Evidence-based research (EBR) is the systematic and transparent use of prior research to inform a new study so that it answers questions that matter in a valid, efficient, and accessible manner. This study surveyed experts about existing (e.g., citation analysis) and new methods for monitoring EBR and collected ideas about implementing these methods. We conducted a cross-sectional study via an online survey between November 2022 and March 2023. Participants were experts from the fields of evidence synthesis and research methodology in health research. Open-ended questions were coded by recurring themes; descriptive statistics were used for quantitative questions. Ideas proposed in this study for monitoring the implementation of EBR can be used to refine methods and define responsibility but should be further explored in terms of feasibility and acceptability. Different methods may be needed to determine if the use of EBR is improving over time.
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Background: In general people after stroke do not meet the recommendations for physical activity to conduct a healthy lifestyle. Programs to stimulate walking activity to increase physical activity are based on the available insights into barriers and facilitators to physical activity after stroke. However, these programs are not entirely successful. The purpose of this study was to comprehensively explore perceived barriers and facilitators to outdoor walking using a model of integrated biomedical and behavioral theory, the Physical Activity for people with a Disability model (PAD). Methods: Included were community dwelling respondents after stroke, classified ≥ 3 at the Functional Ambulation Categories (FAC), purposively sampled regarding the use of healthcare. The data was collected triangulating in a multi-methods approach, i.e. semi-structured, structured and focus-group interviews. A primarily deductive thematic content analysis using the PAD-model in a framework-analysis’ approach was conducted after verbatim transcription. Results: 36 respondents (FAC 3–5) participated in 16 semi-structured interviews, eight structured interviews and two focus-group interviews. The data from the interviews covered all domains of the PAD model. Intention, ability and opportunity determined outdoor walking activity. Personal factors determined the intention to walk outdoors, e.g. negative social influence, resulting from restrictive caregivers in the social environment, low self-efficacy influenced by physical environment, and also negative attitude towards physical activity. Walking ability was influenced by loss of balance and reduced walking distance and by impairments of motor control, cognition and aerobic capacity as well as fatigue. Opportunities arising from household responsibilities and lively social constructs facilitated outdoor walking. Conclusion: To stimulate outdoor walking activity, it seems important to influence the intention by addressing social influence, self-efficacy and attitude towards physical activity in the development of efficient interventions. At the same time, improvement of walking ability and creation of opportunity should be considered
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BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
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BACKGROUND: Multimorbidity, the co-occurrence of two or more chronic medical conditions within a single individual, is increasingly becoming part of daily care of general medical practice. Literature-based discovery may help to investigate the patterns of multimorbidity and to integrate medical knowledge for improving healthcare delivery for individuals with co-occurring chronic conditions. OBJECTIVE: To explore the usefulness of literature-based discovery in primary care research through the key-case of finding associations between psychiatric and somatic diseases relevant to general practice in a large biomedical literature database (Medline). METHODS: By using literature based discovery for matching disease profiles as vectors in a high-dimensional associative concept space, co-occurrences of a broad spectrum of chronic medical conditions were matched for their potential in biomedicine. An experimental setting was chosen in parallel with expert evaluations and expert meetings to assess performance and to generate targets for integrating literature-based discovery in multidisciplinary medical research of psychiatric and somatic disease associations. RESULTS: Through stepwise reductions a reference set of 21,945 disease combinations was generated, from which a set of 166 combinations between psychiatric and somatic diseases was selected and assessed by text mining and expert evaluation. CONCLUSIONS: Literature-based discovery tools generate specific patterns of associations between psychiatric and somatic diseases: one subset was appraised as promising for further research; the other subset surprised the experts, leading to intricate discussions and further eliciting of frameworks of biomedical knowledge. These frameworks enable us to specify targets for further developing and integrating literature-based discovery in multidisciplinary research of general practice, psychology and psychiatry, and epidemiology.
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Through a qualitative examination, the moral evaluations of Dutch care professionals regarding healthcare robots for eldercare in terms of biomedical ethical principles and non-utility are researched. Results showed that care professionals primarily focused on maleficence (potential harm done by the robot), deriving from diminishing human contact. Worries about potential maleficence were more pronounced from intermediate compared to higher educated professionals. However, both groups deemed companion robots more beneficiary than devices that monitor and assist, which were deemed potentially harmful physically and psychologically. The perceived utility was not related to the professionals' moral stances, countering prevailing views. Increasing patient's autonomy by applying robot care was not part of the discussion and justice as a moral evaluation was rarely mentioned. Awareness of the care professionals' point of view is important for policymakers, educational institutes, and for developers of healthcare robots to tailor designs to the wants of older adults along with the needs of the much-undervalued eldercare professionals.
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BACKGROUND: The design and manufacturing of effective foot orthoses is a complex multidisciplinary problem involving biomedical and gait pattern aspects, technical material and geometric design elements as well as psychological and social contexts. This complexity contributes to the current trial-and-error and experience-based orthopedic footwear practice in which a major part of the expertise is implicit. This hampers knowledge transfer, reproducibility and innovation. OBJECTIVE/METHODS: A systematic review of literature has been performed to find evidence of explicit knowledge, quantitative guidelines and design motivations of pedorthists. RESULTS: 17 studies have been included. No consensus is found on which measurable parameters ensure proper foot and ankle functioning. Parameters suggested are: neutral foot positioning and control of rearfoot motion, maximum arch, but also tibial internal/external rotation as well as a three point force system. Also studies evaluating foot orthoses centering on the diagnosis or orthosis type find no clear guidelines for treatment or for measuring the effectiveness. CONCLUSIONS: A gap in the translation from diagnosis to a specific, customized and quantified effective orthosis design is identified. Suggested solutions are both top-down, fitting of patient data in simulations, as well as bottom-up, quantifying current practices of pedorthists in order to develop new practical guidelines and evidence-based procedures.
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BackgroundUnderstanding cultural perceptions of illness is crucial for effective healthcare delivery. This study examines the ethnomedical concept of ikirimi, a culturally recognized illness in Rwanda characterized by perceived uvula abnormalities, and its traditional management through uvulectomy. This study explores the cultural understanding of ikirimi, its perceived causes, symptoms, and treatments, as well as barriers to integrating modern healthcare.MethodsAn exploratory qualitative approach was employed, involving in-depth semi-structured interviews with eight participants: traditional healers, individuals who underwent traditional uvulectomy, and healthcare providers. A grounded theory approach which analyzes data in systematic manner to generate new theories was applied, with coding conducted in English after initial transcription and analysis in Ikinyarwanda to preserve Indigenous concepts.ResultsParticipants described ikirimi as an illness affecting the uvula (named as akamironko or akamirabugari or agashondabugari in Ikinyarwanda), characterized by swelling, elongation, and pus-like discoloration. Reported symptoms included fever, difficulty swallowing, coughing, and weakness, with children identified as the most affected group. Traditional healers diagnosed ikirimi through visual inspection of uvular morphology and movement and treated it by cutting the affected part of uvula and is known as guca Ikirimi ‘traditional uvulectomy’. Barriers to integrating modern healthcare included skepticism about biomedical care, judgmental attitudes from providers, and communication gaps. Despite the prevalence of ikirimi, its biomedical correlates remain unclear, though participants associated it with severe throat illnesses such as tonsillopharyngitis.ConclusionThe findings highlight ikirimi as a socially constructed illness with deep cultural roots, significant health implications, and persistent barriers to modern healthcare. Addressing these barriers requires culturally sensitive approaches that integrate Indigenous knowledge with biomedical practices. Future research should explore the biomedical correlates of ikirimi and foster collaboration between traditional and modern healthcare systems to improve patient outcomes.
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Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiat- ing event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a standardized way to map and organize toxicological mechanistic information. As such, AOPs inform on key events underlying toxicity, thus supporting the development of New Approach Methodologies (NAMs), which aim to reduce the use of animal testing for toxicology purposes. However, the establishment of a novel AOP relies on the gathering of multiple streams of evidence and infor- mation, from available literature to knowledge databases. Often, this information is in the form of free text, also called unstructured text, which is not immediately digestible by a computer. This information is thus both tedious and increasingly time-consuming to process manually with the growing volume of data available. The advance- ment of machine learning provides alternative solutions to this challenge. To extract and organize information from relevant sources, it seems valuable to employ deep learning Natural Language Processing techniques. We review here some of the recent progress in the NLP field, and show how these techniques have already demonstrated value in the biomedical and toxicology areas. We also propose an approach to efficiently and reliably extract and combine relevant toxicological information from text. This data can be used to map underlying mechanisms that lead to toxicological effects and start building quantitative models, in particular AOPs, ultimately allowing animal-free human-based hazard and risk assessment.
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Purpose: The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods: Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Results: Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theorydriven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Conclusion: Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology.
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Objective To develop and internally validate a prognostic model to predict chronic pain after a new episode of acute or subacute non-specific idiopathic, non-traumatic neck pain in patients presenting to physiotherapy primary care, emphasising modifiable biomedical, psychological and social factors. Design A prospective cohort study with a 6-month follow-up between January 2020 and March 2023. Setting 30 physiotherapy primary care practices. Participants Patients with a new presentation of non-specific idiopathic, non-traumatic neck pain, with a duration lasting no longer than 12 weeks from onset. Baseline measures Candidate prognostic variables collected from participants included age and sex, neck pain symptoms, work-related factors, general factors, psychological and behavioural factors and the remaining factors: therapeutic relation and healthcare provider attitude. Outcome measures Pain intensity at 6 weeks, 3 months and 6 months on a Numeric Pain Rating Scale (NPRS) after inclusion. An NPRS score of ≥3 at each time point was used to define chronic neck pain. Results 62 (10%) of the 603 participants developed chronic neck pain. The prognostic factors in the final model were sex, pain intensity, reported pain in different body regions, headache since and before the neck pain, posture during work, employment status, illness beliefs about pain identity and recovery, treatment beliefs, distress and self-efficacy. The model demonstrated an optimism-corrected area under the curve of 0.83 and a corrected R2 of 0.24. Calibration was deemed acceptable to good, as indicated by the calibration curve. The Hosmer–Lemeshow test yielded a p-value of 0.7167, indicating a good model fit. Conclusion This model has the potential to obtain a valid prognosis for developing chronic pain after a new episode of acute and subacute non-specific idiopathic, non-traumatic neck pain. It includes mostly potentially modifiable factors for physiotherapy practice. External validation of this model is recommended.
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