BackgroundMaking evidence-based decisions often requires comparison of two or more options. Research-based evidence may exist which quantifies how likely the outcomes are for each option. Understanding these numeric estimates improves patients’ risk perception and leads to better informed decision making. This paper summarises current “best practices” in communication of evidence-based numeric outcomes for developers of patient decision aids (PtDAs) and other health communication tools.MethodAn expert consensus group of fourteen researchers from North America, Europe, and Australasia identified eleven main issues in risk communication. Two experts for each issue wrote a “state of the art” summary of best evidence, drawing on the PtDA, health, psychological, and broader scientific literature. In addition, commonly used terms were defined and a set of guiding principles and key messages derived from the results.ResultsThe eleven key components of risk communication were: 1) Presenting the chance an event will occur; 2) Presenting changes in numeric outcomes; 3) Outcome estimates for test and screening decisions; 4) Numeric estimates in context and with evaluative labels; 5) Conveying uncertainty; 6) Visual formats; 7) Tailoring estimates; 8) Formats for understanding outcomes over time; 9) Narrative methods for conveying the chance of an event; 10) Important skills for understanding numerical estimates; and 11) Interactive web-based formats. Guiding principles from the evidence summaries advise that risk communication formats should reflect the task required of the user, should always define a relevant reference class (i.e., denominator) over time, should aim to use a consistent format throughout documents, should avoid “1 in x” formats and variable denominators, consider the magnitude of numbers used and the possibility of format bias, and should take into account the numeracy and graph literacy of the audience.ConclusionA substantial and rapidly expanding evidence base exists for risk communication. Developers of tools to facilitate evidence-based decision making should apply these principles to improve the quality of risk communication in practice.
Background: Population breast cancer screening programs by mammography are offered to women based on age. It has been suggested that a screening program based on genetic risk profile could be more effective by targeting interventions at those at higher genetic risk. This study explores women’s attitudes towards genetic testing for breast cancer susceptibility in order to target breast cancer prevention. Methods: A qualitative study was conducted using 4 focus groups with 26 women aged 42–73 years. Women were selected irrespective of personal or family history of breast cancer. Discussions were audiotaped and content analyzed. Results: The results show that in general women are positive towards a breast cancer screening program based on genetic risk profile, provided that in the low-risk group, though less frequent, women are still offered mammography screening (i.e. right to screening (a)). Other themes that women addressed were: (b) value of the genetic risk information (e.g. possibilities for cancer prevention at younger ages, less screening burden for low-risk women), (c) personal autonomy (e.g. free choice to undergo testing), (d) dealing with test results (e.g. burden of risk, motivation to reduce the risk), (e) discrimination, and (f) financial aspects and priority (e.g. with respect to other health care programs). Conclusion: These results suggest that women currently offered breast cancer screening based on age have a positive attitude towards population susceptibility screening for breast cancer, but also identified issues that need to be discussed and studied further, especially if women in the low-risk group were no longer to be offered mammography screening.
Background: Long waiting times for elective surgical treatment threaten timely care provision in several countries. The purpose of this study was to assess the impact of waiting for elective general surgery on the quality of life and psychosocial health of patients.
This study presents a process analysis of multi-attribute decision making. The decision problems concerned the selection of the most suitable candidate for a job opening. The problems varied in terms of complexity, i.e. the number of candidates and the number of attributes used to describe these alternatives. Resultsshow that with an increasing number of alternatives, subjects ( N = 48) used fewer attributes for the evaluation of alternatives, and made, on average, less references to the alternatives. The type ofjudgment most often used was absolute dimensional (comparison of an attribute to an absolute standard) and was used more often at the beginning than toward the end of the decision process. Overall, judgments were predominantly positive. The percentage of positive judgments decreased with increasing complexity, and toward the end of the decision process. Significantly more judgments, particularly positive ones, concerned the finally chosen alternative as compared to the rest of the alternatives. Finally, analysis of subjects' usage of decision rules revealed that increasing the number of alternatives resulted in an increasing use of elimination strategies. Implications of these findings for the design of decision aids will be discussed.KEY WORDS Multi-attribute decisions Task complexity Protocol analysis in multi-attribute decision problems were absolute (i.e. comparisons with a criterion), while only a third were comparative (i.e. mutual comparisons of two or more alternatives on a particular attribute). This tendency increased toward the end of the protocol. Van Raaij (1977) studied the decision process of 50 subjects with the information board technique. His findings suggest that more interalternative or comparative evaluations were made in the first part of the decision process, and that more intra-alternative or absolute evaluations were made in the second part.In the study to be presented here, subjects were asked to solve a personnel selection problem. Task complexity is operationalized in terms of the number of choice alternatives and the number of attributes. The purpose of the process analysis is to investigate (1) how much information decision makers use in solving decision problems differing in complexity (information selection), (2) how decision makers use the information (type of judgment and evaluative sign), and (3) what kind of decision rules are used. The major differences with earlier process-tracing research can be summarized as follows. First, the way in which information is used and evaluated is analyzed more extensively by including more coding categories to analyze decision processes. Previous research (e.g. Biggs et al., 1985;Onken et al., 1985;Olshavsky, 1979; Payne, 1976) focused on depth of search and decision rule used. In the present study additional categories are: (a) number of attributes used and references made to each alternative as a function of its position in the final preference order;' (b) standard of comparison (absolute versus comparative) in order to investigate h...
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