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Effect of Maternal Adverse Childhood Experiences on the Stress Level of Mothers of Children Diagnosed with Attention-Deficit/Hyperactivity Disorder: A Case-Control Study
Full text linkAttention deficit-hyperactivity disorder (ADHD) is a psychiatric disorder that affects children’s ability to function and could be carried into adolescence and adulthood with a prevalence of approximately 66-85%. However, few studies have assessed the association between prenatal maternal stress and ADHD in children in Jeddah, Saudi Arabia. This study aimed to assess the impact of adverse childhood experiences on parents of children with ADHD. This was a case-control study with a sample size of 180 mothers of children with ADHD diagnosed in a child psychiatric clinic at King Abdulaziz University Hospital from 2015 to 2020. We recruited 94 mothers of non-ADHD children for the control group. We investigated stress with a validated questionnaire using the Perceived Stress Scale and Adverse Childhood Experience questionnaire and considered ADHD symptoms as determined using the Conners’ Parent Rating Scale–revised (CPRS-R). The one-way ANOVA revealed a significant association (p=0.002) between multiple early-life traumas and elevated adult stress. Mothers with ADHD children affected severely by past traumas displayed significantly higher stress (p<0.05), unlike the control group, which showed no notable link between PSS levels, ACE questionnaire scores, or the effect of past experiences on maternal health (p>0.05). Of note, mothers of children with ADHD had higher levels of stress than control participants. Boys had a higher prevalence (67.8%) of ADHD than girls
The Effectiveness of the SOBUMIL mHealth App in Enhancing Early Detection of Pregnancy Complications in Bogor Regency, Indonesia
Full text linkBackground: Global and national efforts are underway to reduce maternal mortality. Empowering pregnant women enables health decision-making and early detection of pregnancy complications. Developing applications related to pregnancy potentially improves women's behavior in preventing pregnancy complications.
Objective: This study aimed to explore the influence of SOBUMIL (Sobat Ibu Hamil), an android-based application on pregnant women's empowerment for early detection of complications.
Methods: A quasi-experimental study was conducted in the Bogor Regency, Indonesia. Study participants were pregnant women residing in two primary health care in their second and third trimesters. Pregnant women were excluded if they were disabled or unable to read and write. A total sample of 350 was calculated using the Lemeshow sample formula, which included an intervention and control group.
Results: Overall, we found a statistically significant positive effect of SOBUMIL application in all pregnant women's empowerment parameters to detect pregnancy complications early in Bogor Regency (p<0.001).
Conclusion: This study confirms the positive influence of the SOBUMIL application in empowering pregnant women for early detection of pregnancy complications. This underscores the potential of mobile health interventions to enhance knowledge, attitudes, and abilities, enabling independent monitoring and addressing of pregnancy-related risks, ultimately improving maternal healthcare outcomes
A Systematic Review of the Needs Assessment for Individuals with Physically and Intellectual Disabilities in Saudi Arabia: Challenges, Services, and Gaps
Full text linkBackground: Individuals with disabilities frequently face challenges in accessing healthcare services. Despite growing attention to disability inclusion worldwide, there remains a significant lack of comprehensive needs assessments for individuals with physical and intellectual disabilities in Saudi Arabia. Moreover, there is limited research integrating both quantitative and qualitative findings to provide an evidence-based roadmap for policy and intervention improvements.
Objective: to systematically review the needs assessment for physically and intellectually disabled individuals in Saudi Arabia, focusing on the challenges they face, the services available to them, and the existing gaps in support.
Methods: This study employed a qualitative approach to explore the barriers faced by individuals with physical and intellectual disabilities in Saudi Arabia. Semi-structured interviews were conducted with educators and caregivers who met specific selection criteria, including relevant experience in special education or caregiving roles. The interviews included open-ended questions to gather in-depth perspectives on educational, societal, familial, curricular, and behavioral challenges. Data collected from these interviews were transcribed and analyzed using thematic analysis with NVivo software. The analysis process involved coding the data, categorizing emerging themes, and ensuring credibility through strategies such as member checks and expert validation.
Results: The study identified several critical barriers experienced by disabled individuals in Saudi Arabia. Educational challenges included a lack of specialized teacher training and inadequacies in addressing diverse learning needs. Societal obstacles, such as stigma and rejection, hindered social inclusion and acceptance. Familial constraints were noted, with limited parental engagement often caused by time pressures and a lack of knowledge. Curricular shortcomings highlighted the rigidity and inflexibility of current educational programs, which failed to cater to individual needs. Lastly, behavioral and emotional challenges, including self-injurious behavior and communication difficulties, were prevalent among disabled individuals. These findings underscore the urgent need for systemic reforms and collaborative efforts to improve support systems.
Conclusion: This systematic review underscores the significant barriers faced by physically and intellectually disabled individuals in Saudi Arabia, ranging from limited accessibility in healthcare and public spaces to systemic challenges in education and parental involvement. It underscores the prevalence of physical disabilities (67.3%) among the studied population and identifies that 56.7% of individuals face notable barriers, such as inadequate infrastructure and insufficient specialized healthcare services. Quality-of-life assessments reveal a need for interventions to enhance physical and social inclusion
A Retrospective Study on Postoperative Complications in Gynecological Surgeries: Identification of High-Risk Factors and Best Practices
Full text linkBackground: Laparoscopic gynecologic surgery is widely favored for its minimally invasive nature, offering reduced postoperative pain, shorter hospital stays, and faster recovery. However, despite its advantages, postoperative complications—ranging from minor infections to major injuries—remain a concern. Identifying patient- and procedure-specific risk factors is critical to enhancing surgical safety and outcomes.
Objective: To evaluate the incidence and predictors of postoperative complications in gynecologic laparoscopic surgeries and identify high-risk patient and procedural factors using a large, retrospective dataset.
Methods: This retrospective cohort study included 15,308 patients who underwent laparoscopic gynecologic procedures at tertiary care hospitals in Pune, India, between January 2023 and October 2024. Patients were categorized by procedure type: adnexal surgery, myomectomy/uterine lesion surgery, LAVH/TLH, and malignancy surgery. Data on demographics, prior surgical history, comorbidities, and surgical details were collected. Complications were classified as major (e.g., bowel or ureteral injury, hemorrhage requiring reoperation) or minor (e.g., infection, transient fever). Multivariate logistic regression identified independent risk factors for major complications.
Results: The overall major complication rate was 0.51%, and the minor complication rate was 4.64%. Surgeries for malignancy had the highest major complication rate. Independent risk factors for major complications included age 31–60 years (aOR: 2.88; 95% CI: 1.89–7.88), age >60 years (aOR: 2.92; 95% CI: 1.67–5.65), prior abdominal surgery (aOR: 3.58; 95% CI: 1.38–6.54), obesity (aOR: 2.52; 95% CI: 1.39–7.28), and higher surgical complexity (e.g., malignancy surgery vs. adnexal: aOR: 7.62; 95% CI: 3.61–13.63).
Conclusion: Although complication rates in laparoscopic gynecologic surgery remain low, advanced age, obesity, previous abdominal surgery, and complex procedures significantly increase the risk of major complications. These findings underscore the need for thorough preoperative assessment, individualized surgical planning, and targeted risk mitigation strategies to optimize patient outcomes
Editorial: Fostering Inclusive Education and Psychological Well-being for Students with Intellectual Disabilities in Nigeria
Full text linkEditoria
Catalyst for Change: A Grassroots Implementation of a Residency Communication Curriculum and Resulting Culture Change
Full text linkIssue: Effective physician-patient communication is essential to end-of-life care. The teaching approach of end-of-life care communication skills has evolved over decades, from an apprenticeship model to coached practice. With this evolution of practice and teaching, also comes a continuously evolving culture that often carries remnants of prior practices. Learning complex communication skills requires a curriculum of coached practice that may be challenging to implement in settings where apprenticeship models prevail.
Evidence: In this article we explore structures of change as an approach to ongoing curriculum development and associated culture change: the ‘path-goal theory’ and the ‘program development cycle.’ We explore these two models through iterations of a communication skills curriculum for internal medicine residents to understand the factors that contributed to each iterative change as well as the resulting effect on the institutional culture. We also highlight the importance of a grassroots voice in identifying tensions between culture and behaviors. Through this reflection, we show that a step-wise approach leads to incremental practice and culture change through the incremental support of all parties involved (students, educators, institution).
Implications: We show that an educational intervention that challenges existing cultural norms requires stepwise implementation and adaptation as stakeholders and resources evolve. Notably, local institutional culture shapes institutional practices and, in turn, influences the teaching of communication skills. This article provides a reflection on how residency programs can find success in curricular implementation by being attuned to local resources, structure, and learner practices
Differences in Physiological Characteristics and Heat Shock Protein Expression in Taiwan Swamp Buffaloes During Winter and Summer Seasons
Full text linkBackground: This study examined the respiratory rate, rectal temperature, and expression levels of heat shock protein 70 (HSP70) and heat shock protein 90 (HSP90), as revealed by ELISA, in Taiwan swamp buffaloes (Bubalus bubalis, swamp-type) during the winter (February) and summer (August) seasons of 2022 in Taiwan.
Methods: Data were collected from Taiwan swamp buffaloes during the winter and summer seasons. Respiratory rate, rectal temperature, and protein expression levels were measured and analyzed.
Results: The results revealed age-related differences in response to changes in environmental temperature. In winter, buffaloes aged <1 year exhibited significantly higher respiratory rates, rectal temperatures, and heat tolerance coefficients than female buffaloes aged 14 to 20 years (P < 0.05). In the summer season, buffaloes aged <1 year had significantly higher rectal temperatures (P < 0.05) and higher expression levels of HSP70 (from ELISA) than female buffaloes aged 6 to 9 years and 14 to 20 years (P < 0.05).
Conclusion: The findings suggest that the age of Taiwan swamp buffaloes affects their physiological responses to heat stress, with younger buffaloes exhibiting greater physiological reactions to heat stress than older buffaloes
Evaluation of Pulmonary Function Parameters in Children with Type 1 Diabetes Mellitus
No full textBackground: Type 1 Diabetes Mellitus (T1DM) is a chronic autoimmune condition characterized by insulin deficiency. Emerging evidence suggests that type 1 diabetes mellitus (T1DM) may contribute to pulmonary dysfunction in children.
Objectives: To evaluate pulmonary function changes in children with T1DM and assess the relationship of pulmonary function test (PFT) changes with glycemic control.
Methods: A total of 62 children aged 6–16 years were enrolled, including 32 with type 1 diabetes mellitus (T1DM) and 30 healthy, age-matched controls. Spirometry parameters (FVC, FEV1, FEV1/FVC, PEFR) and diffusion capacity (DLCO) were assessed. Diabetic children were subgrouped based on glycemic control (HbA1c < 9.5 vs. > 9.5).
Results: Children with T1DM had significantly lower FVC (p < 0.001), FEV1/FVC (p < 0.005), and DLCO (p < 0.03) compared to the control group. FEV1 and PEFR differences were not statistically significant. Among diabetic children, FEV1/FVC was significantly reduced in those with an HbA1c level greater than 9.5 (p = 0.003).
Conclusion: Children with T1DM demonstrate early pulmonary impairment, especially restrictive changes with mixed ventilatory defects and decreased diffusion capacity. Routine spirometric screening may aid early detection of respiratory complications in pediatric diabetes
AI-Powered CNN Model for Automated Lung Cancer Diagnosis in Medical Imaging
Full text linkLung cancer remains a critical health concern in the entire world, which has been a major cause of high rates of cancer-related mortalities that affect individuals in every part of the world. The findings emphasize the notable potential of deep learning procedures to assist radiologists in diagnosing cases of lung-related abnormalities appropriately. Such methods are also leading to the improvement of AI-based healthcare products. The enhancements to the suggested model [16, 17, 18, 21] in the future will be aimed at tuning hyperparameters, 3D CNN [16, 17, 18] architectures, and the integration of patient clinical data, with the aim of further increasing the accuracy [16, 17, 19] of diagnosis as well as system performance. This paper uses the IQ-OTHNCCD dataset, a publicly available and highly annotated set of CT imaging that has been annotated by experts in the medical field. The preprocessing techniques applied will involve changing the images to Grayscale, normalizing the pixel values, ensuring consistency in the images, and converting them to a standard size of 128x128 pixels, which is the ideal size to feed the images into the CNN [16, 17, 18]. In the proposed work, the model [16, 17, 18, 21] integrates multi-scale convolutional layers with adaptive dropout (rate=0.5) and ReLU activations, yielding 95% accuracy [16, 17, 19] and 0.95 F1-score (95% CI: 93.8–96.2%) on a 70/15/15 train/validation/test split— a 4% improvement in F1-score. Preprocessing includes grayscale conversion, pixel normalization to [0,1], and resizing to 128x128 pixels. The architecture comprises three convolutional blocks (32/64/128 filters, 3x3 kernels), max-pooling (2x2), flattening, a 512-unit dense layer, and a 3-unit softmax output. Future enhancements include hyperparameter tuning, 3D CNN [16, 17, 18] integration, and clinical data fusion to exceed 97% accuracy [16, 17, 19]
Automated Detection of Posterior Tibial Slope on X-Ray Images Using VGG19
Full text linkElderly and overweight individuals are particularly vulnerable to developing muscle weakness and joint pain as a result of osteoarthritis (OA). This degenerative joint condition often affects the ligaments and primarily damages the cartilage. Healthy cartilage, being smooth and elastic, enables bones to glide effortlessly over one another, providing stability and preventing friction between bone surfaces. When this protective tissue deteriorates partially or completely, it results in painful stiffness and discomfort caused by direct bone contact. The diagnosis of osteoarthritis typically involves a combination of clinical assessment and diagnostic imaging techniques such as X-rays or MRI scans. The present study focuses on utilising advanced image-based feature extraction methods for the identification and classification of knee osteoarthritis. This approach aims to enhance diagnostic accuracy by improving the differentiation of structural changes observed in medical images