Bioengineered FeZn/GA@Cu nanocomposite utilizing spent coffee ground extract and gum arabic: Enhanced nitrate removal via (RSM) and machine learning optimization.

This research focused on synthesizing an eco-friendly FeZn/GA@Cu nanocomposite using spent coffee grounds and Gum Arabic (GA). The study aimed to investigate its effectiveness as both a photocatalyst and an adsorbent, specifically for removing nitrates from aqueous solutions. The prepared nanocomposite was characterized using various analytical techniques, including XRD, TGA, FESEM with EDS, TEM, BET, FTIR, zeta potential, UV-DRS, and VSM. The RSM method, an impressive removal efficiency of 95.28 % for nitrate was projected under the specific conditions of an optimal dose of 1.82 g/L, an initial concentration of 60.00 mg/L, a pH level of 5.85, and a reaction duration of 48.90 min. It was ascertained that the peak efficiency of 98.25 % could be achieved with a carefully calibrated dose of 1.94 g/L, an initial concentration of 62.69 mg/L, a pH of 5.16, and a reaction time contained within 45.75 min. The synthesized nanocomposites have shown potential antibacterial activity against gram+ve (Staphylococcus aureus) and gram-ve (Escherichia coli) pathogens. This study suggests that the FeZn/GA@Cu nanocomposite synthesized using spent coffee grounds has potential as a photocatalyst for removing nitrate from aqueous solutions.

YouTube Video Clips on Breastfeeding Education and Promotion for Arabic-Speaking Populations: A Social Media Content Analysis.

Background/Objective: Although the benefits of breastfeeding are well-documented and widely recognized, reports indicate that optimal breastfeeding rates are low in Arabic-speaking countries. This is a significant concern given the health benefits associated with breastfeeding for both infants and mothers. Previous research has shown that education interventions can increase breastfeeding knowledge, attitudes, and practices in Arabic-speaking populations. The social media platform YouTube holds significant potential for distributing customized health education for diverse audiences; specifically, this platform has the potential to empower mothers and normalize long-term breastfeeding. The aim of this study was to evaluate the quality of YouTube videos on breastfeeding available in the Arabic language. Methods: We used standard procedures to search YouTube for Arabic breastfeeding videos posted on YouTube in December 2023. Videos were evaluated using the three scales of the DISCERN quality evaluation instrument (reliability, information quality, video quality) and total score. Comparative statistics were generated. Results: In total, 165 videos met the inclusion criteria, with 29.7% in the Education category; 43.6% were in Egyptian Arabic dialect. Almost all (91.75%) of the educational videos had a "medium" quality assessment. Educational videos and those using health professionals had higher quality assessments than those in other categories or done with other speakers. Conclusion: The results of this review suggest that most content on the topic of breastfeeding was of only medium reliability and informational quality. New mothers seeking breastfeeding information or support may be in need of specific problem-solving information at a time when they are living with the often-difficulty reality of caring for a newborn or very young infant. There is a clear need for accurate, culturally congruent information to effectively support breastfeeding in Arabic-speaking countries. Future efforts should focus on improving the quality of online health education content, with implications for public health strategies and policy development.

Jordanian Arabic Version of the Dizziness Handicap Inventory.

Objective: This study aimed to establish and validate a Jordanian Arabic version of the Dizziness Handicap Inventory (DHI-JA) equivalent to the original DHI in English (DHI-E). Methods: The THI-E questionnaires were translated into formal Jordanian Arabic by two bilingual volunteer audiologists. The final version, curated by the author, was administered to 20 participants with normal balance and 64 patients experiencing dizziness at the Middle East Hearing and Balance Centre. Results: The results demonstrated excellent internal consistency and reliability of DHI-JA. A highly significant correlation was observed between the total scores and sub-scores of DHI-JA and DHI-E. Conclusion: This study concludes that the DHI-JA is a valid and reliable tool for assessing the severity of dizziness and balance disorders in the Jordanian Arabic-speaking population.

Is Arabic online patient-centered information about dental extraction trustworthy? An infodemiological study.

Background: Assessment of the Arabic online patient-centered information is understudied. The study aims to assess the quality and readability of the Arabic web-based knowledge about dental extraction. Methods: The first 100 Arabic websites focusing on dental extraction were gathered using popular terms from Google, Bing, and Yahoo searches. These sites were organized and their quality was assessed using three key standards: the Journal of the American Medical Association (JAMA) benchmark criteria, the DISCERN instrument, and the inclusion of the Health on the Net Foundation Code of Conduct (HON code) seal. Additionally, the ease of reading of these websites was evaluated through various online readability indexes. Results: Out of 300 initially reviewed websites on dental extraction in Arabic, 80 met the eligibility criteria. Nonprofit organizations were most common (41.3%), followed by university/medical centers (36.3%), and commercial entities (21.3%). Government organizations were minimally represented (1.3%). All websites were medically oriented, with 60% offering Q&A sections. Quality assessment showed moderate scores on the DISCERN instrument, with no site reaching the highest score. JAMA benchmarks were poorly met, and none had the HON code seal. Readability was generally high, with most sites scoring favorably on readability scales. Conclusions: The rapidly evolving online information about dental extraction lacks readability and quality and can spread misinformation. Creators should focus on clear, unbiased content using simple language for better public understanding.

Voices Unheard: A Reflective Lifeworld Research Study of Older Arabic-Speaking Female Migrants and Their Experience of Existential Loneliness.

INTRODUCTION: Existential loneliness (EL) is an unavoidable, deeper sense of loneliness. EL has been described as disconnection from life and the universe, experienced even in the presence of family and friends. Meaninglessness, loss of health and significant others seem to trigger older persons EL. Older Arabic-speaking women are a large migrant group in Sweden and there is a lack in knowledge about their experience of EL. Therefore, this study aimed to describe the phenomenon of EL as experienced by older Arabic-speaking female migrants. METHODS: This study was based on a phenomenological approach known as reflective lifeworld research (RLR). Ten older migrated Arabic-speaking women were included in the study. Lifeworld interviews were conducted to collect data. The data were analysed in accordance with the phenomenological RLR principles of openness, flexibility and bridling. RESULTS: This study shows that EL is experienced when there is a lack of attachment to place and people. EL is experienced more distinctively in the beginning of the migration process. It was difficult sharing feelings of EL with anyone. Feelings of meaninglessness occurred when entering a new lifeworld and triggered EL. EL was however attenuated when being able to practise their religion. CONCLUSION: Lack of attachment to place and people as well as feelings of meaninglessness brought existential loneliness to the fore for the older Arabic-speaking female migrants. There was a collision of lifeworlds not at least by the fact moving as a Muslim woman to one of the most secular countries in the world. Practising their religion attenuated their EL. To promote better health for this group of women, it is of importance to be aware of EL and its mode of expression. IMPLICATIONS FOR PRACTICE: It is crucial to let the voice of older Arabic-speaking female migrants be heard and to be aware of their experience of EL and its mode of expression in order to promote better health. Further, educational training for nursing professionals and nursing students needs to be provided to develop skills how to be aware of and address EL.

To Reconstruct or Not to Reconstruct: Piloting a Vietnamese and Arabic Breast Reconstruction Decision Aid in Australia.

Currently, there are no resources to support culturally and linguistically diverse (CALD) women with breast cancer to make decisions about undergoing breast reconstruction (BR). This study evaluated the usability and acceptability of decision aids (DAs) for Vietnamese- and Arabic-speaking women. This two-phase qualitative recruited Vietnamese- (Phase 1) and Arabic-speaking (Phase 2) adult (age ≥ 18 years) women who were diagnosed with breast cancer and could read Vietnamese/Arabic. Women participated in either think-aloud telephone interviews (Phase 1) or semi-structured telephone interviews (Phase 2) and provided feedback on the DA. Interviews were audio-recorded, translated, and transcribed from Vietnamese/Arabic to English, and inductive thematic analysis was undertaken. Additionally, Arabic-speaking women completed the Preparation for Decision Making (PrepDM) scale in Round 2. Twenty-five women were recruited in two phases (Phase 1: Vietnamese-speaking women, n = 14; Phase 2: Arabic-speaking, n = 11). Three themes were developed in Phase 1: (1) DA content and reception; (2) linguistic attributes and cultural appropriateness; and (3) factors that improve the DAs' impact. Three themes were developed in Phase 2: (1) varying perceptions of DA content; (2) linguistic and cultural suitability of information; and (3) impact of DA on decision making. Women from both phases identified areas for improvement: minimising the use of medical terminology, considering the cultural taboos associated with the word 'breast', and addressing remaining information gaps. Both language DAs were generally perceived as acceptable and useful in providing information about BR options and prompting women's reflections about the suitability of BR as part of their treatment. The mean PrepDM score for Arabic-speaking women in Round 2 was 4.8/5 (SD = 0.3). Further work is needed to ensure that culturally adapted DAs take into account the myriad of information needs and health literacy levels. The key role of healthcare professionals in shared decision making among CALD populations should also be considered.

Translation, transcultural adaptation, and convergent validity of the Arabic version of the Mukbang addiction scale.

INTRODUCTION: The present study evaluated the psychometric properties of the Arabic translation of the Mukbang Addiction Scale (MAS) among Arabic-speaking adults from the general population. Specifically, it aimed to assess the factorial structure through a confirmatory factor analysis, determine the composite reliability through Cronbach alpha and McDonald's omega scores, assess gender invariance, and evaluate the convergent validity by examining its correlation to eating addiction and psychological distress. METHODS: A total of 370 individuals with a mean age of 21.94 ± 2.29 years participated in this study, which was conducted using an online platform. The participants were surveyed on demographic information, mukbang addiction, food addiction, and psychological distress. Translation was conducted using the forward and backward technique. RESULTS: The findings demonstrated excellent internal consistency of the Arabic MAS (McDonald's omega coefficient = 0.93). Confirmatory factor analyses validated the one-factor structure of the scale, while establishing measurement invariance across sex at the configural, metric, and scalar levels. No sex differences were observed in the Mukbang addiction levels. Lastly, the MAS scores were significantly and positively correlated with food addiction and psychological distress, supporting their convergent validity. CONCLUSION: The current research provides evidence supporting the reliability and validity of the Arabic version of the MAS as a self-report method for assessing addictive Mukbang watching. While further validations are needed to corroborate the present findings, this measure can be effectively utilized across different fields, including schools, mental health centers, and researchers aiming to understand this global phenomenon. Mukbang refers to individuals or hosts consuming large quantities of food while interacting with their audiences through recorded video or a live stream. The Mukbang phenomenon has gained substantial popularity among young individuals over the past years, rising concerns about its potential impact on their eating habits and health, especially when overconsumed. Overconsumption of mukbang content, or Mukbang addiction, aligns with the core features of addiction, including compulsive engagement, tolerance, and withdrawal symptoms, making it comparable to other addictive behaviors. Mukbang addiction can lead to detrimental effects on mental and physical health, including neglect of balanced nutrition, disordered eating habits, obesity, feelings of guilt, shame, poor self-esteem, distorted self-images, body dissatisfaction, heightened anxiety or depression, and social isolation. Given these significant impacts, valid and reliable tools are crucial to enable an accurate assessment of Mukbang addiction. This study proposes to translate, adapt and examine the psychometric properties of the Mukbang Addiction Scale (MAS) in a sample of Arabic-speaking individuals from the general population. Findings showed that the six MAS items loaded on a single factor with strong internal consistency and good convergent validity, preliminarily indicating its potential validity and reliability for assessing addictive mukbang-watching among Arabic-speaking individuals.

ArabBert-LSTM: improving Arabic sentiment analysis based on transformer model and Long Short-Term Memory.

Sentiment analysis also referred to as opinion mining, plays a significant role in automating the identification of negative, positive, or neutral sentiments expressed in textual data. The proliferation of social networks, review sites, and blogs has rendered these platforms valuable resources for mining opinions. Sentiment analysis finds applications in various domains and languages, including English and Arabic. However, Arabic presents unique challenges due to its complex morphology characterized by inflectional and derivation patterns. To effectively analyze sentiment in Arabic text, sentiment analysis techniques must account for this intricacy. This paper proposes a model designed using the transformer model and deep learning (DL) techniques. The word embedding is represented by Transformer-based Model for Arabic Language Understanding (ArabBert), and then passed to the AraBERT model. The output of AraBERT is subsequently fed into a Long Short-Term Memory (LSTM) model, followed by feedforward neural networks and an output layer. AraBERT is used to capture rich contextual information and LSTM to enhance sequence modeling and retain long-term dependencies within the text data. We compared the proposed model with machine learning (ML) algorithms and DL algorithms, as well as different vectorization techniques: term frequency-inverse document frequency (TF-IDF), ArabBert, Continuous Bag-of-Words (CBOW), and skipGrams using four Arabic benchmark datasets. Through extensive experimentation and evaluation of Arabic sentiment analysis datasets, we showcase the effectiveness of our approach. The results underscore significant improvements in sentiment analysis accuracy, highlighting the potential of leveraging transformer models for Arabic Sentiment Analysis. The outcomes of this research contribute to advancing Arabic sentiment analysis, enabling more accurate and reliable sentiment analysis in Arabic text. The findings reveal that the proposed framework exhibits exceptional performance in sentiment classification, achieving an impressive accuracy rate of over 97%.

Assessing mental health literacy in Jordan: a factor analysis and Rasch analysis study.

Background: Mental health literacy (MHL) research in Jordan is sparse and validated MHL measures are lacking. The present study validated a Jordanian version of the Mental Health Literacy Scale (MHLS) and examined Jordanian individuals' MHL. Method: A Google Forms survey was designed, and the link was shared through various Jordanian social media platforms. Factor analysis and Rasch analysis were performed to validate the Jordanian version of the MHLS. Binary logistic regression was performed to assess variables associated with MHL. Results: The Jordanian MHLS was administered to 974 participants (74.4% females; median age 27 years). The mean MHL score of the participants was 71.1% indicating average literacy levels. The factor analysis indicated that 27 items distributed across four factors had the best model fit. The Rasch analysis confirmed item separation reliability and person reliability. The regression showed a correlation between educational attainment, income, marital status and MHL level. These findings emphasize the role of educational attainment in MHL, pointing to the necessity of integrating mental health education into formal curricula to enhance MHL across all societal levels. Stigma and limited-service availability act as barriers to mental health service and access, which compound the challenge of improving MHL. Targeted educational interventions and policy reforms may help improve MHL, thereby contributing to improving mental health outcomes in Jordan and potentially other similar settings.

Synthesis and Superficial Modification "In Situ" of Copper Selenide (Cu2-x Se) Nanoparticles and Their Antibacterial Activity.

Copper selenide nanoparticles (Cu2-x Se NPs) have received a lot of attention in recent decades due to their interesting properties and potential applications in various areas such as electronics, health, solar cells, etc. In this study, details of the synthesis and characterization of copper selenide nanoparticles modified with gum arabic (GA) are reported. Also, through transmission electronic microscopy (TEM) analysis, the transformation of the morphology and particle size of copper selenide nanoparticles in aqueous solution was studied. In addition, we present an antimicrobial study with different microorganisms such as Staphylococcus aureus (S. aureus), Escherichia coli (E. coli) and Candida albiacans (C. albicans). Copper selenide nanoparticles were characterized by X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry analysis (DSC) and TEM. XRD confirmed the crystal-line structure of the nanoparticles such as cubic berzelanite with a particle size of 6 nm ± 0.5. FTIR and TGA corroborated the surface modification of copper selenide nanoparticles with gum arabic, and DSC suggested a change in the structural phase from cubic to hexagonal. TEM analysis demonstrated that the surface modification of the Cu2-x Se NPs stabilized the nanostructure of the particles, preventing changes in the morphology and particle size. The antimicrobial susceptibility analysis of copper selenide nanoparticles indicated that they have the ability to inhibit the microbial growth of Staphylococcus aureus, Escherichia coli and Candida albicans.

Validation of an Arabic tool for assessing vaccination literacy: A factor and Rasch analysis.

Vaccine literacy is a significant part of health literacy. Although several tools have been developed to assess vaccine literacy, such tools are lacking in Arabic. Validating an Arabic version of a tool that evaluates vaccine literacy is critically important, as it would aid in understanding the decision-making process regarding vaccinations among individuals in Arabic-speaking countries. Therefore, the current study aimed to validate an Arabic tool for assessing vaccine literacy in adult vaccination. An online questionnaire was distributed to people throughout Jordan by sharing the questionnaire link via various social media platforms. The reliability and validity of the Arabic version of the vaccination literacy assessment tool (HLVa-Ar) were evaluated using factor analysis and Rasch analyses. The two-factor model generated fit indices were in the acceptable range (χ2/df = 2.48, RMSEA = 0.06, SRMR = 0.05, GFI = 0.94, CFI = 0.97, and TLI = 0.96). Cronbach's alpha for functional Vaccination literacy (VL) and interactive/critical VL were 0.91 and 0.88 respectively. The Rasch analysis indicated acceptable infit/outfit values and high item and person separation reliabilities for the two factors (0.852, 0.868, and 0.771, 0.818 respectively). Overall, the 420 participants displayed a good understanding of the general benefits and importance of vaccination. The HLVa-Ar was shown to be a valid and reliable tool that portrayed a wide range of vaccination literacy levels in the studied sample and provided valuable insights into participants' vaccination knowledge. The findings emphasize the need for developing targeted strategies to improve vaccination literacy and increase vaccination rates.

Psychometric properties of the arabic version of PHEEM applied on a sample of medical residents in Syria.

BACKGROUND: The clinical learning environment (CLE) plays a crucial role in shaping the learning experiences and professional development of medical professionals. Understanding and optimising this environment is essential for improving doctors' knowledge acquisition, clinical skills, and overall well-being. The development of the Postgraduate Hospital Educational Environment Measure (PHEEM) and its translation to numerous languages has been a milestone in clinical education. Even though PHEEM was recently translated into Arabic, its psychometric properties in this form remain unevaluated. Therefore, this study aims to conduct a comprehensive psychometric analysis of the Arabic version of the PHEEM questionnaire. METHODS: This is a cross-sectional questionnaire survey validation study. The defined population were medical residents in Damascus, Syria. A paper-based survey as well as an online-based one were conducted using several non-probability sampling methods namely, convenience, river and, snowball sampling between June 15, 2023, and June 21, 2023. Both exploratory (EFA) and confirmatory (CFA) factor analyses were conducted. Several psychometric criteria were applied including scree plot, eigenvalue > 1.5 and the 'proportion of variance accounted for' criterion. RESULTS: A total of 543 participants completed the questionnaire (56.9% female). Kaiser-Meyer-Olkin measure for sample adequacy was high (0.937) and the P-value for Bartlett's test was < 0.001. EFA revealed five meaningful factors which were labelled: perception of teachers, learner's engagement and social participation, external regulation, work culture, and living conditions. These factors had the following eigenvalues: 12.6, 2.18, 2.03, 1.86, and 1.41 respectively, with a total explained variance of 43.45%. Cronbach's Alpha was 0.938. CFA confirmed the model structure of EFA (SRMR = 0.067 and RMSEA = 0.066). The Average Variance Explained (AVE) value of any given factor was > 0.7. DISCUSSION: The Arabic PHEEM inventory demonstrated satisfactory psychometric properties. The extracted domains are of theoretical relevance to the psychosocial-material conceptual framework for learning environment. Nonetheless, this validation was performed in the Syrian context; therefore, future studies in other Arabic countries are recommended to support the applicability of Arabic PHEEM in the wide Arab World.

Translation and validation to the Arabic language version of the climate change anxiety scale (CCAS).

BACKGROUND: The Arab world is one of the global regions the most directly concerned by, and suffering from climate change's adverse consequences. As such, there appears to be a strong need for an understanding of how Arab people may emotionally respond to climate change. Providing valid and reliable measures of climate change anxiety (CCA) can help gain a clear overview of the situation in Arab countries, and allow to intervene timely and effectively to mitigate any adverse effects on Arab people's mental health. To this end, the present study sought to validate the Arabic language version of the Climate Change Anxiety Scale (CCAS) in a sample of native Arabic-speaking adults from the general population of Lebanon. METHODS: This study adopted a cross-sectional approach and enrolled 763 adults between July and September 2023. RESULTS: A confirmatory analysis of the one-factor model showed poor fit indices as follows: CFI = 0.90, GFI = 0.83, SRMR = 0.048 and RMSEA 0.131 [90% CI 0.123, 0.138). The two-factor model showed a satisfactory fit with a high CFI of and a GFI of 0.91 and a SRMR of 0.04 and RMSEA of 0.05 [90% CI 0.04, 0.06]. Both McDonald's omega and Cronbach alpha values were high for the overall CCAS score (α = 0.96 and ω = 0.96) in the whole sample. Configural, metric and scalar invariance across gender was demonstrated. No significant difference was found between males and females in terms of total CCAS scores (24.53 ± 10.59 vs. 26.03 ± 11.17, t(761) = -1.82, p = .069). Higher CCA, functional impairment and cognitive impairment scores were significantly associated with higher depression, anxiety and stress. CONCLUSION: The reliability and validity of the CCAS in its Arabic version were proven. The availability of this self-report measure could offer a chance to assess CCA among Adults speaking Arabic, and to spread its future use for screening and research purposes.

Psychometric properties of the arabic translation of the Physical Appearance Comparison Scale-Revised (PACS-R) in adults.

BACKGROUND: Physical comparison may be a factor in body dissatisfaction and related issues, like eating disorders and depression. The Physical Appearance Comparison Scale-Revised (PACS-R) is a scale developed to assess the frequency of physical comparison. Because there is no validated scale for body comparison in Arabic, this study aims to address this gap by validating the PACS-R in the Arabic language. METHODS: The PACS-R was translated to Arabic following a conventional forward-backward translation procedure, and was administered to a sample of 359 Lebanese adults along with The Depression Anxiety Stress Scale, and the Rosenberg self-esteem scale (RSES) for convergent validity. The factor structure was studied by confirmatory factor analysis (CFA), and composite reliability was assessed using McDonald's omega and Cronbach's alpha. RESULTS: Results suggested a one-factor structure of the Arabic PACS-R, with good internal consistency (McDonald's ω = 0.97 / Cronbach α = 0.97). Measurement invariance was established across sex groups, with no significant difference being reported between males and females in terms of PACS-R scores (15.42 ± 10.64 vs. 13.16 ± 11.88; t(357) = 1.84; p = .066). Finally, adequate convergent validity was tested and found to be adequate, with PACS-R scores found to be correlated negatively with self-esteem and positively with psychological distress. CONCLUSION: The present findings preliminarily establish the Arabic PACS-R as an effective instrument for researchers and practitioners aiming to explore the physical comparison among Arabic-speaking populations, thus contributing to research and clinical work in the Arabic community.

Fabrication of graphitic carbon nitride/gum Arabic/potassium carrageenan composite for efficient adsorption of erythromycin: Kinetic and thermodynamic studies.

Erythromycin (ERY) molecules are robust to the environment and hard to remove due to their aromatic structure. Nowadays, numerous researches have reported that the ERY amount in water is above the standard level and its removal is necessary. Here, we prepared three solid adsorbents: graphitic carbon nitride (g-C3N4), potassium carrageenan beads (Cr), and graphitic carbon nitride/gum Arabic/potassium carrageenan composite (g-ACr). Several techniques such as XRD, SEM, TEM, TGA, ATR-FTIR, Zeta potential, and N2 adsorption were employed to characterize the fabricated adsorbents. Five essential factors of adsorbent dose, initial ERY concentration, contact time, temperature, and pH were optimized to investigate the batch adsorption of ERY. The maximum adsorption capacity of 356.12 mg/g was attained by g-ACr composite at an adsorbent dose of 1.25 g/L, contact time of 6 h, and pH 7 at 15 °C. The data showed that the experimental findings exhibited the best agreement with Langmuir, Temkin, and DR isotherm models, in addition to the kinetic models of pseudo-second-order, Elovich, and intra-particle diffusion. The evaluated thermodynamic factors designated that the ERY adsorption is endothermic, physisorption, favorable, and spontaneous process. The g-ACr reusability displayed a decline in the adsorption capacity after seven adsorption/desorption runs by 5.7 %. Finally, this work outcomes depict that g-ACr composite is an efficient reusable adsorbent for ERY elimination from wastewater.

Psychometric properties of the Benign and Malicious Envy Scale: A cross-cultural study in the Arab Maghreb countries.

BACKGROUND: The Benign and Malicious Envy Scale (BeMaS) is designed to assess the trait of envy and evaluate individual differences in people's tendency to experience benign or malicious envy towards superior comparison standards. OBJECTIVE: This study aimed to examine the factor structure of the BeMaS in Arab culture through exploratory and confirmatory factor analysis and to ensure the measurement equivalence of the benign and malicious envy scale across three countries in the Arab Maghreb region (Algeria, Tunisia, and Morocco). METHODS: The study was conducted on a sample of 1047 students from various universities across three countries, Algeria (n = 401), Tunisia (n = 289), and Morocco (n = 357), and implemented a cross-sectional study design. The study involved individuals aged 18-64 (M = 22.00, SD = 4.79). Most were females (64.4 %, n = 674), with substantial male representation (35.6 %, n = 373). All participants completed the Arabic BeMaS. RESULTS: The confirmatory factor analysis results indicated that the Arabic BeMaS has a two-factor structure for the total sample and each subsample. However, some modifications were necessary in the Tunisian sample. The overall results suggest that the two-factor structure of the BeMaS is valid and reliable in the Arab context. At the same time, differences between the three groups suggest cultural differences despite similarities in language, geographic proximity, and shared customs and traditions. Additionally, the results highlight the need for further research into envy, particularly within Arabic culture. Religious and cultural traditions may significantly influence how envy is experienced and perceived, making such cultural differences important to investigate. CONCLUSION: In summary, this study contributes to our measurement of Envy in the Arab context by validating BeMaS and highlighting the importance of cultural factors in measuring and explaining envy. However, further research is needed to deepen our understanding of this complex emotion in different cultural and social contexts.

The Arabic Version of Compulsive Exercise Test among Saudi Population; Translation and Validation.

Compulsive exercise is a condition characterized by uncontrollable exercise behaviour that may lead to severe and harmful physical and psychological consequences. Indeed, compulsive exercise is among the early symptoms of eating disorders that may affect different age groups. Globally and among Arab countries, compulsive exercise is common, while the screening methods used to assess compulsive exercise are limited. Thus, the Compulsive Exercise Test (CET) has emerged as a tool to assess cognitive, behavioural, and emotional factors related to compulsive exercise. The CET is a self-report, Likert-type scale comprising five distinct subscales. The increase in the CET scores is more likely associated with worsened pathology. Since the Arab countries lack such an assessment tool, we aimed to translate the CET into Arabic, validate the translated version, confirm the factor structures, and assess the internal consistency of the different subscales. Herein, we used the forward-backward translation method as recommended by the World Health Organization (WHO). The overall validity index of the translated version showed a score higher than 0.78, while the scale-level content validity index based on the average calculating method (S-CVI/Ave) and the agreement method (S-CVI/UA) were 0.91 and 0.58, respectively. Moreover, we recruited 399 Arabs living in Saudi to measure the internal consistency, and the value of the substantive internal consistency with Cronbach's α was 0.81. Subsequently, four of the Arabic-CET subscales had substantive internal consistency with Cronbach's α values higher than or equal to 0.70. Furthermore, the exploratory factor analysis results supported the substantial use of the five-subscale model. Taken together, our study supports using the Arabic-CET version to measure exercise compulsiveness among Arabs.

A comprehensive dataset for Arabic word sense disambiguation.

This data paper introduces a comprehensive dataset tailored for word sense disambiguation tasks, explicitly focusing on a hundred polysemous words frequently employed in Modern Standard Arabic. The dataset encompasses a diverse set of senses for each word, ranging from 3 to 8, resulting in 367 unique senses. Each word sense is accompanied by contextual sentences comprising ten sentence examples that feature the polysemous word in various contexts. The data collection resulted in a dataset of 3670 samples. Significantly, the dataset is in Arabic, which is known for its rich morphology, complex syntax, and extensive polysemy. The data was meticulously collected from various web sources, spanning news, medicine, finance, and more domains. This inclusivity ensures the dataset's applicability across diverse fields, positioning it as a pivotal resource for Arabic Natural Language Processing (NLP) applications. The data collection timeframe spans from the first of April 2023 to the first of May 2023. The dataset provides comprehensive model learning by including all senses for a frequently used Arabic polysemous term, even rare senses that are infrequently used in real-world contexts, thereby mitigating biases. The dataset comprises synthetic sentences generated by GPT3.5-turbo, addressing instances where rare senses lack sufficient real-world data. The dataset collection process involved initial web scraping, followed by manual sorting to distinguish word senses, supplemented by thorough searches by a human expert to fill in missing contextual sentences. Finally, in instances where online data for rare word senses was lacking or insufficient, synthetic samples were generated. Beyond its primary utility in word sense disambiguation, this dataset holds considerable value for scientists and researchers across various domains, extending its relevance to sentiment analysis applications.

ArzEn-MultiGenre: An aligned parallel dataset of Egyptian Arabic song lyrics, novels, and subtitles, with English translations.

ArzEn-MultiGenre is a parallel dataset of Egyptian Arabic song lyrics, novels, and TV show subtitles that are manually translated and aligned with their English counterparts. The dataset contains 25,557 segment pairs that can be used to benchmark new machine translation models, fine-tune large language models in few-shot settings, and adapt commercial machine translation applications such as Google Translate. Additionally, the dataset is a valuable resource for research in various disciplines, including translation studies, cross-linguistic analysis, and lexical semantics. The dataset can also serve pedagogical purposes by training translation students and aid professional translators as a translation memory. The contributions are twofold: first, the dataset features textual genres not found in existing parallel Egyptian Arabic and English datasets, and second, it is a gold-standard dataset that has been translated and aligned by human experts.

Constraining current neuroanatomical models of reading: the view from Arabic.

There is a growing interest in imaging understudied orthographies to unravel their neuronal correlates and their implications for existing computational and neuroanatomical models. Here, we review current brain mapping literature about Arabic words. We first offer a succinct description of some unique linguistic features of Arabic that challenge current cognitive models of reading. We then appraise the existing functional neuroimaging studies that investigated written Arabic word processing. Our review revealed that (1) Arabic is still understudied, (2) the most investigated features concerned the effects of vowelling and diglossia in Arabic reading, (3) findings were not always discussed in the light of existing reading models such as the dual route cascaded, the triangle, and the connectionist dual process models, and (4) current evidence is unreliable when it comes to the exact neuronal pathways that sustain Arabic word processing. Overall, despite the fact that Arabic has some unique linguistic features that challenge and ultimately enrich current reading models, the existing functional neuroimaging literature falls short of offering a reliable evidence about brain networks of Arabic reading. We conclude by highlighting the need for more systematic studies of the linguistic features of Arabic to build theoretical and neuroanatomical models that are concurrently specific and general.