Psychology, Health & Medicine, 2015 Vol. 20, No. 4, 410–418, http://dx.doi.org/10.1080/13548506.2014.958506

Factors influencing risky decision-making in patients with cerebral infarction Jingjing Gonga,1, Yan Zhangb,1, Bing Wuc, Jun Fenga, Weiwei Zhanga, Shijie Wanga, Yonghua Huanga* and Xinhuai Wuc* a

Department of Neurology, General Hospital of Beijing Command PLA, Beijing, China; Air Force Aviation Medicine Research Institute, Beijing, China; cDepartment of Radiology, General Hospital of Beijing Command PLA, Beijing, China b

(Received 19 March 2014; accepted 14 August 2014) Numerous studies have found that the framing effect is common in medical scenarios, but few studies have examined the influence of the framing effect upon thrombolytic therapy for cerebral infarction. In this study, 1040 inpatients and outpatients in the department of neurology were recruited to explore whether there is a framing effect in decision-making within thrombolytic therapy, and if so, which factors influence that effect. The findings from Study 1 indicate that the framing effect occurred in patients both with and without cerebral infarction (χ2 = 7.90, p = .005; χ2 = 5.16, p = .023, respectively), with both groups displaying risk-seeking behavior (thrombolytic therapy) in the positive frame and no risk aversion or risk seeking in the negative frame. The results of Study 2 show that the patients preferred risk seeking in both collaborative and individual decision-making. In the collaborative decision-making group, the patients in the senior group showed the framing effect (χ2 = 5.35, p < .05), with the patients in the positive frame (G) showing more significant risk seeking than both those in the negative frame (H) and those in the other positive frame (A, C, and E). In summary, decision-making about thrombolytic therapy in patients with cerebral infarction is influenced by the framing effect, and some influencing factors should be attended in clinical practice. Further research is necessary to guide the treatment of cerebral infarction. Keywords: framing effect; thrombolytic therapy; cerebral infarction; decision making

Introduction When people make decisions, they have different risk preferences that are affected by different semantic descriptions of the same issue. This phenomenon is called the framing effect and indicates that people make decisions in terms of the potential value of losses and gains rather than the final consequences (Gong et al., 2012). Prior to the description of the framing effect, it is hypothesized that the preferences for the greatest expected utility are not affected by the presentation of the options (Nelson, Stefanek, Peters, & McCaul, 2005). However, this hypothesis was questioned by Simon who stated that an organism requires only very simple perceptual and choice mechanisms to

*Corresponding authors. Email: [email protected] (Y. Huang); [email protected] (X. Wu) 1 These authors contributed equally to this work. © 2014 Taylor & Francis

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“satisfy its several needs”, and no “utility function” must be postulated for the organism (Simon, 1956), which was followed by many studies indicating that subjects violate utility theory when making decisions (Baron, 2000). Simon’s study was followed by the work of Tversky and Kahneman who first experimentally confirmed the concept of the “framing effect” (Tversky & Kahneman, 1981). Although some studies failed to report the observation of the framing effect (McElroy & Seta, 2003; Sieck & Yates, 1997), numerous studies provide evidence of the framing effect in a number of contexts. Notably, the framing effect in decision-making is affected by many variables, most of which often interact with one another. For instance, it has been reported that many individual variables could be obliged to the modulation of the framing effect in healthcare decisions including impulsiveness, involvement in personal healthcare, and attitude toward the patient’s own health (Lauriola, Russo, Lucidi, Violani, & Levin, 2005). Stoner studied medical decision-making among older subjects, either as individuals or as a part of a dyad, when confronted with positively or negatively framed messages (survival or mortality) about the option between surgery and radiation for lung cancer treatment. This study found that the framing effect occurs in older adults not only as individuals but also under collaborative decision-making (Stoner, 2007). Paese et al. found that the tendency of risky decision-making was influenced by the task model and the combination of decision makers (collaborative decision/individual decision) (Paese, Bieser, & Tubbs, 1993). In addition, customer product evaluation has been found to be affected by the information framework, the order of the information presented, and the reliability of the information sources (Buda & Zhang, 2000). Life is full of socially and economically risky decision-making, such as in clinical practice where examination and treatment involve decisions with potentially dire consequences. For example, acute cerebral infarction, a neurological disease with high morbidity, high mortality, and high disability rate, will be effectively treated with early thrombolytic therapy if possible, which significantly improves the prognosis. However, the therapy involves a risk of bleeding complications, such as cerebral hemorrhage, which may lead to death in some cases. Some patients refuse thrombolytic therapy to avoid the possibility of severe bleeding complications, a decision that can negatively influence prognosis and place a heavy social and economic burden on individuals, families, and their community. In the present study, we examined whether there is a framing effect in decision-making about thrombolytic therapy, and if so, which factors may influence patient decision-making behavior. As few previous studies investigated these questions, the present study was designed to provide additional evidence. This study consisted of two parts: the Study 1 was designed to compare differences in decision-making about thrombolytic therapy between patients with and without cerebral infarction. The purpose of the Study 2 was to study the influence of collaborative vs. individual decision-making, information resources (senior doctors/junior doctors), and message framework upon the decision-making tendencies of patients with cerebral infarction. Research questions Study 1 In Study 1, we wondered whether the framing effect would occur in the infarction group or the non-infarction group. If the framing effect occurred, what was the risk preference of the participants in different frameworks?

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Methods Study 1 Participants A total of 490 outpatients and inpatients in the Department of Neurology were consecutively recruited, in which 270 patients were diagnosed by brain MRI as having a “cerebral infarction,” including acute cerebral infarction, lacunar infarction, and old cerebral infarction, without undergoing thrombolytic therapy. The remaining 220 patients were free of cerebral infarction, as confirmed by cranial MRI. The two groups were matched in age, gender, and education (see Table 1). Procedures The experiment was approved by the Academic Committee of General Hospital of Beijing Command PLA, China. The ethics committee of the same department approved the experimental procedure and written consent form. All of the participants had completed primary (years of education ≤6 years, MMSE score >20) or post-primary education (years of education >6 years, MMSE score >24). All of the patients were able to communicate verbally and successfully completed the questionnaires. Each subject gave their informed consent to participate in the experiment and was provided with an exquisite teacup for compensation. In the cerebral infarction group, 150 patients were present in the positive frame, while 120 were present in the negative frame. In the non-cerebral infarction group, 110 patients made choices in the positive frame, and 110 patients made choices in the negative frame. There were 263 valid questionnaires (97.41%) collected in the cerebral infarction group and 208 valid questionnaires (94.55%) in the non-infarction group. Stimuli The medical scenario was “acute cerebral infarction,” and it was assumed that the patients were fit for thrombolytic therapy. The experimental context and details about the framework messages were shown in Table 2. The participants were divided into two groups: one group with cerebral infarction and one group without cerebral infarction. Each group was separated into two subgroups (positive/negative framework messages). Data analysis General descriptive statistics and χ2 tests were performed by the SPSS14.0 software package (p < .05). Table 1.

Demographic data of the two groups.

Group Framing type N Gender Male Female Age Education (years)

Group with cerebral infarction Positive frame 145 74 71 52.65 ± 11.36 10.36 ± 3.05

Negative frame 118 61 57 54.19 ± 8.37 11.51 ± 3.79

Group without cerebral infarction Positive frame 103 60 43 52.49 ± 9.49 10.21 ± 4.36

Negative frame 105 55 50 51.11 ± 10.26 11.74 ± 3.18

Psychology, Health & Medicine Table 2.

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Medical scenarios and framing messages.

Medical Acute cerebral infarction is a common disease resulting in serious damage to an scenario individual’s health. Cerebral blood flow and tissue perfusion can be restored quickly and effectively by early thrombolytic therapy: intravenous injection of recombinant tissue plasminogen activator (rTPA), which can also reduce reperfusion injury, promote the survival of nerve cells, decrease infarct size, encourage better recovery of neurological function, and reduce patient mortality and complications. However, this treatment is accompanied by the risk of bleeding complications, including fatal cerebral hemorrhage, but we will try our best to reduce the risk of these complications. If you or your relatives are faced with the threat of acute cerebral infarction, there are two therapies; according to clinical studies and observations, the expected results of each therapy are as follows: Positive frame Negative frame Treatment 1 (risk seeking): It is reported Treatment 1 (risk seeking): It is reported that rTPA thrombolytic therapy is of that rTPA thrombolytic therapy is of lower inefficiency and less severe higher efficiency and much more mild disability in the prognosis, but there are disability (or no disability) in the prognosis, but there are less patients with more patients with major bleeding events minor bleeding or no bleeding Treatment 2 (risk aversion): It is reported Treatment 2 (risk aversion): It is reported that rt-PA thrombolytic therapy is of non-thrombolytic therapy is of lower higher inefficiency and more severe efficiency and less mild disability (or no disability) in the prognosis, but there are disability in the prognosis, but there are more patients with minor bleeding or no fewer patients with major bleeding events bleeding Which option would you prefer? Which option would you prefer?

Results Study 1 The findings indicate that the framing effect occurred in both groups (χ2 = 7.90, p = .005; χ2 = 5.16, p = .023, respectively). Both of the groups showed risk seeking (thrombolytic therapy) in the positive frame, while there was neither risk aversion nor risk seeking in the negative frame (see Table 3). Discussion Study 1 As mentioned above, it has been reported that the framing effect is affected by involvement in personal healthcare (Lauriola et al., 2005). Specifically, much more attention would be paid to the information about cerebral infarction by the patients with cerebral infarction, and it could be hypothesized that the farming effect would be absent in the cerebral infarction group because of the protection of the relative knowledge of infarction from the cognitive biases. However, the findings of Study 1 showed that the infarction group preferred the same risky seeking as the non-infarction group in the positive frame, demonstrating that the pursuit of the improved prognosis seemed to overwhelm the fear of the side effect of thrombolytic therapy in both groups. Research questions Study 2 In Study 2, we wondered whether the framing effect would occur in the individual decision-making group or the collective decision-making group? What’s the influence of the information resources (information from the junior doctors or the senior doctors) upon the risk preferences in the positive frame and the negative frame?

414 Table 3.

J. Gong et al. Decision-making in the two groups. Risk

Groups

Frame

Cerebral infarction

Positive Negative χ2 Positive Negative χ2

No cerebral infarction

N

Aversion

Seeking

145 118 7.90** 103 105 5.16*

50 61

95 57

35 52

68 53

*p < .05; **p < .01.

Methods Study 2 Participants A total of 550 outpatients and inpatients in the Department of Neurology were selected consecutively, and the participants were diagnosed by brain MRI as having a “cerebral infarction,” including acute cerebral infarction, lacunar infarction, and old cerebral infarction, without undergoing thrombolytic therapy. Procedures The procedures of the experiment were similar to the Study 1. The patients were randomly divided into individual and collaborative decision-making groups. In the collaborative group, each patient and two of their relatives discussed the issue with one another, but the patient was required to make the final decision. Each decision-making group was divided into two subgroups: a junior doctor group (the messages were conveyed to the patients by junior doctors) and a senior doctor group (the messages were conveyed to the patients by senior doctors). Finally, each doctor group consisted of two frame messages: either positive or negative. To facilitate distinguishing different subgroups, these subgroups were marked as A, B, C, D, E, F, and G (see Table 5). There were 521 valid questionnaires (94.73%) collected in all, and the demographic data are shown in Table 4. Stimuli The medical scenario was similar to Study 1.

Table 4.

Demographic data of the two groups.

Group Frame N Gender Male Female Age Education (years)

Individual Positive 129 76 53 50.15 ± 10.11 11.17 ± 4.21

Collaborative Negative 121

70 51 51.32 ± 7.31 10.63 ± 4.49

Positive

Negative

140

131

85 55 50.99 ± 9.12 11.54 ± 4.10

78 53 52.21 ± 11.41 10.72 ± 3.69

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Data analysis General descriptive statistics and χ2 test were performed by the SPSS14.0 software package (p1 < .05). A Brunden test (K = 7) was used for further comparison, with p2 < .00417 as an indicator of significance. Results Study 2 The results demonstrate that the patients preferred risk seeking in both the collaborative and individual decision-making groups. In the individual decision-making group, the patients were not affected by framing effects in either the junior doctor group (χ2 = .50, p1 > .05) or the senior doctor group (χ2 = 3.26, p1 > .05). In the collaborative decisionmaking group, the patients in the junior group showed no evidence of the framing effect (χ2 = 2.80, p1 > .05), while the patients in the senior group displayed the framing effect (χ2 = 5.35, p1 < .05). In this group, the patients receiving the positive frame showed more significant risk seeking than those in the negative frame. A Brunden test (K = 7) was used to further compare the risk preference of group G with groups A, B, C, D, E, and F. The results suggest that there was no significant difference in risk preference between G, B, D, or F, while there was a significant difference in risk preference between G, A, C, and E, indicating that group G showed more risk seeking than the other groups (see Table 5). Discussion Study 2 Different from the previous report that the framing effect occurs in older adults not only as individuals but also under collaborative decision-making (Stoner, 2007); it was found in Study 2 that the older patients failed to show the framing effect in both the collaborative and individual decision-making groups, except for the patients in the senior group Table 5. The influence of collaborative decision makers, information resources, and frame upon decision-making in the two groups.

Combination

Information resources

Individual decision-making

Collaborative decision-making

Risk N

Junior doctors

Positive (A) Negative (B) χ12

56 55 .50

23 19

33 36

9.337 .003* 5.257 .025

Senior doctors

Positive (C) Negative (D) χ12

73 66 3.26

33 20

40 46

13.777 .000* 3.449 .075

Junior doctors

Positive (E) Negative (F) χ12

64 63 2.80

24 15

40 48

7.432 .007* .962 .397

Senior doctors

Positive (G) Negative (H) χ12

76 68 5.35*

13 23

63 45

Note: χ12 positive vs. negative frame; *p1 < 0.05; **p1 < 0.01. χ22 G vs. A, B, C, D, E, F; *p2 < 0.00417.

Aversion Seeking

χ22

Frame

p2

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in the collaborative decision-making group. Such findings indicate that risky decisionmaking be influenced by information resources and the combination of decision makers (collaborative or individual). According to the present findings, to improve the thrombolytic rate, it might be speculated for clinical practice that patients with acute cerebral infarction might be exposed to a positive frame of information and encouraged to discuss with relatives and communicate with senior doctors about thrombolytic therapy decision-making. Collective discussion In clinical practice, where abundant medical decision-making must be made by doctors and patients, it has been found in numerous studies that the framing effect is common in medical scenarios (Armstrong, Schwartz, Fitzgerald, Putt, & Ubel, 2002; Gong et al., 2013; McNeil, Pauker, Sox, & Tversky, 1982; Rothman, Martino, Bedell, Detweiler, & Salovey, 1999). Interestingly, compared to the classical framing effect, it has been reported that there is a reversal in risky preference during the medical decision process: subjects prefer risk aversion in the positive framework and risk seeking in the negative framework (McNeil et al., 1982). This observation appears to be partly supported by the present findings in Study 1: in the positive frame, risk seeking (thrombolytic therapy) was preferred by patients both with and without cerebral infarction. A similar result has also been observed for surgery treatment (Moxey, O’Connell, McGettigan, & Henry, 2003). Additionally, it has been admitted that participants’ knowledge of the medical decision either from their relatives or from their direct experiences could help them make unbiased decision. That is to say, patients could be protected by their previous knowledge and experiences from the impact of the framing effect (Hughes, 1993). Therefore, it can be hypothesized that there should be an absence of the framing effect in patients with cerebral infarction. However, the findings of Study 1 showed no difference in decision-making between the two groups of patients. This may be because the two groups of subjects were all neurological patients, which might be similar in terms of personal healthcare. Future studies should focus on examining the effect of personal involvement in healthcare by comparing patients with cerebral infarction to healthy controls. Decision-making biases in collaborative decisions, such as sunk-cost bias and confirmation bias, have been reported (Christine, 1998; Schulz-Hardt, Frey, Lüthgens, & Moscovici, 2000). Paese and colleagues examined the framing effect in collaborative decisions involving three individuals (Paese et al., 1993) and observed that groups showed more risk aversion across framing conditions (positive or negative) compared to choices made by individuals in the medical scenario. This finding seems to differ from the present results: subjects preferred the risk-seeking options, and the framing effect only occurred in the collaborative decision when the messages were provided by senior doctors. Such a framing effect is called unidirectional, in which the decision-making preference moves from one level to a more extreme level without a reversal in risk tendency. The other type of framing effect is called bidirectional (classic framing effect), in which the risk-seeking choice is favored in the negative frame and the risk averse choice is preferred in the positive frame. Several factors might account for the differences between Paese’s study and the present results. Firstly, the participants in the present study are older than those in Paese’s study, and it has been suggested that older people are more susceptible to the influence of the semantic frame and older subjects prefer risk seeking in comparison with younger subjects (Kim, Goldstein, Hasher, &

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Zacks, 2005). Secondly, in comparison with Western subjects, Chinese subjects tend to make risk-seeking decisions (Li, Fang, & Zhang, 2000). Thirdly, there are differences in medical scenarios, participants’ identity, data formats, and other variables between the two studies. There are few studies that have examined the impact of the type of decision-making (collaborative or individual) upon the framing effect bias, especially in older participants, as older adults or patients often turn to relatives or friends for discussion and suggestion when they make decisions regarding treatment options (Strough, Patrick, Swenson, Cheng, & Barnes, 2003). It is very difficult for older people to make final decisions depending only upon themselves. Considering the lack of collaborative decision-making research, the previous results may not be generalizable to this older population. Limitations There were some flaws in the present study. Firstly, the sample size should be enlarged in Study 2 because there are more influencing factors in the discussion in Study 2 compared to Study 1. Secondly, the homogeneity of the decision makers should be considered in the collaborative decision-making group. Yaniv investigated the influence of group composition upon decision-making and found that, in comparison with individual risk tendency, the preferences of the homogeneous group were polarized to amplify the framing effect, while the preferences of the heterogeneous group converged, leading to a reduction in the framing effect to zero (Yaniv, 2011). Therefore, the issue of homogeneity in collaborative decision-making should be discussed in future research. Moreover, in clinical practice, the actual decision makers regarding thrombolytic therapy are more likely to be the relatives of the patients than the patients themselves, which indicates that the method of collaborative decision-making should be refined and studied. Future directions The patients’ responses to obscure information about thrombolytic therapy were discussed in the present study. As some patients will focus on specific information about thrombolytic therapy, such as thrombolytic success rate and incidence of bleeding, the differences between clear and vague information in the framework messages should be further studied in the future. Conclusions In summary, decision-making about thrombolytic therapy in patients with cerebral infarction is influenced by the framing effect, and some influencing factors (e.g. collaborative/individual decision-making, information resources) should be attended in clinical practice. Further research is necessary to guide the treatment of the cerebral infarction, increase the rate of thrombolytic therapy, and reduce injury to patients with cerebral infarction. Funding This research was supported by the Beijing Natural Science Foundation [grant number 7123230] and the National Natural Science Foundation of China [grant number 31000461], [grant number 81171100].

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Factors influencing risky decision-making in patients with cerebral infarction.

Numerous studies have found that the framing effect is common in medical scenarios, but few studies have examined the influence of the framing effect ...
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