Radwan Qasrawi
Biographic Data
| ID | 4465954 |
|---|---|
| NAME | Radwan Qasrawi |
| GIVEN NAMES | Radwan |
| FAMILY NAME | Qasrawi |
| SIGNATURE | QASRAWI R |
| AFFILIATIONS | Al-Quds University |
| ORCID | 0000-0001-8671-7026 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
The impact of online food delivery applications on dietary pattern disruption in the Arab region
Background: While online food delivery applications (OFDAs) offer convenient food accessibility, their impact on dietary behaviors remains insufficiently explored, especially in the Arab region. This study applies machine learning (ML) techniques to identify the key behavioral and nutritional factors contributing to dietary disruption linked to OFD platforms. Methods: We conducted a cross-sectional study which involved 7,370 adults across 10 Arab…
Determinants of Child Growth in Palestine (Ages 5–17): A Structural Equation Modeling Approach to Food Insecurity, Nutrition, and Socioeconomic Factors
Background : The growth patterns of children and adolescents are influenced by multiple factors. This study employed structural equation modeling (SEM) to determine the primary factors influencing the growth of Palestinian children and adolescents in the West Bank (WB). Methods : A cross-sectional survey conducted in 2022 in the WB collected data from 1400 households, of which 500 with children aged 5-17 years and were selected for analysis. The …
The impact of digital literacy and internet usage on health behaviors and decision-making in Arab Mena countries
The association between food preferences, eating behavior, and body weight among female university students in the United Arab Emirates
Introduction This cross-sectional study investigated the associations between lifestyle, eating habits, food preferences, consumption patterns, and obesity among female university students in the United Arab Emirates (UAE). Methods Approximately 4,728 participants, including both Emirati and Non-Emirati students (International Students). Data collection involved face-to-face interviews and anthropometric measurements, showing an interrelated rela…
Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques
Food insecurity is a public health concern that affects children worldwide, yet it represents a particular burden for low- and middle-income countries. This study aims to utilize machine learning to identify the associations between food insecurity and nutrient intake among children aged 5 to 18 years. The study's sample encompassed 1040 participants selected from a 2022 food insecurity household conducted in the West Bank, Palestine. The results…
Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years
This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking
Perspectives and practices of dietitians with regards to social/mass media use during the transitions from face-to-face to telenutrition in the time of Covid-19: A cross-sectional survey in 10 Arab co…
During the COVID-19 pandemic, most healthcare professionals switched from face-to-face clinical encounters to telehealth. This study sought to investigate the dietitians’ perceptions and practices toward the use of social/mass media platforms amid the transition from face-to-face to telenutrition in the time of COVID-19. This cross-sectional study involving a convenient sample of 2,542 dietitians (mean age = 31.7 ± 9.5; females: 88.2%) was launch…
Machine learning techniques for identifying mental health risk factor associated with schoolchildren cognitive ability living in politically violent environments
The findings can inform evidence-based strategies for preventing and mitigating the detrimental effects of political violence on individuals and communities, highlighting the importance of addressing the needs of children in conflict-affected areas and the potential of using technology to improve their well-being
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the Covid-19 pandemic
The ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally
Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the Covid-19 pandemic in 10 Arab countries
Background The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries. Methods …
The Impact of Covid-19 on Physical (In)Activity Behavior in 10 Arab Countries
Insufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in t…
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Sex disparities in food consumption patterns, dietary diversity and determinants of self-reported body weight changes before and amid the Covid-19 pandemic in 10 Arab countries
Background The COVID-19 pandemic along with its confinement period boosted lifestyle modifications and impacted women and men differently which exacerbated existing gender inequalities. The main objective of this paper is to assess the gender-based differentials in food consumption patterns, dietary diversity and the determinants favoring weight change before and amid the COVID-19 pandemic among Arab men and women from 10 Arab countries. Methods …
The Impact of Covid-19 on Physical (In)Activity Behavior in 10 Arab Countries
Insufficient physical activity is considered a strong risk factor associated with non-communicable diseases. This study aimed to assess the impact of COVID-19 on physical (in)activity behavior in 10 Arab countries before and during the lockdown. A cross-sectional study using a validated online survey was launched originally in 38 different countries. The Eastern Mediterranean regional data related to the 10 Arabic countries that participated in t…
Perspectives and practices of dietitians with regards to social/mass media use during the transitions from face-to-face to telenutrition in the time of Covid-19: A cross-sectional survey in 10 Arab co…
During the COVID-19 pandemic, most healthcare professionals switched from face-to-face clinical encounters to telehealth. This study sought to investigate the dietitians’ perceptions and practices toward the use of social/mass media platforms amid the transition from face-to-face to telenutrition in the time of COVID-19. This cross-sectional study involving a convenient sample of 2,542 dietitians (mean age = 31.7 ± 9.5; females: 88.2%) was launch…
Machine learning techniques for identifying mental health risk factor associated with schoolchildren cognitive ability living in politically violent environments
The findings can inform evidence-based strategies for preventing and mitigating the detrimental effects of political violence on individuals and communities, highlighting the importance of addressing the needs of children in conflict-affected areas and the potential of using technology to improve their well-being
Machine learning techniques for the identification of risk factors associated with food insecurity among adults in Arab countries during the Covid-19 pandemic
The ML algorithms seem to be an effective method in early detection and prediction of food insecurity and can profoundly aid policymaking. The integration of ML approaches in public health strategies could potentially improve the development of targeted and effective interventions to combat food insecurity in these regions and globally
The association between food preferences, eating behavior, and body weight among female university students in the United Arab Emirates
Introduction This cross-sectional study investigated the associations between lifestyle, eating habits, food preferences, consumption patterns, and obesity among female university students in the United Arab Emirates (UAE). Methods Approximately 4,728 participants, including both Emirati and Non-Emirati students (International Students). Data collection involved face-to-face interviews and anthropometric measurements, showing an interrelated rela…
Investigating the Association between Nutrient Intake and Food Insecurity among Children and Adolescents in Palestine Using Machine Learning Techniques
Food insecurity is a public health concern that affects children worldwide, yet it represents a particular burden for low- and middle-income countries. This study aims to utilize machine learning to identify the associations between food insecurity and nutrient intake among children aged 5 to 18 years. The study's sample encompassed 1040 participants selected from a 2022 food insecurity household conducted in the West Bank, Palestine. The results…
Machine Learning Approach for Predicting the Impact of Food Insecurity on Nutrient Consumption and Malnutrition in Children Aged 6 Months to 5 Years
This study provides insights into the differential risks for growth issues among children, offering valuable information for targeted interventions and policymaking
The impact of online food delivery applications on dietary pattern disruption in the Arab region
Background: While online food delivery applications (OFDAs) offer convenient food accessibility, their impact on dietary behaviors remains insufficiently explored, especially in the Arab region. This study applies machine learning (ML) techniques to identify the key behavioral and nutritional factors contributing to dietary disruption linked to OFD platforms. Methods: We conducted a cross-sectional study which involved 7,370 adults across 10 Arab…
Determinants of Child Growth in Palestine (Ages 5–17): A Structural Equation Modeling Approach to Food Insecurity, Nutrition, and Socioeconomic Factors
Background : The growth patterns of children and adolescents are influenced by multiple factors. This study employed structural equation modeling (SEM) to determine the primary factors influencing the growth of Palestinian children and adolescents in the West Bank (WB). Methods : A cross-sectional survey conducted in 2022 in the WB collected data from 1400 households, of which 500 with children aged 5-17 years and were selected for analysis. The …
The impact of digital literacy and internet usage on health behaviors and decision-making in Arab Mena countries
Medicine (10 works) · Environmental health (9 works) · Agriculture (5 works) · Food security (5 works) · Geography (5 works) · Biology (4 works) · Economics (4 works) · Food insecurity (4 works) · Food Security and Health in Diverse Populations (4 works) · Mobile Health and mHealth Applications (4 works)