Objectives: Informed by the dual process theory of supportive message, the aim of this study is to systematically describe symptom communication, including its relationship with patient outcomes.
Data Sources: This is a mixed-methods study with an exploratory design. By examining symptom communication that occurred in oncology and hospice outpatient clinics, the qualitative phase employed conversation analysis to validate a typology of interaction patterns. The subsequent quantitative phase examined the relationship between interaction patterns and patient outcomes.
Conclusion: A total of 52 cancer patients' outpatient communications with their health care providers were included in the analysis. Ten unique interaction patterns were identified and defined. Among the 10 interaction patterns, some patterns are significantly associated with critical patient outcomes, including satisfaction, health communication self-efficacy, and symptom agreement between patients and their health care providers. This study represents one of the few mixed-methods studies to examine the patterns of real outpatient symptom communications and link them to concrete patient outcomes.
Implications For Nursing Practice: Our results present various interaction patterns that are commonly used in medical encounters and suggest that using some patterns affects critical patient outcomes.
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http://dx.doi.org/10.1016/j.soncn.2022.151355 | DOI Listing |
Viruses
December 2024
Department of Experimental and Clinical Medicine, University of Florence, Viale Morgagni 48, I-50134 Florence, Italy.
Background: Understanding the interference patterns of respiratory viruses could be important for shedding light on potential strategies to combat these human infectious agents.
Objective: To investigate the possible interactions between adenovirus type 2 (AdV2), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A/H1N1 pandemic (H1N1pdm09) using the A549 cell line.
Methods: Single infections, co-infections, and superinfections (at 3 and 24 h after the first virus infection) were performed by varying the multiplicity of infection (MOI).
Viruses
December 2024
Department of Medical Laboratory Science and Biotechnology, Asia University, Taichung 41354, Taiwan.
This study investigated a library of known and novel glycyrrhizic acid (GL) conjugates with amino acids and dipeptide esters, as inhibitors of the DENV NS2B-NS3 protease. We utilized docking algorithms to evaluate the interactions of these GL derivatives with key residues (His51, Asp75, Ser135, and Gly153) within 10 Å of the DENV-2 NS2B-NS3 protease binding pocket (PDB ID: 2FOM). It was found that compounds and exhibited unique binding patterns, forming hydrogen bonds with Asp75, Tyr150, and Gly153.
View Article and Find Full Text PDFVaccines (Basel)
December 2024
Department of Environmental, Agricultural & Occupational Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
Human papillomavirus (HPV) remains the most prevalent sexually transmitted infection in the United States (U.S.).
View Article and Find Full Text PDFVaccines (Basel)
November 2024
Laboratory of Biology of Cellular Interactions, Department of Morphology, Federal University of Minas Gerais, Belo Horizonte 31270-901, MG, Brazil.
Background/objectives: Considering the large number of candidates in vaccine-testing studies against different pathogens and the amount of time spent in the preclinical and clinical trials, there is a pressing need to develop an improved in vivo system to quickly screen vaccine candidates. The model of a polyester-polyurethane sponge implant provides a rapid analysis of the specific stimulus-response, allowing the study of a compartmentalized microenvironment. The sponge implant's defined measurements were standardized as a compartment to assess the immune response triggered by the vaccinal antigen.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Automation, North China Electric Power University, Baoding 071003, China.
To address the difficulty in detecting workers' violation behaviors in electric power construction scenarios, this paper proposes an innovative method that integrates knowledge reasoning and progressive multi-level distillation techniques. First, standards, norms, and guidelines in the field of electric power construction are collected to build a comprehensive knowledge graph, aiming to provide accurate knowledge representation and normative analysis. Then, the knowledge graph is combined with the object-detection model in the form of triplets, where detected objects and their interactions are represented as subject-predicate-object relationship.
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