构建健康相关决策的经济和行为后果研究的新范式

I. Levin, M. Lauriola
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For example, a person’s health status was rated higher when the same level of vitamin intake was stated in terms of its distance above an established low-protection level compared to when it was stated in terms of its distance below an established high-protection level. 1.0 Introduction versky and Kahneman’s (1981) classic ―Asian disease problem‖ sparked considerable interest in ―information framing‖ effects—how the same information can lead to different decisions depending on the way that information is labeled or framed. In the case of the Asian disease problem, respondents were more apt to make risky decisions when options were described in terms of potential losses than when they were described in terms of potential gains. This is known as the ―Risky Choice Framing Effect.‖ A somewhat simpler framing effect that doesn’t necessarily involve the element of risk is known as the ―Attribute-Framing Effect.‖ An Attribute-Framing Effect is found when the evaluation of a given object or product differs depending on whether a key attribute is described in positive terms or negative terms. Because a single attribute within any given context is the subject of the framing manipulation, attribute-framing experiments provide researchers with a very general and, indeed, flexible paradigm to test how the positive/negative valence of available information influences one's judgment processes. Experimental studies of attribute framing often involve consumer judgments, including health-related judgments. For instance, Levin and Gaeth (1988) showed that perceptions of the quality and healthiness of ground beef depended on whether the beef is labeled as ―75% lean‖ or ―25% fat.‖ Levin, Gaeth, Schreiber and Lauriola (2002) added an analysis of the economic impact of attribute framing by showing that consumers were willing to spend an average of 8.2 cents more for a one-pound package of ―80% lean ground beef‖ than for a one-pound package of ―20% fat ground beef.‖ Attribute framing sometimes involves the evaluation of risky behaviors. For instance, Van Schie & Van der Pligt, (1995) showed that emphasizing \"potential positive outcomes\" rather than ___________________ Readers with comments or questions are encouraged to contact the authors via email. \"negative ones\" in a risky option led to increased preference for this option. This has important implications for T International Business & Economics Research Journal Volume 2, Number 9 26 health-related decisions. McNeil, Pauker, Sox and Tversky (1982) showed that a medical treatment was more apt to be selected when it was described in terms of success rate rather than failure rate. After an extensive literature review, Levin, Schneider & Gaeth (1998) came to the conclusion that the processes accounting for attribute framing effects are associative processes which produce more favorable evaluations when the framed attribute primes positive associations rather than negative ones. We refer to this process and its expected effects as the \"standard\" attribute framing effect. In the present study we provide a different and, perhaps more general, form of attribute-framing, where a given attribute is first described relative to a reference point, and then the framing valence is inferred based on whether the distance from the reference point is viewed as a positive or a negative. We define the positive/negative conditions in terms of valence consistent shifts associated with gains and losses relative to higher or lower standards of risk and protection. Thus, describing one's health status as a given level above a lower standard of risk is expected to produce a consistent negative shift in valuation compared to describing one’s health status as a given level below a higher standard of risk which is expected to produce a consistent positive evaluation shift. 2.0 Aims and Scope In the present study, we first test the so-called \"general\" attribute-framing effect by comparing valence consistent shifts across variations in standard of reference. Thus, for example, we expect positive consistent shifts when evaluating one's exposure to risk as being below a higher standard of risk. Conversely, we expect negative consistent shifts when evaluating one's exposure to risk as being above a lower standard of risk. Second, we expand on previous research by comparing this \"general\" attribute-framing effect in two different health domains: either evaluating one's exposure to risk factors such as high cholesterol or judging one's exposure to protective factors such as vitamin intake. We administered four different versions of the attribute-framing problem by providing different frames of reference for a health-risk and health-protection scenario. (A, B, C, and D in the figure). We define each condition as representing positive or negative framing, depending on whether that condition represents a particular value as being below a stated high-risk or high-protection level, or as being above a stated low-risk or low-protection level. This represents an extension of earlier definitions of attribute framing. Condition A describes one's blood cholesterol level as 4/10 above the low-risk level. 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For example, a person’s health status was rated higher when the same level of vitamin intake was stated in terms of its distance above an established low-protection level compared to when it was stated in terms of its distance below an established high-protection level. 1.0 Introduction versky and Kahneman’s (1981) classic ―Asian disease problem‖ sparked considerable interest in ―information framing‖ effects—how the same information can lead to different decisions depending on the way that information is labeled or framed. In the case of the Asian disease problem, respondents were more apt to make risky decisions when options were described in terms of potential losses than when they were described in terms of potential gains. This is known as the ―Risky Choice Framing Effect.‖ A somewhat simpler framing effect that doesn’t necessarily involve the element of risk is known as the ―Attribute-Framing Effect.‖ An Attribute-Framing Effect is found when the evaluation of a given object or product differs depending on whether a key attribute is described in positive terms or negative terms. Because a single attribute within any given context is the subject of the framing manipulation, attribute-framing experiments provide researchers with a very general and, indeed, flexible paradigm to test how the positive/negative valence of available information influences one's judgment processes. Experimental studies of attribute framing often involve consumer judgments, including health-related judgments. For instance, Levin and Gaeth (1988) showed that perceptions of the quality and healthiness of ground beef depended on whether the beef is labeled as ―75% lean‖ or ―25% fat.‖ Levin, Gaeth, Schreiber and Lauriola (2002) added an analysis of the economic impact of attribute framing by showing that consumers were willing to spend an average of 8.2 cents more for a one-pound package of ―80% lean ground beef‖ than for a one-pound package of ―20% fat ground beef.‖ Attribute framing sometimes involves the evaluation of risky behaviors. For instance, Van Schie & Van der Pligt, (1995) showed that emphasizing \\\"potential positive outcomes\\\" rather than ___________________ Readers with comments or questions are encouraged to contact the authors via email. \\\"negative ones\\\" in a risky option led to increased preference for this option. This has important implications for T International Business & Economics Research Journal Volume 2, Number 9 26 health-related decisions. 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We define the positive/negative conditions in terms of valence consistent shifts associated with gains and losses relative to higher or lower standards of risk and protection. Thus, describing one's health status as a given level above a lower standard of risk is expected to produce a consistent negative shift in valuation compared to describing one’s health status as a given level below a higher standard of risk which is expected to produce a consistent positive evaluation shift. 2.0 Aims and Scope In the present study, we first test the so-called \\\"general\\\" attribute-framing effect by comparing valence consistent shifts across variations in standard of reference. Thus, for example, we expect positive consistent shifts when evaluating one's exposure to risk as being below a higher standard of risk. Conversely, we expect negative consistent shifts when evaluating one's exposure to risk as being above a lower standard of risk. 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引用次数: 5

摘要

其次,我们通过比较两个不同健康领域的“一般”属性框架效应来扩展先前的研究:要么评估一个人对高胆固醇等风险因素的暴露程度,要么判断一个人对维生素摄入量等保护因素的暴露程度。通过为健康风险和健康保护情景提供不同的参考框架,我们管理了四个不同版本的属性框架问题。(图中A, B, C, D)。我们将每个条件定义为代表积极或消极框架,这取决于该条件代表的特定值是低于规定的高风险或高保护水平,还是高于规定的低风险或低保护水平。这代表了属性框架的早期定义的扩展。A描述的是一个人的血液胆固醇水平比低风险水平高4/10。我们将这种情况定义为负面框架,因为一个人的血液胆固醇水平被描述为相对于低风险参考点的风险增加,这容易被视为不好或负面的。条件B描述的是一个人的血液胆固醇水平低于高危水平的6/10。我们将这种情况定义为积极框架,因为一个人的血液胆固醇水平被描述为相对于高风险参考点的风险损失,这往往被视为良好或积极的。因此,我们预计条件A的风险评级高于条件b。条件C描述一个人的维生素E摄入量比低保护水平高4/10。我们将这种情况定义为积极框架,因为一个人的维生素消耗水平被描述为与低保护参考点相比获得了保护。条件D描述一个人的维生素E摄入量低于高保护水平的6/10。我们将这种情况定义为负框架,因为一个人的维生素消耗水平被描述为与高保护水平相比缺乏保护。因此,我们预计条件C的保护水平要高于条件d。《国际商业与经济研究杂志》第2卷第9期
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Paradigm For Studying The Economic And Behavioral Consequences Of Framing Health-Related Decisions
Traditional attribute framing effects occur when the same object is evaluated differently depending on whether a particular attribute is labeled or framed in positive or negative terms. For example, in one of our earlier studies, “80% lean ground beef” was evaluated more favorably and was “worth” 8 cents more per pound than “20% fat ground beef.” In the present study of health-related judgments and decisions, attribute framing effects were extended to situations where consumers had to infer framing valence depending on whether one’s health status was described in comparison to a lower standard or a higher standard of reference. For example, a person’s health status was rated higher when the same level of vitamin intake was stated in terms of its distance above an established low-protection level compared to when it was stated in terms of its distance below an established high-protection level. 1.0 Introduction versky and Kahneman’s (1981) classic ―Asian disease problem‖ sparked considerable interest in ―information framing‖ effects—how the same information can lead to different decisions depending on the way that information is labeled or framed. In the case of the Asian disease problem, respondents were more apt to make risky decisions when options were described in terms of potential losses than when they were described in terms of potential gains. This is known as the ―Risky Choice Framing Effect.‖ A somewhat simpler framing effect that doesn’t necessarily involve the element of risk is known as the ―Attribute-Framing Effect.‖ An Attribute-Framing Effect is found when the evaluation of a given object or product differs depending on whether a key attribute is described in positive terms or negative terms. Because a single attribute within any given context is the subject of the framing manipulation, attribute-framing experiments provide researchers with a very general and, indeed, flexible paradigm to test how the positive/negative valence of available information influences one's judgment processes. Experimental studies of attribute framing often involve consumer judgments, including health-related judgments. For instance, Levin and Gaeth (1988) showed that perceptions of the quality and healthiness of ground beef depended on whether the beef is labeled as ―75% lean‖ or ―25% fat.‖ Levin, Gaeth, Schreiber and Lauriola (2002) added an analysis of the economic impact of attribute framing by showing that consumers were willing to spend an average of 8.2 cents more for a one-pound package of ―80% lean ground beef‖ than for a one-pound package of ―20% fat ground beef.‖ Attribute framing sometimes involves the evaluation of risky behaviors. For instance, Van Schie & Van der Pligt, (1995) showed that emphasizing "potential positive outcomes" rather than ___________________ Readers with comments or questions are encouraged to contact the authors via email. "negative ones" in a risky option led to increased preference for this option. This has important implications for T International Business & Economics Research Journal Volume 2, Number 9 26 health-related decisions. McNeil, Pauker, Sox and Tversky (1982) showed that a medical treatment was more apt to be selected when it was described in terms of success rate rather than failure rate. After an extensive literature review, Levin, Schneider & Gaeth (1998) came to the conclusion that the processes accounting for attribute framing effects are associative processes which produce more favorable evaluations when the framed attribute primes positive associations rather than negative ones. We refer to this process and its expected effects as the "standard" attribute framing effect. In the present study we provide a different and, perhaps more general, form of attribute-framing, where a given attribute is first described relative to a reference point, and then the framing valence is inferred based on whether the distance from the reference point is viewed as a positive or a negative. We define the positive/negative conditions in terms of valence consistent shifts associated with gains and losses relative to higher or lower standards of risk and protection. Thus, describing one's health status as a given level above a lower standard of risk is expected to produce a consistent negative shift in valuation compared to describing one’s health status as a given level below a higher standard of risk which is expected to produce a consistent positive evaluation shift. 2.0 Aims and Scope In the present study, we first test the so-called "general" attribute-framing effect by comparing valence consistent shifts across variations in standard of reference. Thus, for example, we expect positive consistent shifts when evaluating one's exposure to risk as being below a higher standard of risk. Conversely, we expect negative consistent shifts when evaluating one's exposure to risk as being above a lower standard of risk. Second, we expand on previous research by comparing this "general" attribute-framing effect in two different health domains: either evaluating one's exposure to risk factors such as high cholesterol or judging one's exposure to protective factors such as vitamin intake. We administered four different versions of the attribute-framing problem by providing different frames of reference for a health-risk and health-protection scenario. (A, B, C, and D in the figure). We define each condition as representing positive or negative framing, depending on whether that condition represents a particular value as being below a stated high-risk or high-protection level, or as being above a stated low-risk or low-protection level. This represents an extension of earlier definitions of attribute framing. Condition A describes one's blood cholesterol level as 4/10 above the low-risk level. We define this condition as negative framing because one's blood cholesterol level is described as an increase in risk relative to a low-risk reference point, which is apt to be viewed as bad or negative. Condition B describes one's blood cholesterol level as 6/10 below the high-risk level. We define this condition as positive framing because one's blood cholesterol level is described as a loss of risk relative to a high-risk reference point, which is apt to be viewed as good or positive. We thus expect risk to be rated higher in Condition A than in Condition B. Condition C describes one's Vitamin E consumption level as 4/10 above the low-protection level. We define this condition as positive framing because one's vitamin consumption level is described as a gain of protection in comparison to a low-protection reference point. Condition D describes one's Vitamin E consumption Level as 6/10 below the high-protection level. We define this condition as negative framing because one's Vitamin Consumption level is described as a loss of protection in comparison to a high-protection level. We thus expect protection level to be rated higher in Condition C than in Condition D. International Business & Economics Research Journal Volume 2, Number 9
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