Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Björn Büdenbender"'
Autor:
Björn Büdenbender, Anja K. Köther, Maximilian C. Kriegmair, Britta Grüne, Maurice S. Michel, Georg W. Alpers
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-13 (2023)
Abstract Background Shared decision-making is the gold standard for good clinical practice, and thus, psychometric instruments have been established to assess patients’ generic preference for participation (e.g., the Autonomy Preference Index, API)
Externí odkaz:
https://doaj.org/article/57754631a9a547569f33cc9d371f8424
Autor:
Björn Büdenbender, Anja K. Köther, Britta Grüne, Maurice S. Michel, Maximilian C. Kriegmair, Georg W. Alpers
Publikováno v:
Health Expectations, Vol 26, Iss 2, Pp 740-751 (2023)
Abstract Introduction Certain sociodemographic characteristics (e.g., older age) have previously been identified as barriers to patients' participation preference in shared decision‐making (SDM). We aim to demonstrate that this relationship is medi
Externí odkaz:
https://doaj.org/article/35c7086d44c746c2bddd1e2f98f48fe8
Autor:
Anja K. Köther, Björn Büdenbender, Britta Grüne, Sonja Holbach, Johannes Huber, Nicolas vonLandenberg, Julia Lenk, Thomas Martini, Maurice S. Michel, Maximilian C. Kriegmair, Georg W. Alpers
Publikováno v:
Cancer Medicine, Vol 11, Iss 15, Pp 2999-3008 (2022)
Abstract Objective Patient‐centered care and shared decision making (SDM) are generally recognized as the gold standard for medical consultations, especially for preference‐sensitive decisions. However, little is known about psychological patient
Externí odkaz:
https://doaj.org/article/6f27a25e89b644f38e86d9109498e18c
Publikováno v:
PLoS ONE, Vol 18, Iss 2, p e0281309 (2023)
Automatic facial coding (AFC) is a promising new research tool to efficiently analyze emotional facial expressions. AFC is based on machine learning procedures to infer emotion categorization from facial movements (i.e., Action Units). State-of-the-a
Externí odkaz:
https://doaj.org/article/c1d1812887b6403dacd530b568505f3d
Publikováno v:
PLoS ONE, Vol 17, Iss 3, p e0263863 (2022)
Automatic facial coding (AFC) is a novel research tool to automatically analyze emotional facial expressions. AFC can classify emotional expressions with high accuracy in standardized picture inventories of intensively posed and prototypical expressi
Externí odkaz:
https://doaj.org/article/d0772b4ffd2549b987b03aa041e3dd59
Autor:
Britta Grüne, Anja K. Köther, Björn Büdenbender, Maximilian Lenhart, Johannes Huber, Georg W. Alpers, Maurice Stephan Michel, Maximilian C. Kriegmair
Publikováno v:
European Urology Focus. 8:851-869
Context Decision aids (DAs) aim to support patients in the process of shared decision-making for complex treatment decisions. To improve patient-centered care in uro-oncology, it is essential to evaluate the availability and quality of existing DAs.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b737a203192215331145670b454af899
https://doi.org/10.1016/j.euf.2021.04.013
https://doi.org/10.1016/j.euf.2021.04.013
Autor:
Georg W. Alpers, Anja K. Köther, Björn Büdenbender, Maximilian C. Kriegmair, Maurice Stephan Michel, Britta Grüne
Publikováno v:
World Journal of Urology. 39:4491-4498
This study aims to determine the degree of shared decision-making (SDM) from urological patients’ perspective and to identify possible predictors. Overall, 469 urological patients of a university outpatient clinic were recruited for this prospectiv
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a8643fe90bbdea17af17b5a8065aa52
https://doi.org/10.1007/s00345-021-03794-3
https://doi.org/10.1007/s00345-021-03794-3
Autor:
Björn Büdenbender, Maximilian C. Kriegmair, Maximilian Lenhart, Georg W. Alpers, Anja K. Köther, Maurice Stephan Michel
Publikováno v:
Patient Education and Counseling. 104:1229-1236
Objectives Emotional distress can be a potential barrier to shared decision making (SDM), yet affect is typically not systematically assessed in medical consultation. We examined whether urological patients report anxiety or depression prior to a con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d24b5ba3f63a4199934d296684860f0
https://doi.org/10.1016/j.pec.2020.10.037
https://doi.org/10.1016/j.pec.2020.10.037
Publikováno v:
Behaviour research and therapy. 156
Machine learning (ML) may help to predict successful psychotherapy outcomes and to identify relevant predictors of success. So far, ML applications are scant in psychotherapy research and they are typically based on small samples or focused on specif
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::697d443df56fb772801221ca42fb0af5
https://pubmed.ncbi.nlm.nih.gov/35715257
https://pubmed.ncbi.nlm.nih.gov/35715257
Autor:
Britta, Grüne, Anja K, Köther, Björn, Büdenbender, Maurice S, Michel, Maximilian C, Kriegmair, Georg W, Alpers
Publikováno v:
World journal of urology. 39(12)
This study aims to determine the degree of shared decision-making (SDM) from urological patients' perspective and to identify possible predictors.Overall, 469 urological patients of a university outpatient clinic were recruited for this prospective s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::08b5934407b25845f88b6793c6e1217b
https://pubmed.ncbi.nlm.nih.gov/34338818
https://pubmed.ncbi.nlm.nih.gov/34338818