Down syndrome: Knowledge and attitudes among future healthcare providers

Rabbani, Syed Arman; Mossa, Mohammed Sariah Haroosh; Al-Nuaimi, Ghaya Abdulrahman Mohammed Al-Moosa; Khateri, Fatema Ali Hasan Mohammed Al

doi:10.1016/j.jtumed.2023.03.013

Cited by 2 publications

(2 citation statements)

References 20 publications

(43 reference statements)

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“…Parental awareness plays a crucial role in the context of Down syndrome, as it is essential for parents to possess a comprehensive understanding of the potential conditions associated with Down syndrome [55,56]. Such awareness can significantly contribute to the accurate diagnosis and appropriate treatment of this disorder [57,58]. The introduction of cell-free prenatal screening and the parallel sequencing of maternal plasma cell-free DNA (cfDNA) has brought about a profound transformation in the standard approach to prenatal Down syndrome diagnosis [47].…”

Section: Prenatal Diagnosticsmentioning

confidence: 99%

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Koul,

Ahmad,

Bhat

et al. 2023

Biomedicines

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Down syndrome arises from chromosomal non-disjunction during gametogenesis, resulting in an additional chromosome. This anomaly presents with intellectual impairment, growth limitations, and distinct facial features. Positive correlation exists between maternal age, particularly in advanced cases, and the global annual incidence is over 200,000 cases. Early interventions, including first and second-trimester screenings, have improved DS diagnosis and care. The manifestations of Down syndrome result from complex interactions between genetic factors linked to various health concerns. To explore recent advancements in Down syndrome research, we focus on the integration of artificial intelligence (AI) and machine learning (ML) technologies for improved diagnosis and management. Recent developments leverage AI and ML algorithms to detect subtle Down syndrome indicators across various data sources, including biological markers, facial traits, and medical images. These technologies offer potential enhancements in accuracy, particularly in cases complicated by cognitive impairments. Integration of AI and ML in Down syndrome diagnosis signifies a significant advancement in medical science. These tools hold promise for early detection, personalized treatment, and a deeper comprehension of the complex interplay between genetics and environmental factors. This review provides a comprehensive overview of neurodevelopmental and cognitive profiles, comorbidities, diagnosis, and management within the Down syndrome context. The utilization of AI and ML represents a transformative step toward enhancing early identification and tailored interventions for individuals with Down syndrome, ultimately improving their quality of life.

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Section: Prenatal Diagnosticsmentioning

confidence: 99%

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Koul,

Ahmad,

Bhat

et al. 2023

Biomedicines

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“…Mixed results have been published in this regard.Syed Arman Rabbani et al in their study have found good knowledge among 74.0% of the future health care workers and 67% of them had positive attitude towards children with Down syndrome. Age >25 years (AOR: 4.39, 95% CI: 1.88-21.93), female gender (AOR: 1.88, 95% CI: 1.16-3.07) and single relationship status (AOR: 9.16, 95% CI: 4.19-20.01) were independent predictors of knowledge level of the participants [7]. Katrina Tyzack et al in their study have found good knowledge about the Down syndrome among the health care professionals [8].The present study was conducted in Al Ahsa district of Saudi Arabia to evaluate the knowledge and attitude of nursing staffs towards children suffering from DS and to assess the association of their knowledge and attitude towards DS with their sociodemographic characteristics.…”

Section: Introductionmentioning

confidence: 96%

Down syndrome: Knowledge, perception and attitude of the nursing staffs working at the primary health care centers of Al Ahsa district of Saudi Arabia

Abdulelah Al shaikh,

Tayseer Fathielalim Abdelhalim Ayed,

Ibrahim Al Sultan

et al. 2024

Int. J. Sci. Res. Arch.

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Introduction: Down syndrome (DS), an autosomal abnormality, is considered the most common and best known chromosomal disorder affecting all countries, all races, and both sexes. DS is a leading cause of specific birth defect and the most commonly identified genetic form of mental retardation. An early structured multidisciplinary family-based care in the neuropsychological development for children with disabilities associated with DS is the need of the hour. In this multidisciplinary effort the role of para medical staffs such as nurses cannot be neglected. They play pivotal role in screening, counseling and helping the parents to cope with the children suffering from DS. Therefore a sound knowledge about DS and a positive attitude towards the children suffering from DS is necessary for them. Material and methods: It was a cross sectional study conducted at the Primary health Care centers of Al ahsa region of Saudi Arabia All the nurses working at the MOH primary health centers of Al Ahsa region of Saudi Arabia were the study population. The study sample was calculated by applying the formula as suggested by Fisher‟s and cited by Mugenda & Mugenda (1999).The calculated sample was 225 nursing staffs working at different MOH operated Primary Health care Centers. Random sampling was done from the list of nurses working at the different primary health care centers of Al Ahsa region of Saudi Arabia till the required sample size was achieved. The data were collected on the data collection sheet using a self-administered bilingual questionnaire Arabic /English (A modified validated questionnaire). The data sheet included on demographics characteristics, questions regarding assessment of knowledge ( magnitude of DS, screening process for DS, signs and symptoms and consequences of DS) and questions related to attitude towards the children suffering from DS. The data were entered and analyzed by using SPSS Version 24. Frequency distribution of basic information and knowledge and attitude scores were constructed and expressed as numbers and percentages. Bivariate analysis was conducted by using a Chi-squared test to examine the association between variables and to assess the relationship between basic information and knowledge and attitude scores. A P value of < 0.05 was be considered as statistically significant. Results and discussion: A total of 131 participants completed this survey. The mean age of the participants was 36.85 years.. The majority of the participants (58.0%) were female. Most of the participants were married (93.1%). The majority of the participants were diploma holders while 24.4% were graduated and 6.1% post graduate. Staff nurse constituted 85.5% of the participants while 5.3% were midwife and 9.2% head nurse. More than fifteen percent (15.3%) of the participants had their family member affected by DS. The mean knowledge regarding the Down syndrome was 4.85. Majority of the participants (59.6%) had good knowledge about the Down syndrome. The mean attitude score of the participants was 3.65. Almost sixty two percent of the participants had positive attitude towards the Down syndrome. The good knowledge about Down syndrome was significantly more among the female participants than male (59.21% vs.41.07%, P=0.045). Degree of good knowledge was not significantly associated with the marital status, educational level The better percentage of good knowledge was significantly more prevalent among the head nurse as compared to the staff nurse and the midwife (66.66% vs.61.60% vs.57.14%., P=0.034). The female participants had significantly higher positive attitude than their male counterpart (67.10% vs, 54.54, P=0.043. There was no significant association of the attitude of the participants towards Down syndrome with marital status, educational qualification The positive attitude towards the Down syndrome was more among the midwife than those of staff nurse and the head nurse(71.42% vs.62.5% vs.50%,P=0.032). The participants without the family history of Down syndrome had better positive attitude towards down syndrome than those with the family history of down syndrome (62.16% vs.60.0$,P= 0.521). Conclusion: The present study has shown that the participants lacked knowledge on the screening methods of detecting Down syndrome. The attitude of the participants towards children suffering from Down syndrome had been satisfactory. There is a need of formulating an education programme on Down syndrome to teach the nurses about the screening methods of Down syndrome among the pregnant women before the birth of the baby and among the children after the birth.

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Down syndrome: Knowledge and attitudes among future healthcare providers

Cited by 2 publications

References 20 publications

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Unraveling Down Syndrome: From Genetic Anomaly to Artificial Intelligence-Enhanced Diagnosis

Down syndrome: Knowledge, perception and attitude of the nursing staffs working at the primary health care centers of Al Ahsa district of Saudi Arabia

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