Journal of Advanced Biomedical Sciences

Design and Psychometric Evaluation of the Iranian Version of Public Awareness of Anxiety and Depression Symptoms Scale: A Mixed Methods Study

2025-07-02T12:21:41+00:00

Background & Objectives: Awareness of the symptoms of anxiety and depression, two prevalent psychiatric disorders, can significantly contribute to the diagnosis, management, and prevention of mental health conditions. The assessment and measurement of awareness levels regarding anxiety and depression symptoms necessitate the utilization of specialized and validated instruments in this domain. This study was conducted with the aim of designing and psychometrically evaluating the Iranian version of Public Awareness of Anxiety and Depression Symptoms Scale.

Materials & Methods: The present study employed an exploratory sequential mixed methods design and was conducted in two distinct phases. In the qualitative phase, questionnaire items were initially extracted. Subsequently, in the quantitative phase, the validation of the designed instrument was undertaken, utilizing face validity, content validity; construct validity, internal consistency, and stability assessments.

Results: The initial questionnaire comprised 42 items, which were reduced to 30 items following multiple sessions and revisions by the research team. According to the results of the exploratory factor analysis, factor loadings for the items ranged from 0.57 to 0.89, all of which were statistically significant. The two dimensions introduced in the original instrument were confirmed with acceptable values. The intra-class correlation coefficient for the entire instrument was calculated at 0.92. Furthermore, the reliability of the instrument, assessed through internal consistency using Cronbach’s alpha, was determined to be 0.98 for the entire instrument.

Conclusion: The present questionnaire is a valid and reliable instrument for assessing public awareness of anxiety and depression symptoms. Consequently, healthcare system managers and policymakers can employ this tool to evaluate public awareness of anxiety and depression symptoms.

Food Insecurity Status and Its Associated Factors Among Residents of the City of Fasa (Southwest Iran), 2022

2025-07-02T12:22:01+00:00

Background & Objectives: Due to the potential adverse effects of unbalanced food consumption on physical, social, and mental health, the careful monitoring and assessment of food insecurity and hunger is of critical importance. This study aimed to assess the prevalence of food insecurity and its associated factors among the residents of the city of Fasa in southwest Iran.

Materials & Methods: This cross-sectional, descriptive-analytical study was conducted during the second half of 2022 and included 715 households (comprising 2,867 individuals from an approximate population of 110,000 in Fasa). A cluster sampling method was employed to select participants. Data on food insecurity were collected using a standardized questionnaire.

Results: The prevalence of food insecurity in this study was 42%. Moreover, food insecurity was found to be significantly associated with female-headed households, households headed by individuals with substance addiction, larger household size, and lower income levels. In contrast, no significant relationship was observed between food insecurity and smoking habits (cigarettes or hookah), educational background, or the employment status of either parent.

Conclusion: The findings of this study demonstrate that nearly half of the surveyed households experienced some degree of food insecurity, highlighting a significant public health concern in this region. Policymakers, along with health and development organizations, may utilize these results to develop targeted strategies aimed at mitigating the adverse impacts of food insecurity.

An Efficient Model based on the k-Nearest Neighbors Algorithm for Parkinson’s Disease Detection

2025-07-02T12:22:25+00:00

Background & Objectives: Parkinson’s disease (PD) is a neurological disorder characterized by the progressive loss of brain cells, significantly affecting body movement. Early diagnosis not only reduces healthcare costs but also helps prevent adverse outcomes for patients. Researchers are increasingly utilizing intelligent machine learning methods to enhance the accuracy and efficiency of PD diagnosis.

Materials & Methods: Although several data mining techniques have achieved reasonable accuracy in diagnosing PD, they often encounter trade-offs between accuracy and execution speed and are sensitive to parameter settings and data outliers. The k-Nearest Neighbors (KNN) algorithm, for example, is valued for its simplicity and speed but suffers from limitations such as sensitivity to neighborhood size and reliance on majority voting, both of which can degrade performance. To address these challenges, this study employs an advanced variant of the KNN algorithm, referred to as Multiple Local Mean Vector-based Nearest Neighbor Classification (MLMV-NNC), alongside a neural network classifier trained using Bayesian backpropagation. The MLMV-NNC method enhances traditional KNN by incorporating multiple local mean vectors, thereby reducing the influence of outliers and improving classification robustness.

Results: The proposed diagnostic approach demonstrates superior performance in detecting PD. Specifically, the model achieves an accuracy of 99%, precision of 96%, specificity of 98.6%, and sensitivity of 100%. Furthermore, a comparative analysis with traditional methods, including Support Vector Machines (SVM) and Artificial Neural Networks (ANN), highlights the superior performance of the proposed method.

Conclusion: The findings indicate that the combination of MLMV-NNC and a neural network trained via Bayesian backpropagation constitutes a highly effective approach for diagnosing PD. This method not only improves accuracy but also mitigates common challenges such as sensitivity to parameter settings and data outliers, offering a promising alternative to conventional classification techniques.

Exploring the Impact of Diabetes Mellitus and Hypertension on Depression in Youth: Insights from the Fasa Cohort

2025-07-02T12:22:51+00:00

Background & Objectives: Depression frequently coexists with chronic conditions such as diabetes mellitus (DM) and hypertension (HTN), compounding health risks and complicating disease management. While this relationship is well-documented in adults, its dynamics among adolescents and young adults remain insufficiently explored, particularly in culturally diverse contexts. This study aimed to assess the prevalence and associations of major depressive disorder (MDD), DM, and HTN among individuals aged 15–34 years in Fasa, Iran.

Materials & Methods: A cross-sectional analysis was conducted on 3,014 participants from both rural and urban areas of Fasa. Data on depression, DM, and HTN were collected using validated self-report questionnaires and clinical assessments. Statistical analyses included Chi-square tests and logistic regression models to evaluate associations, adjusting for age, gender, smoking status, and other potential confounders.

Results: Depression and DM were more prevalent among males (30.2% and 2.1%, respectively) compared to females (20.4% and 1.2%), whereas HTN was more common among females (7.0%). Depression was significantly associated with HTN in both univariate (OR = 2.710) and multivariate (OR = 2.547) models. Age and smoking status emerged as significant predictors of depression. Although a potential association between depression and DM was identified in the univariate analysis, it did not remain statistically significant after adjustment.

Conclusion: This study highlights a significant gender-specific association between depression and HTN among youth, emphasizing the necessity for integrated, age-specific, and gender-sensitive mental and physical health interventions. No robust association was found between depression and DM.

Challenges of Patient Management in Aerial Emergency Services: A Qualitative Study

2025-07-02T12:23:26+00:00

Background & Objectives: Air ambulances play a crucial role in delivering medical care to patients in high-risk or life-threatening situations within the shortest possible time. However, during such missions, aerial emergency medical personnel face numerous challenges in patient management that negatively impact their performance. Accordingly, this study aims to explore the barriers to effective patient management in aerial emergency medical services as perceived by prehospital emergency care personnel in southern Iran.

Materials & Methods: This qualitative study employed purposeful sampling to select participants. A total of 21 in-depth, semi-structured individual interviews were conducted with emergency medical personnel experienced in aerial emergency services. The data were analyzed using Graneheim and Lundman’s content analysis approach .

Results: The qualitative data analysis yielded three main themes and nine sub-themes. The main themes included: (1) Inefficient management of human and organizational resources, (2) Lack of professional competencies, and (3) Occupational stress and physical injuries .

Conclusion: Senior managers in emergency medical services are encouraged to utilize the findings of this study to identify key factors that hinder effective patient management and care delivery in aerial emergency settings. Implementing targeted interventions to address these challenges may enhance personnel performance, improve patient safety, and elevate the overall quality of services provided.

Quercetin Ameliorates Clothianidin-Induced Cardiotoxicity in Rats

2025-07-02T12:25:32+00:00

Background & Objectives: Clothianidin, a widely used neonicotinoid insecticide, has raised environmental and health concerns due to its potential toxicity. Quercetin, a flavonoid abundant in various dietary sources, exhibits potent antioxidant properties and effectively scavenges reactive oxygen species (ROS). The present study aimed to evaluate the potential protective effects of quercetin against clothianidin-induced cardiotoxicity in a rat model.

Materials & Methods: Forty-two rats were randomly assigned to six groups: (1) Normal control group: rats received 0.9% NaCl intraperitoneally (IP); (2) Vehicle control group: rats were administered 5% dimethyl sulfoxide (DMSO) IP daily; (3) Clothianidin group: rats received clothianidin (20 mg/kg/day) every three days for 21 days (seven injections); (4–6) Treatment groups: rats received clothianidin as in group 3, concurrently with quercetin at doses of 2.5, 5, or 10 mg/kg IP daily for 35 days. Serum enzyme activities of creatine kinase-MB (CK-MB) and lactate dehydrogenase (LDH) were measured. In cardiac tissue, total antioxidant capacity (TAC), malondialdehyde (MDA), and nitrate/nitrite levels were assessed. Histopathological evaluations of cardiac tissue were also conducted.

Results: Clothianidin administration induced significant cardiac injury, evidenced by decreased TAC and increased levels of MDA, nitrate/nitrite, CK-MB, and LDH. Quercetin at a dose of 10 mg/kg significantly mitigated the cardiotoxic effects of clothianidin, as indicated by reduced CK-MB and LDH levels. Furthermore, quercetin enhanced TAC and reduced MDA and nitrate/nitrite concentrations in cardiac tissue compared to the clothianidin-only group.

Conclusion: Histopathological and biochemical analyses suggest that quercetin at 10 mg/ kg exerts cardioprotective effects against clothianidin-induced toxicity, likely through its antioxidant mechanisms.

Enhancing Wound Healing in Aesthetic Surgery: The Role of Chitosan–Moringa oleifera Gel

2025-07-02T12:25:06+00:00

Background & Objectives: This study aimed to evaluate the efficacy of chitosan gel infused with the hydroalcoholic extract of Moringa oleifera leaf powder in promoting wound healing and reducing scar formation following cosmetic breast surgery.

Materials & Methods: A total of 42 patients undergoing cosmetic breast surgery were enrolled in this randomized controlled study. Each patient’s breast was divided into two lateral hemispheres: one side received Moringa oleifera gel, while the other served as a control with a placebo gel. The gels were applied for two weeks postoperatively. Scar appearance was assessed at two weeks and three months post-surgery using the Vancouver Scar Scale (VSS), which evaluates vascularity, pigmentation, elasticity, and height. Data were analyzed to compare outcomes between the treated and control sites.

Results: Of the initial 42 patients, 36 completed the study. Twenty-five and thirty-one patients were evaluated at the two-week and three-month follow-ups, respectively. Wounds treated with the Moringa-infused gel demonstrated an 84% improvement in healing compared to those treated with the placebo. Statistically significant improvements were observed in all evaluated parameters—including vascularity, pigmentation, height, and elasticity—in favor of the Moringa oleifera gel.

Conclusions: Chitosan gel infused with the hydroalcoholic extract of Moringa oleifera leaf powder significantly enhances wound healing and improves scar appearance following cosmetic breast surgery. These findings highlight its potential as a valuable adjunct in postoperative wound care for reducing scarring and promoting tissue regeneration.

Association between Sleep Duration and Dyslipidemia: Insights from the Fasa Adults Cohort Study (FACS), 2014–2021

2025-07-02T12:24:59+00:00

Background & Objectives: Sleep duration is increasingly recognized as a critical determinant of overall health, particularly in relation to cardiovascular risk. Dyslipidemia, a leading contributor to cardiovascular disease, has been linked inconsistently to sleep duration, especially among rural populations.

Materials & Methods: This population-based cohort study utilized data from the Fasa Adults Cohort Study (2014–2021), comprising 10,118 adults aged 35 to 70 years from the rural districts of Sheshdeh and Qarabolagh, Fasa County, Iran. Participants were categorized based on self-reported sleep duration (<7 hours vs. ≥7 hours). Anthropometric measurements, blood pressure, and fasting lipid profiles were collected. Dyslipidemia was defined according to Adult Treatment Panel III (ATP III) criteria. Statistical analyses included chi-square tests, t-tests, and multivariable logistic regression.

Results: Individuals with short sleep duration (<7 hours) exhibited significantly higher body mass index (BMI), waist circumference, and low-density lipoprotein cholesterol (LDL-C) levels, as well as lower high-density lipoprotein cholesterol (HDL-C) levels (all p-values < 0.001). Short sleep duration was significantly associated with increased odds of dyslipidemia (adjusted odds ratio [OR] = 1.119; 95% confidence interval [CI]: 1.024–1.223; p = 0.013) and low HDL-C (adjusted OR = 1.239; 95% CI: 1.140–1.347; p < 0.001). No significant associations were observed with total cholesterol, triglycerides, or LDL-C.

Conclusion: Short sleep duration is significantly associated with dyslipidemia and adverse lipid profiles, particularly reduced HDL-C levels. These findings highlight the importance of sleep health in mitigating cardiovascular risk, especially in underserved rural populations. Promoting sufficient sleep may serve as a viable preventive strategy against metabolic disorders. Further longitudinal studies are warranted to clarify underlying causal mechanisms.