Pain is one of the most common reasons that drives people to go to hospitals. It has been found that several factors affect the practices of pain management. In this regard, this study aimed at investigating the underlying determinants in terms of pain management practices. Based on reviewing the previous studies and the suggestions of the KAP model, it was hypothesized that the main elements of the KAP model (attitudes and knowledge) significantly predict the variation in the practices of nurses regarding pain management. A questionnaire comprising the KAP model’ s constructs , i.e. knowledge and attitude towards pain management , as well as pain management practices, was used to collect data from 266 registered nurses ( n=266) who are deemed competent in the management of patients’ pain in the Jordanian public hospitals. The two constructs, attitude and knowledge, which are the main determinants of the KAP model were found to independently predict nurses’ practices of managing patients’ pain. Knowledge of pain management was found to be the strongest predictor. Additionally, it was found that about 69% of the variance in pain management could be explained by the constructs of the KAP model. Therefore, it is recommended that the Jordanian hospitals and universities focus on nurses’ knowledge and attitude towards pain management in order to enhance their practices in the field of pain management.

Introduction: In the current era, different health issues exist because of the lifestyle we have adopted. Mostly, people suffer from different deadly disorders like diabetes because of their own behavior. Gamification is considered to be a good source to maintain a healthy life. Gamification has benefits over other games as it involves changing the behavior of the individual. It helps in giving support to unhealthy people and by changing their behavior, makes their health better. Objective: Gamification has several advantages, but little is known about it. In this systematic review, we examined studies that illustrate the benefit of gamification in health and well-being. For this objective, we recognized the benefits of gamification based on existing research and performed a complete literature review of empirical studies on gamification for health and well-being. Methodology: We collected 30 papers containing empirical evidence on the influence of gaming on health and well-being. The inclusion criteria entailed peer-reviewed articles published from 2012 to 2023. The studies were published in English language and their methodology was randomized controlled trials. Results: The majority of the studies indicated positive impacts, less than half mixed effects, and some of the evidence was intermediate. The results for health-related behavior were clear, whereas the results for cognitive outcomes were varied. According to the collected information, gamification could promote health and wellness, particularly behaviors related to health. Several studies, however, demonstrated a mixed or neutral influence. Conclusion: From the findings of the studies, it could be easily stated that gamification helps in changing the behavior of the individual. However, due to fewer studies used in the review and due to restrictions in certain limits in articles, it could not clearly be concluded that gamification provides the same response in individuals of varying ages. A greater number of studies should be included, and the findings should be carefully examined to know clearly about the effect of gamification in response to the changing behavior of individuals of varying ages.

This study was designed to investigate the effects of curcumin (CMN) soluble complex (SC) prepared by melt casting (HM) and hot-melt extrusion (HME) technology. Phase solubility (PS) study, in silico molecular modeling, aqueous solubility, drug release, and physicochemical investigation including a novel dyeing test was performed to obtain an optimized complex by a central composite design (CCD). The results show that the HME-SC produces better improvements towards solubility (0.852 ± 0.02), dissolution (91.87 ± 0.21% at 30 min), with an ideal stability constant (309 and 377 M⁻¹ at 25 and 37 °C, respectively) and exhibits A_L type of isotherm indicating 1:1 stoichiometry. Intermolecular hydrogen bonding involves the formation of SC, which does not undergo any chemical modification, followed by the complete conversion of the amorphous form which was identified by XRD. The in vitro cytotoxicity showed that IC₅₀ was achieved in the SW480 (72 µM.mL⁻¹) and Caco-2 (40 µM.mL⁻¹) cells while that of pure CMN ranged from 146 to 116 µM/mL⁻¹. Apoptosis studies showed that cell death is primarily due to apoptosis, with a low rate of necrosis. In vivo toxicity, confirmed by the zebrafish model, exhibited the safety of the HME-SC. In conclusion, the HME-SC potentially enhances the solubility and cytotoxicity to the treatment of colorectal cancer (CRC).

The lockdown after the COVID-19 pandemic not only caused public health crises and income stress but also put millions at risk of food insecurity and malnutrition across the globe, especially in low and middle-income countries [LMICs]. This study evaluated the effects of financial stress and household socio-economic deprivation on the nutritional status of 1551 children under the age of five during COVID-19 in Pakistan. A self-administered questionnaire was used between November 2020 and April 2021 to collect information on age, height, children’s weight, and socio-economic status from 1152 rural households from underdeveloped regions in Punjab, Pakistan. With the help of the proportionate simple random sampling method, this study employed a model (binary logistic regression) to calculate the likelihood of malnourishment. The findings showed that the stunting, underweight, and wasting prevalence rates during COVID-19 were 58.86%, 41.89%, and 8.11%, respectively, in the Bahawalpur region. According to the binary logistic regression analysis, among the household deprivation status (HDS) categories, the risks of childhood malnutrition were lesser in HDS-2 (OR = 0.05, 95% CI: 0. 005–0.879) and HDS-3 (OR = 0.04, 95% CI: 0.008–0.193). Similar to this, within the financial stress index (FSI) categories, the children in homes with medium financial stress had reduced odds of malnutrition (OR = 0.10, 95% CI: 0.018–0.567), and the children in households with low financial stress had reduced risks of malnutrition (OR = 0.006, 95% CI: 0.005–0.061). The proposed research found that stunting and underweight increased by 17.26% and 12.29% during the COVID-19 lockdown in the Bahawalpur region. Additionally, financial stress and socio-economic deprivation strongly affected children’s nutritional statuses during the COVID-19 lockdown in the Bahawalpur region of Southern Punjab.

Pain management is one of the most recurrent healthcare services provided by nurses. Based on the proposition of the self-efficacy theory, knowledge and attitudes can affect the nurses; confidence and their ability to manage the patients’ discomforts, which consequently affects their ability to apply appropriate pain management practices. The study examines the relationship between knowledge and attitudes towards distress management and the nurse’s individual capability to manage pain. The research is a transverse, correlational design study involving 266 registered nurses (n = 266). The nurses were requested to provide information on pain management via three instruments: attitude to, knowledge of and self-efficacy of pain management. Statistically, the nurses displayed an essential relationship between self-efficacy and attitude towards pain management (β = 0.502, t = 10.119, p< 0.001). Also, the study discovered a substantial connection between the nurses’ familiarity to pain management and their ability to manage it in patients’ pain (β = 0.368, t = 6.619, p < 0.001). This study recommends that future research be undertaken to investigate the mediating effects of self-efficacy on the knowledge and attitude towards agony management relationship and distress management practices. Additionally, in future, scholars can examine the direct relationship between the effectiveness of agony control and pain management routines of nurses.

Background: Artificial intelligence embodies the ability of computers to emulate human intelligence and generate well-informed choices. Quality within the healthcare domain encompasses adopting proficient, patient-centric, secure, and productive services that are unbiased, comprehensive, punctual, and streamlined. In this regard, this study aimed to investigate the impact of artificial intelligence on healthcare quality. This study echoed the World Health Organization’s findings that artificial intelligence has great potential for distributed clinical automation, delivering efficient clinical information, and offering extra support in healthcare settings. Methods: This systematic review employed PRISMA methodology and inclusion and exclusion criteria to search through central databases exploring the impact of artificial intelligence on healthcare quality. Specifically, this study concentrated on randomized controlled trials published in PubMed. The search process employed Boolean operators (AND) and (OR) and the main keywords detailed in the methodological section. As a result, two thousand five hundred forty-four sources were identified. The identified sources underwent a rigorous screening process, which entailed the removal of duplication. These eligibility criteria considered studies published in the English language, availability of full text, thorough description of the research aims, objectives, methodology, findings, and conclusion, the number of references, and general presentation. Out of 2544 identified sources, only 18 sources passed the eligibility criteria and were included in this research. The Meta-analysis was conducted using RevMan 5, Mantel-Haenszel, random effect, and 95% confidence intervals. Results: Overall, the studies were substantially heterogeneous at I²=92%, Z score was 1.93, and the P-value was within the range of less than or equal to 5. Therefore, the general studies provided a significant positive impact of artificial intelligence on healthcare quality. The heterogeneity was minimized through subgroup analysis, where the studies were divided about the objectives. Generally, 6/18 studies yielded an odd ratio of more than 1, reflecting the positive influence of artificial intelligence on healthcare quality. 12/18 studies positively used artificial intelligence in assisted healing or medication adherence, but none were statistically significant. Conclusion: Artificial intelligence does not directly influence healthcare quality but helps improve other functions within healthcare services. Healthcare quality is comprehensive, encompassing evidence-based practice, patient-centric care, effective communication, care coordination, effective risk management strategies, health information technology, health promotion, and disease prevention.