mojtaba abbaszadeh

The high prevalence of mental health problems in prisons has become a global problem. The purpose of this study was to compare the efficacy of group therapy based on acceptance and commitment, cognitive-behavioral therapy, and reality therapy on depression, anxiety, aggression, and physical complaints of male inmates of Isfahan Central Prison.

The present study was a one-blind randomized controlled trial study (pre-test, post-test and follow-up) with a control group. The statistical population included all male prisoners of Isfahan Central Prison, from whom 120 individuals were selected based on systematic random sampling and randomly assigned to three experimental groups and one control group (per group n=30). The experimental groups received group therapy based on acceptance and commitment, cognitive-behavioral therapy, and reality therapy for 12 sessions of 90 minutes, and the control group was placed on the waiting list. Subjects completed the checklist of symptoms of mental disorders (SCL-90) by Dragotis et al., (1994) in three stages. Analysis of variance with repeated measurements and SPSS software was used to analyze the data.

The results of the analysis of variance with repeated measurements showed that group therapy based on acceptance and commitment therapy, cognitive-behavioral therapy, and reality therapy were effective in improving the symptoms of depression, anxiety, aggression, and physical complaints (p<0.05). Also, according to the results of the posthoc test, there was a significant difference between the three treatment groups in the post-test in the research variables (p<0.05).

Group therapy based on acceptance and commitment, cognitive-behavioral therapy and reality therapy improved the symptoms of depression, anxiety, aggression and physical complaints in male prisoners, and cognitive-behavioral  therapy was superior.

The rising prevalence of obesity, as well as its detrimental effects on the brain, has drawn attention to specific dietary patterns. This study aimed to examine the effect of the Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) pattern on anthropometric parameters, hunger hormones, and brain structures in overweight and obese women. 

This randomized trial was conducted in Shiraz between October 2018 and March 2019. We analyzed 37 healthy women with a mean age of 48±5.38 years and a Body Mass Index (BMI) of 32±0.69 Kg/m2. Participants were randomly allocated to a hypocaloric modified MIND diet or a hypocaloric control diet. Differences in anthropometric, laboratory analysis, and brain structure were determined at baseline and three-month follow-up. Data were analyzed using SPSS 22.0. Independent and paired sample t test were used to determine between and within differences. We also used mixed-model ANOVA to compare the mean differences between two-factor groups. 

A more significant weight reduction (P<0.0001), BMI (P<0.0001), percentage of  body fat (P=0.03), waist circumference (P=0.01), and Leptin concentration (P=0.03) were found in the MIND diet group. The results also showed a significant increase in Ghrelin (P=0.002) and GLP-1 (P=0.01) levels in the MIND diet group. The findings revealed no differences in the whole and regional brain structures between the two groups. 

For the first time, this study showed that the MIND diet intervention could improve the devastating effect of obesity on metabolic profiles and anthropometric parameters. However, we could not find its effect on brain structures.Trial registration number: IRCT20190427043387N1.A preprint of this study was published at https://www.medrxiv.org/content/10.1101/2020.06.28.20142018v1.

Looking at developing countries that have experienced extensive industrial progress and high growth rates in recent decades, it can be seen that investment has been one of the most important economic factors that has played a significant role in their development.Therefore, it can be said that investment is one of the most important factors in economic growth and development of any country. In today's world, energy has a special place and importance for all countries of the world. In the last two decades, energy has been mentioned as one of the important factors of production, which along with other factors of production such as labor, capital and raw materials, plays a decisive role in the economic life of countries. So, In the present paper, a dynamic investment model with combined data related to Iranian industries with double-digit ISIC codes during the years 1388 to 1397 is estimated. The main purpose of this article is to investigate the effect of energy carrier prices and firm size on the level of investment in the industrial sector. For this purpose, a dynamic programming system and Euler equations are used.The basic model used in the present study is the dynamic investment model presented below and is based on the Euler equation method introduced by Abel (1980) and modified by Rati et al. (2011).It is assumed that capital and energy are the only inputs to production and debt in finance.We consider managers or shareholders, who choose investments and loans that maximize the present value of dividends subject to capital accumulation and external financing constraints.

Musculoskeletal disorder (MSD) is one of the important problems concerning the staffschr('39') health and productivity in the workplace. Nutritional status and consumption of some foods are also among the determining factors of MSD. So, this study aimed to evaluate the correlation of diet and consumed food groups with MSD.

This cross-sectional study was conducted on 100 office workers. The participantschr('39') anthropometric parameters and their dietary information were collected using a semi-quantitative food frequency questionnaire. The findings were categorized into nine levels. The total scores were calculated for all the items per food group and per person. Nordic musculoskeletal questionnaire was also administered to evaluate the MSD symptoms in nine parts of body.

The score of consumed food groups was compared between individuals “with pain” and “without pain” in nine parts of the body. The scores of fruit intake in individuals “with pain” and “without pain” were 2.94 ± 1.27 vs. 3.29 ± 1.16 and 2.81 ± 1.10 vs. 3.49 ± 1.38 in terms of neck and wrists, respectively. The difference between the two groups were significant (P < 0.05). Furthermore, the participants with pain in the neck consumed significantly lower amounts of cereals and nuts (P = 0.03, 0.04). In the case of the shoulder pain, consuming legumes and nuts in the “without pain” group was higher than the group of participants who had pain (P = 0.01, P = 0.03). Fat intake was higher in the patients who had pain in their hips (P = 0.02).

Less pain was reported in the musculoskeletal system by higher consumption of fruits, nuts, and legumes. It seems that plant-based dietary pattern is more effective in musculoskeletal health.

Electrocardiography is one of the most useful and common tools for examining heart function. In studies in the 1960s, heart rate variability (HRV) was introduced and used as a non-invasive tool to evaluate the functions of the autonomic nervous system and other functional disorders of the heart under various conditions. In addition to the clinical applications of heart rate variability, this physiological parameter is also widely used in ergonomics and occupational health. In the study of mental workload, exposure to industrial noise, shift work, stress, and other parameters related to the workplace benefit heart rate variability. Heart rate variability is regulated by the autonomic nervous system and by the sinoatrial (SA) node. The autonomic nervous system is divided into sympathetic and parasympathetic branches, the autonomic nervous system is divided into sympathetic and parasympathetic branches, thereby affecting the heart rate and heart rate variability. Sympathetic activity tends to increase heart rate and decrease heart rate variability, while parasympathetic tend to reduce heart rate and increase heart rate variability. The most prominent component of the variable heart rate period is a respiratory arrhythmia (RSA), which is considered to be 0.15 to 0.4 Hz. The high-frequency component is only affected by parasympathetic neural activity. Another component of heart rate variability is the low-frequency (LF) component in the frequency range, 0.04 to 0.15 Hz. This component is affected by sympathetic and parasympathetic neural activity. Many computational methods have been developed for HRV analysis, each of which is associated with strengths and weaknesses. Although there may still be difficulties in interpreting this index, it provides researchers and health experts with reliable non-invasive physiological information. HRV parameters can be classified in terms of time, frequency, and nonlinear methods. The commercially available ECG equipment does not usually include HRV features due to the lack of standard diagnostic protocols. As an alternative to this commercial software, many simple, online and free, device-independent, and portable software has been developed for HRV analysis and cardiovascular research.Heart Rate Variability Quantification: Heart rate variability can be measured in long-term (24 hours), short-term (5 minutes), and very short-term periods (less than 5 minutes) and can be analyzed as time- -domain, frequency-domain, and non-linear.1. Time-domain measuresThe simplest method to analyze heart rate variability is time-domain. Analysis of heart rate variability in the time-domain is performed through both statistical and geometric analysis, both of which are based on heart rate or RR intervals between successive QRS series. Using these methods, the heart rate can be assessed at any point in time or between normal consecutive sets. Statistical parameters recommended by the European Society of Cardiology and the American Society of Pacing Electrophysiology include: 1) SDNN 2) NN50 3) SDSD 4) SDANN 5) RMSSD 6) SDSD 7) NN50 count (Table 1).Table 1: time-domain measures of HRV Variable Units Description [1]SDNN ms Standard deviation of all NN intervals SDRR[2] ms standard deviation of RR interval series SDANN ms Standard deviation of the averages of NN intervals in all 5 min segments of the entire recording SDNN index ms Mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording pNN50 % NN50 count divided by the total number of all NN intervals HR Max –HR Min bmp The average difference between the highest and lowest HRs during each respiratory cycle rMSSD ms Root mean square of successive RR interval difference HRV triangular index   Integral of the density of the RR interval histogram divided by its height TINN ms Baseline width of the RR interval histogram  2. Frequency-domain measures:Time-domain measurements information about the overall change in time series or maximum variable amplitude, but no information about periodic heart rate fluctuations. Data frequency domain analysis provides information on how power distribution is a function of frequency. According to the European Society of Cardiology, the power range of a healthy person is usually divided into four main frequency bands. The range of components used is usually: high-frequency (0.4 - 0.15 Hz), low-frequency (0.15-0.04 Hz), very low frequency (0.04 - 0.003 Hz) and infinitely low frequency (<0.003 Hz).Table 2: frequency-domain measures of HRV Variable Units Description ULF power ms2 Absolute power of the ultra-low-frequency band (≤0.003 Hz) VLF power ms2 Absolute power of the very-low-frequency band(0.0033–0.04 Hz) LF peak Hz Peak frequency of the low-frequency band (0.04–0.15 Hz) LF power ms2 Absolute power of the low-frequency band (0.04–0.15 Hz) LF power nu Relative power of the low-frequency band (0.04–0.15 Hz) in normal units LF power % Relative power of the low-frequency band (0.04–0.15 Hz) HF peak Hz Peak frequency of the high-frequency band (0.15–0.4 Hz) HF power ms2 Absolute power of the high-frequency band (0.15–0.4 Hz) HF power nu Relative power of the high-frequency band (0.15–0.4 Hz) in normal units HF power % Relative power of the high-frequency band (0.15–0.4 Hz) LF/HF % Ratio of LF-to-HF power  3. Nonlinear measures:The parameters commonly used in the analysis of time and frequency domain HRV are not always suitable for analysis due to the existence of various nonlinear phenomena in physiological signal parameters. Therefore, the use of nonlinear techniques is recommended. Pincus developed Approximate Entropy (ApEn) as a nonlinear complexity index to determine the random quantity of a physiological time series. Richman and Moorman developed a sample entropy (SampEn), a new family of statistics, to measure the complexity and data of clinical and experimental time series, and compared it to ApEn.Common heart rate analysis tools: HRV analysis has led to the development of several commercial and non-commercial software. Most commercial equipment for heart monitoring and HR analysis includes software that depends on devices for HRV analysis, but there are also software-independent. In addition to commercial tools, several free non-commercial software have been developed.Kobius:This powerful software is based on MATLAB. Kobius (version 2.1) is a free and non-commercial software for researchers and physicians (http://kubios.uef.fi 7). This software can analyze HRV in time-, frequency-domine, and non-linear indicators. Kobius is compatible with Windows and Linux operating systems, and supports both ECG and RR data formats, and performs the pre-processing operations required to detect QRS and correct corrections.gHRV:gHRV is based on the Python programming language and performs heart rate variability analysis for a specified period of time. The software can be easily run on Windows, Apple OS X Linux, or GNU operating systems. Data and formats supported by gHRV include heart rate in WFDB and ASCII formats, (IBI (InterBeat Intervals ASCII files), heart rate monitoring in polar (common heart rate recording form), and Santo wristbands. The pre-processing step involves deleting and interpolate. Updated versions of gHRV are available for free at http://ghrv.milegroup.net. This website provides information on how to download, install, and use. GHRV analyzes HRV in terms of time, frequency, and nonlinear domain.KARDIA:KARDIA is based on MATLAB programming language. All functions of this software are written in a single program (kardia.m) which is available for free (at http://sourceforge.net/projects/mykardia/). Execution of m-file requires MATLAB 7 or updated version with MATLAB signal processing toolbox. KARDIA can calculate the heart rate in any method sampled by the user by interpolating using fixed, linear, or splint methods. Linear parameters of heart rate variability in time and frequency range and nonlinear parameters can be quantified by analyzing fluctuations.VARVI:VARVI is free software designed in Python programming language for HRV analysis in response to various visual stimuli. This HRV software measures the person who is watching a video. This software has wide applications in psychiatry and psychological studies. VARVI software is available at varvi.milegroup.net.RHRV:This software is based on R programming language for HRV statistical calculations. This programming language (R) is originally implemented in the S language and is compatible with Windows and MacOSX. Several advantages of this software are available. The data file containing the heart rate in WFDB and ASCII format is entered into the software. Software package is available for download and installation.ARTiiFACT :ARTiiFACT is a MATLAB-based tool with compiler 4.13 for artifact processing and HRV analysis. ARTiiFACT has options for processing a set of data, analyzing HRV by the autoregressive and nonlinear domain model, as well as correcting respiration-related distortions, which allows raw data from the ECG to be applied bypassing the filter over, and over. Set their bypass at the appropriate critical frequency. Software, tutorials and user manuals are available for free upon request (email tobias.kaufmann@uni-wuerzburg.de).LabVIEW:LabVIEW software is a design-specific operating system that provides a development environment. It can also be used to analyze heart rate variability. LabVIEW is supported by Windows, Linux GNU or Apple OSX.POLYAN:POLYAN is based on MATLAB programming language and has a computing environment with the aim of excellent performance in numerical and visual calculations. The software can be easily run on Windows operating systems, Linux GNU or Apple OS X. POLYAN is a free software specifically designed for the simultaneous analysis of multiple signals (multi-parameter approach) to evaluate the performance of an Autonomic nervous system.aHRV:aHRV is a commercial software developed by Nevrokard for heart rate variability analysis. The software supports data in the form of ASCII, binary files in European data format and many dedicated formats.

HRV plays an important role in assessing ANS fluctuations in healthy individuals and heart patients and promoting understanding of disease mechanisms and physiological phenomena. Currently, there are commercial or semi-commercial tools that possible simultaneous ECG recording, respiration, blood pressure. Commercially available recording systems are not usually separated by HRV analysis features. Software developers have not prioritized this because HRV is not yet included in standard diagnostic protocols. However, various developers and research groups are developing software tools tailored to their specific needs. [1] - Standard deviation of NN intervals[2] - Standard deviation of RR intervals

Car Accident reports shows that the main cause of accidents is driver error and unsafe behavior. Workload of the major factors affecting driver that has a direct impact on the incidence of traffic accidents. This study aimed to evaluate aspects of mental work load of auditory-verbal secondary task was performed while driving.
Twenty professional bus driver randomly selected and participated in this study.
The bus driving simulator and the burden of driver activities (DALI) was used. Experiment was created from two blocks: the first block drivers are only driving activity carried out and the second block in addition to the driver, auditory-verbal secondary task also responded to. To compare the results of two blocks, independent t-test and to investigate the relationship between a brake reaction time and mental load analysis, Pearson correlation coefficient was used.
The results showed that secondary task all aspects of mental workload increases significantly.
A brake reaction time and the number of collisions dramatically increased in terms of the secondary task. The relationship between mental workload and increase reaction time was seen braking and collision numbers.
The results of this study suggest that secondary task during driving can cause to increase the brake reaction time and risk of accidents by increasing the drivers’ mental workload of drivers and interfering with driving activity. These results indicate that driving experience does not reduce the effect of secondary activity during driving.

Musculoskeletal disorders are among the most important and common occupational injuries leading to disability of employees. An increasing trend of musculoskeletal disorders among sonographer specialists has been reported in the literature. This study, therefore, set out with the aim of assessing the musculoskeletal disorders among sonographer specialists working in centers covered by Tehran University of Medical Sciences.
In this cross-sectional study all sonographer specialists of Tehran University of Medical Sciences (totally 53 specialists) were selected on census method. Customized questionnaires based on Standardized Nordic Questionnaire were used to assess musculoskeletal disorders in this community. SPSS software was exploited to data analysis. All participants were informed in terms of the study objectives and ethical issues such as confidentiality of study community were all considered.
The prevalence of WMSDs in current study was 86%. Pain and discomfort wasmore often reported in neck, shoulder and wrist, respectively. Sustained probe usage, types of patient table andchair as well as sustained shoulder abduction were the most risk factors that perceived by ultrasound specialists. Ergonomic evaluations showed that changes should be made soon. Age, experience, scanning hours per week and break duration provided the largest set of significant clusters of pain in body sections (p Since scanning is considered as the major task of sonographers, the prevalence of musculoskeletal disorders was high among participants in the present study. Ergonomics evaluations and interventions of sonographer’s workplace to allow them to remain productive are necessary.

 The present study aimed to investigate the relationship between traffic noise and drivers' reaction time (RT) and their error in estimates of movement time. 

 In over all, 80 university students with at least 3 years postlicense experience of driving were divided into two groups including traffic noise exposure and control group. S5 test of Vienna test system package was used for assessment of RT. In addition, time-movement anticipation was employed for measuring the rate of error in estimation of movement time before exposing to the traffic noise. After a 1-month interval, participants in the experimental group were exposed to traffic noise about 2 h and the tests were performed again for both groups. 

 Accordingly, RT was statistically higher after traffic noise exposure for male and female. However, there was no significant difference between time of movement before and after exposure to traffic noise both for male and female (P > 0.05). In addition, no difference was shown between movement time, number of accurate estimates, and number of estimates with gross errors before and after of traffic noise exposure in experimental and control group. 

 The results suggest that traffic noise may be associated with poorer mental processing, which can result in longer RT during driving. Therefore, traffic noise would expose drivers to consequent accidents and incidents.

One of the most important subjects in the analysis of driver’s behavior had been situation awareness during the past decade. However، no study has been investigated the relation among component of situation awareness and performance and cognitive abilities of bus drivers. Current study aimed to survey relationship between bus drivers’ situation awareness، driving performance and cognitive abilities using driving simulator. In this study، 30 professional bus drivers who have diploma or higher degree participated. Situation awareness measured by SAGAT technique and tests UFOV، EFT and WMS were used for measuring of cognitive abilities. Brake reaction time and lane departures were criteria for driving performance. Accordingly، the result showed significant relation between drivers’ situation awareness before and after hazard conditions. Among WMS، divided attention، selective attention and EFT with level 1 of situation awareness was seen significant relation. The result of current study released a significant correlation among WMS and divided attention with lane departure. Results showed، in general، the driver''s situational awareness in dangerous conditions increases. The study showed that cognitive ability affects only level 1 of situational awareness. According to role of situational awareness in driving performance، the results of lane keeping showed that perception might be a key factor in driving performance.

Shift work is one of the inevitable consequences of technology in which in the recent years numerous studies have been done about its effect on health. Somatic, psychological and social disturbances are among the problems that are seen more in people with shift work than other people. The current study aims to determine the prevalence of these disturbances in one of the LPG and gas refinery complex, oil companies. This cross-sectional case-control study was carried out at 180 shift-work people as case group and 90 day-work people as control group at the security section of the oil refinery company. Data of shift workers were collected with Survey of Shift workers (SOS) questionnaire. The questionnaire consisted of questions on demographic characteristics and health problems associated with shift work. Statistical analyses were performed using SPSS Ver.19 at a significance level of 5%. The mean (SD) of shift working and day-work workers were estimated to be 41 ± 4.8 and 39 ± 4.1 years, respectively. The results showed that health problems shift-workers were more prevalent than day-work workers. The differences were significant in gastrointestinal disease, cardiovascular disease, hypertension and fatigue (P < 0.05). According to the result of this study, shift work can be a risk factor for the incidence of somatic and psychological disturbances. Initiatives should be implemented to prevent these complications in shift workers.

Musculoskeletal disorders (MSDs) represent one of the leading causes of occupational injury and disability in the developed and industrially developing countries. This study was conducted to investigate the prevalence of MSDs and evaluate the risk of these disorders among welders of a steel manufacturing industry. This descriptive-analytical study was achieved on all 243 welders employed in a steel manufacturing industry. Nordic Musculoskeletal Questionnaire (NMQ) was used to study the prevalence of MSDs. Meanwhile, QEC technique was employed to evaluate the risk of exposure to these disorders. For data analysis, central statistical indices, T-test and Chi-square test were used. The results suggested the highest prevalence of symptoms of musculoskeletal disorders in low back, trunk and knees, respectively. QEC technique showed a high and very high risk of exposure to MSDs in 64.6 % of welders. This study demonstrated that the prevalence of WMSDs in welders under study was high. Based on the obtained results, the most significant ergonomic problems in welders were found to be awkward postures, manual material handling and back bending and twisting. Furthermore, the results suggested that QEC can present reliable findings in evaluating the risk level of exposure to WMSDs.