Once initiated by the information about a weather or climate event, the threat and adjustment/coping appraisal processes will begin. These parallel processes and the psychological biases that can affect them largely occur automatically, outside of awareness, and without much contribution of rational, and deliberative processing (Kihlstrom 1987). A variety of cognitive, social, and decision-making biases can influence the cognitive mediating processes of the PMT model (and similar components in any health behaviour model, for that matter, Nicholls 1999). Although the operation of such characteristics and biases precludes a true representation of the objective variables, the threat and adaptation appraisals incorporate these biases and will reflect them in people's intended or actual behaviours (Floyd et al. 2000). That is, people act on the basis of their biases and the PMT model will reflect this.
The presence of intrinsic and extrinsic rewards for failing to prepare, muddling through, or performing risky behaviours increases the likelihood of a maladap-tive outcome. People who are curious about the nature of rare or extreme weather events may experience those events as intrinsically rewarding (Burt 2004). Unusual weather also may provide opportunities for testing oneself regarding the use of skills or abilities in professional or recreational roles (Floyd et al. 2000). Extrinsic rewards may take the form of increased compensation, professional advancement, and/or greater respect for an employee who reports for work during dangerous weather.
Evaluation of weather as dangerous and perceiving one's vulnerabilities to the event decreases the probability of a maladaptive response. Prior negative experiences with weather events that resulted in injury, death, or property losses and a corresponding negative emotionality could lead to greater appraisals of the dangers posed by extreme weather; it also could increase people's sense of vulnerabilities (Weber 2006). In a broad review of the literature, Weinstein (1989) observed that personal experiences with hazards lead people to view hazards as more frequent and themselves as more vulnerable, to think more frequently of the hazards and with greater clarity, and to take precautions that are appropriate given the hazards people faced in the past. In this regard, Stewart (2007) observed that people whose families experienced weather-related property damages reported significantly greater overall weather salience and greater effects of weather upon their day-to-day moods. More specifically, Weinstein et al. (2000) observed that survivors from three communities struck by tornadoes took more precautions 14 months afterward to the extent people were preoccupied with tornadoes. Mulilis et al. (2003) reported similar results following a tornado outbreak in western Pennsylvania. People who are psychologically traumatized by extreme weather also may maintain a heightened state of arousal, emotional numbing, and re-experiencing symptoms that may combine to overestimate the severity of subsequent weather and their vulnerabilities to it (Norris et al. 1999).
Perceptions of rewards and vulnerabilities are seldom veridical representations of the actual weather or climate scenarios. Human cognition and decision-making processes are subject to a variety of social, cognitive, and motivational biases that are reflected in the choices people make. Such biases affect the adaptation decisions people make in the face of weather and climate events. A discussion of some of the biases that have appeared in the weather and climate literature follows below. This listing is by no means exhaustive of all the psychological biases that exist, however it provides an indication of the kinds of biases that can skew threat, adjustment, and coping appraisals.
Optimistic bias involves discounting or not attending to negative characteristics of a situation and instead placing greater emphasis upon positive, but unlikely outcomes. This bias also leads one to believe that he or she is less likely to experience negative events than are other people (Weinstein 1980; Weinstein and Klein 1996). Such a bias would serve to decrease the appraisal of impending conditions as severe or dangerous. In describing optimism about natural hazards that borders on denial, Eric Holdeman, director of emergency management for Seattle's King County, outlined four stages: "One is, it won't happen. Two is, if it does happen, it won't happen to me. Three: if it does happen to me, it won't be that bad. And four: if it happens to me and it's bad, there's nothing I can do to stop it anyway" (Ripley 2006, p. 56). Other researchers observed that people would not evacuate ahead of a hurricane because they believed that their homes were built strong enough to withstand the storm (Blendon et al. 2006) or that they could simply "ride it out" (Smith and McCarty 2007).
Second, and by way of gathering information from others or from the environment directly, people may engage in confirmatory bias whereby they only attend to or value information that is in accord with a belief that they want to support. For example, someone who believes that global warming does not exist may attempt to confirm this position by citing a colder than normal winter as evidence. For shorter-fused events, people may play one weather information source against another to confirm the response that they would like to make.
Third, anchoring effects of one's prior experiences with various weather events may serve as an erroneous standard for comparison of weather or climate conditions that are forecasted to occur (Tversky and Kahneman 1974). For example, a person previously may have experienced the outer bands of wind and rain from a hurricane and erroneously concluded that hurricanes generally are not that bad. Such anchoring beliefs may lead the people to discount the severity of subsequent storms so that they do not make preparations or evacuate (Dash and Gladwin 2005; Glantz 2005). A wide variety of weather events, to the extent that they are remembered, may function as evaluative anchors.
A forth phenomena, known as hindsight bias, also pertains to past weather events. This bias essentially involves the erroneous belief that previously-experienced events were more predictable than they were in actuality (Blank et al. 2007). Like the anchoring effect, if the hindsight bias is played forward, people may assume that weather events can be predicted with greater precision and specificity than is the case. This bias also may feed an all's well that ends well mentality. Here, people may take no adaptive efforts ahead of an event and experience, fortuitously, no negative consequences. This could further reinforce making no preparations or taking adaptive measures ahead of subsequent events (Glantz 2005).
A fifth bias concerns what is done with information that is obtained by observing and comparing with other people. The actor-observer bias, a special case of the fundamental attribution error, involves overweighting the role of dispositional variables in evaluating the behaviour of others (i.e., actors), while overweighting the role of situational variables in making attributions about oneself (i.e., the observer's behaviour). For example, an observer may witness person who has become stranded while attempting to drive across a flooded road. According to this bias, the observer may attribute that circumstance to the driver being unskilled, unknowledgeable, fool-hearty, and so forth, without considering the driver's situation that led to the behaviour. The danger of the actor-observer bias is that the observer may think him or herself more skilled or knowledgeable than the driver and perhaps more likely to attempt risky maneuvers, only to attribute later failures or losses to the constraints of the situation.
Sixth, social comparison can also induce biases in assessing the nature of weather or climate risks. Although objective and reliable information about how to prepare or evacuate ahead of a weather event may have been given, an individual may gauge his or her own levels of threat and action by engaging in downward and upward comparisons with other people. Although this may be a useful heuristic to a point, if others are not themselves responding or taking the appropriate precautions then one ultimately may be under-prepared.
According to PMT, higher levels of response efficacy and self-efficacy increase the likelihood of an adaptive response whereas higher response costs may preclude performing an adaptive behaviour. Response efficacy in Fig. 10.1 pertains to a more generalized knowledge of what to do or not do that may be adaptive in responding to a weather or climate event (Kroemker and Mosler 2002). For example, response efficacy would be evident in knowing that the safest place to be during a tornado is in either a basement or storm cellar (i.e., the lowest, most protected area in a building). Similarly, knowing that one should wear light-colored clothing and adequately hydrate while also avoiding exertion in the hottest portion of the day would evidence response efficacy. Response efficacy is concerned with knowing that or knowing what.
Self-efficacy pertains to the individual's appraisal that he or she could actually perform the adaptive response; it is concerned with knowing how. Self-efficacy could emerge from prior experience in taking adaptive measures or from knowledge of how to assemble components of learned responses into a novel adaptive response. Others' adaptive responses may cue similar responses in an observer. This person may then evaluate his or her responses, socially compare with others, and then alter or self-correct the response (Bandura 1986). Self-efficacy perceptions may increase with successive repetitions and refinements of the response. Thus, self-efficacy for weather and climate adaptation depends upon a knowledge base that informs repeated practice.
People may learn about the appropriate adaptive responses to various weather and climate scenarios (response efficacy) during their formal education as children (i.e., Kindergarten through 12th Grade in the United States), among other sources.
Because systematic educational coverage of adaptive behaviours for natural disasters has been lacking, the American National Red Cross developed the Masters of Disaster (MoD) curriculum for grades K-8 (American National Red Cross 2000). English and Spanish language versions of the curricula exist in DVD form to facilitate adoption. In addition to general preparedness and prevention, the curriculum also includes specific education on how to prepare and adapt to: earthquakes, wildfires, tornadoes, hurricanes, floods, fire, and lightning. MoD is valuable in providing knowledge that underlies response efficacy and can provide practice to enhance self-efficacy.
Weather services and other governmental agencies periodically conduct educational outreach campaigns locally that are designed to educate and remind residents in affected areas about extreme weather events that may require their attention. Within the United States, the National Weather Service had developed a range of online resource materials that are available for the general population, for educators, and children. To the extent that these materials are used to build response efficacy and self-efficacy, people will be in a better position to adapt.
The likelihood that an adaptive response is performed will be decreased to the extent that a person perceives increasing costs, which are broadly conceived here in terms of time, money, emotional effort, convenience, and/or interpersonal resources, among other variables. With respect to secondary adaptation, a driver may believe that the time required to take an alternate route (adaptive response) is too great compared to the estimated risk of driving through a flooded roadway (risky response). People living near coastlines or rivers may not have the financial resources to purchase flood insurance or, in the case of hurricanes, to purchase storm shutters by way of primary adaptation. Response costs may also take the form of financial opportunities that are lost when one evacuates, concerns about crowded roadways, and concerns about possessions being damaged or stolen (Blendon et al. 2006; Smith and McCarty 2007). Regarding attachment costs, younger family members may not evacuate ahead of extreme weather because they want to remain and provide care for elderly or infirm family who cannot evacuate or because they have concerns about the care and safety of their pets (Blendon et al. 2006; Dow and Cutter 2000; Smith and McCarty 2007).
The general adaptational load that a person is experiencing at the time that a weather or climate-related adaptation is required also relates to response cost. That is, the range of events in a person's life that require adaptation, adjustment, and coping constitute an emotional overhead that may limit the resources available to make an adaptive response. Evidence for the existence of a finite pool of worry and other emotional concerns comes from clinical and personality psychology where the accumulation of stressors can lead to problems in making satisfactory emotional adaptations (Kanner et al. 1981; Lazarus 1993; Linville and Fischer 1991). Similarly, Hansenet al. (2004) observed that a finite pool of worry for events such as climate, politics and so forth existed among farmers. This means that people may only have a limited amount of adaptive capacity for the events that they face. Further, the level of adaptive capacity that people possess at any given time may help to explain, in part, the variability that exists in their adaptive behaviour for various atmospheric events (Kroemker and Mosler 2002).
Like the other decision-making components discussed thus far, perceptions of response costs are susceptible to biases and distortions. Some people may exaggerate costs or awfulize about the time or monetary opportunities lost by pursuing adaptive responses. Biasing response costs upward while also optimistically biasing weather severity and one's vulnerability downward may produce a risky response. Similarly, people may remember prior near-misses of storms for which they evacuated and then inflate the costs of responding adaptively to subsequent storms (Blendon et al. 2006; Dow and Cutter 1998; Glantz 2005).
Threat appraisals, adjustment and coping appraisals, and the experienced level of fear come together in the protection motivation node of the PMT model (see Fig. 10.1). The model predicts that an adaptive response will follow to the extent that fear of one's vulnerability to severe events and the appraisal for making an adaptive response outweigh the threat appraisals associated with maladaptive responses (Rogers and Prentice-Dunn 1997). Fear, and presumably other similar affective states (e.g., worry), provides the motivation for taking protective action. In behavioural terms, fear functions as an aversive state; responses that lead to its decrease or disappearance are negatively reinforced by the abatement of fear. This reduction in fear following an adaptive behaviour makes performing that behaviour more likely in the future.
The creators of PMT were prescient in incorporating both cognitive and emotional processes in their model (Rogers 1975; Rogers and Prentice-Dunn 1997). In some respects the PMT model anticipated more recent scholarship in the field of decision-making and risk-taking under conditions of uncertainty (Loewenstein et al. 2001; Slovic et al. 2004; Slovic and Peters 2006). This research has challenged the existing consequentialist decision-making models (e.g. Kahneman and Tversky 2000) that viewed emotional processes as deriving from cognitive evaluations of anticipated outcomes and subjective probabilities or from behavioural outcomes following a decision. The risk-as-feelings perspective (see Fig. 10.2) recognizes that feelings stemming from the benefit (or harm) from taking the risk previously exists alongside cognitively-based evaluations of factual, descriptive, or abstract information about the risk (Kaplan 1991; Loewenstein et al. 2001; Slovic et al. 2004; Weber 2006). In other words, both rational, deliberate cognitive evaluations and intuitive, rapid, gut-level emotions contribute to decisions. Research using the risk-as-feelings perspective finds, contrary to the predictions of rational choice theories, that people tend to underweight the likelihood of
rare events occurring and overweight the likelihood of more common events (Hertwig et al. 2004; Weber et al. 2004). The reason for this stems from taking a small number of risks and not encountering the rare and negative outcome (e.g., experiences of remaining outside during a thunderstorm and not being injured by lightning) such that emotionally-based experiential estimates of the risk are lower (Hertwig et al. 2004).
The PMT model explicitly specifies fear as the emotion that stems from perceptions of weather severity and vulnerability and that serves to increase motivation for an adaptive, protective response. The more general risk-as-feelings model suggests that other emotions in addition to fear could influence decision-making. For instance, using a five-category emotional classification, it is possible that curiosities and interests about weather and climate may create the emotions of happiness or desire that stem from the intrinsic rewards node of the PMT (Fig. 10.1). Similarly, emotions of anger or disgust concerning response costs (e.g., anger at having to evacuate or disgust with conditions of the shelter) may contribute to risk-taking or other responses that have maladaptive outcomes. These possibilities suggest that the PMT model could be expanded productively to include the more general risk-as-feelings perspective. Thus, cognitive mediating processes in the model may more appropriately become cognitive-emotional mediating processes.
Response preferences (for either risky/maladaptive or adaptive responses) are likely constructed dynamically and reflect particular situational values of the variables that comprise the PMT (Slovic 1995). Risky or adaptive choices are also domain specific (Blais and Weber 2006; Weber et al. 2002). That is, people who report benefits in taking social risks may not experience benefits in pursuing ethical or financial risks. Weather-related risk-taking also comprises its own specific domain that is related to health and recreational risk-taking but not to other forms of risk such as social, financial or ethical (Stewart and Weber 2007). By contrast, response preferences are likely not to be as affected by longstanding personality traits (e.g., a risky personality type, a generally self-efficacious personality, Stern 1992). Although personality variables may have some slight effects on a PMT node such intrinsic or extrinsic rewards, their contributions are likely less influential than those pertaining directly to the situation in which the risk decision is being made.
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