Perceptions of Active Versus Passive Risks,and the Effect of Personal Responsibility

Abstract

Not getting vaccinated or not backing up computer files are examples of passive risk taking: risk brought on or magnified by inaction. We suggest the difficulty in paying attention to absences, together with the reduced agency and responsibility that is associated with passive choices, leads to the perception of passive risks as being less risky than equivalent active risks. Using scenarios in which risk was taken either actively or passively, we demonstrate that passive risks are judged as less risky than equivalent active risks. We find the perception of personal responsibility mediates the differences between the perception of passive and active risks. The current research offers an additional explanation for omission or default biases: The passive nature of these choices causes them to appear less risky than they really are.

Keywords

risk decision making passive judgment personal responsibility

Consider the following alternatives: parking your car in a restricted zone or not moving your car once you realize it is parked in a restricted zone. Which of these options seems riskier to you? The former most likely seems to be a bolder, riskier choice, even though the risk involved in both cases is equal—receiving a parking fine or having your car towed away.

It is common to think of risk taking as an active action, as even the term “risk taking” suggests. Accordingly, research on risk-taking behavior focuses mainly on issues such as drug and alcohol abuse, promiscuous sexual activity, smoking, reckless driving, gambling, or participating in dangerous sports (Andrew & Cronin, 1997; Blaise & Weber, 2006; Carlin & Robinson, 2009; Slovic, 1987). However, in many real-life situations, risk is also embodied in abstaining from taking action rather than in taking it, as is the case when avoiding recommended medical screen tests, not exercising regularly, or neglecting to purchase proper travel insurance.

Although the research on risk has predominantly focused on the actions people take that put them at risk, recent evidence suggests risk taking can also appear in passive form (Keinan & Bereby-Meyer, 2012). In line with the common definition of the riskier choice as the one with the greater outcome variance (e.g., Yechiam & Ert, 2011), we define passive risk taking as foregoing an opportunity to act to reduce outcome variance. We have demonstrated passive risk taking is not linked to classic risk correlates such as sensation seeking but shows ties to inaction-oriented tendencies such as procrastination and avoidance—variables previously not regarded as relevant to risk taking (Keinan & Bereby-Meyer, 2012). Thus, passive risk taking may be considered a unique domain of risk taking.

In the current research, we aim to deepen our understanding of the passive risk concept by examining the perception of passive risks. We hypothesize that the nature of passive risks, often being in the background of everyday life and capturing little attention, together with the diminished agency (and consequently reduced personal responsibility) people associate with passive choices, leads people to consider them less risky than equivalent active risks. If risks accepted passively are perceived as less risky than identical active risks, this view may influence decision making, leading to amplified risk taking in passive risk situations.

Inaction Biases and Passive Choices

Previous studies have examined people’s tendency to not act in situations in which actions can lead to gain. This research has demonstrated several decision-making biases, which we next address and distinguish from the concept of passive risk taking.

The most prominent inaction bias identified is the status quo bias—people’s tendency to prefer the status quo to similar or even better options (Kahneman, Knetsch, & Thaler, 1991; Samuelson & Zeckhauser, 1988). Samuelson and Zeckhauser (1988) suggested this preference stems from a desire to minimize loss or regret should the chosen alternative prove to be less desirable than expected. People’s inherent motivation for consistency and dissonance reduction (Bator & Cialdini, 2006), together with their motivation to defend, bolster, and justify the status quo, as suggested by system justification theory (Jost et al., 2012; Jost et al., 2010; Kay et al., 2009), also contributes to the status quo bias.

Some have argued people prefer the default option, rather than the status quo, because simply presenting an option as a default raises the likelihood it will be chosen, even if it is not the status quo (Kahneman et al., 1991). Humans’ preference for defaults receives even neurological reinforcement, because choosing the default stimulates reward areas in the brain (Yu, Mobbs, Seymour, & Calder, 2010).

Another widely researched inaction bias is termed omission bias—people’s tendency to prefer harm caused by omissions to equal or lesser harm caused by acts (Ritov & Baron, 1990, 1992). This effect was first detected in experiments examining people’s reluctance to get vaccinated but has been demonstrated in other fields as well (Hayashi, 2015; Ritov & Baron, 1990). The mechanisms behind omission bias are similar to those perpetuating status quo bias, mainly loss aversion and an attempt to minimize future blame or regret (Ritov & Baron, 1999), as well as the implementation of heuristics such as “do no harm” (Baron & Ritov, 2004).

Passive risk taking differs from these reviewed inaction biases, most importantly because it refers specifically to risk. It is an individual difference tendency (Keinan & Bereby-Meyer, 2012), as well as a situational property. Although Samuelson and Zeckhauser (1988) suggested the tendency to prefer the status quo may result in increased risk-taking behavior, they did not suggest this tendency to be due to an underestimation of risk, but rather to regret avoidance. Avoidance of regret, as well as striving for consistency or minimizing dissonance, which increases people’s commitment to the status quo (Samuelson & Zeckhauser, 1988), does not play a major role in passive risk taking. People usually do not avoid exercising regularly because they feel committed to their current state of not exercising and might regret doing otherwise. Regret avoidance may contribute to passive risk taking in certain situations (such as if someone underwent a medical screening test and realized his or her illness has no cure), but it is most likely not the driving force behind this tendency.

Passive Risks

We suggest that a crucial aspect of passive risks that distinguishes them from active risks is related to their perceptual nature. In contrast to active risk taking, which is usually visible and physically present, passive risk situations are less obvious because, oftentimes, no vivid cues signal the absence of actions. Accordingly, Newman, Wolff, and Hearst (1980) found that participants who needed to learn that an absence of a feature determines the uniqueness of a stimulus failed to grasp the concept, despite having seeing it numerous times. Furthermore, when people estimate whether two events are causally related, they usually consider information about the co-occurrence and ignore the co-absences (Alloy & Tabachnik, 1984). Gilbert (2006) suggested that this difficulty in paying attention to absences is one factor that accounts for the misrepresentation of future events. In line with that assertion, we suggest this inferior ability to devote attention to the absence of events leads to passive risks being less available to our consciousness, to be underestimated, and thus to be perceived as less risky. We need to be motivated to devote attention to passive risks. A sense of personal responsibility may serve as a motivator for deeper processing of information.

Personal Responsibility and Passive Risk Perception

The literature suggests people are perceived as more personally responsible for actions than for inactions, because actions are viewed as involving more agency and intent on the part of the decision maker (Kahneman & Miller, 1986; Ritov & Baron, 1990). Norm theory suggests inactions are often considered the “norm,” whereas actions are regarded as a deviation from the norm, by altering the “natural” scheme of things (Kahneman & Miller, 1986). Accordingly, actions are more mutable than inactions because generating mental alternatives to actions is easier (Catellani & Milesi, 2001; Gleicher et al., 1990; Landman, 1987). Buying stock seems less “normal” compared with not selling stock you already own, because thinking of an alternative to the act of buying stock is easier (not buying the stock). Because mutable behaviors are perceived as more causal and blameworthy than less mutable choices (Branscombe, Owen, Garstka, & Coleman, 1996; Nario-Redmond & Branscombe, 1996), people are perceived to be less responsible for their omissions than for their commissions (Heider, 1958; Kahneman & Miller, 1986). Indeed, omissions are deemed less immoral than commissions and are not regarded as causing outcomes (Spranca, Minsk, & Baron, 1991).

Lerner and Tetlock (1999) suggested accountability, which is closely related to personal responsibility and involves the expectation that one may be called to justify one’s actions (Tetlock, 1992), stimulates self-critical forms of thought, and increases awareness of one’s own judgment processes. Furthermore, accountability may cause people to seek more information regarding the risky decisions they are required to make (Lion & Meertenz, 2001).

Because we are less to blame for our inactions, we are probably less motivated to invest mental effort in processing passive risk choices. This lack of motivation, together with the difficulty in processing inactions, is expected to cause passive risk to capture less attention, entail a reduced sense of responsibility on the part of the actor, and consequently be perceived as less risky.

The Current Research

In three experiments, we presented participants with scenarios depicting people in a risky situation, which they either entered into actively or passively (by not doing something to exit the situation once they became aware of the risk). Participants were asked to evaluate the risk that the person in the scenario is taking. In Experiment 1, we aim to show that passive risks are evaluated as being less severe than active risks, whereas in Experiments 2 and 3, we suggest and examine perceived responsibility as the mechanism that accounts for this effect.

Experiment 1

Method

Participants

Forty-six students (23 females, M_age = 25) participated in the experiment in exchange for a 1-in-25 chance of winning 50 Israeli Shekels (~US $12). We selected this sample size to enable proper analysis. Participants were recruited from a university subject pool and performed the experiment online.

Procedure

We told participants they would be reading three pairs of scenarios (presented in random order) and would be asked to answer a question after reading each pair. Each pair of scenarios contained an active risk-taking scenario and a passive risk-taking scenario describing the same risk. The first scenario refers to parking a car in a “residents only” parking zone and risking it being towed away (active risk), as opposed to realizing the car is parked in a “residents only” parking zone only after having parked it there, and not moving it (passive risk). The second scenario refers to buying a house near a power plant, or not selling a house after realizing a power plant is being built in the area. The third scenario refers to joining a high-risk pension fund in a new place of employment, compared with not switching from a high-risk pension fund assigned as a default in a new place of employment (see Appendix A of the Supplemental Material for complete scenarios).

Participants received both versions of each scenario. After indicating they had finished reading both versions, they were asked the following question: “Who is taking the greater risk, the person in Scenario A or the person in Scenario B?” To eliminate any memory issues or confusion, both scenarios remained on the screen while participants answered the questions. Furthermore, all scenario pairs were presented in random order on the screen (right side/left side) to avoid any biases stemming from appearance order, reading order, or location on the screen.

Results and Discussion

We ran a χ² test for each of the three scenarios (one question for each scenario pair). As demonstrated in Table 1, participants indicated the active risk taker takes significantly more risk in all three scenarios.

Table 1.

Frequencies of Participants Who Defined Behavior in a Specific Scenario as Riskier.

Who is taking more risk?	Active risk taker (n observed)	Passive risk taker (n observed)	χ² value	p
Parked-car scenario	42	4	31.4	<.001
House-selling scenario	32	14	7.04	<.001
Pension-fund scenario	35	11	12.52	<.001

The results show, as hypothesized, that when evaluating two similar risk-taking incidences, participants perceived the risks taken actively as riskier than those taken passively. We found this increase in the perception of risk in three different contexts. One limitation of our research method is that asking participants to choose which of the two scenarios in the pair depicts greater risk does not give them an opportunity to answer that the risk involved in the two scenarios is identical. We addressed this limitation in Experiment 2.

Experiment 2

After Experiment 1 offered preliminary support for the notion that passive risks are underestimated compared with active risks, we designed Experiment 2 with two objectives in mind: addressing the procedural limitations of Experiment 1, and examining whether people are considered less responsible for damages caused by passive risk taking compared with damages caused by active risk taking.

To enable participants to indicate identical levels of risk perception for the two scenarios, in the current experiment, we asked participants to evaluate the risk in each scenario on a 7-point Likert-type scale (1 = not at all, 4 = moderately so, 7 = very much so), instead of choosing the riskier scenario. Asking people to rate the perceived riskiness of an activity or a situation on a psychometric scale is a common method for measuring risk perception (Benthin, Slovic, & Severson, 1993; Slovic, Peters, Grana, Berger, & Dieck, 2007).

Method

Participants

Forty-five students (32 females, M_age = 24.3) participated in the experiment in exchange for a 1-in-10 chance of winning 50 Israeli Shekels (~US $12). Sample size resembles Experiment 1. Participants were recruited from a university pool and performed the experiment online.

Procedure

We told participants they would be reading three pairs of scenarios (presented in random order) and would be asked to answer two questions for each scenario after reading each pair. This experiment was based on the scenarios described in Experiment 1 with the following changes: In addition to the risk-taking question (e.g., “To what extent is Josh taking a risk?”), we also asked participants to evaluate how responsible for damages they perceived the person in the scenario to be should the risk depicted materialize (e.g., “If the car is indeed towed away, to what degree is Josh responsible for that outcome?”). Participants answered all questions on a 7-point Likert-type scale (1 = low, 7 = high).

When participants indicated they had finished reading both scenarios, one of the scenarios was presented again, followed by the questions, which were presented one at a time. After answering the questions for the first scenario, the second scenario appeared on the screen, followed by the questions. We also measured the time (seconds) participants took to evaluate the risk in each scenario.¹

Results

Table 2 presents participants’ estimation of risk and responsibility levels regarding the different scenarios, as a function of the type of risk (active/passive).

Table 2.

Participants’ Estimation of the Risk and Responsibility in the Scenario, M (SD).

Scenario	Risk (n = 45)		Responsibility (n = 45)
Scenario	Active	Passive	Active	Passive
Parked car	6.09 (1.24)	5.58 (1.27)	6.82 (0.44)	6.27 (0.99)
House selling	6.02 (0.94)	5.64 (1.19)	5.69 (1.38)	4.31 (1.72)
Pension fund	5.64 (1.19)	5.02 (1.41)	6.29 (1.12)	4.91 (1.52)

We ran a repeated-measures ANOVA with risk perception as the dependent variable, with the scenario (1/2/3) and the type of risk (active/passive) as repeated factors. The analysis revealed a significantly higher estimation of risk for the active risk-taking scenario (M = 5.92, SD = 0.74) than of the passive risk-taking scenario (M = 5.42, SD = 0.83); F(1, 44) = 18.00, p < .001, η² = 0.29. The difference in the estimated risk for the different scenarios was significant, F(2, 88) = 3.90, p < .03, η² = 0.08. Importantly, the interaction between the type of risk and the scenario was not significant.

Mediation analysis

Next, we performed a mediation analysis. We proposed that active risks elicit a higher sense of responsibility than passive risks, which in turn increases risk perception. To test the significance of the overall indirect effect of the type of risk (active vs. passive) on risk estimation via the perception of personal responsibility, we conducted a bootstrapping analysis (with 5,000 iterations) that models mediation in a repeated-measures design, using the MEMORE 1.1 macro for SPSS (Montoya & Hayes, 2017).

This analysis revealed the indirect effect was significantly different from zero (95% confidence interval [CI] = [0.05, 0.61]). Passive risks thus appear to evoke a lower sense of responsibility than active risks, which reduces the estimation of risk. The mediation model and the path coefficients are illustrated in Figure 1.

Figure 1.

The effect of the type of risk on risk estimation mediated by perceived responsibility.

Discussion

As hypothesized, participants assessed passive risk taking as less risky, compared with active risk taking. In line with that finding, people in the scenarios were perceived as less responsible for damages brought on by passive risks compared with active risks. This perception of personal responsibility for damages mediates the difference in the assessment of passive and active risks. That is, passive risks evoke less sense of responsibility, which in turn leads to a reduced perception of risk compared with active risks.

Experiments 1 and 2 were both conducted in a within-subjects design, meaning people were exposed to both versions of risk taking (passive/active), before making their judgments. The comparison might have amplified the effects received, and passive risk situations might seem less risky only when explicitly compared with similar risks taken actively. Some decision-making biases have been known to “disappear” when choices were evaluated individually and not in a comparison context, as in ambiguity-avoidance bias (Fox & Tversky, 1995). However, Hsee, Loewenstein, Blount, and Bazerman (1999) found other biases are amplified when evaluated individually. Thus, examining whether this “passive is less risky” effect holds true in a noncomparative context as well is important.

Another limitation we aim to overcome in Experiment 3 is the differences in the perceived cost of reducing active compared with passive risk. If avoiding risk is costly, one may be especially motivated to perceive the situation as less risky. For example, in the “house near power plant” scenario used in the current and in the previous experiment, the cost of minimizing risk may have differed between the active and passive scenarios: looking for a different house to buy versus leaving your home. In the parked-car and pension-fund scenarios, the differences in the cost of reducing the two types of risks seem negligible. Although we did not find an interaction between the content of the scenario and the type of risk, in Experiment 3, we aimed to better control the cost of the two conditions.

Experiment 3

In Experiment 3, each participant was exposed to either two active or two passive scenarios to test whether passive risk is evaluated as less risky, even when comparisons are not readily available.

We designed new scenarios while ensuring the cost of risk avoidance in the active and passive scenarios was similar. The active and passive scenarios were identical except for the manner in which the risk was taken. In the current experiment, we also measured perceived personal responsibility using three items and incorporating derived and related concepts such as accountability, blame, and control (Schlenker, Britt, Pennington, Murphy, & Doherty, 1994), in contrast to the single item used in Experiment 2. Furthermore, we manipulated the question order so that in one condition, participants answered the questions regarding accountability, control, and blame, before being asked to assess the risk levels; in the other condition, the order was reversed. This manipulation enables us to examine whether active risk takers are perceived as more responsible or blameworthy for the results of their risk taking without being “primed” with a question regarding risk. Finally, the participants in Experiment 3 were Americans from the general population and not Israeli students as in Experiments 1 and 2. By doing so, we were able to examine whether our findings can be generalized to the general population, regarding age and education level.

Method

Participants

Two hundred eight responders (71 women; M age = 32.71, SD = 20.62) received US $0.25 for answering the questionnaire on Amazon Mechanical Turk (MTurk) administered in English. Most of the participants had at least 2 years of college, but education levels varied. Sample size for each of the four experimental conditions resembles Experiments 1 and 2.

Procedure

Participants were randomly assigned to one of the two risk conditions (active/passive). All participants read two scenarios and were asked to answer four questions regarding each scenario.

The first scenario described a man who had $1,500 and decided to buy high-risk stock (active scenario) or a man who owned $1,500 worth of high-risk stock and decided to hang on to the shares, hoping their value would rise (passive scenario). The second scenario described a 35-year-old engineer whose place of employment brought in a dermatologist to screen interested employees for skin cancer, as a courtesy. In the active condition, the company automatically set up appointments for all employees to be screened, but the man in the scenario canceled his appointment. The passive condition involved no automatically assigned appointments. The man in the scenario simply did not go in for the screening (see Appendix B of the Supplemental Material for scenarios).

After participants read each scenario, we asked them to answer one question regarding risk: To what extent is the person in the scenario taking a risk? In addition, we asked three questions regarding personal responsibility should the risk materialize: To what extent is the person described in the scenario accountable for the outcome? How much control did the person have over the outcome? To what extent is the person to blame? All four questions were answered on a scale of 1 to 7.

Half the participants answered the questions regarding personal responsibility before answering the risk question, and the other half answered in the reverse order. The order of the scenarios was also counterbalanced. Half the participants received the cancer scenario first, and the other half received the stock scenario first.

Results and Discussion

We ran a repeated-measures ANOVA with the perceived risk as the dependent variable, with the scenario (cancer/stock) as a repeated factor and the type of risk (active/passive) as a between-subjects factor (Table 3 presents the means and the standard deviations of the different conditions). We found a significant effect for the type of risk: Participants assessed active risk taking (M = 5.45, SD = 0.97) as significantly riskier than passive risk taking (M = 5.06, SD = 1.01); F(1, 206) = 8.04, p < .01, η² = 0.04. We also found a significant effect for the scenarios, F(1, 206) = 220.63, p < .01, η² = 0.52, with no significant interaction between the type of risk and the scenarios.

Table 3.

Participants’ Estimation of the Risk and Responsibility in the Scenario, M (SD).

Scenario	Risk		Responsibility
Scenario	Active (n = 102)	Passive (n = 106)	Active (n = 102)	Passive (n = 106)
Cancer screening	4.63 (1.51)	4.21 (1.58)	3.93 (1.45)	3.55 (1.6)
Stocks	6.26 (0.83)	5.90 (1.02)	5.4 (1.08)	5.2 (1.09)

We calculated a measure of personal responsibility based on the three questions separately for the cancer scenario (Cronbach’s α = .87) and for the stock scenario (Cronbach’s α = .6).

Mediation analysis

Next, we performed a mediation analysis to examine whether personal responsibility mediates the effect. To test the significance of the overall indirect effect of the type of risk (active vs. passive) on risk perception, via the estimation of personal responsibility, we used a bootstrapping analysis (with 5,000 iterations) that models mediation using the PROCESS macro for SPSS (Hayes, 2013). This analysis revealed the indirect effect was significantly different from zero (95% CI = [0.0057, 0.2466]). Consistent with the results of Experiment 2, passive risks compared with active risks evoke a lower sense of responsibility, which reduces the perception of risk. The mediation model and the path coefficients are illustrated in Figure 2. When predicting risk perception by the type of risk and personal responsibility, the effect of the type of risk remains significant (b = 0.29, p < .05), indicating partial mediation.

Figure 2.

The effect of the type of risk on risk estimation mediated by perceived responsibility.

The results of Experiment 3 show passive risks are underestimated even when evaluated separately, without any direct comparisons with active risks. As in Experiment 2, the results show once again that this difference in risk perception is partially due to a reduced sense of personal responsibility associated with passive risk taking.

General Discussion

The current research effort set out to demonstrate that people perceive passive risk as less risky than similar risk taken actively. The results obtained in Experiments 1 to 3 confirm our hypothesis and show people generally judge scenarios depicting passive risk taking as less risky compared with scenarios depicting similar yet active risk taking. One could argue the effect arose due to our use of the active term risk taking in all of our questions, which may have caused a “linguistic matching effect.” We addressed this issue in an experiment in which we asked participants to evaluate the riskiness of the behavior rather than the level of risk taking. We replicated the results regarding the underestimation of passive risks, thus ruling out this explanation (see Experiment 4 in Supplemental Material).

We found the underestimation of passive risks in a within-subjects design that allowed for a direct comparison of both versions of a scenario, as well as in a between-subjects design in which subjects were only exposed to one version of the risk, across a number of everyday scenarios. Furthermore, we found the effect with students as participants (Experiments 1 and 2), as well as with participants from the general population (Experiment 3). This convergence of evidence across various experimental conditions, subject pools, and hypothetical scenarios, controlling for variables such as order or cost, suggests the “passive is less risky” effect is fairly stable.

We suggest and demonstrate that a person who takes passive risks is perceived as less responsible for any damages brought on by their risky choice. This reduction in perceived personal responsibility mediates the differences in risk perception of passive compared with active risks. This reduced responsibility for the consequences of passive risks concurs with the way the justice system operates. People are usually accused of transgressions they committed, rather than actions they neglected to take. Consequently, we probably perceive passive risk as less risky than active risk, which may indeed be the case, at least from a legal point of view. But many passive risks have no legal implications, for example, health risks we do not reduce, such as screening for colon cancer or getting flu vaccinations. The findings of the current research suggest stressing people’s personal responsibility for complying with recommended preventive measures may raise risk perception and increase preventive action.

Passive risk taking may involve not only motivational shortcomings but also some emotional limitations. In a fairly recent article, Andrade and Van Boven (2010) demonstrated people’s difficulty in correctly predicting their affective reaction to events in which they decide not to pursue some course of action. They suggest this underestimation stems partly from people’s belief that events they chose not to experience have little influence on their affective experience. Accordingly, the underestimation of passive risks may stem from a difficulty in anticipating future regret or frustration that is likely to surface should risks materialize. This idea can potentially provide important additional insight to the phenomenon of passive risk taking and should be explored in future research.

The increased risk perception in active compared with passive risk situations may be amplified by beliefs regarding “tempting fate” or “magical thinking” (Risen & Gilovich, 2008; Tykocinski, 2008). Research has shown people have an intuition or belief that actions that tempt fate increase the likelihood of negative outcomes: “If I plan ahead to go on a picnic, it will increase the likelihood of rain that day.” This intuition is due in large part to people’s tendency to attend to negative prospects and to use accessibility as a cue when judging likelihood (Risen & Gilovich, 2008). If we think something bad might happen, we think about it quite a bit, which in turn causes us to believe it is very likely to happen. Actions are perceived to tempt fate more so than inactions (Risen & Gilovich, 2007), which may cause actions that seem to tempt fate to be perceived as riskier than inactions. Because we generally tend to think less about our inactions, this may affect our judged likelihood of their possible consequences.

The knowledge gained in this research on passive risk taking may enrich our understanding of inaction biases such as the omission bias (Ritov & Baron, 1992). People might prefer to suffer possible harm as a result of their inactions rather than actions not only because they fear their actions would cause greater regret (Ritov & Baron’s 1992 explanation) but also because they underestimate the severity of the risks brought on by inaction. People may prefer omissions and defaults, such as not getting vaccinated or not having a mammogram scan, due to reduced risk perception of their passive choices. Our findings may also extend the work of Spranca et al. (1991), which demonstrated that omissions are deemed less causal than commissions, to situations involving risk taking, rather than immoral behaviors. Passive risk taking may seem less causal than active risk taking.

To better understand passive risk taking, future research should explore the decision-making process that eventually results in such behavior. Unlike active risk taking, in which the decision to take risk is usually clear and even involves physical arousal (Studer & Clark, 2011), decisions regarding passive risks can be more elusive. Although some passive risks have a relatively clear deadline by which nonaction effectively means taking on the risk (e.g., not reading a contract before signing), many others are ongoing in nature and therefore allow for a window of deliberation or avoidance. This ongoing nature is especially true for major health risks and long-term financial issues but can also occur in day-to-day situations such as not backing up computer files. This mode of deliberation (“I should look into installing a burglar alarm”) may not feel like risk taking, because we have not made any decisions yet, but it is in fact passive risk taking, because no action has been taken to minimize existing risk. To make matters even more complicated, the time that passes while this issue is being “deliberated on” and no decision has been made may also serve as stochastic information regarding the probability of encountering the hazard. The passage of time with no materialization of risk may give a false indication of safety or immunity (“My house hasn’t been broken into—this must be a safe neighborhood”).

Ferrari, Johnson, and McCown’s (1995) work on personal tendency for decisional procrastination (a maladaptive pattern of postponing decisions when faced with conflicts and choices) may be useful in understanding which individuals are more susceptible to continuous deliberation and therefore more likely to take passive risks. Note that decisional procrastination and task-avoidant procrastination are separate tendencies that correlate with different personality factors (Milgram & Tenne, 2000). Passive risk taking has already been linked to procrastination (Keinan & Bereby-Meyer, 2012), so future research should focus on whether it is the decision making or the task avoidance that contributes most to passive risk taking.

In conclusion, some degree of passive risk taking is expected in life. Nonetheless, passive risk taking in situations involving real danger of grave results, or simple actions that can minimize existing risks, is definitely maladaptive. Further research exploring personal and situational factors that may foster or reduce passive risk taking will help elucidate this decision-making phenomenon.

Footnotes

Authors’ Note

This study is part of the first author’s doctoral dissertation, which was done under the supervision of the second author.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

The online supplemental material is available with the manuscript on the PSPB website.

Notes

References

Alloy

L. B.

Tabachnik

(1984). Assessment of co-variation by humans and animals: The joint influence of prior expectations and current situational information. Psychological Review, 91, 112-149.

Andrade

E. B.

Van Boven

(2010). Feelings not forgone: Underestimating affective reactions to what does not happen. Psychological Science, 21, 706-711.

Andrew

Cronin

(1997). Two measures of sensation seeking as predictors of alcohol use among high school males. Personality and Individual Differences, 22, 393-401.

Baron

Ritov

(2004). Omission bias, individual differences, and normality. Organizational Behavior and Human Decision Processes, 94, 74-85.

Bator

R. J.

Cialdini

R. B.

(2006). The nature of consistency motivation: Consistency, aconsistency, and anticonsistency in a dissonance paradigm. Social Influence, 1, 208-233.

Benthin

Slovic

Severson

(1993). A psychometric study of adolescent risk perception. Journal of Adolescence, 16, 153-168.

Blaise

A. R.

Weber

E. U.

(2006). A Domain-Specific Risk-Taking (DOSPERT) Scale for adult populations. Judgment and Decision Making, 1, 33-47.

Branscombe

N. R.

Owen

Garstka

T. A.

Coleman

(1996). Rape and accident counterfactuals: Who might have done otherwise and would it have changed the outcome? Journal of Applied Social Psychology, 26, 1042-1067.

Carlin

B. I.

Robinson

D. J.

(2009). Fear and loathing in Las Vegas: Evidence from blackjack tables. Judgment and Decision Making, 4, 385-396.

10.

Catellani

Milesi

(2001). Counterfactuals and roles: Mock victims’ and perpetrators’ accounts of judicial cases. European Journal of Social Psychology, 31, 247-264.

11.

Ferrari

J. R.

Johnson

J. J.

McCown

W. G.

(1995). Procrastination and task avoidance: Theory, research, and treatment. New York, NY: Plenum.

12.

Fox

C. R.

Tversky

(1995). Ambiguity aversion and comparative ignorance. The Quarterly Journal of Economics, 110, 585-604.

13.

Gilbert

(2006). Stumbling on happiness. New York, NY: Alfred A. Knopf.

14.

Gleicher

Kost

K. A.

Baker

S. M.

Strathem

A. J.

Richman

S. A.

Sherman

S. J.

(1990). The role of counterfactual thinking in judgment and affect. Personality and Social Psychology Bulletin, 16, 284-295.

15.

Hayashi

(2015). Omission bias and perceived intention in children and adults. British Journal of Developmental Psychology, 33, 237-251.

16.

Hayes

A. F.

(2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York, NY: Guilford Press.

17.

Heider

(1958). The psychology of interpersonal relations. New York, NY: Wiley.

18.

Hsee

C. K.

Loewenstein

G. F.

Blount

Bazerman

M. H.

(1999). Preference reversals between joint and separate evaluations of options: A review and theoretical analysis. Psychological Bulletin, 125, 576-590.

19.

Jost

J. T.

Chaikalis-Petritsis

Abrams

Sidanius

van der Toorn

Bratt

(2012). Why men (and women) do and don’t rebel: Effects of system justification on willingness to protest. Personality and Social Psychology Bulletin, 38, 197-208.

20.

Jost

J. T.

Liviatan

van der Toorn

Ledgerwood

Mandisodza

Nosek

B. A.

(2010). System justification: How do we know it’s motivated? In Bobocel

R. C.

Kay

A. C.

Zanna

Olson

(Eds.), The psychology of justice and legitimacy: The Ontario Symposium (Vol. 11, pp. 173-203). Hillsdale, NJ: Lawrence Erlbaum.

21.

Kahneman

Knetsch

J. L.

Thaler

R. H.

(1991). Anomalies: The endowment effect, loss aversion, and status quo bias. The Journal of Economic Perspective, 5, 193-206.

22.

Kahneman

Miller

D. T.

(1986). Norm theory: Comparing reality to its alternatives. Psychological Review, 93, 136-153.

23.

Kay

A. C.

Gaucher

Peach

J. M.

Laurin

Friesen

Zanna

M. P.

Spencer

S. J.

(2009). Inequality, discrimination, and the power of the status quo: Direct evidence for a motivation to see the way things are as the way they should be. Journal of Personality and Social Psychology, 97, 421-434.

24.

Keinan

Bereby-Meyer

(2012). “Leaving it to chance”—Passive risk taking in everyday life. Judgment and Decision Making, 7, 705-715.

25.

Landman

(1987). Regret and elation following action and inaction: Affective responses to positive versus negative outcomes. Personality and Social Psychology Bulletin, 13, 524-536.

26.

Lerner

J. S.

Tetlock

P. E.

(1999). Accounting for the effects accountability. Psychological Bulletin, 125, 255-275.

27.

Lion

Meertenz

R. M.

(2001). Seeking information about a risky medicine: Effects of risk-taking tendency and accountability. Journal of Applied Social Psychology, 31, 778-795.

28.

Milgram

Tenne

(2000). Personality correlates of decisional and task avoidant procrastination. European Journal of Personality, 14, 141-156.

29.

Montoya

A. K.

Hayes

A. F.

(2017). Two-condition within-participant statistical mediation analysis: A path-analytic framework. Psychological Methods, 22(1), 6-27.

30.

Nario-Redmond

M. R.

Branscombe

N. R.

(1996). It could have been better or it might have been worse: Implications for blame assignment in rape cases. Basic and Applied Social Psychology, 18, 347-366.

31.

Newman

J. P.

Wolff

W. T.

Hearst

(1980). The feature-positive effect in adult human subjects. Journal of Experimental Psychology: Human Learning and Memory, 6, 630-650.

32.

Risen

J. L.

Gilovich

(2007). Another look at why people are reluctant to exchange lottery tickets. Journal of Personality and Social Psychology, 93, 12-22.

33.

Risen

J. L.

Gilovich

(2008). Why are people reluctant to tempt fate. Journal of Personality and Social Psychology, 95, 93-307.

34.

Ritov

Baron

(1990). Reluctance to vaccinate: Omission bias and ambiguity. Journal of Behavioral Decision Making, 3, 263-277.

35.

Ritov

Baron

(1992). Status-quo and omission bias. Journal of Risk and Uncertainty, 5, 49-61.

36.

Ritov

Baron

(1999). Protective values and omission bias. Organizational Behavior and Human Decision Processes, 79, 79-94.

37.

Samuelson

Zeckhauser

(1988). Status quo bias in decision making. Journal of Risk and Uncertainty, 1, 7-59.

38.

Schlenker

B. R.

Britt

T. W.

Pennington

Murphy

Doherty

(1994). The triangle model of responsibility. Psychological Review, 101, 632-652.

39.

Slovic

(1987). Perception of risk. Science, 236, 280-285.

40.

Slovic

Peters

Grana

Berger

Dieck

G. S.

(2007). Risk perception of prescription drugs: Results of a national survey. Theraputic Innovation and Regulatory Science, 41(1), 81-100.

41.

Spranca

Minsk

Baron

(1991). Omission and commission in judgment and choice. Journal of Experimental Social Psychology, 27, 76-105.

42.

Studer

Clark

(2011). Place your bets: Psychophysiological correlates of decision-making under risk. Cognitive, Affective, & Behavioral Neuroscience, 11, 144-158.

43.

Tetlock

P. E.

(1992). The impact of accountability on judgment and choice: Towards a social contingency model. Advances in Experimental Social Psychology, 25, 331-376.

44.

Tykocinski

(2008). Insurance, risk and magical thinking. Personality and Social Psychology Bulletin, 34, 1346-1356.

45.

Yechiam

Ert

(2011). Risk attitude in decision making: In search of trait-like constructs. Topics in Cognitive Science, 3, 166-186.

46.

Mobbs

Seymour

Calder

A. J.

(2010). Insula and striatum mediate the default bias. Journal of Neuroscience, 30, 14702-14707.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.27 MB