poliTE-Literatur-Datenbank

Bylund, Carma L.; Peterson, Emily B.; Cameron, Kenzie A. (2012): A practitioner's guide to interpersonal communication theory. An overview and exploration of selected theories. In: Patient education and counseling 87 (3), S. 261-267. DOI: 10.1016/j.pec.2011.10.006

DOI: http://www.ncbi.nlm.nih.gov/pubmed/22112396

Abstract: OBJECTIVE To provide a brief overview of selected interpersonal theories and models, and to present examples of their use in healthcare communication research. RESULTS Nine interpersonal communication theories and their application to healthcare communication are discussed. CONCLUSION As healthcare communication interactions often occur at an interpersonal level, familiarity with theories of interpersonal communication may reinforce existing best practices and lead to the development of novel communication approaches with patients. PRACTICE IMPLICATIONS This article serves as an introductory primer to theories of interpersonal communication that have been or could be applied to healthcare communication research. Understanding key constructs and general formulations of these theories may provide practitioners with additional theoretical frameworks to use when interacting with patients.

Keywords: Adult, Communication, familiarity, Guidelines as Topic, Health Services Research, Humans, Interpersonal Relations, Kommunikationswissenschaft, Models, Theoretical, Professional-Patient Relations, Überblick

Jain, Rahul; Grabner, Michael; Onukwugha, Eberechukwu (2011): Sensitivity analysis in cost-effectiveness studies. From guidelines to practice. In: PharmacoEconomics 29 (4), S. 297-314. DOI: 10.2165/11584630-000000000-00000

DOI: http://www.ncbi.nlm.nih.gov/pubmed/21395350

Abstract: Cost-effectiveness analysis (CEA) is one of the main tools of economic evaluation. Every CEA is based on a number of assumptions, some of which may not be accurate, introducing uncertainty. Sensitivity analysis (SA) formalizes ways to measure and evaluate this uncertainty. Specific sources of uncertainty in CEA have been noted by various researchers. In this work, we consolidate across all sources of uncertainty, discuss the imbalanced attention to SA across different sources, and discuss criteria for conducting and reporting SA to help bridge the gap between guidelines and practice. Guidelines on how to perform SA have been published for many years in response to requests for greater standardization among researchers. Decision makers tasked with reviewing new health technologies also seem to appreciate the additional information conveyed by a robust SA, including the attention to important patient subgroups. Yet, past reviews have shown that there is a substantial gap between the guidelines' suggestions and the quality of SA in the field. Past reviews have also focused on one or two but not all three sources of uncertainty. The objective of our work is to comprehensively review all different sources of uncertainty and provide a concise set of criteria for conducting and presenting SA, stratified by common modelling approaches, including decision analysis and regression models. We first provide an overview of the three sources of uncertainty in a CEA (parameter, structural and methodological), including patient heterogeneity. We then present results from a literature review of the conduct and reporting of SA based on 406 CEA articles published between 2000 and mid-2009. We find that a minority of papers addressed at least two of the three sources of uncertainty, with no change over time. On the other hand, the use of some sophisticated techniques, such as probabilistic SA, has surged over the past 10 years. Lastly, we identify criteria for reporting uncertainty-robust SA and also discuss how to conduct SA and how to improve the reporting of SA for decision makers. We recommend that researchers take a more comprehensive view of uncertainty when planning SA for an economic evaluation.

Keywords: Cost-Benefit Analysis/statistics & numerical data, Data Interpretation, Statistical, Guidelines as Topic, Humans, Übersicht, Uncertainty, Sensitivity analysis (SA)

Cromey, Douglas W. (2010): Avoiding twisted pixels. Ethical guidelines for the appropriate use and manipulation of scientific digital images. In: Science and engineering ethics 16 (4), S. 639-667. DOI: 10.1007/s11948-010-9201-y

DOI: http://www.ncbi.nlm.nih.gov/pubmed/20567932

Abstract: Digital imaging has provided scientists with new opportunities to acquire and manipulate data using techniques that were difficult or impossible to employ in the past. Because digital images are easier to manipulate than film images, new problems have emerged. One growing concern in the scientific community is that digital images are not being handled with sufficient care. The problem is twofold: (1) the very small, yet troubling, number of intentional falsifications that have been identified, and (2) the more common unintentional, inappropriate manipulation of images for publication. Journals and professional societies have begun to address the issue with specific digital imaging guidelines. Unfortunately, the guidelines provided often do not come with instructions to explain their importance. Thus they deal with what should or should not be done, but not the associated 'why' that is required for understanding the rules. This article proposes 12 guidelines for scientific digital image manipulation and discusses the technical reasons behind these guidelines. These guidelines can be incorporated into lab meetings and graduate student training in order to provoke discussion and begin to bring an end to the culture of "data beautification".

Keywords: Absichtslosigkeit (Fehler), Codes of Ethics, Data Compression/ethics, Elektronische Bildverarbeitung, Ethics, Research, Ethik, Guidelines as Topic, Image Processing, Computer-Assisted/ethics, Intentionalität, Mensch-Technik-Relationen (MTR), Nachvollziehbarkeit des Sinns von Regeln/Anweisungen etc., Photography/ethics, Realtechnik, Science/ethics, Scientific Misconduct, Technik