Cluster Sampling Research Articles

The ACT-DR5 MCMF galaxy cluster catalog

Galaxy clusters are useful cosmological probes and interesting astrophysical laboratories. As the cluster samples continue to grow in size, a deeper understanding of the sample characteristics and improved control of systematics becomes more crucial. For this analysis we created a new and larger ACT-DR5-based thermal Sunyaev–Zel’dovich Effect- (tSZE-) selected galaxy cluster catalog with improved control over sample purity and completeness. We employed the red sequence based cluster redshift and confirmation tool MCMF together with optical imaging data from the Legacy Survey DR-10 and infrared data from the WISE satellite to systematically identify true clusters from a new cluster candidate detection run on the ACT-DR5 dataset. The resulting ACT-DR5 MCMF sample contains 6,237 clusters with a residual contamination of 10.7%. This is an increase of 49% compared to the previous ACT-DR5 cluster catalog, making this new catalog the largest tSZE-selected cluster catalog to date. The zphot>1 subsample contains 703 clusters, three times more than in the previous ACT-DR5 catalog. Cross-matching the ACT-DR5 MCMF cluster catalog with a deeper tSZE sample from SPTpol 500d allows us to confirm the completeness and purity of the new ACT-DR5 MCMF sample. Cross-matching to the two largest X-ray-selected cluster samples, the all-sky RASS MCMF and the western Galactic hemisphere survey eRASS1, confirms the sample purity of the RASS MCMF sample and in the case of eROSITA eRASS1 reveals that 43% of the matched clusters are designated in eRASS1 as X-ray point sources rather than groups and clusters. Cross-correlating the ACT-DR5 MCMF cluster catalog with ACT-DR6 lensing maps results in a 16.4σ detection of Cosmic Microwave Background (CMB) lensing around the clusters, corresponding to the strongest signal found so far for a galaxy cluster sample. Repeating the measurement for the z > 1 cluster subsample yields a significance of 4.3σ, which is the strongest CMB lensing detection in a z>1 cluster sample to date.

Inference in cluster randomized trials with matched pairs

This paper studies inference in cluster randomized trials where treatment status is determined according to a “matched pairs” design. Here, by a cluster randomized experiment, we mean one in which treatment is assigned at the level of the cluster; by a “matched pairs” design, we mean that a sample of clusters is paired according to baseline, cluster-level covariates and, within each pair, one cluster is selected at random for treatment. We study the large-sample behavior of a weighted difference-in-means estimator and derive two distinct sets of results depending on if the matching procedure does or does not match on cluster size. We then propose a single variance estimator which is consistent in either regime. Combining these results establishes the asymptotic exactness of tests based on these estimators. Next, we consider the properties of two common testing procedures based on t-tests constructed from linear regressions, and argue that both are generally conservative in our framework. We additionally study the behavior of a randomization test which permutes the treatment status for clusters within pairs, and establish its finite-sample and asymptotic validity for testing specific null hypotheses. Finally, we propose a covariate-adjusted estimator which adjusts for additional baseline covariates not used for treatment assignment, and establish conditions under which such an estimator leads to strict improvements in precision. A simulation study confirms the practical relevance of our theoretical results.

THE INFLUENCE OF DATA SAMPLING ON SOLVING THE PROBLEM OF PATTERN RECOGNITION FOR DIAGNOSTICS OF INDUSTRIAL EQUIPMENT

With the sophisticated technology that modern industrial organizations are equipped with, state prediction and diagnostics are essential duties. The current research aims to develop a more accurate modified artificial intelligence system for industrial equipment diagnostics in the oil and gas industry. Researching faulty signals and processing methods utilized by equipment in the oil and gas industry, as well as assessing the advantages and disadvantages of different signal extraction strategies, are the first steps in the process. The second is the application of artificial intelligence to decision-making and equipment defect detection. This method widely used by the oil and gas sectors to lower equipment failure rates. The recommended diagnostic system helps organizations reduce the financial risks associated with equipment defects by increasing production dependability, enabling for maintenance planning, predicting probable failures, and expediting equipment repairs. The article is devoted to the study of the data sampling influence on the classifier’s predictive ability in diagnosing of the industrial equipment. Various types of data samples were considered, such as: simple random sample, cluster sample, systematic sample. According to the results of listed data samples were built classifiers based on particle swarm optimization and ensemble models (bagging and voting type). The best results were achieved using the systematic sampled dataset and an ensemble modeling strategy with voting, which combines forecasting based on a neural net, gradient boosted trees and naive Bayes models: accuracy 93.6%; classification error 8%; recall 94.32%; precision 93.87%. The resulting best strategy for diagnosing equipment based on data sampling and an ensemble model was used for implementation in FMEA (Failure Mode and Effects Analysis) technology in order to obtain an improved version, which is adapted for working with big data.

Optimizing population mean estimation under ranked set sampling with applications to Engineering

This article aims to develop two novel mean estimators of finite populations under ranked set sampling. The suggested estimators result in a high-efficiency gain due to their efficient formulation by taking the linear combination of classical estimators using optimization constants. We also discuss the theoretical properties and derive bias and mean squared error up to the first order of approximation. To theoretically validate our proposed estimators, we derive the conditions under which our estimators prevail over the competing estimators. The findings suggest that when ranked set sampling is implemented effectively, it saves cost and improves precision, serving as a potent instrument for improved decision-making, specifically in engineering applications, such as environmental monitoring, resource management, and quality control. An empirical and simulation study has been conducted using real and synthetic data to validate our methodology empirically. The suggested estimators offer a significant contribution to survey sampling in estimating mean under ranked set sampling. Further, the proposed estimator can be seamlessly adapted in other sampling designs such as simple random sampling, stratified random sampling, cluster sampling, etc, as well as in estimating other parameters such as variance, skewness, coefficient of correlation, etc. in various domains.

Predictors of health preventive behavior among university students in the post-COVID-19 era in Wuhan via TikTok journeying

TikTok has become increasingly popular among young people in China and there is growing number of young people who start to pay great attention to their health through this platform. Wuhan is a significant location for this study, since it was the initial epicenter of COVID-19. However, little is known about the extent to which university students in Wuhan, China, rely on TikTok for health-related information and how this affects their preventive health actions in the post-COVID-19 era. Therefore, it is crucial to look into the direct effects of TikTok users’ search for health information and their actions to protect their health, as well as the mediating functions of e-health literacy and COVID-19 risk perception. The impact of TikTok as a social media platform on the health-related behaviors of university students was examined using the Media Dependency Theory which explains how media use can have significant effects on individuals’ attitudes, beliefs, and behaviors. 426 questionnaires were gathered by cluster sampling from a sample of Wuhan university students. Mplus8 was used to perform structural equation modelling, which looked at the relationships between these variables. The results showed a positive correlation between users’ TikTok health information seeking and their health preventive behavior (β = 0.303, p < 0.001). Furthermore, it was discovered that this relationship is mediated by e-health literacy and COVID-19 risk perception in series (β =0.029, p<0.001). The findings demonstrate how TikTok functions as a platform that supports university students’ efforts to protect their health. The results also imply that students’ post-COVID-19 preventive measures for health in search of health information on TikTok are significantly influenced by their e-health literacy as well as their perception of COVID-19 danger. By obtaining more accurate health-related information, university students are equipped with more health skills and have correct attitude towards the disease. In summary, these results advance the knowledge of how TikTok, a social media platform, affects the health-related behaviors of university students.

Dental Caries and Erosive Tooth Wear Among 12-Year-Old Hong Kong Children

ObjectiveThis study is to investigate the dental caries, erosive tooth wear status, and oral health-related habits of 12-year-old Hong Kong children. MethodsThis cross-sectional survey recruited 12-year-old children using clustered random sampling from three main districts. The trained examiner examined the children's caries status using the criteria recommended by the World Health Organization and recorded their caries experience using the decayed, missing, and filled tooth (DMFT) index. The children's tooth wear status was determined using the Basic Erosive Wear Examination (BEWE) index. Their oral hygiene practice was collected using a self-administered questionnaire. ResultsWe recruited 445 children and 396 children participated (response rate: 89%). Their mean DMFT was 0.29 ± 0.73. Seventy children (18%, 70/396) had caries experience (DMFT > 0) and they had 116 teeth suffered from caries. Among these 116 carious teeth, 75 teeth (65%, 75/116) were filled (FT), one tooth (1%, 1/116) was extracted (MT), and 40 teeth (34%, 40/116) were carious (DT). Five children had more than one decayed tooth (DT > 1), and one child had the highest number of decayed teeth (DT) at 4. BEWE results showed 284 (72%, 284/396) children had no erosive tooth wear (BEWE = 0). No child had severe erosive tooth wear (BEWE = 3). However, children consuming lemon tea or lemonade and vitamin C drinks 3 times a week or more showed significantly higher BEWE scores. Additionally, 380 (96%, 380/396) children brushed their teeth daily and 116 children (29%, 116/396) flossed their teeth. ConclusionMost 12-year-old Hong Kong children had neither caries experience nor tooth wear, and their oral health-related habits were satisfactory. SignificanceThis study updated the caries status of the permanent dentition of 12-year-old Hong Kong children. The information offers updated oral health data for the local, regional, and global authorities for planning effective public health programmes to improve the oral health of children.

Assessment of knowledge and behavioral risk factors of reproductive tract infections among married women of 15–49 years in rural areas of Haldwani block, Uttarakhand

ABSTRACT Background: One of the most serious public health issues in India is reproductive tract infections (RTIs), which have a profound effect on the lives of men and women, as well as their families and communities. Objectives: To describe the sociodemographic traits, assess women’s RTI knowledge, and determine which behavioral risk factors are involved in female RTI. Methods: Using a 30-cluster sampling approach, a cross-sectional study design was employed to examine RTIs in 30 villages located in the Haldwani block of the district Nainital. Results: It was shown that just 7.6% of women knew enough about RTIs. Among the 450 women surveyed, the percentage of RTI cases was significantly lower for those who used the barrier method during menstruation (7.7%), had more than three children (25.7%), had a trained person deliver their baby in a hospital (24.1%), used condoms as a family planning method (5.6%), used sanitary pads during menstruation (25.6%), and maintained good personal hygiene (22.4%). Conclusion: The study revealed that the participants’ understanding of RTI was lacking.

Alumni Rating Index and Monitoring Dashboard Technology to Improve University’s Performance and Service Quality

Limited number of university ranking systems have considered the perspectives of alumni or individuals who have availed themselves of the educational programs or services provided by the institutions. In Malaysia, there is a lack of comprehensive rankings or assessments that primarily focus on assessing university performance through the lens of student experiences. In the absence of authentic user experiences, prospective students and other relevant parties commonly rely on conventional academic rankings such as the QS or THE to ascertain the quality of a university. The primary aims of this research endeavour encompass the identification of pivotal variables for the evaluation of higher learning institution’s performance, the creation of an alumni rating index, and the establishment of a performance monitoring tool utilizing dashboard technology. The goals are to enhance performance and service quality of institutions of higher education. The present study utilizes a quantitative research approach and centres its investigation on many cohorts of graduates originating from a prominent Malaysian university. A rigorous cluster sampling procedure was implemented. The assessment of alumni rating is conducted across twelve dimensions, with each component being evaluated using appropriate variables that enable the calculation of the desired index and facilitate the execution of intricate studies. The analytics that were performed and the alumni rating index that was calculated were subsequently shared with stakeholders through the use of an analytical dashboard. The dashboard was developed on user experience (UX) design principles. The evaluation of the produced dashboard is thereafter conducted by a group of stakeholders who have direct involvement in enhancing alumni engagement. The findings suggest that the university attained elevated ratings in the domains of social involvement, educational resources, and financial value. However, the scores for financial aid, student development, and student well-being were significantly lower. Despite the provision of various financial support, the respondents hold the belief that these forms of assistance are inadequate. The paper concludes by demonstrating the implementation of an alumni rating dashboard. The research is expected to facilitate the development of a localise university rankings and ratings, as well as informed policy-making efforts at the ministry level.

Constructing a Galaxy Cluster Catalog in IllustrisTNG300 Using the Mulguisin Algorithm

We present a new simulated galaxy cluster catalog based on the IllustrisTNG simulation. We use the Mulguisin (MGS) algorithm to identify galaxy overdensities. Our cluster identification differs from the previous friends-of-friends (FoF) cluster identification in two aspects: (1) we identify cluster halos based on the galaxy subhalos instead of unobservable dark matter particles, and (2) we use the MGS algorithm, which separates galaxy overdensities hosted by massive galaxies. Our approach provides a cluster catalog constructed in a way similar to the construction of observed cluster catalogs using spectroscopic surveys. The MGS cluster catalog lists 303 halos with M 200 > 1014 M ⊙, including ∼10% more than the FoF catalog. The MGS catalog includes more systems because we separate some independent massive MGS cluster halos that are bundled into a single FoF halo. These independent MGS halos are apparently distinguishable in the galaxy spatial distribution and the phase-space diagram. Because we construct a refined cluster catalog that identifies local galaxy overdensities, we evaluate the effect of MGS clusters on the evolution of galaxies better than when using the FoF cluster catalog. The MGS halo identification also enables effective identifications of merging clusters by selecting systems with neighboring galaxy overdensities. We thus highlight the fact that the MGS cluster catalog is a useful tool for studying clusters in cosmological simulations and for comparing with observed cluster samples.

Mental Health Problems Among Indonesian Adolescents: Findings of a Cross-Sectional Study Utilising Validated Scales and Innovative Sampling Methods

PurposeThis study aimed to estimate the prevalence of mental health problems and identify potential risk and protective exposures for adolescents in Indonesia. MethodsAn innovative sampling approach was applied to simultaneously recruit school- and community-based adolescents aged 16–18 years old from Jakarta (urban megacity) and South Sulawesi (remote province). We used multistage cluster sampling for in-school (N = 1,337) and respondent driven sampling for out-of-school (N = 824) adolescents. Mental health was measured using two validated scales: Kessler-10 and Center for Epidemiologic Studies Depression Scale-Revised . Psychiatric interviews were conducted in a subsample (N = 196) of students from Jakarta to validate the self-report scales. ResultsThe estimated population prevalence of psychological distress and depression were 24.3% (95% CI = 21.5–27.2) and 12.6% (10.5–14.4) for in-school and 23.7% (20.7–26.7) and 23.5% (20.4–26.5) for out-of-school adolescents, respectively. In participants who completed a psychiatric interview, common psychiatric morbidities were social anxiety, depression, and suicidality. Compared to in-school females, male in-school adolescents reported a lower prevalence of psychological distress (16.9% (13.1–20.7) vs. 30.4% (26.4–34.4)) and depression (10.1% (7.2–13.1) vs. 14.6 (11.4–17.8)). By contrast, for out-of-school adolescents, males reported a higher prevalence of psychological distress (25.2% (21.6–28.9) vs. 20.2% (15.1–25.3)) and depression (26.3% (22.5–30.1) vs. 16.9% (11.8–21.9)). In-school adolescents who did not seek healthcare despite a perceived need were more likely to report psychological distress and depression. DiscussionAdolescent mental health problems are highly prevalent in Indonesia, with substantial variation by gender, geography, and school enrolment. This study and its approach to sampling and measurement may serve as a model to improving mental health surveillance across other settings.

The relationship between explicit and implicit educational values and learning burnout among senior high school students

This study aimed to demonstrate the relationship between explicit and implicit educational values and learning burnout among senior high school students in China. Using stratified cluster sampling, 768 students from six high schools participated in a survey on explicit educational values and learning burnout. The Single Category Implicit Association Test (SC-IAT) explored students’ implicit attitudes toward educational values. The results showed that an emphasis on economic benefit was placed first among all explicit educational values. In contrast, the external value of education was more likely to be recognized in implicit educational values. Explicit and implicit educational values were significantly negatively correlated with learning burnout. However, there were no significant correlations between the explicit and implicit educational values, suggesting that the two belong to relatively independent psychological structures.

Prevalence and pattern of bullying victimization among early adolescent students in Sri Lanka: A School based cross-sectional study

Background: Bullying victimization has resulted in various forms of detrimental effects on mental and social wellbeing of adolescents. The study was designed to determine the prevalence and pattern of bullying victimization among early adolescent students in Sri Lanka.Methods: A school based cross-sectional study was conducted among 2641 grade seven, eight and nine students in 43 government schools in an educational zone in Kegalle district in Sri Lanka selected by stratified random cluster sampling method. The validated Sinhala version of Olweus Bully/Victim Questionnaire (OBVQ) was used to assess the victimization status, its subtypes and patterns of victimization according to the category of schools.Results: The response rate was 96.01%. The prevalence of bullying victimization among 12-14 years aged schooling adolescents in the Kegalle educational zone was 59% (95% CI = 57.1-60.9). Verbal bullying was the commonest type of victimization 45.2% (95% CI = 43.24-47.16). Calling names teasing in a hurtful way (36.3%), trying to disrupt the friendship among friends (22.3%) pinching, scratching by nails, pulling from the hair, ear and dress (22.4%) were the most frequently existing bullying activities among victims. Overall bullying victimization and subtypes of bullying victimization were significantly higher among male students (p=&lt;0.001), younger age group (12 years) (p=&lt;0.001) and significantly less in category IAB schools (p=&lt;0.001).Conclusions: Prevalence of bullying victimization and subtypes of victimization among early adolescent students in the Kegalle educational zone was high. It was significantly more among males and in younger age and more observed in type 2 schools.

Association and relevant factors between objective masticatory performance and subjective masticatory ability among community-dwelling older adults

Background/purposeDentists often focus on masticatory performance (MP) rather than masticatory ability (MA) and treatment expectations when evaluating older adults. This study aimed to determine if MA aligns with MP and to explore influencing factors. Materials and methodsThis cross-sectional study utilized a multi-stage stratified cluster sampling, including one thousand community-dwelling adults aged 60 and older. Participants underwent oral exams and questionnaire interviews, assessing tooth count and Eichner index (EI) levels. MP and MA were quantified using a standard gummy jelly test and a 14-food group questionnaire, respectively. Multivariable linear regressions analyzed correlations between MP, MA, and related factors. ResultsApproximately 25 % of participants exhibited poor MP. Factors contributing to poor MP included increased age rise, low education, number of chronic diseases, tooth loss, without the assistance of removable dentures, and being in EI group C (all P < 0.05). Tooth count showed a significant negative correlation with MP (P < 0.001). Participants' MP declined significantly from good to poor, with MA scores decreasing from 11.96 to 7.52 (P < 0.001). The tooth number was a common factor influencing MA across food groups (all P < 0.05). The decline in MA among older adults was linked to age rise, tooth loss, lack of assistance of removable dentures, and being in EI group C. ConclusionSelf-rated MA in older adults effectively reflects their MP. Maintaining a high tooth count to meet occlusal support and the use of dentures to assist with tooth loss in older adults help to improve their MA.

Association Between Ward's Triangle Bone Mineral Density Levels and Abdominal Aortic Calcification: Data from the National Health and Nutrition Examination Survey 2013–2014.

BACKGROUND & AIMSDespite extensive research into the cardiovascular implications of abdominal aortic calcification (AAC), there is a scarcity of robust studies exploring its association with Ward's triangle bone mineral density (BMD). This study aimed to evaluate this relationship in a nationally representative sample and compare the predictive value with femoral neck BMD and total femur BMD. METHODSWe conducted a cross-sectional analysis of 2013-2014 National Health and Nutrition Examination Survey (NHANES) data, utilizing a complex, stratified, multistage, cluster sampling design. BMD measurements at Ward's triangle, femoral neck, and total femur were assessed using DXA scans. AAC severity was defined by a Kauppila score of ≥5. Predictors of AAC-24 scores were identified through correlation and linear regression models. Stratified regression and restricted cubic splines were applied to explore subgroup and dose-response relationships. RESULTSOf the 2,965 participants representing 116,562,500 individuals in the U.S., 11% had severe AAC. Ward's triangle BMD showed a significant negative association with AAC-24 scores (β = -1.90, 95% CI: -2.80 to -1.00, P < 0.002) and a reduced risk of severe AAC (OR = 0.85, 95% CI: 0.76 to 0.95, P = 0.010). Non-linear associations were observed between Ward's triangle BMD and AAC outcomes. Ward's triangle BMD outperformed femoral neck and total femur BMD in predicting AAC. CONCLUSIONSHigher Ward's triangle BMD is linked to lower odds of severe AAC, highlighting its potential for improved early detection of AAC over femoral neck and total femur BMD. Healthcare providers should consider the implications of reduced Ward's triangle BMD for systemic atherosclerosis and recommend early AAC screening for enhanced cardiovascular risk management.

LoVoCCS. II. Weak Lensing Mass Distributions, Red-sequence Galaxy Distributions, and Their Alignment with the Brightest Cluster Galaxy in 58 Nearby X-Ray-luminous Galaxy Clusters

The Local Volume Complete Cluster Survey is an ongoing program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts 0.03 < z < 0.12 and X-ray luminosities in the 0.1–2.4 keV band L X500c > 1044 erg s−1) with the Dark Energy Camera, capturing data in the u, g, r, i, z bands with a 5σ point source depth of approximately 25th–26th AB magnitudes. Here, we map the aperture masses in 58 galaxy cluster fields using weak gravitational lensing. These clusters span a variety of dynamical states, from nearly relaxed to merging systems, and approximately half of them have not been subject to detailed weak lensing analysis before. In each cluster field, we analyze the alignment between the 2D mass distribution described by the aperture mass map, the 2D red-sequence (RS) galaxy distribution, and the brightest cluster galaxy (BCG). We find that the orientations of the BCG and the RS distribution are strongly aligned throughout the interiors of the clusters: the median misalignment angle is 19° within 2 Mpc. We also observe the alignment between the orientations of the RS distribution and the overall cluster mass distribution (by a median difference of 32° within 1 Mpc), although this is constrained by galaxy shape noise and the limitations of our cluster sample size. These types of alignment suggest long-term dynamical evolution within the clusters over cosmic timescales.

A Network Structure of Mental Health and Problematic Mobile Phone Use Among Middle School Students.

Numerous studies have shown that the mental health of middle school students is closely related to problematic mobile phone use. The purpose of this study is to investigate the network structure between the dimensions of the Middle School Students Mental Health Scale and the items of the Self-Rating Questionnaire for Adolescent Problematic Mobile Phone Use by using the network analysis, to clarify the core symptoms and bridge symptoms of the network structure, and to provide ideas and methods for intervening in the mental health and problematic mobile phone use of middle school students. A stratified cluster sampling method was used to select 1637 students from four general middle schools in Xiamen in June 2020 for the survey, and the Middle School Students Mental Health Scale (MSSMHS-60) and the Self-Rating Questionnaire for Adolescent Problematic Mobile Phone Use (SQAPMPU) were used. SPSS28.0 was used for descriptive statistical analysis and R (version 4.2.1) for network analysis. 1. The core symptoms of the network of middle school students' mental health and problematic mobile phone use were "spending more time playing with the phone in order to be satisfied", anxiety, and depression; 2. The bridge symptoms of the network of middle school students' mental health and problematic mobile phone use were academic stress, psychological disequilibrium, and "depression without phone". Reducing the time of smartphone use and relieving anxiety and depression can improve the mental health of middle school students and reduce the incidence of problematic mobile phone use; helping middle school students adjust their study pressure and improving their social support level can reduce the severity of problematic mobile phone use.

Drivers of COVID-19 Vaccination among Eligible Adults in Abuja, Nigeria: A Mixed-Methods Study Using the WHO Behavioral and Social Drivers of Vaccination Framework.

Despite the availability of COVID-19 vaccines, Nigeria still faces significant COVID-19 vaccine hesitancy, with only 60.7% of the eligible population fully vaccinated as of 20 March 2023. Our study, part of a community-based effort to improve knowledge and uptake of the COVID-19 vaccine in the Gwagwalada Area Council of Abuja, the Federal Capital Territory (FCT) of Nigeria, utilized the WHO's Behavioral and Social Drivers (BeSDs)-of-vaccination framework to examine the drivers of COVID-19 vaccination among eligible adults. This was a mixed-method study with focus group discussions (FGDs) and in-depth interviews (IDIs) involving 40 purposively sampled participants. We triangulate qualitative findings with data from a household survey of 1512 eligible adults identified using a two-stage systematic cluster sampling approach. All data were collected from the 1-18 November 2022. The household survey showed 46% COVID-19 vaccine uptake, with Pearson chi-square and Fisher's exact test showing significant associations between vaccine uptake and gender, religion, and education. Multivariate logistic regression showed that confidence in vaccine safety, knowing vaccination sites and family/friends' endorsement of COVID-19 vaccination were the strongest items associated with vaccine uptake in the thinking-and-feeling, practical-issue, and social-process domains, respectively. Multiple items measuring these domains aligned with BeSD priority question, demonstrating the robustness of the pared-down framework. Qualitative data corroborated these findings. To address vaccine hesitancy and increase uptake, community-driven approaches to improve trust in vaccine safety and benefits and promote positive vaccination norms are needed. In addition, service delivery strategies to make vaccination services easily accessible and identifiable should be developed and tailored to community needs.

Prevalence of risky sexual behaviour and its associated factors among youths of Pokhara metropolitan city, Nepal: a cross-sectional study

IntroductionRisky sexual behaviour, which puts young people at greater risk of acquiring HIV AIDS and sexually transmitted infection, is a significant public health concern all around the world. In 2020,...

Exploring internet addiction during Covid-19 pandemic: a comparative study considering psychological, social, familial and individual aspects in University students.

Internet addiction causes a variety of social, interpersonal, psychological, and physical issues. We are confronting a worldwide crisis about internet addiction and its effects. Utilizing five questionnaires to survey university students during the COVID-19 epidemic, the current study sought to evaluate internet addiction and associated risk variables. At the University of Medical Sciences in North Iran, a cross-sectional analytical investigation was carried out. The sample was done among 318 students, selected through the random cluster sampling method. Data collection was done during August and September 2021. Based on our findings, the prevalence of internet addiction was 28.9% (92/318). Our results revealed that women are at twice the twice the risk of internet addiction as men (p = 0.028). Students in the medicinal field (p = 0.043; students with a positive history of mental illness in the family) p = 0.001 (and students with a fear of COVID-19) p = 0.002 (recognized in the risk of Internet addiction, thus depression) p < 0.001 (anxiety) p < 0.001 (somatization) p = 0.001 (and psychological distress) p < 0.001 are risk factors for internet addiction. Age, marital status, place of living, total social support, and use of Alcohol/cigarettes are not risk factors for internet addiction. The findings suggest that university students with a fear of COVID-19, depression, anxiety, somatization, psychological distress and a positive history of mental illness in the family, particularly medicinal field students, are at significant risk for Internet addiction.

The Role of Age-friendly City Indicators in Predicting Social Belonging in Older Adults Residing in Mohammadiyeh County, Qazvin, Iran

Objectives A strong sense of belonging is crucial for the physical and mental health of older adults and their social interactions. The age-friendly city offers various opportunities for social participation of older adults. The present study aims to determine the role of age friendly-city indicators in predicting social belonging of older adults residing in Mohammadiyeh County, Qazvin Province, Iran. Methods &amp; Materials This descriptive-analytical study was conducted on 300 older adults in 2022, who were selected by a cluster sampling method from six municipal districts of Mohammadiyeh County. Data were collected using a demographic checklist, an age-friendly city scale, and a social belonging scale. Data analysis was conducted in SPSS software version 23 using multivariate linear regression analysis. The significance level was set at 0.05. Results The mean age of participants was 67.55±6 years, ranging from 60 to 84 years. The majority of them were male (n=157, 52.33%), married (n=216, 72%), and illiterate (n=157, 52.33%). Among the age-friendly city indicators, the highest score was related to the safety/ease of transportation (16.86±4.51) and open public spaces (45.61±11.47) indicators. The results of multivariate regression analysis showed that marital status (β=-0.150, P=0.006), lower than high school education (β=0.170, P=0.003) and high school diploma (β=0.192, P=0.001), and the age-friendly city indicator of safety/ease of transportation (β=0.328, P&lt;0.001) were predictors of social belonging in older adults. Conclusion The majority of older adults in Mohammadiyeh County are dissatisfied with age-friendly indicators. Those who feel safe and have easy access to public transportation are more likely to have a stronger sense of social belonging. The results of this study can effectively help policymakers and city managers in proper planning in order to develop an age-friendly city.