The aims of this study were (1) understanding the contextual factors influencing health outcomes in heat-exposed outdoor workers, (2) identifying key mechanisms and linking these factors with (3) wearable device-based intervention outcomes. Based on these results, we aimed to propose an explanatory intervention model for wearable usage in heat-exposed outdoor workers. A scoping review was conducted to identify relevant studies on heat-exposed outdoor workers. Of the 410 studies initially screened, 19 studies were selected for an in-depth review. The different studies showed a diverse overview of wearable device-based interventions for heat-exposed outdoor workers with different methodological approaches, including all aspects of context-mechanism-outcome configurations.
Contextual factors
Several contextual factors emerged from the scoping review that contribute to the health risks of heat-exposed outdoor workers. Most studies primarily focused on male workers from labor-intensive industries like construction, agriculture, and groundwork. These outdoor workers often face compounded risks due to obesity, pre-existing health conditions, and a lack of sufficient health and safety measures on the job [37, 49]. These factors exacerbate the health risks associated with heat exposure [65]. The physiological strain imposed by working in high temperatures can lead to conditions such as heat stress, dehydration, heat exhaustion, and even heat stroke [66]. The most significant contributors to heat-related health issues are extreme temperatures in the work environments, combined with long working hours and strenuous physical tasks [12]. Outdoor workers, for example, farmworkers, often have limited access to cooling systems, shaded areas, and adequate hydration, exacerbating their vulnerability to heat illnesses [16, 50]. In addition to the inherent dangers of these environments, the limited access to health resources and the physical preconditions of the outdoor workers make it critical to explore effective intervention strategies emphasizing the need for tailored interventions in these vulnerable populations.
Pre-existing health conditions like obesity were highlighted as critical factors that make certain workers more prone to heat-related illnesses [37]. Thus, these individuals will benefit even more from wearable device-based interventions [49]. Regarding a previously reported high prevalence of obesity among construction workers (28%) in the USA [67,68,69] and overweight or obese farmworkers (81% of male workers and 76% of female workers) [70], this appears to be of particular relevance.
All the studies included were published in or after 2015. On the one hand, the introduction of wearable technology started around this time, for example, with personal activity trackers and the first Apple Watch in 2014 [71]. On the other hand, there was a growing interest in the effects of rising global temperatures, extreme weather, and climate change on worker health [72, 73]. Regarding regional differences, more than half of the studies were conducted in the USA. Almost one-third of the citizens in the USA used a wearable device in 2020 [74]. This underlines the higher establishment and distribution of wearables in high-income countries [75]. Furthermore, the adoption of health-monitoring technologies, such as wearable devices to measure heart rate and core body temperature, has been suggested to monitor worker health in real time. Nevertheless, the assessment of different intertwined biometrics is complex, and the devices were unreliable and less functional initially [76]. In a recent scoping review, the reliability and validity of wearables to monitor heat stress and strain were synthesized [38]. The authors reported an overestimation of temperature due to direct sunlight, overheating of the systems, and an all-beats detection failure or data loss due to movement, pressure, or not wearing the device tight enough [38, 77]. Wearables have become better at recording data over time. Nevertheless, direct validation or reliability testing of the devices in the outdoor work context is scarce [38]. Furthermore, considering contextual factors and mechanisms is becoming even more important in capturing usage and monitoring under certain circumstances. In accordance with the results of this scoping review, practical concerns such as the cost of these technologies, worker acceptance and compliance, and employer support were identified as barriers to widespread implementation [78,79,80].
Mechanisms
Worker involvement and awareness of environmental hazards were substantiated as underlying mechanisms of wearable device-based interventions. Workers should be actively involved in such programs, and their opinions and ideas should be collected, listened to, and implemented [81]. The high usefulness of monitored results was identified by surveys and interviews on workers’ feedback, needs, and perceptions of wearable technology [36, 55].
Moreover, the connection between hazard awareness and environmental health literacy was identified. Environmental health literacy, which refers to an individual’s ability to understand, evaluate, and use environmental health information to reduce risk and improve both personal and environmental health [82], is essential in creating safer work environments. The use of wearable sensors to report individually collected data, such as heat exposure and heart rate, has shown promise in improving environmental health literacy among outdoor workers. For instance, when ground maintenance workers were equipped with wearable devices, the graphically visualized temperature and heart rate data helped 94% of participants better understand the health risks associated with heat exposure [82]. To ensure the effectiveness of interventions, occupational health professionals must develop tailored strategies that address the unique challenges faced by workers with low environmental health literacy, language barriers, or inadequate safety measures [49] and consider the complexities of their work environments, such as varying climate conditions and the physical demands of labor [83].
Feedback to users and the determination of indicators of heat-related illness, including physiological measurements like heart rate and core body temperature, were identified as two additional key mechanisms for effective interventions. Feedback to users (e.g., real-time report-back visualizations) appeared to be a powerful mechanism to improve environmental health literacy and promote wearable device-based environmental monitoring [82]. Moreover, the value of a health parameter report-back, together with comparative benchmarks and an interpretative context, has been reported for a public health setting and described as helpful in raising environmental health literacy on environmental exposures [84, 85].
Outcomes
Three outcomes of wearable device-based interventions in outdoor workers could be identified: Healthy workplaces, action and adoption of health-promoting behavior, and technology use. The reviewed studies examined physiological outcomes such as core body temperature and heart rate in response to heat exposure. In a few studies, combined monitoring was performed using a multi-parameter monitoring wearable sensor measuring heart rate, breathing rate, skin temperature, and activity level [49]. Due to the correlation between heart rate and activity level, a combined evaluation is advisable. However, when using multi-parameter monitoring, it is important to consider how many parameters are recorded and ultimately reported back to the workers. An information overload can lead to excessive demands in already complex work situations [86]. However, these multi-component measurements reflect a holistic picture of the heat-exposed situation, which is currently poorly developed or lacking in the workplace [87].
Regarding technology use, data privacy is a consideration when deploying wearable sensors to monitor health outcomes. As these devices collect sensitive health information, there are risks related to unauthorized access and misuse of personal data. Ensuring that data is collected, stored, and processed in compliance with data privacy laws and regulations such as the General Data Protection Regulation is essential. Organizations must implement robust data protection measures and maintain transparency with users about how their data will be used and shared [88].
Despite the concerns regarding data privacy, there has been positive feedback regarding using multi-parameter monitoring wearable sensors. Users often report increased awareness of their physiological states, which can lead to better self-regulation and proactive measures to mitigate heat-related risks. For example, knowing their heart rate and body temperature can prompt users to take breaks, hydrate, or seek cooler environments, ultimately enhancing their safety and well-being [50, 60]. Several studies indicate that when users feel empowered by technology to manage their health, their overall satisfaction and engagement with the devices increase [89,90,91]. This feedback loop can foster a workplace culture of health and safety, encouraging employees to utilize these tools actively.
Developing the explanatory intervention model
Pre-existing and well-established models, frameworks, or theories were selected and discussed in an iterative process to design an explanatory intervention model [40, 92]. To address the mentioned context-mechanism-outcome configurations [40] of the research questions, the following three models were selected for the present study to cover (1) policy and practices for improving workplace health to capture the contextual factors (2), health promotion and natural hazards preparedness to address the mechanisms and outcomes in using wearables, and (3) technology acceptance and usage behavior to capture both contextual factors and the outcomes of wearables in heat-exposed outdoor workers:
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The WHO Healthy Workplace Model [81],
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The Precaution Adoption Process Model [93, 94],
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The Unified Theory of Acceptance and Use of Technology [95].
In the following, these three models or theories are briefly explained to give a more detailed insight.
The WHO healthy workplace model
The WHO Healthy Workplace Model was developed to provide a holistic and flexible framework for creating healthy workplace programs in various countries, workplaces, and cultures [81]. The WHO Healthy Workplace Model is comprised of four large “avenues of influence” (i.e., the content of issues), contains a process of continuous improvement, and is guided by the two core principles of leadership and worker involvement [81]. The four “avenues of influence” have been designated: (1) physical work environment, (2) psychosocial work environment, (3) personal health resources, and (4) enterprise involvement in the community [81]. They represent specific areas employers and workers can influence to create a workplace that protects and promotes all workers’ health, safety, and well-being [81]. In the present scoping review, the first three “avenues of influence” were considered particularly relevant as plausible contextual factors and mechanisms for the explanatory intervention model:
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The physical work environment includes factors that may affect workers’ physical safety, (mental) health, and well-being, for example, physical hazards such as excessive heat. Means and ways to positively influence the physical work environment include, for instance, personal protective equipment, such as safety boots for construction workers, and training workers on safety procedures [81].
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2)
The psychosocial work environment refers to organizational culture, attitudes, values, or daily practices that can affect workers’ mental and physical well-being. Workers may experience psychosocial hazards as mental stressors, for example, problems with work demands and time pressures [81]. Ways to influence these psychosocial hazards could be the reduction of workload by reallocation of work or flexibility in the timing or location of work [81].
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Personal health resources in the workplace are health services, information, or resources that aim to promote workers’ physical and mental health. Employers may enhance these personal health resources, for example, by providing medical services, including health assessments or medical surveillance [81]. Worker involvement deserves special attention due to its dependence on individual acceptance of and participation in effective, healthy workplace programs [81]. In the process of selecting and implementing wearable technology, worker involvement is likely to promote a positive user experience [96] and appears critical to the successful implementation of the new technology [97].
The precaution adoption process model
The Precaution Adoption Process Model [93, 94] is a health behavior model and well-established health promotion theory [98] and explains how individuals come to take action to prevent illness, injuries, or harm caused by external hazards and health threats [94, 98]. In this model, the process of adopting a new precaution or health-promotion behavior involves seven stages in which an individual may be: (1) unaware of potential health risks (2), unengaged (3), undecided about acting (4), decide not to act (5), decide to act by adopting a new precaution or behavior (6), act (7), maintain the protective behavior over time to mitigate health risks [94, 98]. The Precaution Adoption Process Model has previously been used to characterize technology adoption and describe behavioral responses to protective technologies in mine workers [98]. In that study, the Precaution Adoption Process Model has proven suitable for identifying barriers to technology acceptance and adopting protective behavior [98]. Therefore, the Precaution Adoption Process Model contributes important aspects of technology adoption to the explanatory intervention model of the present scoping review. In this context, unawareness (stage 1) of a health risk or necessary precaution behavior refers to heat stress and respective preventive measures. The transition from stage 1 “unaware” to one of the “decision-making” stages 2 to 7 may be supported by media messages specifically tailored towards hazards and precaution measures, but also by communication with significant others or personal experience of hazards [94]. In the context of wearable device-based interventions, stage 5) “decide to act” refers to the intention to use wearables as a preventive strategy against hazardous heat effects, while stage 6) “act” involves the actual use of wearables to support and guide preventive behaviors. If such behavior were repeated customarily, stage 7) “maintenance” would be achieved [94]. Outcomes of an intervention program depend on the various individual stages of program participants and may, therefore, vary accordingly regarding knowledge, skills, engagement, and readiness for healthy behavior [99, 100].
The unified theory of acceptance and use of technology
The Unified Theory of Acceptance and Use of Technology [95] integrates elements from eight popular user acceptance models. It addresses the acceptance of technology as a precondition for the use of technology and thus serves as a well-established theory to explain and predict technology use [95]. In the Unified Theory of Acceptance and Use of Technology, the behavioral intention to use new technology, i.e., wearable technology, is determined by the following preconditions: (1) performance expectancy, (2) effort expectancy, and (3) social influence. These preconditions for technology use determine both user acceptance and usage behavior of technology. Furthermore, the Unified Theory of Acceptance and Use of Technology also incorporates age, gender, experience, and voluntariness of use as four moderating variables that affect the influence of the direct determinants of technology use behavior [95]. In the original study by Venkatesh et al. [95], a diverse population across various sectors, including healthcare, education, and business environments, was involved. This broad demographic allowed for a comprehensive analysis of how user characteristics interact with the model’s constructs, providing insights applicable to a wide range of technology adoption scenarios [95]. For instance, younger users may have different expectations regarding technology performance than older users, while gender may influence perceptions of the effort required to use technology effectively [95].
The explanatory intervention model
The explanatory intervention model (see Fig. 2) was developed based on the context-mechanism-outcome configurations identified in the scoping review. The included studies varied in their contribution to the context-mechanism-outcome configurations. Some offered rich contextual detail and plausible causal mechanisms (e.g., feedback systems, worker awareness), while others provided more limited or indirect insights. We considered this variation in the development of our intervention model and highlighted where assumptions were grounded in stronger theoretical contributions.
Contextual factors such as user characteristics, work environments, or preconditions of technology use were directly mapped to corresponding components in the model. Key mechanisms – like worker involvement or real-time feedback – emerged across the studies and were incorporated as central elements driving behavioral change and technology adoption. The model’s outcomes – behavioral adaptation, effective technology use, and healthy workplaces – reflect the aggregated findings of the reviewed interventions. Thus, the model synthesizes empirical insights from the literature into a structured framework for planning, implementing, and evaluating wearable device-based interventions for heat-exposed outdoor workers. Furthermore,
the various components extracted from the three mentioned models or theories enhanced the explanatory intervention model. Regarding contextual factors, (1) the aspects of user characteristics (e.g., age, gender, experience, and voluntariness of use), and (2) the preconditions of technology use (e.g., the size, weight, and robustness of sensor-based technology applications, the time investment and perceptibility of real-time feedback, and company commitment and regulations) were taken from the Unified Theory of Acceptance and Use of Technology. Additionally, the “avenues of influence” [81] were considered particularly relevant as plausible contextual factors for the explanatory intervention model to examine the effectiveness of wearable device-based interventions in outdoor workers, therefore, (3) the physical and psychosocial work environments and (4) personal health resources were found as results in the present scoping review and taken as influencing factors from the WHO Healthy Workplace Model. Most studies addressed specific work environments (e.g., construction, agriculture, and groundwork) as an essential influence on effective wearable device-based interventions. They added the psychosocial climate of safety while using a wearable and reporting symptoms of heat-related illnesses. This is accompanied by the health resources and conditions at work, such as the availability of shade and drinking water in the fields [49].
To address key mechanisms, the following aspects were included: (1) the determination of indicators for heat-related illness, (2) feedback to users, (3) worker involvement (from the WHO Healthy Workplace Model), and (4) environmental health literacy with its component awareness of environmental hazards (from the Precaution Adoption Process Model). The definitions of indicators and the heat-related illness risk measured by temperature and heart rate are important mechanisms in monitoring and reporting reliable and valid parameters. These parameters are linked with user feedback (e.g., report-back packets of heart rate and temperature). Most workers perceived the report-back of monitored temperatures and heart rates as very useful and thus were willing to change their protective behavior [91]. Therefore, worker awareness of environmental hazards and environmental health literacy are combined in the explanatory model. Together with worker involvement (e.g., perceptions and attitudes toward using digital technology), they can be a protective mechanism in developing heat strain at work [37].
Finally, the following outcomes were added: (1) the action and adoption of health-promoting behavior (from the Precaution Adoption Process Model), (2) technology use (from the Unified Theory of Acceptance and Use of Technology), and (3) healthy workplaces (from the WHO Healthy Workplace Model). Adopting health-promoting behaviors captures workers’ transition from awareness to actively implementing protective measures, such as staying hydrated or seeking shade. Technology use focuses on factors like ease of use, perceived usefulness, and trust in wearables, which are critical for ensuring consistent and effective device adoption. Together, these behaviors and technologies contribute to creating healthy workplaces where organizational culture and worker engagement foster sustained improvements in safety and well-being.
The spatial proximity of the factors in the model reflects their proximity in terms of content. In addition, the respective factors that are more likely to be related can be recognized on a horizontal visual axis. Exemplarily, physical, organizational, and social contextual factors include user characteristics and work environments under which outdoor workers operate. Indicators for heat-related illness serve as measurable mechanisms to identify when workers with specific user characteristics in a specific work environment are at risk of heat-related illness or when preventative actions should be triggered. For example, in a conducive work environment (e.g., a farming site or groundwork setting that offers shaded rest areas, portable cooling systems, or supportive policies like flexible work hours), workers with specific user characteristics (e.g., physical fitness levels, medical conditions such as heat sensitivity, or occupational roles like field laborers or machinery operators) wear advanced sensors that monitor their biometric data (e.g., body temperature, heart rate, physical activity, and hydration levels). These sensors provide real-time feedback on physiological metrics, visualizing the current status through clear indicators (e.g., green for safety, yellow for caution, and red for critical) and encouraging workers to adopt health-promoting behaviors, such as taking breaks, drinking water, or relocating to shaded areas. Additionally, based on this data, supervisors can dynamically adjust workloads, reassign tasks to cooler locations, or shift work hours to avoid peak heat, ensuring safety and optimizing productivity in physically demanding outdoor environments. Over time, these measures become ingrained as standard practices, reducing heat-related illnesses and fostering a culture of health promotion.
Strengths and limitations
One of the primary strengths of this scoping review is that it broadens the usability of findings by expanding the scope to include the context-mechanism-outcome configurations [40]. While Cannady et al. [38] focus in a recent scoping review on identifying relevant devices and their reliability and validity, we synthesize the integration of the context-mechanism-outcome configurations that enhance the adaptability of insights across different contexts. The two reviews are a perfect complement to finding out which wearables can be used for heat-exposed outdoor workers [38] and to understand the respective mechanisms and rationale of how and why specific mechanisms lead to certain outcomes in certain contexts. This ensures that our findings are not limited to a particular domain or scenario, making the model more versatile and applicable to a broader range of settings.
Another strength review is the proposal of an explanatory intervention model that provides insights at different levels. This approach offers a model that can be useful for understanding and planning complex wearable device-based interventions for heat-exposed outdoor workers. By incorporating various dimensions, the model allows for more nuanced strategies in real-world applications, enhancing its practical relevance.
However, several limitations must be acknowledged. First, while a scoping review was conducted to inform the model development, it was not entirely systematic. This methodological choice was made to provide a broad overview of the available evidence. Still, it may have resulted in the omission of some relevant studies, limiting the comprehensiveness of the review. Consequently, while the scoping review provides valuable insights, future work would benefit from a fully systematic review with clear research questions to ensure that all relevant literature is considered.
Second, the subjective interpretation of findings presents a potential source of bias. Although we have taken measures to ensure objectivity, including interpretations based on expert opinions or previous literature may lead to conclusions influenced by prior assumptions.
Third, one might argue that other theories and models could have been considered to generate an explanatory intervention model proposal. However, given the large number of models, frameworks, or theories potentially to be considered for the generation of the explanatory intervention model, there was a need for a pragmatic decision regarding the number of models, frameworks, or theories to be taken forward [40, 92]. While the proposed model offers substantial contributions by expanding the usability of findings and integrating different factors, the limitations regarding subjectivity and the non-systematic nature of the review should be addressed in future research to enhance the rigor and reliability of the findings.
Implications and future research directions
The findings from this scoping review offer valuable insights into the application of wearable technology for heat-exposed outdoor workers, particularly in the context of environmental health literacy [82] and precision prevention in occupational health [101]. The key question of context-mechanism-outcome configurations can be addressed by considering how such technology can enhance individual awareness, health behavior, and employer responsibility, particularly in high-risk outdoor environments. Real-time physiological and environmental monitoring can improve environmental health literacy, increase awareness of personal risk factors, such as heat stress, and enable timely preventive actions. This heightened awareness may contribute to better health outcomes as workers become more informed about how environmental conditions affect their well-being.
The use of wearable sensors aligns with the principles of precision prevention in occupational health [102] by tailoring interventions to individual workers’ needs and resources. By continuously monitoring physiological indicators (such as heart rate and body temperature) and environmental factors (such as ambient temperature), this technology allows for personalized preventive strategies. Workers can receive individualized feedback on their risk of heat-related illness, which can help them take appropriate preventive measures, such as adjusting their work intensity or hydrating.
Based on the findings, several practical recommendations can be delineated regarding the dissemination of information: Employers and workers should be made aware of the availability and usefulness of wearable-based technology for both physiological and environmental monitoring. Educational campaigns or targeted communications can help bridge knowledge gaps, ensuring that both parties understand the potential benefits of such technologies. Monitoring results from wearable devices need to be communicated understandably. This is essential to improve outdoor workers’ understanding and awareness of their individual heat exposure risk [55]. Simplified, user-friendly interfaces and regular feedback on heat exposure should be integrated into wearable systems to enhance workers’ ability to interpret and act on the data [36, 60, 61]. Outdoor workers should be equipped with wearable-based technology as part of their personal protective equipment [37]. Employers can incorporate these devices as a token of appreciation, reflecting a commitment to worker health and safety [49, 81]. This can foster a sense of value and responsibility, increasing worker engagement with preventive practices.
Further research and targeted actions will be essential to assess the usability of wearables and the acceptance regarding data privacy/ownership [36] while optimizing the deployment and effectiveness of these technologies. To further enhance the effectiveness of interventions, new study designs such as micro-randomized trials and just-in-time adaptive interventions should be considered. Micro-randomized trials allow for continuously adapting interventions in real time [103, 104]. By randomizing at the right decision-making time, micro-randomized trials can provide insights into the effectiveness of specific interventions (e.g., rest breaks or hydration prompts) under different conditions. This study design is particularly valuable for assessing how well wearable device-based interventions work in dynamic environments like outdoor workplaces, where heat exposure fluctuates throughout the day. Just-in-time adaptive interventions use a personalized, context-aware intervention model that delivers support exactly when needed. For outdoor workers, just-in-time adaptive interventions may provide timely notifications based on their physiological data (e.g., rising body temperature or heart rate) and environmental conditions (e.g., increased heat exposure). This approach ensures that interventions, such as reminders to hydrate or reduce physical activity, are provided at the right time, in the right place, to the right individual [105,106,107], they are most beneficial, minimizing the risk of heat stress for outdoor workers.
