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Tuesday, October 21, 2008: 3:00 PM
Grand Ballroom B/C (Hyatt Regency Penns Landing)
Purpose: Numeric information is often provided in decisions, but may not be useable by patients and consumers without assistance from information providers. The objective of this paper was to examine whether a manipulation of affective meaning (i.e., the extent to which an attribute can be mapped onto an affective good/bad scale) could help decision makers use important numeric information. A set of four studies examined this effect and possible theoretical mechanisms underlying the effect, including cognitive simplification, categorization, and affect.
Methods: We presented college-student, employed-aged, or elderly adults with numeric quality indicators about health plans or hospitals. Half of participants were presented with the numeric information made easier to evaluate through the use of affective markers (labels indicating the goodness or badness of the indicator shown); the other participants were shown only the numeric information. Each study examined the impact of the presence versus absence of the affective markers on judgments or choices. Possible cognitive and affective mechanisms underlying the effect were tested using measures of affect, memory, and reaction times.
Results: The results demonstrated that an affective-markers manipulation influenced preferences and the weight given to attributes in choice and led to a greater integration of important attributes and less influence of irrelevant mood states. In addition, this influence depended on numeracy. For participants low in numeracy, affective markers appeared to provide more meaning to numeric information and to influence judgments more. Tests of underlying mechanisms were most consistent with affect rather than cognitive simplification or categorization processes.
Conclusion: Numbers appear to be just that—numbers. The present results suggest that consumers may not use them as information until available data is analyzed to determine their affective meaning or until the data acquire affective meaning through other means such as affective markers. These results are consistent with the constructed-preferences approach in decision making. We argue that the affective labels act as overt markers of affective meaning and guide choices. Decision makers need help in interpreting not only what the numbers are but also what they mean, and this meaning is tied to affect at least in the present context. How health information is communicated to patients should be tested for its effectiveness just as health products themselves are tested.
Methods: We presented college-student, employed-aged, or elderly adults with numeric quality indicators about health plans or hospitals. Half of participants were presented with the numeric information made easier to evaluate through the use of affective markers (labels indicating the goodness or badness of the indicator shown); the other participants were shown only the numeric information. Each study examined the impact of the presence versus absence of the affective markers on judgments or choices. Possible cognitive and affective mechanisms underlying the effect were tested using measures of affect, memory, and reaction times.
Results: The results demonstrated that an affective-markers manipulation influenced preferences and the weight given to attributes in choice and led to a greater integration of important attributes and less influence of irrelevant mood states. In addition, this influence depended on numeracy. For participants low in numeracy, affective markers appeared to provide more meaning to numeric information and to influence judgments more. Tests of underlying mechanisms were most consistent with affect rather than cognitive simplification or categorization processes.
Conclusion: Numbers appear to be just that—numbers. The present results suggest that consumers may not use them as information until available data is analyzed to determine their affective meaning or until the data acquire affective meaning through other means such as affective markers. These results are consistent with the constructed-preferences approach in decision making. We argue that the affective labels act as overt markers of affective meaning and guide choices. Decision makers need help in interpreting not only what the numbers are but also what they mean, and this meaning is tied to affect at least in the present context. How health information is communicated to patients should be tested for its effectiveness just as health products themselves are tested.