Background: The first step toward organizing research activities is to obtain a correct perception of available capabilities. This study was conducted to investigate the researchers' views about barriers affecting research activities.
Methods: This descriptive, cross-sectional study was conducted using the census method. The population consisted of the faculty members of Birjand University of Medical Sciences in 2014. The research tool was a questionnaire in six areas of financial, facility, professional, scientific, personal, and organizational- managerial barriers. The results were analyzed using descriptive statistics and Friedman test.
Results: Faculty members confirmed that although all barriers affected research activities, organizational-managerial barriers (3.73 ± 0.63) had the greatest and scientific barriers (3.15 ± 0.93) had the lowest effect, respectively. The results of Friedman test showed that there is a significant difference between the mean values of factors related to various barriers affecting research activities from the viewpoint of the participants' answers.
Conclusions: Research activities are affected by numerous barriers. Strategies, such as empowering researchers, employing new technologies in the creation of research teams, and benefiting from research experts in various stages of research, may have a positive effect on the removal of the barriers.
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http://dx.doi.org/10.4103/jehp.jehp_26_17 | DOI Listing |
Annu Rev Public Health
January 2025
1Center for Health Policy Research, University of California, Los Angeles, California, USA; email:
Achieving health equity necessitates high-quality data to address disparities that have remained stagnant or even worsened over time despite public health interventions. Data disaggregation, the breakdown of data into detailed subcategories, is crucial in health disparities research. It reveals and contextualizes hidden trends and patterns about marginalized populations and guides resource allocation and program development for specific needs in these populations.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Private Practice, Ballito, South Africa.
Background: Barriers to mental health assessment and intervention have been well documented within South Africa, in both urban and rural settings. Internationally, evidence has emerged for the effectiveness of technology and, specifically, app-based mental health tools and interventions to help overcome some of these barriers. However, research on digital interventions specific to the South African context and mental health is limited.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.
Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.
View Article and Find Full Text PDFAm J Drug Alcohol Abuse
January 2025
Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Kratom is a plant with alkaloids acting at opioid, serotonergic, adrenergic, and other receptors. Consumers report numerous use motivations. To distinguish subgroups of kratom consumers by kratom-use motivations using latent-class analysis.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
Institute for Health Care Management and Research, University of Duisburg-Essen, Essen, Germany.
Background: Artificial intelligence (AI)-based clinical decision support systems (CDSS) have been developed for several diseases. However, despite the potential to improve the quality of care and thereby positively impact patient-relevant outcomes, the majority of AI-based CDSS have not been adopted in standard care. Possible reasons for this include barriers in the implementation and a nonuser-oriented development approach, resulting in reduced user acceptance.
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