. Conclusion: The SES index impacts all aspects of life, especially health status. The introduced method is comprehensive and applicable to both rural and urban populations. Due to ever-changing lifestyles, constant technological advances, and sociopolitical changes in each society, the tool requires modification in a specific time intervals.
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