Jundishapur Journal of Health Sciences
Volume:16 Issue: 3, Jul 2024

Context: 

Rigidity is a cardinal motor symptom in Parkinson's disease (PD), and evaluating these symptoms remains a significant challenge for researchers and neurologists. This scoping review utilizes a methodology to extract, categorize, and compare biomechanical parameters (MPs) for rigidity assessment from studies spanning the years 1980 to 2023.

Evidence Acquisition: 

Electronic databases, including Google Scholar, ScienceDirect, PubMed, Springer, and Civilica, were systematically searched to identify research on rigidity assessment in PD utilizing various biomechanical parameters. Additionally, reference lists of identified papers were reviewed to identify additional relevant studies. A total of 53 articles met the inclusion criteria and were evaluated.

Based on the results of 53 studies, viscoelastic parameters, electromyogram (EMG) signal measurements, impedance, work, and torque-angle slopes (stiffness) were identified as essential and commonly recommended parameters for rigidity evaluation in Parkinsonian patients. Furthermore, correlations between these parameters and clinical scores have been reported. Introducing biomechanical parameters capable of identifying rigidity and its severity, along with their classification, could contribute to a better understanding, modeling, and evaluation of rigidity.

This review could be of interest to both biomechanists and neurologists, facilitating a common language for discussing aspects of rigidity in diseases such as Parkinson's.

Students with social anxiety disorder (SAD) face unique challenges that can significantly impact their academic performance, social interactions, and overall well-being.

This study aimed to explore the impact of metacognitive therapy (MCT) on depression, emotion regulation, and self-concept among students diagnosed with SAD.

The study employed a quasi-experimental research design with a pre-test-post-test format and a control group. The statistical population consisted of students diagnosed with SAD at the University of Tehran in 2022. A total of 36 students with SAD were selected for the research sample through purposive sampling and were divided into experimental (n = 18) and control (n = 18) groups. The experimental group participated in ten 90-minute sessions of MCT, while the control group did not receive any intervention. Data collection involved administering the Liebowitz Social Anxiety Scale, Beck Depression Inventory, Emotion Regulation Questionnaire, and Beck Self-concept Test. The collected data were analyzed using multivariate analysis of covariance (MANCOVA) in SPSS-24.

The results indicated that Metacognitive Therapy (MCT) significantly decreased depression (F = 50.65, P = 0.001, η² = 0.63) and significantly increased cognitive reappraisal (F = 61.81, P = 0.001, η² = 0.67), expressive suppression (F = 34.72, P = 0.001, η² = 0.54), and self-concept (F = 48.53, P = 0.001, η² = 0.62) in students with SAD.

The findings of this study enhance our understanding of the therapeutic benefits of MCT for students struggling with SAD. By addressing critical psychological areas such as depression, emotion regulation, and self-concept, MCT shows promise as a valuable intervention for improving the well-being and functioning of students dealing with SAD.

Prehospital factors are critical contributors to delays in managing patients with ST elevation myocardial infarction (STEMI), potentially leading to increased mortality and morbidity. Identifying and addressing these obstacles could significantly reduce the mortality and morbidity of these patients and enhance healthcare performance.

This study aims to evaluate the prehospital factors associated with delays in primary percutaneous coronary intervention (PPCI) among patients with STEMI.

In this prospective study, 394 STEMI patients treated with PPCI were evaluated, with the interval between symptom onset and the start of the procedure being measured and recorded. Patients were categorized into two groups based on this interval: Appropriate and delayed (< 90 minutes vs. ≥ 90 minutes). The potential predictors of delay were identified and assessed.

In this study, 394 STEMI patients were evaluated and categorized into 192 patients with delayed PPCI and 202 patients with on-time PPCI. Multivariate analysis revealed that being female (OR: 1.59, 95% CI: 1.08 - 2.01, P-value: < 0.01), having no past medical history of cardiovascular disease (CVD) (OR: 1.49, 95% CI: 1.09 - 1.90, P-value: < 0.01), no family history of CVD (OR: 1.28, 95% CI: 1.04 - 1.53, P-value: 0.03), a lower education level than academic (OR: 1.44, 95% CI: 1.05 - 1.84, P-value: < 0.01), symptom onset between 18:00 and 06:00 (OR: 1.58, 95% CI: 1.10 - 2.06, P-value: 0.01), and transport by ambulance versus private vehicle (OR: 1.57, 95% CI: 1.07 - 2.08, P-value: < 0.01) were significantly associated with a higher risk of delayed PCI. Conversely, higher socioeconomic status (OR: 0.68, 95% CI: 0.51 - 0.86, P-value: 0.02) and having a caregiver at home (OR: 0.52, 95% CI: 0.32 - 0.72, P-value: < 0.01) were significantly associated with a lower risk of delayed PPCI.

Reducing factors that contribute to delays in PPCI can lead to improved public health outcomes and greater health opportunities for the population. Delays in STEMI patients were significantly associated with living in rural areas, lower education levels, and female gender. Conversely, using private vehicles for transport, having a caregiver present, and higher socioeconomic status may reduce the risk of delayed PPCI.

Self-care is a fundamental aspect of health, encompassing conscious and purposeful actions by individuals for themselves, their children, and their families to maintain health.

This study aimed to determine the effect of an educational intervention based on the Health Belief Model (HBM) on self-care behaviors among health workers in comprehensive urban health service centers in Rudbar in 2019.

In this quasi-experimental study, 89 health workers from comprehensive urban health service centers in Rudbar city, Gilan, participated. The participants were randomly assigned into control and intervention groups. An educational intervention, consisting of five 60 - 75 minute sessions based on the HBM, was designed and implemented for the intervention group. Outcome data were collected before and three months after the educational intervention using a questionnaire that measured HBM constructs and health-promoting self-care behaviors. Data analysis was performed using the chi-square test and Mann-Whitney U test.

The age range of most participants (43%) was 30 - 39 years, and 86% of participants were female. Both experimental and control groups were comparable in demographic characteristics, HBM constructs, and health-promoting self-care behavior at pretest. The educational intervention based on the HBM improved the mean scores of the HBM constructs (except for perceived benefits) and dimensions of self-care behavior (P < 0.05 for all). The average score of self-care behavior in the intervention group increased from 128.4 before the intervention to 148.37 after the intervention.

According to the results, using the HBM, with its suitable methods and structure for engaging employees actively, was effective for designing educational interventions to promote self-care behaviors in health workers. Therefore, it can be used as a suitable framework for planning educational interventions to enhance self-care behaviors among health workers.

Municipal solid waste (MSW) landfills are significant contributors to the emission of greenhouse gases, particularly methane, during the breakdown of waste materials. Researchers have undertaken extensive investigations into quantifying methane emissions from landfills, utilizing various methodologies beyond reliance on the LandGEM model. Numerous studies have underscored the efficacy of this model in predicting methane generation and exploring its utility in activities such as energy generation and emission mitigation strategies.

Municipal solid waste landfills are vital contributors to greenhouse gas emissions, notably methane, during waste decomposition. Significant research has focused on estimating methane output from landfills, utilizing various approaches beyond the LandGEM model. Studies highlight the model's potential in assessing methane generation and its relevance to activities like energy generation and emission management.

The LandGEM simulation model is employed to forecast future waste generation and provide valuable insights into the environmental consequences of landfill management on the island. By analyzing population data and waste generation statistics from 2023 to 2042, the study utilizes the LandGEM software to estimate methane emissions, incorporating site-specific data and waste composition analysis.

The findings reveal that 36% of the total waste on Kish Island consists of putrescible material, with food waste being a significant component. Over the study period, approximately 1,282,637 tons of waste are projected to be disposed of in the Kish landfill. The LandGEM model predicts the highest landfill gas emission in 2043, primarily methane, along with carbon dioxide and non-metallic organic compounds. The estimated quantities for these gases in 2043 are 5.415E+03, 1.486E+04, and 2.327E+02 metric tons, respectively.

This research highlights the importance of tailored waste management strategies to mitigate environmental impacts and emphasizes the need for efficient gas collection systems. A proposed gas collection system combining vertical wells, horizontal trenches, and under-membrane pipes is discussed to enhance efficiency and reduce environmental risks. The study provides valuable insights into waste management and landfill gas emissions on Kish Island, underscoring the significance of accurate emission prediction and effective management to minimize environmental consequences and optimize the utilization of renewable energy resources.