A thorough knowledge of biases in intervention studies and how they influence study results is essential for the practice of evidence-based medicine. The objective of this review was to provide a basic knowledge and understanding of the concept of biases and associated influence of these biases on treatment effects, focusing on the area of rehabilitation research. This article provides a description of selection biases, confounding, and attrition biases. In addition, useful recommendations are provided to identify, avoid, or control these biases when designing and conducting rehabilitation trials. The literature selected for this review was obtained mainly by compiling the information from several reviews looking at biases in rehabilitation. In addition, separate searches by biases and looking at reference lists of selected studies as well as using Scopus forward citation for relevant references were used. If not addressed appropriately, biases related to intervention research are a threat to internal validity and consequently to external validity. By addressing these biases, ensuring appropriate randomization, allocation concealment, appropriate retention techniques to avoid dropouts, appropriate study design and statistical analysis, among others, will generate more accurate treatment effects. Based on their impact on clinical results, a proper understanding of these concepts is central for researchers, rehabilitation clinicians, and other stakeholders working on this field.
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BMC Res Notes
January 2025
Department of General Surgery, The Royal Marsden Hospital, London, UK.
Research progress and innovation are hindered by barriers, inequalities, and exclusions within academia. Embracing equality, diversity, and inclusion (EDI) is not only an ethical imperative but also essential for advancing knowledge and addressing global challenges. EDI principles ensure that researchers from all backgrounds have equitable opportunities to contribute to and benefit from research.
View Article and Find Full Text PDFBMC Med Ethics
January 2025
Faculty of Law, University of Montreal, Ch de la Tour, Montreal, QC, H3T 1J7, Canada.
Background: Considering the disruptive potential of AI technology, its current and future impact in healthcare, as well as healthcare professionals' lack of training in how to use it, the paper summarizes how to approach the challenges of AI from an ethical and legal perspective. It concludes with suggestions for improvements to help healthcare professionals better navigate the AI wave.
Methods: We analyzed the literature that specifically discusses ethics and law related to the development and implementation of AI in healthcare as well as relevant normative documents that pertain to both ethical and legal issues.
BMC Public Health
January 2025
Department of Movement and Training Science, University of Wuppertal, Wuppertal, Germany.
Background: Workplace health promotion is essential for individual and organisational well-being and disease prevention, also in industrial workers. As the transfer of the evidence on the effectiveness of such programs into practice is limited due to scattered effects, the need for a consolidation of the available studies is given. The purpose of this systematic review was to synthesise the evidence on the effectiveness of workplace health promotion programs for industrial workers.
View Article and Find Full Text PDFBMC Surg
January 2025
Department of Obstetrics and Gynecology, Firoozgar Clinical Research and Development Center (FCRDC), School of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Background: Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intelligence (AI) may be more accurate in predicting outcomes.
View Article and Find Full Text PDFBMC Plant Biol
January 2025
College of Life Sciences, Nanjing Normal University, Nanjing, 210023, China.
Background: The confused taxonomic classification of Crucigenia is mainly inferred through morphological evidence and few nuclear genes and chloroplast genomic fragments. The phylogenetic status of C. quadrata, as the type species of Crucigenia, remains considerably controversial.
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