Abstract
Background:
Occupational safety and health professionals facilitate safer workplaces through the development and implementation of interventions. Empirically validated theories can enhance the likelihood that an intervention will be successful in achieving the desired outcome; however, occupational safety interventions are often devoid of theory or utilize frameworks that fail to take a comprehensive approach to conceptualizing occupational safety processes.
Focus of the Article:
The current paper seeks to address these gaps by proposing an interdisciplinary and integrated model of occupational safety (IIMOS).
Importance to the Social Marketing Field:
IIMOS takes an interdisciplinary approach, examining the combined influence of concepts from psychology, social marketing, and occupational safety on behavioral change. This model accounts for the influence that threat appraisal, coping appraisal, and customer service factors can have on safety behaviors’ initiation/adoption and maintenance.
Recommendations for Research and Practice:
IIMOS may inform the design, implementation, and evaluation of occupational safety and health programs. Although future empirical work must still test the model’s propositions, the model’s in-depth application of social marketing techniques is a novel addition to the field. This model can encourage practitioners to develop innovative products, build relationships with consumers, and design upstream efforts to support program adoption.
Introduction
Unintentional and preventable injuries are the third-leading cause of death in the United States (Centers for Disease Control and Prevention, 2017). In 2019, 5,333 unintentional fatal injuries were work related (Bureau of Labor Statistics, 2020). Fatalities can occur in any employment context but are most likely to happen in the construction, transportation, agriculture, business, and government sectors. The most common types of workplace injuries result from overexertion, contact with objects and equipment, transportation accidents, slips/trips/falls, and exposure to harmful substances (National Safety Council, 2020).
Given these staggering numbers, it is evident that occupational safety is essential to protecting the health of working populations. Occupational safety and health (OSH) is an interdisciplinary field that focuses on minimizing hazardous conditions, coaching employees in safe behaviors, and fostering safe environments in the workplace (American Public Health Association [APHA], 2020; World Health Organization, 2020). OSH professionals charged with these tasks are trained in a variety of disciplines, including industrial hygiene, toxicology, epidemiology, psychology, and education (APHA, 2020). Perhaps reflecting the siloed nature of this training, workplace safety interventions often reference theories from a single field in their efforts to encourage behavioral adoption. Commonly utilized theories include social exchange theory (Sinclair et al., 2013) from sociology, the theory of reasoned action (Tan Wilhelm et al., 2000) from psychology, and the social marketing planning model (Chapman et al., 2003) from marketing. Despite benefitting from the wisdom of a variety of unique disciplines, OSH has yet to establish a model of behavioral adoption and maintenance that integrates the insights gained from disparate fields. The proposed integrated and interdisciplinary model of occupational safety (IIMOS) draws from the field of psychology to explain the cognitive and affective constructs that influence the initial adoption of safety behavior while using insight from social marketing to better frame long-term program effectiveness.
The use of theory is commonly viewed as a best practice in intervention design (Bartholomew & Mullen, 2011). Moreover, meta-analytic efforts support this assessment, documenting the increased effectiveness of theoretically based interventions as opposed to those that are atheoretical. Despite such evidence, OSH interventions have been criticized for lacking theoretical support entirely (see, e.g. Anger et al., 2015), relying on theory from a single field (Sublet & Lum, 2008), or drawing on the expertise of natural scientists or engineers who may lack familiarity with constructs that accurately describe human behavior (see Ménard & Trant, 2020). When theory is employed in the OSH context, interventions are limited by their focus on short-term behavioral adoption (see, e.g. van Bavel et al., 2019).
IIMOS overcomes the aforementioned limitations by presenting a comprehensive, holistic, and true-to-life representation of the cognitive, affective, and programmatic factors that predict the initiation of safety behavior and behavioral maintenance. The current paper suggests that although initial behavioral uptake may be framed using insights from the psychology field, the overall success of an OSH program should be considered within a larger social marketing framework. Following a review of social marketing in the OSH context, model propositions are explicated, and recommendations for future research and practitioner use of IIMOS are provided.
Social Marketing and OSH
Drawing from seminal literature in the field, Storey et al. (2008) described social marketing efforts as those that use commercial marketing strategies to engage consumers in a voluntary exchange that ultimately fulfills an individual or societal good. The use of social marketing in OSH has been limited, with Sublet and Lum (2008) identifying only two studies that claimed to apply social marketing principles. Consistent with other health contexts (Almestahiri et al., 2017), common characteristics of a social marketing approach were not fully applied within the two programs evaluated. IIMOS suggests that OSH interventions will achieve increased success if they remain focused on three elements of the social marketing approach by (a) recognizing that the adoption of a safety behavior represents an exchange between employee and employer, (b) identifying competition that may impact employee adoption of the advocated behavior, and (c) establishing a marketing mix that addresses the product, place, price, and promotional elements (i.e., the 4 Ps) associated with the behavioral outcome in question (Almestahiri et al., 2017; Andreasen, 2002).
In line with Edgar et al. (2017), IIMOS identifies the core product of an OSH intervention as the relevant benefits that will be obtained via behavioral adoption. Although context specific, core OSH products could include corollary benefits such as keeping oneself or others safe or avoiding occupation-related disabilities that impede gainful employment (Cullen et al., 2008). These core products are supported by tangible products, including the physical goods (e.g., personal protective equipment [PPE] such as goggles and gloves) or services (e.g., training programs) (see Edgar et al., 2017) that one uses to obtain the core product. Acquisition of these products takes place via an exchange between employee and employer; employees commit time and effort in order to obtain the product in question, whereas employers provide relevant support (e.g., programs, funding for PPE) in order to obtain their own benefits from adoption (e.g., avoidance of financial penalties, higher productivity, reduced worker compensation premiums) (see Thackeray, 2010). This entire exchange takes place in a competitive environment wherein habitual behaviors (such as those used prior to the introduction of the desired safety behavior) and alternate messaging compete for employee attention and effort (Lavack et al., 2008). Thus, the most successful OSH interventions will be those that use elements of the marketing mix in order to reduce the costs of adoption, highlight product benefits as compared to the competition, and facilitate the exchange process.
IIMOS: Threat Appraisal
Any safety behavior likely originates from a threat or potential threat within one’s environment. Thus, IIMOS begins (see Figure 1) by drawing from the psychological literature to understand individuals’ risk perceptions or their beliefs about the potential danger posed by a hazard in their external environment (Brewer et al., 2007). Building on Roger’s (1975) protection motivation theory (PMT) and drawing from more recent literature on risk perception (Brewer et al., 2007), IIMOS defines threat appraisal as a combination of the perceived likelihood of experiencing a threat, the perceived severity of the threat, one’s perceived vulnerability to the threat, and the rewards associated with choosing a maladaptive response to the threat. Each component of threat appraisal is reviewed before delineating its overall function in IIMOS.
Proposed model.
Perceived likelihood refers to cognitive evaluations of the probability that one will experience harm following exposure to a hazard (Brewer et al., 2007) and is considered a foundational construct within PMT. Measures of this construct often include estimates of one’s personal risk of experiencing an outcome (e.g., “What is the likelihood that you will contract lung cancer by age 65?”; Sheeran et al., 2014, p. 14). As the perceived likelihood of encountering a hazard increases, concurrent increases in the intention to adopt and/or adoption of threat-averting behavior are expected. Robust meta-analytic findings (Floyd et al., 2000) support this relationship, demonstrating a moderate effect of perceived likelihood on intentions/behaviors (d+ = 0.41). 1
Perceived severity, or one’s belief about the adverse consequence of a hazard, has also been adopted from PMT (Rogers, 1975). In the original model, increases in perceived severity were expected to facilitate the intention to adopt a protective response (see Rogers, 1975). Later meta-analytic efforts supported these findings, with mean effect sizes between perceived severity and intentions/behavior in the small (r’s = 0.132 to 0.142; Witte & Allen, 2000) to moderate (d+ = 0.39; Floyd et al., 2000) range. More recent work (Sheeran et al., 2014) has demonstrated that perceived severity can, in fact, heighten the impact of risk perception (i.e., perceived likelihood) on behavioral adoption; the effect sizes of risk perception and behavioral adoption were larger when perceived severity was also increased (d+ = 0.36) compared to when it was not (d+ = 0.16). Thus, action is more likely when one both feels likely to experience a hazard and believes the consequences of that hazard to be severe.
In reviewing more recent conceptualizations of PMT, Norman et al. (2005) indicated that threat appraisal is relevant to the likelihood that one will respond maladaptively to a hazard (e.g., by continuing an unsafe workplace behavior). Specifically, one compares the rewards of a maladaptive behavior/response to one’s perceived likelihood of being harmed or experiencing an adverse event (e.g., property damage) and the estimated severity of its effects. If estimations of risk (i.e., severity combined with likelihood) exceed the rewards offered by the maladaptive behavior, one is more likely to adopt the advocated protective behavior. If, however, the rewards of the maladaptive behavior exceed the threat, continued engagement in the maladaptive behavior is likely (Norman et al., 2005). Consider, for example, Cullen and colleagues’ (2008) development of a safety campaign for coal miners. Commenting on miners’ beliefs, Cullen et al. (2008) noted, “The ability to keep themselves and fellow workers safe is important but is also balanced with the desire to work quickly and efficiently” (p. 14). Following the rationale of PMT, a safety campaign in this context would need to ensure the threat posed by a hazard (i.e., likelihood + severity) exceeded the reward of the maladaptive behavior (working quickly and efficiently but not safely).
Considering only the perceived likelihood, perceived severity, and perceived rewards of the maladaptive response is consistent with the threat appraisal framework presented in PMT. IIMOS deviates from PMT, however, by introducing perceived vulnerability as a final component of risk. Consistent with Brewer et al. (2007) and Windschitl (2003), IIMOS defines perceived vulnerability as an intuitive response to a hazard as compared to an objective assessment of the probability of experiencing harm (i.e., perceived likelihood). Thus, perceived vulnerability lends a simultaneous affective component to the assessment of a hazard in keeping with studies that have differentiated between cognitive (i.e., thought-based) and affective (i.e., feeling-based) components of attitude (see, e.g. Anker et al., 2010).
Supporting the addition of perceived vulnerability to IIMOS, Sheeran et al.’s (2014) meta-analysis found a positive relationship between anticipatory emotions (e.g., fear, worry, or anxiety about an outcome) and intentions (d+ = 0.31) as well as behavior (d+ = 0.21). Their work further demonstrated that the effects of risk perception (i.e., perceived likelihood) on behavior were magnified under conditions in which anticipatory emotions were also aroused. Acknowledging the importance of considering one’s affective evaluation of a hazard, Sheeran et al. (2014) concluded that “…behavior is most likely when affect and cognition point in the same direction” (p. 22).
Although some scholars have provided evidence that the components of a threat should be treated multiplicatively (cf. Sheeran et al., 2014), IIMOS employs additive combinations of variables consistent with recent iterations of PMT and the extended parallel process model (EPPM) (Norman et al., 2005; Popova, 2012). This decision is supported by research demonstrating the direct effects of each individual component of threat appraisal on intentions/behaviors (Floyd et al., 2000; Sheeran et al., 2014). Thus: Proposition 1: Threat appraisal is an additive combination of variables consisting of perceived likelihood, perceived vulnerability, and perceived severity less rewards associated with maladaptive behavior. Proposition 2: Threat appraisal is positively associated with the initiation of safety behavior.
IIMOS: Coping Appraisal
After a threat is perceived, IIMOS suggests that one evaluates response efficacy, self-efficacy, and the response costs associated with a behavior in determining whether to take action. In PMT, this assessment is referred to as one’s coping appraisal (Norman et al., 2005). Response efficacy represents one’s perception of the effectiveness of available solutions to reduce a hazard to health and/or safety (Rogers, 1983). Individuals who feel that available strategies will be effective in managing a hazard will be more likely to enact those solutions. Meta-analytic work has established response efficacy as a consistent and positive predictor of numerous outcomes (Floyd et al., 2000). Response efficacy has been identified as a predictor of intent to vaccinate (Krieger et al., 2011), sexual risk reduction (Casey et al., 2009), and adoption of cancer-preventive behaviors among petrochemical workers (Sakhvidi et al., 2015).
A related variable, self-efficacy, has been touted as a consistent and positive predictor of behavioral engagement across health contexts. Self-efficacy refers to an individual feeling capable of engaging in behaviors required to produce specific outcomes (Bandura, 1998). In the OSH context, self-efficacy has been found to be associated with behaviors such as adolescents’ intentions to perform job-related safety skills (Guerin et al., 2018) and registered nurses’ safe handling of hazardous drugs (Callahan et al., 2016). Floyd et al.’s (2000) meta-analysis of PMT constructs identified self-efficacy as having the largest effect on intention/behavior (d+ = 0.88).
In PMT, the response cost associated with the advocated behavior comprises the third element of coping appraisal (Norman et al., 2005). Response costs may take multiple forms (e.g., time, effort, financial cost, psychological cost) and represent a key element in the exchange process. Employees must “pay” some cost in order to obtain the package of benefits promised by the core product. When costs are reduced, behavioral initiation is more likely.
In the context of HIV/AIDS prevention, Abraham et al. (1994) suggested that it was difficult to differentiate between the rewards offered by a maladaptive behavior and the costs associated with the adoption of a protective behavior. For example, loss of pleasure resulting from condom use (i.e., a response cost associated with behavioral adoption) may not be easily distinguished from enhanced pleasure resulting from unprotected sex (i.e., an anticipated reward of continuing to engage in a maladaptive behavior; see Abraham et al., 1994).
Despite Abraham et al.’s sentiments (1994), the IIMOS maintains response cost as a unique component of coping appraisal. Support for this decision is two-fold. First, Floyd and colleagues’ (2000) meta-analytic work documented a relationship between reduced response costs and behavioral adoption. Second, given IIMOS’ focus on social marketing, the model maintains that response costs are associated with the price of the advocated product; in contrast, rewards of a maladaptive behavior represent the features of “competitors,” which must be addressed by campaign planners. Proposition 3: Coping appraisal is an additive combination of variables consisting of response efficacy and self-efficacy less response costs associated with the adaptive behavior.
Although the direct relationships between specific coping appraisal variables and behavior have been noted (see Floyd et al., 2000), IIMOS identifies coping appraisal as a moderator of the relationship between threat appraisal and initiation of safety behavior. This positioning is consistent with Sheeran and colleagues’ (2014) work. Sheeran et al. (2014) found that the relationship between risk and intention to perform a behavior was larger (d = 0.98) when response and self-efficacy had also been successfully manipulated as compared to studies manipulating only response efficacy (d = 0.38) or addressing neither response factor (d = 0.23). They concluded, “Interventions that simultaneously heightened all three variables [risk perception, response efficacy, self-efficacy] engendered the largest changes in subsequent intentions and behaviors” (Sheeran et al., 2014, p. 22; brackets added). Proposition 4: Coping appraisal moderates the relationship between threat appraisal and initiation of safety behavior; Larger effects characterizing the threat appraisal-behavioral initiation relationship will be observed when coping appraisal is increased.
IIMOS: Service Factors
Under IIMOS, threat and coping appraisals are associated with the initiation of safety behavior. Consistent with the transtheoretical model (Prochaska et al., 2008), the authors suggest that the initiation of safety behavior involves the adoption of a behavior for less than 6 months’ time. To better understand long-term behavioral maintenance (i.e., behavior enacted for 6+ months) and the development of a favorable safety climate at the worksite, IIMOS draws further insight from the field of marketing. Recognizing that participants are consumers, IIMOS suggests that the evaluation of service factors (i.e., perceived value and customer satisfaction) may impact safety performance in the long term.
Safety interventions and related programs often focus on the delivery of information (e.g., health and risk assessments; Anger et al., 2015) and resources (e.g., increased availability and selection of PPE; Rasmussen et al., 2006). Although these interventions provide value, some program planners experience difficulty striking a balance between improved safety outcomes and positive experiences with the delivery of the intervention. Perhaps exemplified by the “safety cop” strategy that some OSH professionals adopt to administer programs (Elston, 2011; Rasmussen et al., 2006), OSH programs can be both approached and perceived as paternalistic or punitive. This approach runs entirely contrary to the voluntary adoption of behaviors advocated by a social marketing strategy (Storey et al., 2008). IIMOS suggests instead that employees should be viewed as consumers who voluntarily choose to adopt a safety behavior. Recognizing that customer satisfaction and perceived value have been identified as driving (re)purchase intention in the commercial marketing literature (Oh, 1999), IIMOS indicates that long-term safety performance is likely only when employees voluntarily adopt a product and favorably evaluate their initial experiences with that product.
Customer satisfaction is a highly studied marketing concept that emerged from work on expectancy disconfirmation theory (Oliver, 1977, 1980) in the retail and service industries. Drawing on work from Oliver (2010), Otto et al. (2020) defined customer satisfaction as “the post-consumption consumer judgment of whether the good or service provided a pleasurable level of overall usage-related fulfillment” (p. 544). When operationalized, this construct typically assesses whether individuals’ use of a service or product was worse or better than originally anticipated (Oh, 1999). Applied within IIMOS, customer satisfaction would, therefore, relate to whether the initiation of a safety behavior resulted in the consumer obtaining the package of initially promoted product benefits in a way that met or exceeded expectations.
Perceived value is a cost-benefit analysis of a product or service that includes “the consumer’s perception of the benefits minus the costs of maintaining an ongoing relationship with a service provider or product” (Vieira, 2013, p. 111). Notably, Vieira’s definition highlights the notion of an “ongoing relationship” between consumer and provider. Applied in this context, IIMOS suggests that consumers evaluate the costs and benefits incurred from the OSH product during their first 6 months of use. Assessment of these costs and benefits is consistent with extant knowledge on social products and preventive innovations. For example, Wood (2008) recognized that some social products have long-term costs, such as a “change in lifestyle” (p. 80); thus, costs may reflect not only those associated with initial product adoption but also those required to maintain its use. On a related note, Rogers (2002) commented on the difficulty of diffusing preventive innovations, indicating that such innovations are hindered by the fact that the anticipated benefits of adoption may not occur until years in the future (if at all). Assessing the perceived value of an OSH program may pose a similar challenge in that consumers are choosing to change their long-term work lifestyle in anticipation of distant benefits. Proposition 5: Service factors represent the additive combination of perceived value and customer satisfaction.
IIMOS: Workplace Safety Performance
As noted in Figure 1, IIMOS identifies behavioral maintenance as a function of the favorable evaluation of service factors. Multiple scholars have highlighted the need to understand the long-term effects of safety programs, such as program adoption (McSween & Matthews, 2001) or long-term knowledge retention and growth in program participants (Ménard & Trent, 2020). By distinguishing between behavioral initiation and maintenance, IIMOS provides a framework in which to assess these relationships.
Drawing from the transtheoretical model (Prochaska et al., 2008), IIMOS defines behavioral maintenance as the consistent continuation of a behavior for 6+ months. Rothman (2000) drew attention to the need for scholars to clearly differentiate between the psychological processes that underlie behavioral initiation and behavioral maintenance. Highlighting the relevance of customer satisfaction to maintenance, Rothman (2000) noted, “To the extent that people’s experiences meet or exceed their expectations, they will be satisfied with the behavior and motivated to maintain it” (p. 66). Similarly, Rothman (2000) cited a series of studies finding that higher long-term costs were reported among those who fail to maintain a behavior, whereas and while greater increased perceived benefits were reported among those who do maintain, thus hinting at the relevance of perceived value to behavioral maintenance.
In commercial contexts, both perceived value (Vieira, 2013) and customer satisfaction (Symanski & Henard, 2001) have also been linked to (re)purchase intentions. Consistent with Symanski and Henard’s (2001) work, as well as studies demonstrating that satisfaction with healthcare providers and experiences has been positively associated with long-term outcomes including adherence to health recommendations (Dang et al., 2013) and continuance of service utilization (Kitapci et al., 2014), IIMOS points to perceived value and customer satisfaction as factors driving behavioral maintenance. Proposition 6: Service factors mediate the relationship between initiation of safety behavior and behavioral maintenance. Proposition 7: Increases in behavioral maintenance are associated with more positive assessments of safety climate.
Discussion and Conclusion
IIMOS meets the previously identified need for increased use of theory in the OHS field (Christian et al., 2009) and differentiation between factors that predict behavioral initiation and maintenance (Rothman, 2000). By utilizing social marketing as a framework to explain the adoption of safety behaviors, the model also highlights relevant steps that may be taken by practitioners to improve safety climate. In discussing the model’s contributions, the current paper outlines the next steps that may be taken by researchers to examine model effectiveness, followed by a review of practical advice for using the model’s propositions in an applied context.
Model Testing
Moving forward, scholars should test the model propositions presented here. In so doing, researchers should pay careful attention to ensuring any measurement instruments accurately reflect specificity of context. For example, IIMOS expands on traditional definitions of threat appraisal by defining the variable as a linear combination of perceived vulnerability, likelihood, and severity less the rewards associated with a maladaptive behavior. Studies in the OSH context have more often assessed threat appraisal by focusing on one of the aforementioned components to the exclusion of the others or by posing general queries about participants’ perceived risk magnitude (e.g., “How much risk do you associate with hazard X?”) (Bohm & Harris, 2010; Nielsen et al., 2011). Tests of IIMOS must clearly measure each component of threat appraisal as defined here in order to accurately account for both cognitive and affective influences on behavior.
In assessing model effectiveness, scholars should also carefully consider the time points at which to implement relevant measures to assess model constructs. A unique contribution of IIMOS is its ability to differentiate between initial behavior adoption and behavioral maintenance. As noted by Rothman (2000), “…we know surprisingly little about people’s psychological experience during their participation in a behavioral change program” (p. 68). Given IIMOS’ long-term focus on behavioral maintenance and safety climate, it would be useful to assess the model using longitudinal studies and structural equation modeling. For example, it may be helpful to inquire about a perceived threat immediately prior to the initial introduction of a safety measure (see Rothman, 2009 for a discussion). However, measures of customer satisfaction and perceived value should be implemented closer to the 6-month mark when initial adoption approaches behavioral maintenance. Although 6 months is a relatively arbitrary indicator of the transition from adoption to maintenance, it is consistent with leading theories of behavioral change (see Prochaska et al., 2008).
It will also be necessary to test IIMOS in the context of safety participation and safety compliance. Scholars (Christian et al., 2009; Neal & Griffin, 2004) have differentiated between these behaviors by categorizing compliance as mandatory (e.g., following procedures, using PPE) and safety participation as voluntary (e.g., communicating, safety committee membership, whistleblowing). The authors posit that IIMOS is equally relevant to safety participation and safety compliance contexts. Compliance-based approaches are often supported by policy. However, breaches in compliance have been routinely observed (Ménard & Trant, 2020). Without on-site regulatory bodies to oversee compliance, behavioral initiation and maintenance still involve an aspect of continued choice on the part of the employee/consumer. Testing IIMOS’ propositions regarding service factors may help to explain breaches in compliance and highlight the role of service factors in supporting policy-based worksite safety changes.
Finally, the authors recommend that the propositions of IIMOS also be evaluated in lab-based experiments. A key contribution of IIMOS is its ability to differentiate between the initiation of a behavior and behavioral maintenance. Rothman (2000) claimed that avoidance-oriented behaviors are easier to maintain than those that are approach oriented. However, he also noted that avoidance-related behaviors may prove difficult to initiate (due to the low potential expectations for one’s experience). Because IIMOS is initiated via threat appraisal, the authors suggest that the model has an innate avoidance orientation, which may assist in behavioral maintenance but could hinder the initial adoption of safety behavior. By manipulating the characteristics of messages contained in the promotional element of the marketing mix, scholars may be able to determine how to optimally communicate environmental hazards in a way that both encourages avoidance of the threat and refrains from raising expectations about the product to the point that they cannot be met via service efforts.
Advice for Practitioners
Assuming that the propositions established by IIMOS receive additional empirical support, the model offers an informative framework for practitioners. By viewing the entire model through a social marketing lens, the following key recommendations for program planners are offered:
Identify a relevant product
Because IIMOS considers the diffusion of OSH programs to represent a voluntary exchange between employee and employer, it is critical that practitioners identify a relevant core product for their audience. As noted by Edgar et al. (2017), this should represent a package of benefits that is relevant to the consumer. Key social marketing strategies such as consumer research and audience segmentation will be necessary in order to identify those benefits (see Andreasen, 2002). Detailed audience assessments may lead not only to the identification of relevant core products (i.e., anticipated benefits) but also, perhaps, to the development of new and innovative tangible products that will support their adoption (see Merritt et al., 2009). For example, by using occupational ethnography, Cullen and colleagues (2008) were able to create a miner safety campaign that highlighted miners’ suggestions in product design (e.g., use of in-group language and development of tangible products such as hard hat stickers to support the core product).
Recognize the competition and identify competitive advantages
As outlined by Wayman et al. (2007), OSH program planners should assess the competition in their environment. This may take the form of alternate/maladaptive behaviors (e.g., previously utilized unsafe behaviors) or competitive messages from alternate sources (e.g., messaging that proper use of PPE interferes with operation efficiency) (Wayman et al., 2007). Per IIMOS, practitioners would then need to reduce the rewards associated with competitive behaviors (thus increasing perceived threat) and promote core product benefits. Promotional strategies, such as developing attractive branding for the core product, using countermarketing to decrease the rewards associated with the maladaptive behavior, or changing social norms, could be useful here (see Luca & Suggs, 2010).
Assess price and place to facilitate response appraisal
IIMOS identifies response appraisal as a linear combination of response efficacy and self-efficacy less response costs. To facilitate favorable response appraisal, practitioners must identify and reduce the costs of behavioral initiation. Such costs should be identified by the audience and involve factors such as time and effort, as well as financial costs (e.g., the purchase of safety equipment) (Wood, 2008). Practitioners may reduce the price to consumers by providing tangible products without cost, by placing tangible products in easy-to-access locations, and by using promotional materials to reinforce product benefits at the point of purchase. For example, many of these strategies have been employed by organizations seeking to manage employee health during the COVID-19 pandemic. In promoting the core product of keeping one’s loved ones and co-workers safe, some organizations have elected to provide employees with free facial coverings, place hand sanitizer stations by entry locations, and post reminders of the need to engage with these tangible products.
Consider relational marketing strategies to address service factors
Recognizing service factors as the drivers of behavioral maintenance within IIMOS, it is critical that program planners move from a transactional to a relational view of marketing (Hastings, 2003). In this view, customer satisfaction and trust are assessed and developed over the long term; moreover, relationships are also built with additional relevant partners outside of the consumer (e.g., project funders, goods suppliers; Hastings, 2003). This perspective is consistent with Truong’s (2014) call for increased emphasis on upstream social marketing efforts. Traditional downstream efforts focus on consumer adoption, whereas upstream efforts focus on promoting changes in the environment that would support adoption. Thus, a relational marketing approach could assist in creating upstream changes to support consumer behavior (Truong, 2014).
Conclusion
Recognizing the multitude of fields that contribute to the development, implementation, and evaluation of OHS programs, IIMOS presents an integrated model of safety behavior. Although future empirical work must test the model’s propositions, IIMOS contributes to the literature by providing a parsimonious understanding of both behavioral initiation and maintenance (see Rothman, 2000). The model’s in-depth application of social marketing techniques is a novel addition to the OHS field that will encourage practitioners to develop innovative products, build relationships with consumers, and design upstream efforts to support program adoption.
Footnotes
Acknowledgements
The authors would like to acknowledge the efforts of Maggie Cregan and Andrew Boyd who assisted with editing and APA formatting of manuscript.
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.
