جستجوی مقالات مرتبط با کلیدواژه « Hierarchical Structure » در نشریات گروه « پزشکی »

Resilience is the process of coping and successfully adapting to challenging and life-threatening situations which is a kind of positive adaptation to adverse conditions. One of the most serious challenges in the industry is maintaining the health and safety of employees while performing their job duties. The present study aimed to quantitatively evaluate resilience engineering indicators in the metal industries of Kashan, Iran, and prioritize using the AHP method.

The present cross-sectional study had two stages. First, the resilience questionnaire was distributed among 110 employees of six metal industry companies in Kashan by convenience sampling method. In the second stage, a questionnaire consisting of 6 questions was completed by 15 occupational health and metal industry experts and then the prioritization of resilience indicators was determined using hierarchical analysis. Expert choice software was used to determine the priorities. The total resilience score was calculated and statistically compared by t-test and ANOVA after weighting.

The results indicated that the six main indicators of emergency preparedness, management commitment, reporting culture, awareness, learning culture, and flexibility with a final score of 0.921, 0,852, 0.517, 0.513, 0.485, and 0. 428 were ranked first to sixth.

Emergency preparedness and management commitment were the most important indicators and the total resilience score in the metal industries of Kashan was 0.619.

In the present study, structural challenges in the governance system of the Ministry of Health, Treatment, and Medical Education of Iran were analyzed based on the network structure model.

The present qualitative study was conducted using a meta-combined approach. The study used the findings of 19 qualitative studies, conducted between 2001 and 2018, and semi-structured interviews with 14 non-randomly selected experts of the Iranian health system. The Kapa-Cohen index was used to calculate the reliability, which was 80%. Also, the Waltz-Basel method was used to assess the content validity of the extracted indices, which was calculated to be 85%. Through the content analysis of the articles and interviews with experts, the structural challenges of the governance system were classified into seven dimensions, including policy-making and decision-making challenges, legal challenges, organizational challenges, managerial challenges, communication challenges, financial challenges, and regulatory challenges.

The findings showed that important challenges in the current governance structure of the Ministry of Health, Treatment, and Medical Education of Iran include the instability of managers, inconsistent speed of policy-making and changes in society, the separated activity of the Health Deputy and Treatment Deputy of the Ministry, lack of defined inter-sectoral cooperation, lack of transparency, lacked knowledge of the requirements of collective decision-making in health policy-makers, the lacked use of evidence-based policy-making, inadequate budget system, and lack of control over the private sector.

According to the challenges and their importance, health policy-makers and planners must provide practical and applicable solutions to address the challenges of the current governance structure.

Periodontal disease is one of the most common oral health problems. Clinical attachment loss occurs in sever periodontal cases (CAL>3). In this study, we applied a classic regression model and the models that consider the hierarchical structure of the data to estimate and compare the effect of different factors on CAL.   This cross-sectional study was performed in 375 pregnant women and 192 mothers of three-year-old children. The data were gathered from 16 health networks of Shahid Beheshti University of Medical Sciences, Tehran, Iran. CAL was determined for 6 teeth per person by a dentist according to WHO standard oral health examination form. Three-level and ordinary logistic regression analyses were applied for data analysis using the STATA software 14.   Of 3,402 examined teeth, 6.3% had CAL> 3mm. Based on the obtained results, the odds of CAL>3mm were 2.4 in the third semester compared to non-pregnant women. The odds of CAL>3mm were 2.86 in women without daily floss use compared to women with routine daily floss use. Posterior teeth were more likely to have CAL>3m than anterior teeth (OR = 1.65) (P-value < 0.05).   According to the AIC index, multi-level logistic regression model has a better fit than ordinary logistic regression model and can estimate the coefficients of factors related to CAL>3mm more precisely. The use of the ordinary logistic regression model in hierarchical data can result in underestimated standard errors of the estimated parameters.