Pub Date : 2024-12-16DOI: 10.1016/j.glmedi.2024.100171
Sirwan Khalid Ahmed
Data saturation is a cornerstone concept in qualitative research, ensuring that data collection ceases once no new themes, insights, or patterns emerge. This concept is critical for achieving methodological rigor, as saturation enhances the credibility and completeness of research findings. Despite its central role, debates persist regarding the point at which saturation is achieved, especially as it varies across qualitative methodologies such as grounded theory, phenomenology, and ethnography. Contemporary scholars argue for a flexible approach to sample sizes and saturation criteria, balancing comprehensive data gathering with respect for emerging themes and contextual sensitivity. This article explores the theoretical foundations, practical applications, and controversies surrounding data saturation. Additionally, it offers recommendations for researchers on determining sample sizes and 16-ietms checklist for achieving saturation, aiming to improve research quality while addressing the methodological challenges inherent in qualitative research.
{"title":"Sample size for saturation in qualitative research: Debates, definitions, and strategies","authors":"Sirwan Khalid Ahmed","doi":"10.1016/j.glmedi.2024.100171","DOIUrl":"10.1016/j.glmedi.2024.100171","url":null,"abstract":"<div><div>Data saturation is a cornerstone concept in qualitative research, ensuring that data collection ceases once no new themes, insights, or patterns emerge. This concept is critical for achieving methodological rigor, as saturation enhances the credibility and completeness of research findings. Despite its central role, debates persist regarding the point at which saturation is achieved, especially as it varies across qualitative methodologies such as grounded theory, phenomenology, and ethnography. Contemporary scholars argue for a flexible approach to sample sizes and saturation criteria, balancing comprehensive data gathering with respect for emerging themes and contextual sensitivity. This article explores the theoretical foundations, practical applications, and controversies surrounding data saturation. Additionally, it offers recommendations for researchers on determining sample sizes and 16-ietms checklist for achieving saturation, aiming to improve research quality while addressing the methodological challenges inherent in qualitative research.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100171"},"PeriodicalIF":0.0,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Urban-rural inequalities in access to healthcare services remain a significant obstacle to development in Africa. Rural communities are more affected by the poor state of the African healthcare system, They lack essential healthcare facilities, have a shortage of healthcare workforce, inadequate transportation facilities that keep them isolated, and high out-of-pocket healthcare costs which put them at risk of the catastrophic effect of healthcare expenditure. Several health insurance schemes have been designed in an attempt to meet the SDG 3.8 goal of universal health coverage and access to quality, safe, effective, and affordable health care in rural communities. However, despite these efforts, there are still significant challenges with access and utilization of these insurance schemes. Artificial intelligence (AI) has been integrated into different areas of healthcare including medical imaging and diagnosis, surgery, and so on, and has improved health outcomes significantly. If adequately leveraged, AI can be useful in risk assessment and in automating claim process, thereby improving accessibility and utilization of health insurance in rural communities. It can also be used in protecting resources for rural healthcare by detecting fraud, thereby increasing the trust of the community in the insurer. Integration of AI into healthcare services can be very useful in improve health insurance access and reducing health disparities in rural communities thus aiding in the fulfilment of universal health coverage.
{"title":"Leveraging artificial intelligence to improve health insurance access and address disparities in rural Africa","authors":"Olajumoke Adesola Adewole , Adewunmi Akingbola , Abiodun Christopher Adegbesan , Theodora Nkechi Ndu-Esekea, Samiat Bisodun Olalemi","doi":"10.1016/j.glmedi.2024.100172","DOIUrl":"10.1016/j.glmedi.2024.100172","url":null,"abstract":"<div><div>Urban-rural inequalities in access to healthcare services remain a significant obstacle to development in Africa. Rural communities are more affected by the poor state of the African healthcare system, They lack essential healthcare facilities, have a shortage of healthcare workforce, inadequate transportation facilities that keep them isolated, and high out-of-pocket healthcare costs which put them at risk of the catastrophic effect of healthcare expenditure. Several health insurance schemes have been designed in an attempt to meet the SDG 3.8 goal of universal health coverage and access to quality, safe, effective, and affordable health care in rural communities. However, despite these efforts, there are still significant challenges with access and utilization of these insurance schemes. Artificial intelligence (AI) has been integrated into different areas of healthcare including medical imaging and diagnosis, surgery, and so on, and has improved health outcomes significantly. If adequately leveraged, AI can be useful in risk assessment and in automating claim process, thereby improving accessibility and utilization of health insurance in rural communities. It can also be used in protecting resources for rural healthcare by detecting fraud, thereby increasing the trust of the community in the insurer. Integration of AI into healthcare services can be very useful in improve health insurance access and reducing health disparities in rural communities thus aiding in the fulfilment of universal health coverage.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100172"},"PeriodicalIF":0.0,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-15DOI: 10.1016/j.glmedi.2024.100173
Md Faiazul Haque Lamem, Muaj Ibne Sahid, Anika Ahmed
Artificial Intelligence (AI) may enhance access to primary health care in rural settings, especially in areas with an underserved and rural populace, due to systemic challenges in infrastructure inadequacies, shortages of trained professionals, and poor preventive measures. This paper discusses the transformative roles of AI technologies in the efforts toward bridging these gaps by improving healthcare delivery and access. With the rise of machine learning (ML) and natural language processing (NLP), AI applications may enhance diagnostic accuracy, speed up and facilitate patient interfaces, and perform resource management more optimally. This list of benefits seems promising, but the realization of AI in healthcare faces quite a few challenges: it requires ethical considerations, assurance of data safety, and sound legal frameworks. While AI, Internet of Things (IoT), and mobile health (mHealth) technologies create innovative solutions in remote monitoring and consultation, these technologies help promote prevention. Realizing the full potential of AI in rural health is thus a challenge in both infrastructural and socio-economic spheres, requiring active collaboration. This present study indicates that it is high time there was an urgent need for high-quality research with real-world evaluation regarding the effectiveness of AI in bringing improvement in health outcomes among people in rural settings.
{"title":"Artificial intelligence for access to primary healthcare in rural settings","authors":"Md Faiazul Haque Lamem, Muaj Ibne Sahid, Anika Ahmed","doi":"10.1016/j.glmedi.2024.100173","DOIUrl":"10.1016/j.glmedi.2024.100173","url":null,"abstract":"<div><div>Artificial Intelligence (AI) may enhance access to primary health care in rural settings, especially in areas with an underserved and rural populace, due to systemic challenges in infrastructure inadequacies, shortages of trained professionals, and poor preventive measures. This paper discusses the transformative roles of AI technologies in the efforts toward bridging these gaps by improving healthcare delivery and access. With the rise of machine learning (ML) and natural language processing (NLP), AI applications may enhance diagnostic accuracy, speed up and facilitate patient interfaces, and perform resource management more optimally. This list of benefits seems promising, but the realization of AI in healthcare faces quite a few challenges: it requires ethical considerations, assurance of data safety, and sound legal frameworks. While AI, Internet of Things (IoT), and mobile health (mHealth) technologies create innovative solutions in remote monitoring and consultation, these technologies help promote prevention. Realizing the full potential of AI in rural health is thus a challenge in both infrastructural and socio-economic spheres, requiring active collaboration. This present study indicates that it is high time there was an urgent need for high-quality research with real-world evaluation regarding the effectiveness of AI in bringing improvement in health outcomes among people in rural settings.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100173"},"PeriodicalIF":0.0,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Suicide attempts are a major public health issue, influenced by a range of factors. Assessing the prevalence of suicide attempts in Bangladesh is crucial for understanding the country's mental health landscape. We searched multiple databases and included 11 articles in the meta-analysis. We used a random-effects model to pool prevalence data. We assessed between-study heterogeneity through the Q-test and I² statistics and conducted subgroup analyses. To evaluate potential publication bias, we utilized a funnel plot and Egger's test. Additionally, meta-regression was performed to identify sources of heterogeneity, while sensitivity analysis was conducted to assess the robustness of the findings. Study quality was assessed using the Joanna Briggs Institute (JBI) tools. The pooled prevalence of suicide attempts in Bangladesh was 4.25 % (95 % CI: 2.28–6.22). The prevalence among males was 3.36 %, while females had a higher prevalence of 4.17 %. The pooled odds ratio for the risk of suicide attempts among females was 1.16 (95 % CI: 0.41–1.91), implying that females were at higher risk than males. We found that the pooled prevalence of suicide attempts among individuals aged 18 and above was 3.42 %. The analysis also uncovered a concerning upward trend in suicide attempts over recent years. The prevalence stood at 3.88 % from 2010 to 2016 and increased to 4.29 % between 2017 and 2023. The pooled prevalence of suicide attempts in Bangladesh revealed significant gender disparities, and a concerning upward trend in recent years, underscoring an urgent need for attention.
{"title":"Suicide attempts in Bangladesh: Prevalence, trends, and disparities","authors":"Tonmoy Alam Shuvo , Kabir Hossain , Asma-Ul-Hosna , Dipu Rani Dey","doi":"10.1016/j.glmedi.2024.100170","DOIUrl":"10.1016/j.glmedi.2024.100170","url":null,"abstract":"<div><div>Suicide attempts are a major public health issue, influenced by a range of factors. Assessing the prevalence of suicide attempts in Bangladesh is crucial for understanding the country's mental health landscape. We searched multiple databases and included 11 articles in the meta-analysis. We used a random-effects model to pool prevalence data. We assessed between-study heterogeneity through the Q-test and I² statistics and conducted subgroup analyses. To evaluate potential publication bias, we utilized a funnel plot and Egger's test. Additionally, meta-regression was performed to identify sources of heterogeneity, while sensitivity analysis was conducted to assess the robustness of the findings. Study quality was assessed using the Joanna Briggs Institute (JBI) tools. The pooled prevalence of suicide attempts in Bangladesh was 4.25 % (95 % CI: 2.28–6.22). The prevalence among males was 3.36 %, while females had a higher prevalence of 4.17 %. The pooled odds ratio for the risk of suicide attempts among females was 1.16 (95 % CI: 0.41–1.91), implying that females were at higher risk than males. We found that the pooled prevalence of suicide attempts among individuals aged 18 and above was 3.42 %. The analysis also uncovered a concerning upward trend in suicide attempts over recent years. The prevalence stood at 3.88 % from 2010 to 2016 and increased to 4.29 % between 2017 and 2023. The pooled prevalence of suicide attempts in Bangladesh revealed significant gender disparities, and a concerning upward trend in recent years, underscoring an urgent need for attention.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100170"},"PeriodicalIF":0.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-12DOI: 10.1016/j.glmedi.2024.100169
Rafay Ali Syed, Javaria Qazi
Workplace violence is a significant occupational risk faced by healthcare personnel in community-based settings, posing a global public health threat. Pakistan, one of the few countries, where polio remains endemic has faced targeted violence against polio workers, hindering its progress in eradicating the disease. This violence has profoundly impacted vaccination campaigns, leading to a resurgence of polio cases and the tragic loss of over 200 polio vaccination workers and security officials in recent years. Such violence not only endangers lives but also hampers vaccination initiatives creating fear among workers and reducing immunization coverage, particularly in high-risk areas. The history of these attacks intensified by a breach of trust has compounded resistance from militant groups and the spread of misinformation. Cultural norms, gender-based resistance, and socio-economic vulnerabilities further impede vaccination efforts. This letter proposes the use of community-based approaches such as employing voluntary community mobilizers (VCMs) to enhance public trust and vaccination coverage through strategies including the establishment of polio immunization centers in vulnerable areas, strengthening multi-sectoral partnerships, involving local influencers to address community concerns and implementing safety measures and incentives for health workers. These strategies aim to improve worker safety, promote vaccine acceptance, and ensure sustainable progress toward a polio-free Pakistan.
{"title":"Targeted violence against community health workers: A critical barrier to Pakistan’s polio eradication goals","authors":"Rafay Ali Syed, Javaria Qazi","doi":"10.1016/j.glmedi.2024.100169","DOIUrl":"10.1016/j.glmedi.2024.100169","url":null,"abstract":"<div><div>Workplace violence is a significant occupational risk faced by healthcare personnel in community-based settings, posing a global public health threat. Pakistan, one of the few countries, where polio remains endemic has faced targeted violence against polio workers, hindering its progress in eradicating the disease. This violence has profoundly impacted vaccination campaigns, leading to a resurgence of polio cases and the tragic loss of over 200 polio vaccination workers and security officials in recent years. Such violence not only endangers lives but also hampers vaccination initiatives creating fear among workers and reducing immunization coverage, particularly in high-risk areas. The history of these attacks intensified by a breach of trust has compounded resistance from militant groups and the spread of misinformation. Cultural norms, gender-based resistance, and socio-economic vulnerabilities further impede vaccination efforts. This letter proposes the use of community-based approaches such as employing voluntary community mobilizers (VCMs) to enhance public trust and vaccination coverage through strategies including the establishment of polio immunization centers in vulnerable areas, strengthening multi-sectoral partnerships, involving local influencers to address community concerns and implementing safety measures and incentives for health workers. These strategies aim to improve worker safety, promote vaccine acceptance, and ensure sustainable progress toward a polio-free Pakistan.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100169"},"PeriodicalIF":0.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The advent of 3D printing technology has a great role in cancer research, offering massive opportunities for drug delivery and development. This commentary provides a well-detailed review of the advancements in 3D printing of cancer models, details their application in imitating the complex tumor microenvironment, and enables more meticulous pre-clinical drug testing. We discuss the various 3D printing techniques like “stereolithography”, “selective laser sintering”, and “fused deposition modeling” with their advantages, effects, and limitations. The commentary also makes headway on the critical problem in these vascular networks. In extension, we explore the future perspectives of 3D-printed cancer models, emphasizing the potential for personalized medicine and high–throughput screening. By accentuating these advancements and challenges, we aim to provide a roadmap for future research and development in the use of 3D printing for cancer drug discovery, contributing to more effective and patient-centric cancer treatments.
{"title":"3D printing of cancer models for drug discovery: Advancements, challenges, and future perspectives","authors":"Tolu Fanibuyan, Abdulbasit Opeyemi Muili, Alimi Kehinde Hikmat, Akinmeji Ayodeji, Ridwanullah Ajedamola Lawal, Mubarak Jolayemi Mustapha, Piel Panther Kuol","doi":"10.1016/j.glmedi.2024.100165","DOIUrl":"10.1016/j.glmedi.2024.100165","url":null,"abstract":"<div><div>The advent of 3D printing technology has a great role in cancer research, offering massive opportunities for drug delivery and development. This commentary provides a well-detailed review of the advancements in 3D printing of cancer models, details their application in imitating the complex tumor microenvironment, and enables more meticulous pre-clinical drug testing. We discuss the various 3D printing techniques like “stereolithography”, “selective laser sintering”, and “fused deposition modeling” with their advantages, effects, and limitations. The commentary also makes headway on the critical problem in these vascular networks. In extension, we explore the future perspectives of 3D-printed cancer models, emphasizing the potential for personalized medicine and high–throughput screening. By accentuating these advancements and challenges, we aim to provide a roadmap for future research and development in the use of 3D printing for cancer drug discovery, contributing to more effective and patient-centric cancer treatments.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-09DOI: 10.1016/j.glmedi.2024.100166
Subhadeep Saha , Priya Das , Tanu Das , Partha Das , Tamal Basu Roy
Introductions
Social participation in different activities for individual older adult people increases the quality of life. But sometimes their age-related physical ailments and their background socio-demographic characteristics create barriers to participation in different societal activities. Little is known about what types of health and background conditions affect social participation in India. Therefore, the study inspects the prospective association between low social participation and different variables based on health and background strata among Indian people aged ≥45 years.
Methods
The current study applied cross-sectional data from the first wave (2017-18) of LASI. The main purpose of the survey was to provide knowledge about the health, well-being, and socio-economic condition of Indian middle-aged and older adults. A sample of 55,449 middle-aged and older adults was viewed for analysis. Multivariable logistic regression models were estimated to find the odds of low social participation over explanatory variables.
Results
In this study, the likelihood of low social participation was positively associated with the risk of having low Activities in Daily Living [AOR: 1.16, CI: 1.05-1.27] and cognitive impairment [AOR:1.69, CI:1.55-1.84]. The likelihood of low social participation was notably higher among those who revealed the following health conditions, i.e., bone/joint surgery [AOR:1.28, CI:1.02-1.59], feeling depressed [AOR:1.15, CI:1.06-1.24], and poor eye-sight for distance-seeing [AOR:1.19, CI:1.07-1.32].
Conclusions
Quality care of individuals to combat several diseases and enhance their physical and mental health will reduce the incidence of low social participation. Opportunities in societal neighbourhoods may facilitate more involvement in social life.
{"title":"Association of social participation with physical and mental health status among Indian adults","authors":"Subhadeep Saha , Priya Das , Tanu Das , Partha Das , Tamal Basu Roy","doi":"10.1016/j.glmedi.2024.100166","DOIUrl":"10.1016/j.glmedi.2024.100166","url":null,"abstract":"<div><h3>Introductions</h3><div>Social participation in different activities for individual older adult people increases the quality of life. But sometimes their age-related physical ailments and their background socio-demographic characteristics create barriers to participation in different societal activities. Little is known about what types of health and background conditions affect social participation in India. Therefore, the study inspects the prospective association between low social participation and different variables based on health and background strata among Indian people aged ≥45 years.</div></div><div><h3>Methods</h3><div>The current study applied cross-sectional data from the first wave (2017-18) of LASI. The main purpose of the survey was to provide knowledge about the health, well-being, and socio-economic condition of Indian middle-aged and older adults. A sample of 55,449 middle-aged and older adults was viewed for analysis. Multivariable logistic regression models were estimated to find the odds of low social participation over explanatory variables.</div></div><div><h3>Results</h3><div>In this study, the likelihood of low social participation was positively associated with the risk of having low Activities in Daily Living [AOR: 1.16, CI: 1.05-1.27] and cognitive impairment [AOR:1.69, CI:1.55-1.84]. The likelihood of low social participation was notably higher among those who revealed the following health conditions, i.e., bone/joint surgery [AOR:1.28, CI:1.02-1.59], feeling depressed [AOR:1.15, CI:1.06-1.24], and poor eye-sight for distance-seeing [AOR:1.19, CI:1.07-1.32].</div></div><div><h3>Conclusions</h3><div>Quality care of individuals to combat several diseases and enhance their physical and mental health will reduce the incidence of low social participation. Opportunities in societal neighbourhoods may facilitate more involvement in social life.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100166"},"PeriodicalIF":0.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel target folate receptor and CD44 receptor are deliberated for effective as chemotherapeutic agents. Usually, these receptors are play a vital role in the functional condition such as cell adhesion, healing and inflammation process. Thus, to treat cancerous cell is most difficult by traditional method can be most easily treated with the use of folic acid and hyaluronic acid-linked chemotherapeutics. Also, the various problems associated with Paclitaxel and Docetaxel like inability to deliver at specific target, affection towards healthy cells, poor aqueous solubility, side effects and acquired drug resistance can be minimized with the use of this targeting technique. In recent years, various studies have been ongoing on minimizing the problems associated with the delivery of docetaxel and paclitaxel, and targeting therapy is one of them. This review gives a clear picture of the concept of targeting therapy for the efficient delivery of docetaxel and paclitaxel using folic and hyaluronic acid conjugates.
{"title":"Role of folate receptor and CD44 in targeting of docetaxel and paclitaxel fabricated conjugates for efficient cancer therapy","authors":"Amol Tatode , Pranav R. Agrawal , Jayshree Taksande , Mohammad Qutub , Tanvi Premchandani , Milind Umekar , Kishor Danao","doi":"10.1016/j.glmedi.2024.100163","DOIUrl":"10.1016/j.glmedi.2024.100163","url":null,"abstract":"<div><div>A novel target folate receptor and CD44 receptor are deliberated for effective as chemotherapeutic agents. Usually, these receptors are play a vital role in the functional condition such as cell adhesion, healing and inflammation process. Thus, to treat cancerous cell is most difficult by traditional method can be most easily treated with the use of folic acid and hyaluronic acid-linked chemotherapeutics. Also, the various problems associated with Paclitaxel and Docetaxel like inability to deliver at specific target, affection towards healthy cells, poor aqueous solubility, side effects and acquired drug resistance can be minimized with the use of this targeting technique. In recent years, various studies have been ongoing on minimizing the problems associated with the delivery of docetaxel and paclitaxel, and targeting therapy is one of them. This review gives a clear picture of the concept of targeting therapy for the efficient delivery of docetaxel and paclitaxel using folic and hyaluronic acid conjugates.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100163"},"PeriodicalIF":0.0,"publicationDate":"2024-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-06DOI: 10.1016/j.glmedi.2024.100164
Kavita Batra, Vidhani S. Goel, Ana L. Reyes, Bertille Assoumou, Dodds P. Simangan, Farooq Abdulla, Deborah A. Kuhls
Data linkage methods, including probabilistic, deterministic, and hybrid are critical for linking medical and public health records, expanding data scope, and improving research outcomes. These methods differ in accuracy, efficiency, and scalability. This letter seeks to identify best practices for enhancing data quality and linkage rates in healthcare and public health research using these techniques. Data linkage enhances data quality by removing duplicates and correcting artifacts, facilitates cost-effective longitudinal studies by integrating existing data, and supports public health through person-oriented statistics and disease registries. Tools like "RecordLinkage" in R and EpiLink have advanced linkage accuracy, particularly in epidemiological studies. A PubMed search in November 2023 identified 176 studies, with 29 meeting inclusion criteria. Hybrid methods showed superior accuracy, with some studies achieving over 90 % linkage rates. Emerging AI-driven methods can further improved scalability, efficiency, and automation, employing privacy-preserving techniques like federated learning to address confidentiality concerns. However, challenges such as inconsistent data, incomplete identifiers, and technical complexities remain, emphasizing the need for standardized protocols and robust ethical frameworks. In low- and middle-income countries (LMICs), tailored strategies such as enhancing health information systems, adopting open-source tools, and fostering regional collaborations are essential to address resource constraints. Initiatives like the Western Australian Data Linkage System exemplify the potential impact of linkage on healthcare and public health. Future research should focus on refining methods, integrating diverse datasets, and leveraging AI to improve linkage efficiency and reliability. By adopting best practices, data linkage can enhance decision-making, optimize interventions, and advance global health research.
{"title":"Unifying and linking data sources in medical and public health research","authors":"Kavita Batra, Vidhani S. Goel, Ana L. Reyes, Bertille Assoumou, Dodds P. Simangan, Farooq Abdulla, Deborah A. Kuhls","doi":"10.1016/j.glmedi.2024.100164","DOIUrl":"10.1016/j.glmedi.2024.100164","url":null,"abstract":"<div><div>Data linkage methods, including probabilistic, deterministic, and hybrid are critical for linking medical and public health records, expanding data scope, and improving research outcomes. These methods differ in accuracy, efficiency, and scalability. This letter seeks to identify best practices for enhancing data quality and linkage rates in healthcare and public health research using these techniques. Data linkage enhances data quality by removing duplicates and correcting artifacts, facilitates cost-effective longitudinal studies by integrating existing data, and supports public health through person-oriented statistics and disease registries. Tools like \"RecordLinkage\" in R and EpiLink have advanced linkage accuracy, particularly in epidemiological studies. A PubMed search in November 2023 identified 176 studies, with 29 meeting inclusion criteria. Hybrid methods showed superior accuracy, with some studies achieving over 90 % linkage rates. Emerging AI-driven methods can further improved scalability, efficiency, and automation, employing privacy-preserving techniques like federated learning to address confidentiality concerns. However, challenges such as inconsistent data, incomplete identifiers, and technical complexities remain, emphasizing the need for standardized protocols and robust ethical frameworks. In low- and middle-income countries (LMICs), tailored strategies such as enhancing health information systems, adopting open-source tools, and fostering regional collaborations are essential to address resource constraints. Initiatives like the Western Australian Data Linkage System exemplify the potential impact of linkage on healthcare and public health. Future research should focus on refining methods, integrating diverse datasets, and leveraging AI to improve linkage efficiency and reliability. By adopting best practices, data linkage can enhance decision-making, optimize interventions, and advance global health research.</div></div>","PeriodicalId":100804,"journal":{"name":"Journal of Medicine, Surgery, and Public Health","volume":"5 ","pages":"Article 100164"},"PeriodicalIF":0.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143092872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-03DOI: 10.1016/j.glmedi.2024.100162
Olajumoke Olarewaju, Samuel Tundealao
Opioid use disorder (OUD) in pregnancy poses considerable risks for both the mother and the child, with rising opioid use among women of reproductive age in the United States. Although OUD is treatable, pregnant individuals frequently encounter obstacles like stigma, legal issues, and inadequate access to healthcare. This commentary examines the factors influencing access to treatment services for pregnant individuals with OUD. The proposed conceptual framework using the socioecological model emphasizes the intricate relationships among these multi-level determinants. At the individual level, social expectations of motherhood, internalized stigma, previous healthcare experiences, insufficient understanding of treatment alternatives, and absence of health insurance frequently establish substantial obstacles to care. At the interpersonal level, healthcare personnel's attitudes, training, and communication are crucial in establishing trust and promoting treatment adherence, while supportive social networks and family involvement enhance care engagement and resilience. Structurally, the systemic constraints, including the variability in Medicaid coverage, geographic inequities, and inadequate integration of prenatal and addiction care, impede access, exacerbated by punitive policies that stigmatize substance use during pregnancy. Comprehending these dynamics can guide treatments designed to enhance treatment linkage and results. Advocating for a compassionate, patient-centered methodology within healthcare systems is crucial for tackling this escalating public health epidemic and mitigating the stigma associated with opioid use during pregnancy.
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