Effective Interventions Research Articles

Prevalence and Burden of Multiple Sclerosis in China, 1990-2019: Findings From the Global Burden of Disease Study 2019.

Multiple sclerosis (MS) is the leading cause of neurologic disability in young adults, but the burden caused by MS in China is lacking. We aimed to comprehensively describe the prevalence and health loss due to MS by demographic and geographical variables from 1990 to 2019 across China. Data were obtained from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019). We used GBD methodology to systematically analyze the prevalence, disability-adjusted life-years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) due to MS by age, sex, and location from 1990 to 2019 in mainland China and its provinces. We also compared the MS burden in China with the world and other Group of 20 (G20) countries. In 2019, 42,571 (95% uncertainty interval [UI] 33,001-53,329) individuals in China had MS, which doubled from 1990. The age-standardized prevalence rate of MS was 2.32 per 100,000 (95% UI 1.78-2.91), which increased by 23.31% (95% UI 20.50-25.89) from 1990, with most of the growth occurring after 2010. There was a positive latitudinal gradient with the increasing prevalence from south to north across China. The total DALYs caused by MS were 71,439 (95% UI 58,360-92,254) in 2019, ranking China third among G20 countries. Most of the MS burden in China derived from premature mortality, with the higher fraction of YLLs than that at the global level and most other G20 countries. From 1990 to 2019, the age-standardized DALY and YLL rate had nonsignificant changes; however, the age-standardized YLD rate substantially increased by 23.33% (95% UI 20.50-25.89). The geographic distribution of MS burden varied at the provincial level in China, with a slight downward trend in the age-standardized DALY rates along with increasing Socio-Demographic Index over the study period. Although China has a low risk of MS, the substantial and increasing prevalent cases should not be underestimated. The high burden due to premature death and geographic disparity of MS burden reveals insufficient management of MS in China, highlighting the needs for increased awareness and effective intervention.

Opportunities for Interventional Radiology in Paediatric Oncology

Interventional oncology (IO) has emerged as a pivotal field within interventional radiology (IR), gaining prominence in the past three decades. It has transcended its initial role in cancer care, expanding beyond biopsies and vascular access to offer a spectrum of percutaneous and transarterial procedures, transforming into a curative and palliative discipline. However, implementing IO in children presents distinctive challenges. While the technical aspects of IO procedures mirror those in adults, paediatric cases require specialised considerations. Radiologists must possess an in-depth understanding of the paediatric disease, tailor imaging modalities to the case, discern unique risks, and interpret disease markers specific to children. Notably, paediatric tumour biopsies demand significantly larger tissue samples for genetic sequencing, staging, and prognostication. Paediatric IO also confronts procedural disparities. Tumours in children may be larger relative to body size, necessitating precise radioembolisation dose calculations. The proximity of critical structures in small bodies amplifies the risk of collateral damage. When performing percutaneous ablation and endovascular therapies, these challenges must also be faced so that radiologists can navigate these complex clinical and technical considerations to ensure safe and effective interventions, all while prioritising the well-being of their young patients. This review summarises the current role and future opportunities for IO in paediatric cancer.

Missed Opportunities: Characteristics of People Who Received a Concurrent HIV/AIDS Diagnosis in New York State From 2016 to 2021.

Late HIV diagnosis is associated with a wide range of negative outcomes. The aim of this study was to identify the characteristics of individuals who received a concurrent diagnosis (CDX) in New York State (NYS) so that more effective interventions can be developed to encourage earlier testing among these populations. The NYS HIV registry was used to identify people who received a CDX from 2016 to 2021. A CDX was a diagnosis that met the criteria for a stage 3 HIV infection within 30 days of the initial HIV diagnosis. Sex at birth, race/ethnicity, transmission risk group, age at diagnosis, region of residence at diagnosis, urbanicity of zip code of diagnosis, and type of diagnosing facility were used as covariates. Bivariate and multivariate risk ratios were calculated to quantify associations between CDX and covariates. There were 14,866 people newly diagnosed with HIV in NYS from 2016 to 2021, of which 19.0% had a CDX. Those with female sex at birth, history of injection drug use, or history of male-to-male sexual contact/history of injection drug use risk were less likely to have a CDX. Increased age, Asian race/ethnicity, residence outside of New York City, and diagnosis at inpatient facilities or emergency rooms were associated with an increased likelihood of a CDX. Populations with the highest proportions of CDX were ones that made up a small percentage of all new HIV diagnoses and may not be benefiting as much from current HIV prevention efforts. There are complex interactions between many factors including geographic and social characteristics that may lead to delayed diagnostic testing.

Answering tough questions: Why is qualitative research essential for public health?

Qualitative research is a crucial approach to uncovering the nuances of public health behaviours and useful insights for effective policies and interventions. We highlight key contributions and innovations of qualitative research as it pertains to public health knowledge and practice, particularly in the time of COVID-19 post-pandemic recovery.

The course of acute low back pain: a community-based inception cohort study.

Acute low back pain (LBP) is increasingly recognized for its potential recurrent nature and long-term implications. This community-based inception cohort study aimed to delineate trajectories of acute LBP over one year and investigate associated biopsychosocial variables. One hundred seventy-six participants with acute LBP were monitored at 5 follow-up time points over 52 weeks. Pain trajectories were identified using a latent class linear mixed model, and their associations with baseline biopsychosocial factors were evaluated through multinomial logistic regression. Four distinct LBP trajectories were discerned: "mild/moderate fluctuating pain" (54.0%), "delayed recovery by week 52" (6.2%), "persistent moderate pain" (33.0%), and "moderate/severe fluctuating pain" (6.8%). Increased baseline pain intensity and history of LBP episodes were significantly linked with less favorable trajectories. Contrary to expectations, psychological variables like stress, anxiety, and depression did not significantly associate with unfavorable trajectories. This study underscores the heterogeneity of acute LBP's course over a year, challenging the conventionally benign perception of the condition. Recognizing these distinct trajectories might enable more tailored, effective clinical interventions for LBP patients. The small sample size of certain trajectories may influence the generalizability of the results. Acute LBP can manifest in different trajectories, with nearly half of the participants experiencing less favorable trajectories. Baseline pain intensity and previous episodes of LBP emerged as key factors, whereas psychological variables had no discernible influence. Recognition of these trajectories may be necessary for improved patient management and targeted interventions.

Pain in Neonates: Perceptions and Current Practices.

All newborns experience pain during routine care, which can have long-lasting negative effects. Despite the availability of effective methods to prevent and reduce pain, most infants will receive ineffective or no treatment. Optimal pain management includes the reduction of the number of procedures performed, routine pain assessment and the use of effective pain-reducing interventions, most notably breastfeeding, skin-to-skin contact and sweet-tasting solutions. Parents are an essential component of the comprehensive assessment and management of infant pain; however, a gap exists regarding the uptake of parent-led interventions and the engagement of families. Practice recommendations for infant pain care are discussed.

Effects of clamshell exercises in terminal extension lag after ACL reconstruction

BackgroundTerminal extension lag (TEL) is common following anterior cruciate ligament reconstruction (ACLR). Clamshell exercises have been suggested as a potential intervention to address TEL, but limited research has been conducted in this area. ObjectiveThis study aimed to determine the effects of Clamshell exercises in terminal extension lag after anterior cruciate ligament reconstruction. MethodsThis randomized controlled trial included 40 participants with a history of ACLR between 1 and 3 years prior. Participants were randomly assigned to either the experimental group (Group A) or the control group (Group B). Group A received conventional exercises along with isolated hip strengthening rehabilitation, while Group B received conventional exercises without specific hip strengthening. The primary outcomes were pain levels (Numeric Pain Rating Scale), knee function (International Knee Documentation Committee scores, (IKDC)), range of motions (goniometer) and strength (sphygmomanometer). ResultsIn between the group comparison shows that all outcome measures (NPRS, IKDC, Goniometer, Sphygmomanometer) show significant results (p < 0.05). Within-group comparisons (paired sample t-test) show that there was a significant difference (p < 0.05) in all outcome measures of both groups. ConclusionThe addition of Clamshell exercises to the rehabilitation program resulted in a significantly greater reduction in TEL compared to the control group. These findings suggest that Clamshell exercises were found to be an effective intervention for addressing TEL after ACLR.

Analyzing electroencephalograph signals for early Alzheimer’s disease detection: deep learning vs. traditional machine learning approaches

Alzheimer’s disease (AD) stands as a progressive neurodegenerative disorder with a significant global public health impact. It is imperative to establish early and accurate diagnoses of AD to facilitate effective interventions and treatments. Recent years have witnessed the emergence of machine learning (ML) and deep learning (DL) techniques, displaying promise in various medical domains, including AD diagnosis. This study undertakes a comprehensive contrast between conventional machine learning methods and advanced deep learning strategies for early AD diagnosis. Conventional ML algorithms like support vector machines, decision trees, and K nearest neighbor have been extensively employed for AD diagnosis through relevant feature extraction from heterogeneous data sources. Conversely, deep learning techniques such as multilayer perceptron (MLP) and convolutional neural networks (CNNs) have demonstrated exceptional aptitude in autonomously uncovering intricate patterns and representations from unprocessed data like EEG data. The findings reveal that while traditional ML methods may perform adequately with limited data, deep learning techniques excel when ample data is available, showcasing their potential for early and precise AD diagnosis. In conclusion, this research paper contributes to the ongoing discourse surrounding the choice of appropriate methodologies for early Alzheimer’s disease diagnosis.

Psychological outcomes in patients with rare cancers: a systematic review and meta-analysis

Rare cancers are those that exhibit an incidence of less than six per 100,000 in a year. On average, the five-year relative survival for patients with rare cancers is worse than those with common cancers. The traumatic experience of cancer can be further intensified in patients with rare cancers due to the limited clinical evidence and the lack of empirical evidence for informed decision-making. With rare cancers cumulatively accounting for up to 25% of all cancers, coupled with the rising burden of rare cancers on societies globally, it is necessary to determine the psychological outcomes of patients with rare cancers. This PRISMA-adherent systematic review (PROSPERO: CRD42023475748) involved a systematic search of PubMed, Embase, Cochrane and PsycINFO for all peer-reviewed English language studies published since 2000 to 30th January 2024 that evaluated the prevalence, incidence and risk of depression, anxiety, suicide, and post-traumatic stress disorder (PTSD) in patients with rare cancers. Two independent reviewers appraised and extracted the summary data from published studies. Random effects meta-analyses and meta-regression were used for primary analysis. We included 32 studies with 57,470 patients with rare cancers. Meta-analyses indicated a statistically significant increased risk-ratio (RR) of depression (RR=2.61, 95% CI: 1.43-4.77, I2=97%) and anxiety (RR=2.66, 95% CI: 1.27-5.55, I2=92%) in patients with rare cancers compared to healthy controls. We identified a high suicide incidence (315 per 100,000 person-years, 95% CI: 162-609, I2=95%), prevalence of depression (17%, 95% CI: 14-22, I2=88%), anxiety (20%, 95% CI: 15-25, I2=96%) and PTSD (18%, 95% CI: 9-32, I2=25%). When compared to patients with common cancer types, suicide incidence, and PTSD prevalence were significantly higher in patients with rare cancers. Systematic review found that having advanced disease, chemotherapy treatment, lower income, and social status were risk factors for negative psychological outcomes. We highlight the need for early identification of psychological maladjustment in patients with rare cancers. Additionally, studies to identify effective interventions are imperative. This study was supported by the National Medical Research Council Transition Award, SingHealth Duke-NUS Oncology Academic Clinical Programme, the Khoo Pilot Collaborative Award, the National Medical Research Council Clinician Scientist-Individual Research Grant-New Investigator Grant, the Terry Fox Grant and the Khoo Bridge Funding Award.

EXPLORING TEAM COHESION IN PROJECT MANAGEMENT

Project management represents an essential area of research with a significant impact on society and the economy. This paper aims to critically analyze the scientific literature on team cohesion and its influence on project outcomes. We employ a qualitative approach based on secondary sources to identify and evaluate critical factors such as knowledge exchange, trust, and team cohesion and to examine how these contribute to project success. The novelty of our work lies in its interdisciplinary approach, integrating perspectives from organizational psychology and project management to investigate the dynamics of team cohesion and its impact on project performance. Within this article, we critically analyzed team cohesion through the lens of individual team member competencies first, leadership styles second, and the relationship between them third. Our results indicate that integrating team cohesion into project dynamics maximizes operational efficiency and enhances resilience and adaptability against unexpected challenges. Managers who adopt specific leadership approaches (e.g., transformational and transactional) are identified as crucial factors in creating and maintaining project team cohesion. Furthermore, the article emphasizes that integrating team cohesion into management practices contributes not only to project success but also to its sustainability. Managers can develop effective strategies and interventions to enhance collaboration and outcomes within project teams by profoundly understanding the relationship between team cohesion and project performance.

Advancements in Adolescent Idiopathic Scoliosis Diagnosis: A Focus on Non-Invasive Techniques

Abstract: Adolescent idiopathic scoliosis (AIS) poses a significant health concern, affecting the spinal curvature of adolescents during their growth period. Early diagnosis of AIS is critical for effective intervention and management. However, conventional diagnostic methods often involve repetitive exposure to X-rays, which can lead to radiation-related side effects. This research paper explores the significance of early diagnosis in AIS and emphasizes the utilization of non-invasive techniques, particularly video raster stereography (VRS), combined with deep ensemble neural networks (DNNs) to enhance diagnostic accuracy while minimizing the risks associated with radiation exposure. We delve into the potential of DNNs in analyzing VRS data and compare its efficacy with other machine learning alternatives

Road Accident Analysis and Classification Using Machine Learning Algorithms

Abstract: India is facing a severe public health crisis characterized by a significant number of road accidents resulting in fatalities and life-altering injuries. This study undertakes a detailed analysis of road accidents in India using multi-year accident data to unveil recurring patterns and identify high-risk demographics. The research meticulously examines the primary causes of these accidents, including driver behavior such as speeding, and inadequate road infrastructure such as poor lighting, signage, potholes, and vehicle malfunctions. Moreover, the paper proposes a comprehensive approach to prevent these tragedies. It suggests strategies for enhancing road design and maintenance, enforcing traffic regulations more rigorously, and conducting targeted public awareness campaigns to promote responsible driving practices. By highlighting the alarming increase in fatalities and the substantial socio-economic costs associated with these accidents, this research emphasizes the critical need for immediate and effective interventions to establish a safer road environment for all citizens in India.

From Nurture to Deviance: A Study on Parenting Style and Juvenile Delinquency

ABSTRACT Drawing on data and quantitative analysis from the 2019 Recidivism Survey conducted by the Ministry of Justice in China, this study unveils a significant correlation between parenting styles, parent-child relationships, and juvenile delinquency. Negative parenting practices can lead to increased anxiety or a lack of self-control, especially in scenarios characterized by inadequate parental supervision. This shortfall in self-regulation is directly associated with a surge in criminal behavior among adolescents, thereby elevating the risk of engaging in delinquent activities. Furthermore, poor parent-child relationships exacerbate the adverse effects of insufficient parental oversight on juvenile misconduct. Youths with diminished social and emotional bonds to their parents are more susceptible to diverging from societal norms and participating in delinquent behaviors. Therefore, effective intervention strategies aimed at curbing juvenile delinquency should focus on improving parental supervision and guidance while simultaneously nurturing positive parent-child relationships.

Moving beyond borders: impacts of interstate migration on Supplemental Nutrition Assistance Program participation

ABSTRACT Understanding the impact of interstate migration on Supplemental Nutrition Assistance Program (SNAP) participation is crucial due to the potential influence of such migration on the effectiveness of social welfare programs. This study shows that interstate migration decreases the probability of SNAP participation, finding a reduction in SNAP benefits of $462.7 among interstate migrants relative to non-migrants in the subsequent year. These findings suggest that simplifying the recertification process for interstate migrants could serve as an effective policy intervention to address these challenges.

Integrative Bioinformatics Approaches to Uncover Hub Genes and Pathways Involved in Cardiovascular Diseases.

Cardiovascular diseases (CVD) represent a significant global health challenge resulting from a complex interplay of genetic, environmental, and lifestyle factors. However, the molecular pathways and genetic factors involved in the onset and progression of CVDs remain incompletely understood. Here, we performed an integrative bioinformatic analysis to highlight specific genes and signaling pathways implicated in the pathogenesis of 80 CVDs. Differentially expressed genes (DEGs) were identified through the integrated analysis of microarray and GWAS datasets. Then, hub genes were identified after gene ontology functional annotation analysis and protein-protein internet (PPI) analysis. In addition, pathways were identified through KEGG and gene ontology enrichment analyses. A total of 821 hub genes related to 80 CVDs were identified, including 135 common and frequent CVD-associated genes. TNF, IL6, VEGFA, and TGFB.1 genes were the central core genes expressed in 50% or more of CVDs, confirming that the inflammation is a key pathological feature of CVDs. Analysis of hub genes by KEGG enrichment revealed predominant enrichment in 201 KEGG pathways, of which the AGE-RAGE signaling pathway in diabetic complications was identified as the common key KEGG implicated in 62 CVDs. In addition, the outcomes showed an overrepresentation in pathways categorized under human diseases, particularly in the subcategories of infectious diseases and cancers, which may be common risk factors for CVDs. In conclusion, this powerful approach for in silico fine-mapping of genes and pathways allowed the identification of determinant hubs genes and pathways implicated in the pathogenesis of CVDs which could be employed in developing more targeted and effective interventions for preventing, diagnosing, and treating CVDs. The function of these hub genes in CVDs needs further exploration to elucidate their biological characteristics.

An agent-based model of the spread of behavioural risk-factors for cardiovascular disease in city-scale populations.

Cardiovascular disease (CVD) is the leading cause of mortality globally, and is the second main cause of mortality in the UK. Four key modifiable behaviours are known to increase CVD risk, namely: tobacco use, unhealthy diet, physical inactivity and harmful use of alcohol. Behaviours that increase the risk of CVD can spread through social networks because individuals consciously and unconsciously mimic the behaviour of others they relate to and admire. Exploiting these social influences may lead to effective and efficient public health interventions to prevent CVD. This project aimed to construct and validate an agent-based model (ABM) of how the four major behavioural risk-factors for CVD spread through social networks in a population, and examine whether the model could be used to identify targets for public health intervention and to test intervention strategies. Previous ABMs have typically focused on a single risk factor or considered very small populations. We created a city-scale ABM to model the behavioural risk-factors of individuals, their social networks (spousal, household, friendship and workplace), the spread of behaviours through these social networks, and the subsequent impact on the development of CVD. We compared the model output (predicted CVD events over a ten year period) to observed data, demonstrating that the model output is realistic. The model output is stable up to at least a population size of 1.2M agents (the maximum tested). We found that there is scope for the modelled interventions targeting the spread of these behaviours to change the number of CVD events experienced by the agents over ten years. Specifically, we modelled the impact of workplace interventions to show that the ABM could be useful for identifying targets for public health intervention. The model itself is Open Source and is available for use or extension by other researchers.

Resistance to pyrethroids and the relationship between adult resistance and knockdown resistance (kdr) mutations in Aedes albopictus in dengue surveillance areas of Guizhou Province, China

The Ae. albopictus mosquito has gained global attention due to its ability to transmit viruses, including the dengue and zika. Mosquito control is the only effective way to manage dengue fever, as no effective treatments or vaccines are available. Insecticides are highly effective in controlling mosquito densities, which reduces the chances of virus transmission. However, Ae. albopictus has developed resistance to pyrethroids in several provinces in China. Pyrethroids target the voltage-gated sodium channel gene (VGSC), and mutations in this gene may result in knockdown resistance (kdr). Correlation studies between resistance and mutations can assist viruses in managing Ae. albopictus, which has not been studied in Guizhou province. Nine field populations of Ae. albopictus at the larval stage were collected from Guizhou Province in 2022 and reared to F1 to F2 generations. Resistance bioassays were conducted against permethrin, beta-cypermethrin, and deltamethrin for both larvae and adults of Ae. albopictus. Kdr mutations were characterized by PCR and sequencing. Additionally, the correlation between the kdr allele and pyrethroid resistance was analyzed. All nine populations of Ae. albopictus larvae and adults were found to be resistant to three pyrethroid insecticides. One kdr mutant allele at codon 1016, one at 1532 and three at 1534 were identified with frequencies of 13.86% (V1016G), 0.53% (I1532T), 58.02% (F1534S), 11.69% (F1534C), 0.06% (F1534L) and 0.99% (F1534P), respectively. Both V1016G and F1534S mutation mosquitoes were found in all populations. The kdr mutation F1534S was positively correlated with three pyrethroid resistance phenotypes (OR > 1, P < 0.05), V1016G with deltamethrin and beta-cypermethrin resistance (OR > 1, P < 0.05) and F1534C only with beta-cypermethrin resistance (OR > 1, P < 0.05). Current susceptibility status of wild populations of Ae. albopictus to insecticides and a higher frequency of kdr mutations from dengue-monitored areas in Guizhou Province are reported in this paper. Outcomes of this study can serve as data support for further research and development of effective insecticidal interventions against Ae. albopictus populations in Guizhou Province.

The mediating role of self-regulated online learning behaviors: Exploring the impact of personality traits on student engagement

AbstractOnline learning environments have become increasingly prevalent in higher education, necessitating an understanding of factors influencing student engagement. This study examines the mediating role of self-regulated online learning in the relationship between five-factor personality traits and student engagement among university students. A sample of 437 university students from educational sciences, social sciences, and health sciences disciplines participated in the study. Data were collected using ‘The Big Five Inventory’ to assess personality traits, the ‘Self-Regulated Online Learning Questionnaire’ to measure self-regulated online learning, and the ‘Student Engagement Scale in the Online Learning Environment’ to evaluate student engagement. Structural equation modeling with bootstrap analysis was employed to analyze the data. The study findings indicate that the five factor personality traits significantly predict self-regulated online learning. Furthermore, self-regulated online learning is a significant predictor of students’ engagement in the online learning environment. Additionally, the five factor personality traits are found to be significant predictors of student engagement in the online learning environment. Lastly, self-regulated online learning plays a partially mediating role in the relationship between the five factor personality traits and student engagement in the online learning environment. This study underscores the importance of considering individual differences in personality traits and fostering self-regulated learning strategies to enhance student engagement in online learning environments. Understanding these dynamics can inform the design of effective interventions aimed at improving student outcomes in online education.

Exploring factors of adherence to weight loss interventions in population with overweight/obesity: an umbrella review.

Adherence is key for achieving the optimal benefits from a weight loss intervention. Despite the number of studies on factors that promote adherence, their findings suggest inconsistent and fragmented evidence. The aim of this study was to review the existing factors of adherence to weight loss interventions and to find factors that facilitate the design of effective intervention programs. Six databases were searched for this umbrella review; after the screening process, 21 studies were included. A total of 47 factors were identified in six groups as relevant for adherence: (i) sociodemographic (n= 7), (ii) physical activity (n= 2), (iii) dietary (n= 8), (iv) behavioral (n= 4), (v) pharmacological (n= 3), and (vi) multi-intervention (n= 23). In addition, a map of adherence factors was created. The main findings are that with respect to demographic factors, the development of personalized intervention strategies based on the characteristics of specific populations is encouraged. Moreover, self-monitoring has been shown to be effective in behavioral, dietary, and multi-interventions, while technology has shown potential in dietary, behavioral, and multi-interventions. In addition, multi-interventions are adherence-promoting strategies, although more evidence is required on adherence to pharmacological interventions. Overall, the factor map can be controlled and modified by researchers and practitioners to improve adherence to weight loss interventions.

Usability and feasibility of the Test of Adherence to Inhalers (TAI) Toolkit in daily clinical practice: The BANANA study

The Test of Adherence to Inhalers (TAI) Toolkit links an adherence measurement instrument (the TAI) to proven effective interventions for different causes of non-adherence to inhaled medication. This study aimed to assess the usability and feasibility of the TAI Toolkit in clinical practice. The TAI Toolkit was piloted in eight primary and secondary care settings. Each study site included 10 patients with asthma and/or COPD and suspected non-adherence. Healthcare professionals (HCPs) recorded clinical data and TAI Toolkit outcomes. Data on usability and feasibility were collected in semi-structured interviews and with the System Usability Score (SUS). Of the included patients, 81% were non-adherent, and sporadic non-adherence was the most common (69%). The TAI Toolkit was valued with a mean SUS-score of 85.9 by the HCPs. They found the toolkit to ‘be visually attractive’, ‘easy-to-use’ and ‘give insight into patients’ adherence’, thereby offering good potential for its use in clinical practice.