Revolutionizing Sleep Health: The Emergence and Impact of Personalized Sleep Medicine.

Personalized sleep medicine represents a transformative shift in healthcare, emphasizing individualized approaches to optimizing sleep health, considering the bidirectional relationship between sleep and health. This field moves beyond conventional methods, tailoring care to the unique physiological and psychological needs of individuals to improve sleep quality and manage disorders. Key to this approach is the consideration of diverse factors like genetic predispositions, lifestyle habits, environmental factors, and underlying health conditions. This enables more accurate diagnoses, targeted treatments, and proactive management. Technological advancements play a pivotal role in this field: wearable devices, mobile health applications, and advanced diagnostic tools collect detailed sleep data for continuous monitoring and analysis. The integration of machine learning and artificial intelligence enhances data interpretation, offering personalized treatment plans based on individual sleep profiles. Moreover, research on circadian rhythms and sleep physiology is advancing our understanding of sleep's impact on overall health. The next generation of wearable technology will integrate more seamlessly with IoT and smart home systems, facilitating holistic sleep environment management. Telemedicine and virtual healthcare platforms will increase accessibility to specialized care, especially in remote areas. Advancements will also focus on integrating various data sources for comprehensive assessments and treatments. Genomic and molecular research could lead to breakthroughs in understanding individual sleep disorders, informing highly personalized treatment plans. Sophisticated methods for sleep stage estimation, including machine learning techniques, are improving diagnostic precision. Computational models, particularly for conditions like obstructive sleep apnea, are enabling patient-specific treatment strategies. The future of personalized sleep medicine will likely involve cross-disciplinary collaborations, integrating cognitive behavioral therapy and mental health interventions. Public awareness and education about personalized sleep approaches, alongside updated regulatory frameworks for data security and privacy, are essential. Longitudinal studies will provide insights into evolving sleep patterns, further refining treatment approaches. In conclusion, personalized sleep medicine is revolutionizing sleep disorder treatment, leveraging individual characteristics and advanced technologies for improved diagnosis, treatment, and management. This shift towards individualized care marks a significant advancement in healthcare, enhancing life quality for those with sleep disorders.

Comparing the Effectiveness of Cognitive Rehabilitation and Binaural Beats on Craving and Comorbidities of Sexual Hyperactivity: A Pilot, Exploratory Quasi-Experimental Study.

Sexual hyperactivity, often linked with substantial psychological and social disturbances, remains under-researched, particularly in contexts like Iran where cultural and social norms may influence the reporting and treatment of such conditions. This study explores the therapeutic potential of cognitive rehabilitation (CR) and binaural beats (BB) in addressing this issue. The primary objective was to compare the effectiveness of CR and BB in reducing symptoms of sexual hyperactivity and associated comorbid conditions, with a focus on fluctuations in sexual desire and overall mental health. Utilizing a quasi-experimental design, the study involved pretest, posttest, and follow-up assessments to evaluate the interventions' impacts. Recruitment through social media yielded 45 participants from a larger pool, who were then assigned to either the CR group, the BB group, or a control group. The CR and BB interventions were administered over a period of 10 sessions, each lasting 20 min, 3 times a week. Significant improvements were observed in both intervention groups compared to the control group. The CR group showed a marked reduction in Sexual Addiction Screening Test (SAST) scores from an initial average of 24.87 to 6.80 at follow-up, indicating a reduction in symptoms of sexual hyperactivity. The BB group also showed improvement, with SAST scores decreasing from 19.93 to 9.57. In terms of mental health comorbidities, the Depression, Anxiety, and Stress Scale (DASS-21) scores decreased notably in the CR group from a baseline of 8.53 to 3.07 post-intervention, and in the BB group from 10.33 to 5.80. Both interventions showed similar effectiveness in reducing anxiety and stress, with no statistically significant differences between the groups for most of the outcomes studied, affirming their potential for clinical application.

Toward Clinical Generative AI: Conceptual Framework.

Clinical decision-making is a crucial aspect of health care, involving the balanced integration of scientific evidence, clinical judgment, ethical considerations, and patient involvement. This process is dynamic and multifaceted, relying on clinicians' knowledge, experience, and intuitive understanding to achieve optimal patient outcomes through informed, evidence-based choices. The advent of generative artificial intelligence (AI) presents a revolutionary opportunity in clinical decision-making. AI's advanced data analysis and pattern recognition capabilities can significantly enhance the diagnosis and treatment of diseases, processing vast medical data to identify patterns, tailor treatments, predict disease progression, and aid in proactive patient management. However, the incorporation of AI into clinical decision-making raises concerns regarding the reliability and accuracy of AI-generated insights. To address these concerns, 11 "verification paradigms" are proposed in this paper, with each paradigm being a unique method to verify the evidence-based nature of AI in clinical decision-making. This paper also frames the concept of "clinically explainable, fair, and responsible, clinician-, expert-, and patient-in-the-loop AI." This model focuses on ensuring AI's comprehensibility, collaborative nature, and ethical grounding, advocating for AI to serve as an augmentative tool, with its decision-making processes being transparent and understandable to clinicians and patients. The integration of AI should enhance, not replace, the clinician's judgment and should involve continuous learning and adaptation based on real-world outcomes and ethical and legal compliance. In conclusion, while generative AI holds immense promise in enhancing clinical decision-making, it is essential to ensure that it produces evidence-based, reliable, and impactful knowledge. Using the outlined paradigms and approaches can help the medical and patient communities harness AI's potential while maintaining high patient care standards.

Impact assessment of self-medication on COVID-19 prevalence in Gauteng, South Africa, using an age-structured disease transmission modelling framework.

OBJECTIVE: To assess the impact of self-medication on the transmission dynamics of COVID-19 across different age groups, examine the interplay of vaccination and self-medication in disease spread, and identify the age group most prone to self-medication. METHODS: We developed an age-structured compartmentalized epidemiological model to track the early dynamics of COVID-19. Age-structured data from the Government of Gauteng, encompassing the reported cumulative number of cases and daily confirmed cases, were used to calibrate the model through a Markov Chain Monte Carlo (MCMC) framework. Subsequently, uncertainty and sensitivity analyses were conducted on the model parameters. RESULTS: We found that self-medication is predominant among the age group 15-64 (74.52%), followed by the age group 0-14 (34.02%), and then the age group 65+ (11.41%). The mean values of the basic reproduction number, the size of the first epidemic peak (the highest magnitude of the disease), and the time of the first epidemic peak (when the first highest magnitude occurs) are 4.16499, 241,715 cases, and 190.376 days, respectively. Moreover, we observed that self-medication among individuals aged 15-64 results in the highest spreading rate of COVID-19 at the onset of the outbreak and has the greatest impact on the first epidemic peak and its timing. CONCLUSION: Studies aiming to understand the dynamics of diseases in areas prone to self-medication should account for this practice. There is a need for a campaign against COVID-19-related self-medication, specifically targeting the active population (ages 15-64).

Investigating and Practicing Orthopedics at the Intersection of Sex and Gender: Understanding the Physiological Basis, Pathology, and Treatment Response of Orthopedic Conditions by Adopting a Gender Lens: A Narrative Overview.

In the biomedical field, the differentiation between sex and gender is crucial for enhancing the understanding of human health and personalizing medical treatments, particularly within the domain of orthopedics. This distinction, often overlooked or misunderstood, is vital for dissecting and treating musculoskeletal conditions effectively. This review delves into the sex- and gender-specific physiology of bones, cartilage, ligaments, and tendons, highlighting how hormonal differences impact the musculoskeletal system's structure and function, and exploring the physiopathology of orthopedic conditions from an epidemiological, molecular, and clinical perspective, shedding light on the discrepancies in disease manifestation across sexes. Examples such as the higher rates of deformities (adolescent idiopathic and adult degenerative scoliosis and hallux valgus) in females and osteoporosis in postmenopausal women illustrate the critical role of sex and gender in orthopedic health. Additionally, the review addresses the morbidity-mortality paradox, where women, despite appearing less healthy on frailty indexes, show lower mortality rates, highlighting the complex interplay between biological and social determinants of health. Injuries and chronic orthopedic conditions such osteoarthritis exhibit gender- and sex-specific prevalence and progression patterns, necessitating a nuanced approach to treatment that considers these differences to optimize outcomes. Moreover, the review underscores the importance of recognizing the unique needs of sexual minority and gender-diverse individuals in orthopedic care, emphasizing the impact of gender-affirming hormone therapy on aspects like bone health and perioperative risks. To foster advancements in sex- and gender-specific orthopedics, we advocate for the strategic disaggregation of data by sex and gender and the inclusion of "Sexual Orientation and Gender Identity" (SOGI) data in research and clinical practice. Such measures can enrich clinical insights, ensure tailored patient care, and promote inclusivity within orthopedic treatments, ultimately enhancing the precision and effectiveness of care for diverse patient populations. Integrating sex and gender considerations into orthopedic research and practice is paramount for addressing the complex and varied needs of patients. By embracing this comprehensive approach, orthopedic medicine can move towards more personalized, effective, and inclusive treatment strategies, thereby improving patient outcomes and advancing the field.

Corrigendum: Time-Trends in Air Pollution Impact on Health in Italy, 1990-2019: An Analysis from the Global Burden of Disease Study 2019.

[This corrects the article DOI: 10.3389/ijph.2023.1605959.].

Attenuating Muscle Damage Biomarkers and Muscle Soreness After an Exercise-Induced Muscle Damage with Branched-Chain Amino Acid (BCAA) Supplementation: A Systematic Review and Meta-analysis with Meta-regression.

BACKGROUND: Branched-chain amino acid (BCAA) supplementation is one of the most popular strategies used by the general population and athletes to reduce muscle soreness and accelerate the recovery process of muscle damage biomarkers after an intense exercise or training session. OBJECTIVES: This systematic review and meta-analysis investigated the effects of BCAA supplementation on muscle damage biomarkers and muscle soreness after exercise-induced muscle damage (EIMD). METHODS: The systematic literature search for randomized controlled trials was conducted using seven databases, up to September 13th, 2022. The eligibility criteria for selecting studies were as follows: studies performed on healthy active participants, using BCAA at least once, controlled with a placebo or control group, performing resistance or endurance exercises, and followed up at least once post-EIMD. The methodological quality of the studies was assessed using the "SIGN RCT checklist". Random-effects meta-analyses were processed to compute the standardized mean difference (Hedges' g). Meta-regression analyses were completed with daily and total dosage and supplementation as continuous moderator variables. RESULTS: Of the 18 studies included in this meta-analysis, 13 were of high quality and five were of acceptable quality. Our results revealed BCAA supplementation elicits a significant effect on reducing creatine kinase (CK) levels immediately (g = - 0.44; p = 0.006) and 72 h (g = - 0.99; p = 0.002), but not 24 h, 48 h, and 96 h post-EIMD. Additionally, a significant effect on delayed onset of muscle soreness (DOMS) was identified at 24 h (g = - 1.34; p < 0.001), 48 h (g = - 1.75; p < 0.001), 72 h (g = - 1.82; p < 0.001), and 96 h (g = - 0.82; p = 0.008), but not immediately post-EIMD. No significant effect was found on lactate dehydrogenase (LDH) levels at any time point. Meta-regression indicated higher daily and total dosages of BCAA, and longer supplementation periods were related to the largest beneficial effects on CK (total dosage and supplementation period) at 48 h, and on DOMS at 24 h (only daily dosage). CONCLUSION: The overall effects of BCAA supplementation could be considered useful for lowering CK and DOMS after EIMD, but not LDH. The longer supplementation period prior to the EIMD could be more effective for CK and DOMS reduction.

Effects of High-Intensity Interval Training on Muscle Strength for the Prevention and Treatment of Sarcopenia in Older Adults: A Systematic Review of the Literature.

Sarcopenia is a significant health concern primarily affecting old adult individuals, characterized by age-related muscle loss, and decreased strength, power, and endurance. It has profound negative effects on overall health and quality of life, including reduced independence, mobility, and daily activity performance, osteoporosis, increased fall and fracture risks, metabolic issues, and chronic diseases like diabetes and cardiovascular conditions. Preventive strategies typically involve a combination of proper nutrition and regular physical activity. Among strength training exercises, high-intensity interval training (HIIT) stands out as the most effective approach for improving muscle function in older adults with sarcopenia. The current review identifies and summarizes the studies that have examined the effects of HIIT on muscle strength in older adults as an element of the prevention and treatment of sarcopenia. A systematic search using several computerized databases, namely, MEDLINE/PubMed, Scopus, SPORTDiscus, and Web of Science, was performed on 12 January 2023, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A total of 224 studies were initially retrieved. A total of five studies met the selection criteria. HIIT training shows improvements in body composition and functional and cardiorespiratory capacity, has benefits on muscle strength, increases muscle quality and architecture, and is associated with muscle hypertrophy in healthy older adults. Nonetheless, given the shortcomings affecting primary research in terms of the limited number of studies and the high risk of bias, further research is warranted.

Volume Measurement of the Cavum Septi Pellucidi: Normative Values Between 20 and 40 Weeks of Gestation.

BACKGROUND: The cavum septi pellucidi (CSP) is a brain-enclosed cavity located on the midline between the two leaflets of the septum pellucidum that separates the lateral ventricles. This structure develops in the fetus from week 18 and can be seen up to week 37 in almost all cases and then begins to disappear. OBJECTIVES: To measure and determine the normative values of the CSP volume in fetuses between 20 to 40 weeks of gestation. METHODS: The study comprised 161 consecutive pregnant women between 20 to 40 weeks of gestation with single viable fetuses. All patients had normal, disease-free pregnancies. Transvaginal or transabdominal ultrasound was used according to the fetal presentation. The fetal head was assessed in mid-sagittal sections. Once the CSP was visualized, its volume was measured using three-dimensional ultrasound with Virtual Organ Computer-aided Analysis software. The width of the CSP was also measured at the biparietal diameter (BPD) plane. RESULTS: Of the 161 fetuses, the CSP volume was measured in 158. In three patients the CSP was not identified. The CSP volume correlated poorly with gestational age (r=0.229) and with the BPD (r=0.295). The mean CSP volume was 0.508 ± 0.372 ml (range: 0.03-1.78 ml). The simple measurement of the CSP width correlated better with gestational age (r=0.535) and the BPD (r=0.484). CONCLUSIONS: The CSP volume had a poor correlation with gestational age; however, the volume did not exceed 2 ml regardless of gestational age. This information can be used to assess pathologies involving the CSP.

Could the Historical Transition from Segmented to Monophasic Sleep Explain the Modern Insurgence of Alzheimer's Disease and Related Dementias?

 In their article, Finch and Burstein explore the hypothesis that Alzheimer's disease and related dementias (ADRD) may predominantly be phenomena of the modern era. Through a review of classical Greek and Latin literature, they found minimal reference to conditions akin to ADRD, suggesting a historical rarity of severe cognitive decline. Instead, ancient texts focused on physical aspects of aging, with cognitive changes, when noted, not resembling modern-day dementia. Finch and Burstein further extend their analysis by drawing parallels with the Tsimane people of Bolivia, known for their low prevalence of dementia and cardiovascular diseases, attributed to lifestyle factors such as diet and physical activity. By comparing historical sleep patterns transitioning from segmented to monophasic sleep with those of the Tsimane community, we enriched Finch and Burstein's research, highlighting the need to take into account a range of diverse factors, including sleep, in understanding the etiopathogenesis of ADRD in today's society.

Evaluating the effectiveness of artificial intelligence-based tools in detecting and understanding sleep health misinformation: Comparative analysis using Google Bard and OpenAI ChatGPT-4.

This study evaluates the performance of two major artificial intelligence-based tools (ChatGPT-4 and Google Bard) in debunking sleep-related myths. More in detail, the present research assessed 20 sleep misconceptions using a 5-point Likert scale for falseness and public health significance, comparing responses of artificial intelligence tools with expert opinions. The results indicated that Google Bard correctly identified 19 out of 20 statements as false (95.0% accuracy), not differing from ChatGPT-4 (85.0% accuracy, Fisher's exact test p = 0.615). Google Bard's ratings of the falseness of the sleep misconceptions averaged 4.25 ± 0.70, showing a moderately negative skewness (-0.42) and kurtosis (-0.83), and suggesting a distribution with fewer extreme values compared with ChatGPT-4. In assessing public health significance, Google Bard's mean score was 2.4 ± 0.80, with skewness and kurtosis of 0.36 and -0.07, respectively, indicating a more normal distribution compared with ChatGPT-4. The inter-rater agreement between Google Bard and sleep experts had an intra-class correlation coefficient of 0.58 for falseness and 0.69 for public health significance, showing moderate alignment (p = 0.065 and p = 0.014, respectively). Text-mining analysis revealed Google Bard's focus on practical advice, while ChatGPT-4 concentrated on theoretical aspects of sleep. The readability analysis suggested Google Bard's responses were more accessible, aligning with 8th-grade level material, versus ChatGPT-4's 12th-grade level complexity. The study demonstrates the potential of artificial intelligence in public health education, especially in sleep health, and underscores the importance of accurate, reliable artificial intelligence-generated information, calling for further collaboration between artificial intelligence developers, sleep health professionals and educators to enhance the effectiveness of sleep health promotion.

Repeated-sprint sets test: a new method for evaluating and forecasting fitness in elite young male soccer players.

The objective of the current study was to explore the correlation between repeated sprint sets (RSS) ability and several physical attributes, including maximum sprint speed, maximal aerobic speed, maximal anaerobic speed, aerobic capacity, and explosive strength. Moreover, the aim was to assess the suitability of RSS as a comprehensive evaluation tool for physical qualities and to determine which physical field tests most accurately predict RSS in elite young male soccer players. A total of thirty-two young elite male soccer players (mean age 14.6 ± 0.3 years; predicted years from peak height velocity (PHV): - 0.4 ± 0.3; years in training: 3.7 ± 0.5) voluntarily participated in the study. The players participated in eight consecutive specific physical tests, with a minimum 72-h recovery between each session to minimize the impact of fatigue during the second trial. The participants completed the tests in the following order: RSS test, Vam-Eval test, a constant velocity test performed until exhaustion at 100% of vVO2max (tlim100), 20-m Multi-Stage Shuttle Run test (VMSRT), Yo-Yo Intermittent Recovery Test level 1 (Yo-Yo IR1), Maximal Anaerobic Shuttle Running Test (VMASRT), Maximal Sprinting Speed Test (20-m flying sprint), Countermovement Jump (CMJ), and Standing Long Jump test (SLJ). The results of the study showed that there were very large negative correlations between tlim100 and SST (sum of sprint times), and large negative correlations between Yo-Yo IR1, Vam-Eval, and SST during RSS in young elite male soccer players (p < 0.05). Additionally, VMASRT and SLJ demonstrated a moderate negative correlation with SST (p < 0.05). In contrast, significant positive correlations were found between 20-m flying sprint and the SST (p < 0.05). According to the stepwise multiple linear regression analysis, the primary predictors of SST, ranked by importance, were tlim100 and Yo-Yo IR1. These two predictors collectively accounted for 72% of the variance in players' SST (p < 0.0001). Due to the importance of aerobic capacity and short repeated accelerations/sprint sets for overall competitive performance in soccer, in conclusion, our results suggest that elite young male soccer players should perform both high intensity interval training and aeorobic capactity exercises as part of soccer training if the primary outcome is to improve repeated sprint ability performance.

Economic microbiology: exploring microbes as agents in economic systems.

Microbial communities exhibit striking parallels with economic markets, resembling intricate ecosystems where microorganisms engage in resource exchange akin to human market transactions. This dynamic network of resource swapping mirrors economic trade in human markets, with microbes specializing in metabolic functions much like businesses specializing in goods and services. Cooperation and competition are central dynamics in microbial communities, with alliances forming for mutual benefit and species vying for dominance, similar to businesses seeking market share. The human microbiome, comprising trillions of microorganisms within and on our bodies, is not only a marker of socioeconomic status but also a critical factor contributing to persistent health inequalities. Social and economic factors shape the composition of the gut microbiota, impacting healthcare access and quality of life. Moreover, these microbes exert indirect influence over human decisions by affecting neurotransmitter production, influencing mood, behavior, and choices related to diet and emotions. Human activities significantly impact microbial communities, from dietary choices and antibiotic use to environmental changes, disrupting these ecosystems. Beyond their natural roles, humans harness microbial communities for various applications, manipulating their interactions and resource exchanges to achieve specific goals in fields like medicine, agriculture, and environmental science. In conclusion, the concept of microbial communities as biological markets offers valuable insights into their intricate functioning and adaptability. It underscores the profound interplay between microbial ecosystems and human health and behavior, with far-reaching implications for multiple disciplines. To paraphrase Alfred Marshall, "the Mecca of the economist lies in economic microbiology."

Epidemiological and Clinical Characteristics of Mpox in Cisgender and Transgender Women and Non-Binary Individuals Assigned to the Female Sex at Birth: A Comprehensive, Critical Global Perspective.

The 2022-2023 Mpox multi-country outbreak, identified in over 110 WHO Member States, revealed a predominant impact on cisgender men, particularly those engaging in sex with men, while less frequently affecting women. This disparity prompted a focused investigation into the gender-specific characteristics of Mpox infections, particularly among women, to address a notable knowledge gap. This review systematically gathers and analyzes the scientific literature and case reports concerning Mpox infections in women, covering a broad geographical spectrum including regions such as Argentina, Brazil, Colombia, Nigeria, Europe, Vietnam, and the United States. The analysis delves into various aspects of Mpox in women, including clinical features, epidemiology, psychological impacts, preparedness strategies, and case studies, with particular attention to pregnant women and those with underlying health conditions. Empirical data from multiple studies underscore the unique epidemiological and clinical patterns of Mpox in women. In the United States, a small percentage of Mpox cases were reported among cisgender women, with a notable portion involving non-Hispanic Black or African American, non-Hispanic White, and Hispanic or Latino ethnicities. The primary transmission route was identified as sexual or close intimate contact, with the virus predominantly manifesting on the legs, arms, and genital areas. Further, a study in Spain highlighted significant disparities in diagnosis delays, transmission modes, and clinical manifestations between genders, indicating a different risk profile and disease progression in women. Additionally, a case from Vietnam, linked to a new Mpox sub-lineage in women, emphasized the role of women in the transmission dynamics and the importance of genomic monitoring. This review emphasizes the necessity for inclusive surveillance and research to fully understand Mpox dynamics across diverse population groups, including women. Highlighting gender and sexual orientation in public health responses is crucial for an effective approach to managing the spread and impact of this disease. The findings advocate for a gender-diverse assessment in health services and further research to explore the nuances of Mpox transmission, behavior, and progression among different groups, thereby enhancing the global response to Mpox and similar public health challenges.

Frequency of brain ventricular enlargement among patients with diabetes mellitus.

AIMS: To determine the prevalence of dilated ventricles and concomitant high blood glucose measures. METHODS: We retrieved blood glucose measures from the emergency department database and selected a subgroup of individuals having both the radiological marker Evans' index (EI) values and blood glucose measures. RESULTS: Out of 1221 consecutive patients submitted to axial Computed Tomography scans, a blood glucose measure was detected in 841 individuals. 176 scans (21 %) showed an EI > 0.30. According to the blood glucose categorization, diabetic patients were 104 (12 %), 25 of them (24 %) were dilated (mean EI 0.33). The age difference between dilated and not-dilated ventricles is about ten years in not-diabetic participants, whereas it is five years in diabetic participants. The age difference between dilated and not-dilated ventricles is about 10 years in diabetic men, whereas it zero in diabetic women. CONCLUSIONS: Pathological ventricular enlargement is more frequent in men and in the elderly. In diabetic patients (especially women), the cerebral ventricles enlarge faster than in non-diabetic individuals. Age, sex, and diabetes may interact in determining how cerebral ventricle size changes over time, especially in diabetic women, making routine brain imaging advisable in these patients after the age of 70 years.

Assessing the Accuracy of Generative Conversational Artificial Intelligence in Debunking Sleep Health Myths: Mixed Methods Comparative Study With Expert Analysis.

BACKGROUND: Adequate sleep is essential for maintaining individual and public health, positively affecting cognition and well-being, and reducing chronic disease risks. It plays a significant role in driving the economy, public safety, and managing health care costs. Digital tools, including websites, sleep trackers, and apps, are key in promoting sleep health education. Conversational artificial intelligence (AI) such as ChatGPT (OpenAI, Microsoft Corp) offers accessible, personalized advice on sleep health but raises concerns about potential misinformation. This underscores the importance of ensuring that AI-driven sleep health information is accurate, given its significant impact on individual and public health, and the spread of sleep-related myths. OBJECTIVE: This study aims to examine ChatGPT's capability to debunk sleep-related disbeliefs. METHODS: A mixed methods design was leveraged. ChatGPT categorized 20 sleep-related myths identified by 10 sleep experts and rated them in terms of falseness and public health significance, on a 5-point Likert scale. Sensitivity, positive predictive value, and interrater agreement were also calculated. A qualitative comparative analysis was also conducted. RESULTS: ChatGPT labeled a significant portion (n=17, 85%) of the statements as "false" (n=9, 45%) or "generally false" (n=8, 40%), with varying accuracy across different domains. For instance, it correctly identified most myths about "sleep timing," "sleep duration," and "behaviors during sleep," while it had varying degrees of success with other categories such as "pre-sleep behaviors" and "brain function and sleep." ChatGPT's assessment of the degree of falseness and public health significance, on the 5-point Likert scale, revealed an average score of 3.45 (SD 0.87) and 3.15 (SD 0.99), respectively, indicating a good level of accuracy in identifying the falseness of statements and a good understanding of their impact on public health. The AI-based tool showed a sensitivity of 85% and a positive predictive value of 100%. Overall, this indicates that when ChatGPT labels a statement as false, it is highly reliable, but it may miss identifying some false statements. When comparing with expert ratings, high intraclass correlation coefficients (ICCs) between ChatGPT's appraisals and expert opinions could be found, suggesting that the AI's ratings were generally aligned with expert views on falseness (ICC=.83, P<.001) and public health significance (ICC=.79, P=.001) of sleep-related myths. Qualitatively, both ChatGPT and sleep experts refuted sleep-related misconceptions. However, ChatGPT adopted a more accessible style and provided a more generalized view, focusing on broad concepts, while experts sometimes used technical jargon, providing evidence-based explanations. CONCLUSIONS: ChatGPT-4 can accurately address sleep-related queries and debunk sleep-related myths, with a performance comparable to sleep experts, even if, given its limitations, the AI cannot completely replace expert opinions, especially in nuanced and complex fields such as sleep health, but can be a valuable complement in the dissemination of updated information and promotion of healthy behaviors.

The Psychometric Properties of the Arabic Version of the Anxiety and Preoccupation About Sleep Questionnaire (APSQ).

Background: Insomnia disorder is a common health condition; it has a role in increasing the possibility of developing other psychological disorders, including anxiety and depression. Anxiety and preoccupation with sleep are two examples of common cognitive factors that contribute to the development of chronic insomnia; thus, it is important to have a tool that assesses worry in insomnia. There is no comprehensive psychiatric measure to assess anxiety and preoccupation with sleep in Arabic. We conducted this study to translate, adapt, and validate the Arabic version of the Anxiety and Preoccupation about Sleep Questionnaire (APSQ), providing a reliable psychometric tool to assess concerns regarding sleep within Arabic-speaking communities. Methods: The translation process of the scale involved several steps, including forward and backward translation. A cross-sectional study was conducted using an online survey completed by 523 participants from various Arabic-speaking countries. Psychometric analysis was performed utilizing the R software, including internal consistency, test-retest reliability, and confirmatory factor analysis. In addition, convergent and divergent against the Athens insomnia scale (AIS) and general anxiety disorder (GAD) were conducted. Results: The Arabic-translated form of the APSQ expresses excellent internal consistency with a value of 0.91 for both Cronbach's α and McDonald's ω. The test-retest reliability of a subsample showed an excellent coefficient of 0.93 (p<0.01). A good fit of the APSQ was observed by CFI = 0.93, TLI = 0.91, SRMR = 0.05, and RMSEA = 0.1. Convergent and divergent against AIS and GAD showed statistically significant correlations of 0.85 (p<0.01) and 0.69 (p<0.01), respectively. Our sample showed a mean APSQ score of 31.28 ± 8.31, and the mean age was 23.62 ± 7.5. Conclusion: The Arabic APSQ is reliable and valid for measuring anxiety and preoccupation with sleep in Arabic countries. Using translated APSQ for clinical diagnosis and research is currently trustworthy.

Adaptive Shooting Disciplines: A Scoping Review of the Literature with Bibliometric Analysis.

Para-archery and para-shooting, two very popular adaptive shooting disciplines that have earned their place as major official events in the Paralympic Games, share some similarities, as well as distinctive features in terms of rules, physiological requirements, and equipment used. The International Paralympic Committee has a clear responsibility to ensure that all sports within its jurisdiction, including adaptive shooting, can achieve excellence in their respective fields. To achieve this, the conduct of well-designed studies and rigorous research is essential. Although some research has been conducted in this area, a comprehensive and systematic evaluation is still needed. Therefore, the present study aims to provide a thorough review and synthesis of existing research on adaptive shooting disciplines, identify strengths and gaps, and suggest future directions. Arksey and O'Malley's methodology is leveraged and enhanced with bibliometric and policy analyses to review literature on adaptive shooting. Databases like PubMed/MEDLINE, Scopus, Web of Science, OvidSP, and EMBASE were searched, focusing on studies in adaptive shooting disciplines and analysing these findings through a blend of thematic and statistical methods. Twenty-four studies totalling 483 para-athletes (299 para-shooters and 184 para-archers) are included in this scoping review, focusing on a range of aspects, including physiological responses (n = 9), research design and measurement methods for evidence-based classification (n = 6), biopsychosocial aspects (n = 3), development of new methods and technologies (n = 4), kinematic and biomechanical assessment (n = 1), and epidemiology of injuries (n = 1). Seven articles focused exclusively on para-archery, thirteen exclusively on para-shooting, and four on both para-archery and para-shooting. In conclusion, the available literature on adaptive shooting disciplines is still very limited, especially regarding para-archery compared to para-shooting. This highlights the need for further research in many key areas to ensure a better understanding of the different disciplines and to provide appropriate support for para-athletes. Future research in para-archery and para-shooting should focus on technological innovations, biomechanical studies, and psychological support to enhance athlete performance and accessibility. Addressing the imbalance between the two disciplines, along with injury prevention and global participation, can drive the sports towards greater inclusivity and equity for para-athletes worldwide.

Effect of COVID-19 on the prevalence of bystanders performing cardiopulmonary resuscitation: A systematic review and meta-analysis.

BACKGROUND: The importance of bystander cardiopulmonary resuscitation (CPR) during out-of-hospital cardiac arrests is especially important in the context of coronavirus disease 2029 (COVID-19) because it can significantly influence survival outcomes. The objective of this meta-analysis was to examine the primary outcomes of bystander CPR during the pandemic and pre-pandemic periods. METHODS: A search was conducted in the PubMed Central, Scopus, and EMBASE databases, as well as the Cochrane Central Register of Controlled Trials database, up to December 10, 2023. In cases where the value of I² was greater than or equal to 50% or the Q-test indicated that the p-value was less than or equal to 0.05, the studies were considered to be heterogeneous. Sensitivity assessment was performed using the leave-one-out methodology. The study protocol was registered in PROSPERO with the ID number CRD42023494912. RESULTS: Twenty-five articles were included in this meta-analysis. Pooled analysis showed that bystander CPR frequency during the COVID-19 pandemic was 38.8%, compared to 44.8% for the pre-pandemic period (odds ratio: 1.04; 95% confidence interval: 0.93-1.16; p = 0.48). CONCLUSIONS: The article's conclusions indicate that the COVID-19 pandemic influenced a reduction in bystander CPR compared to the pre-pandemic period, but this difference was not statistically significant. Further research is recommended to understand attitudes, including the fears of witnesses, before performing CPR on patients with suspected or confirmed infectious diseases. The study highlights the importance of bystander intervention in emergency situations and the impact of a pandemic on public health response behaviors.

A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets.

BACKGROUND: The COVID-19 pandemic has highlighted gaps in the current handling of medical resource demand surges and the need for prioritizing scarce medical resources to mitigate the risk of health care facilities becoming overwhelmed. OBJECTIVE: During a health care emergency, such as the COVID-19 pandemic, the public often uses social media to express negative sentiment (eg, urgency, fear, and frustration) as a real-time response to the evolving crisis. The sentiment expressed in COVID-19 posts may provide valuable real-time information about the relative severity of medical resource demand in different regions of a country. In this study, Twitter (subsequently rebranded as X) sentiment analysis was used to investigate whether an increase in negative sentiment COVID-19 tweets corresponded to a greater demand for hospital intensive care unit (ICU) beds in specific regions of the United States, Brazil, and India. METHODS: Tweets were collected from a publicly available data set containing COVID-19 tweets with sentiment labels and geolocation information posted between February 1, 2020, and March 31, 2021. Regional medical resource shortage data were gathered from publicly available data sets reporting a time series of ICU bed demand across each country. Negative sentiment tweets were analyzed using the Granger causality test and convergent cross-mapping (CCM) analysis to assess the utility of the time series of negative sentiment tweets in forecasting ICU bed shortages. RESULTS: For the United States (30,742,934 negative sentiment tweets), the results of the Granger causality test (for whether negative sentiment COVID-19 tweets forecast ICU bed shortage, assuming a stochastic system) were significant (P<.05) for 14 (28%) of the 50 states that passed the augmented Dickey-Fuller test at lag 2, and the results of the CCM analysis (for whether negative sentiment COVID-19 tweets forecast ICU bed shortage, assuming a dynamic system) were significant (P<.05) for 46 (92%) of the 50 states. For Brazil (3,004,039 negative sentiment tweets), the results of the Granger causality test were significant (P<.05) for 6 (22%) of the 27 federative units, and the results of the CCM analysis were significant (P<.05) for 26 (96%) of the 27 federative units. For India (4,199,151 negative sentiment tweets), the results of the Granger causality test were significant (P<.05) for 6 (23%) of the 26 included regions (25 states and the national capital region of Delhi), and the results of the CCM analysis were significant (P<.05) for 26 (100%) of the 26 included regions. CONCLUSIONS: This study provides a novel approach for identifying the regions of high hospital bed demand during a health care emergency scenario by analyzing Twitter sentiment data. Leveraging analyses that take advantage of natural language processing-driven tweet extraction systems has the potential to be an effective method for the early detection of medical resource demand surges.