Work intensification in the road transport industry: An approach to new working scenarios with automated vehicles

4.1 Participants and procedure

Our sample encompassed 336 professional drivers from the north and center of Portugal (95.5%) with the following types: 60.7%bus drivers; 22.0%taxicab drivers; 11.0%truck drivers; 4.5%ambulance drivers, and 1.8%drivers for waste management. Most of the participants were men, 96.7%; ranging age from 21 to 71 (M = 44.06; SD = 10.65). The seniority among professional drivers was also wide, from those who only have one year of practice to others who had been working for more than 49 years (M = 12.40; SD = 11.59). 89.6%of the participants were employed under permanent contract, with irregular shifts and work schedules (57%) and weekend work schedules (64.2%), and 33.2%working night shifts between 10pm and 7am.

The Ethics Committee of the Faculty of Psychology and Educational Sciences of the University of Porto and the different organizations involved approved the study protocol. Data were collected in several professional drivers’ providers using a self-administered questionnaire, followed by the researchers’ guidance. Participants received all materials consisting of the questionnaire, a covering letter explaining the purpose of the survey, and the guidelines to complete the questionnaire. All the participants gave their informed consent to participate, and we guaranteed their confidentiality and anonymity.

4.2 Measures

Inquérito Saú de e Trabalho (INSAT - Portuguese acronym of Health and Work Survey) is a self-reported questionnaire organized in different axes, that measures working conditions, health and well-being, and the relationship between them [51, 52]. In terms of psychometric properties, INSAT has a good internal consistency, in a Rasch PCM analysis, with a reliability coefficient > 0.8 [53].

Considering the main goal of the present study, only the risk factors and the health problems were used. The risk factors were: (i) workplace environment factors; (ii) toxicological risk factors; (iii) physical risk factors; (iv) psychosocial risk factors; and (v) work characteristics. All items were measured on a 6-point Likert scale ranging from 0 (not being exposed) to 6 (being exposed with high discomfort). The health problems correspond to a common list, which includes amongst others: back pain, headache, respiratory problems, musculoskeletal complains, fatigue, anxiety or irritability, and generalized discouragement. These items were measured using a dichotomous scale “yes” or “no” and if the answer is positive, participants were asked if the health problem is or is not related to the work activity.

4.3 Statistical analysis

A sample characterization was performed based on descriptive analysis to determine the central tendency parameters for scale variables and relative frequency for nominal variables. After this, and to analyze associations between risk factors and health problems, all variables were transformed in nominal variables (no –0; yes –1) and integrated in a bivariate logistic analysis (Enter method). The variables that showed significant associations in this approach were then integrated into a multi-factorial logistic analysis (Backward conditional method). Then, confidence intervals have been determined from the maximum likelihood estimation of coefficients and their standard errors. Statistical analysis used PASW Statistics 20.0 with the level of significance set p < 0.05.

5.1 The risk factors in the transport activity

Descriptive analysis from INSAT, presented in Table 1, shows the frequency distribution of the “yes” answers to risk factors that have a significant impact on the work of professional drivers. More than half of the workers point out as workplace environment risk factors and physical risk factors being exposed to vibrations (55.2%), gases and dust (63.3%), noise (63.9%), intense heat or cold (67.0%), adopting awkward postures (55.5%) and remaining seated for a long period of time (88.9%).

The exposure to psychosocial risk factors, presented in Table 2, shows that being the transport activity a service, the drivers, especially in the case of passenger transport, are in permanent contact with the public, so they have to pay attention to what is going on both inside and outside the vehicle (e.g., give information on timetables, routes, stops or ticketing). A close look at the results reveals precisely risk factors associated with the provision of services to the public: endure the demands (88.6%); deal with situations of tension (76.9%); be exposed to the risk of verbal (58.0%) or physical (46.0%) aggression; be dependent on direct requests from the clients (58.2%); or be exposed to frequent disruptive interruptions (47.4%).

The transport activity has also an undeniable “industrial dimension” [31, 54], which implies the need to follow a set of strict norms, in particular those on the work schedule, the breaks or the time each itinerary shall last. The INSAT results highlight precisely certain conditions within this dimension: work at an intense pace (70.6%); follow production norms or meet strict deadlines (57.6%); continue working beyond the assigned timetable (68.5%); “skip” or shorten a meal or not have a break (69.8%); or a choice over the breaks (64.8%).

Descriptive analysis from INSAT, presented in Table 3, shows the frequency distribution of the health problems related to work (provoked or aggravated). The literature shows a body of knowledge generally coherent about the most prevalent health problems among the road transport workers [29, 55]. At this point, the emphasis goes to the posture-related problems and to the need to remain in the driving position for a long time: back pain (58.2%), fatigue (42.8%), and musculoskeletal disorders (27.6%). In addition to these complains, INSAT data highlight a few more: anxiety or irritability (36.8%) and generalized discouragement (39.8%).

To analyze the association between work risk factors and health problems, a logistic regression was performed. The results are included in Table 4 (headache and back pain), Table 5 (muscular pain and anxiety or irritability) and Table 6 (fatigue and generalized discouragement).

The results showed that some work risk factors were significantly associated with health problems. The analysis of logistic regression results (not adjusted) shows that the following risk factors seem to be related to headache and back pain: “vibrations”; “dust or gases”; “exposed to frequent disruptive interruptions”; “have to skip or shorten a meal or not have a break”; “exposed to the risk of physical aggression from the public”; “deal with situations of tension in the relation with the public”; “exposed to the risk of verbal aggression from the public”; and “in general I feel exploited”.

From the multifactorial analysis, “deal with situations of tension in the relation with the public” (3.157; CI 1.634–6.098, 95%) and “exposed to frequent disruptive interruptions” (2.623; CI 1.571–4.382, 95%) were key factors that increased about three times the perception of headache; and four (4.106; CI 2.258–7.467, 95%) and two times (2.188; CI 1.267–3.780, 95%) the complaint of back pain.

Other risk factors also revealed important associations: “vibrations” (2.760; CI 1.635–4.658, 95%) increased near three times the perception of headache and “in general, I feel exploited” (1.825; CI 1.057–3.151, 95%) increased almost two times the perception of back pain. The same analysis was performed for two other health problems, as presented in Table 5.

The analysis of logistic regression results (not adjusted) revealed that several risk factors were considered related to musculoskeletal disorders and anxiety or irritability: “vibrations”; “dust or gases”; “dependent on direct clients requests”; “have to follow production norms or meet strict deadlines”; “not having my opinion taken into consideration”; “not having recognition by superiors”; “impossible to express myself”; “exposed to the risk of physical aggression from the public”; “exposed to the risk of verbal aggression from the public”; and “in general, I feel exploited”.

From the multifactorial analysis “in general, I feel exploited” was a key factor that increased more than two times the perception of musculoskeletal disorders (2.328; CI 1.085–4.997, 95%) and almost four times the perception of anxiety or irritability (3.918; CI 2.272–6.756, 95%). Other risk factors also revealed important associations: “have to follow production norms or meet strict deadlines” (2.174; CI 1.217–3.885, 95%), “not having my opinion taken into consideration” (2.282; CI 1.187–4.386, 95%) increased more than two times the perception of musculoskeletal disorders and “dependent on direct clients’ requests” (1.943; CI 1.168–3.230, 95%) increased almost two times the perception of anxiety.

Finally, the bivariate and multifactorial analysis also showed important associations with two other health problems, as presented in Table 6.

The analysis of logistic regression results (not adjusted) revealed that several risk factors were considered linked to work-related fatigue and generalized discouragement: “vibrations”; “exposed to frequent disruptive interruptions”; “impossible to express myself”; “exposed to the risk of verbal aggression from the public”; and “in general, I feel exploited”.

From the multifactorial analysis, “in general, I feel exploited” was the key factor that increased more than two times the perception of work-related fatigue (2.431; CI 1.271–4.648, 95%) and more than four times the perception of generalized discouragement (4.049; CI 1.769–9.268, 95%). “Exposed to frequent disruptive interruptions” (4.369; CI 2.252–8.476, 95%), and “impossible to express myself” (3.104; CI 1.336–7.216, 95%) also revealed important associations with generalized discouragement. “Exposed to the risk of verbal aggression from the public” (1.357; CI 1.074–1.713, 95%) revealed an association with work-related fatigue.

The overview of significant associations between work risk factors and health problems are presented in Table 7, indicating how often the exposure to work risk factors increases the probability to declare the identified health problems.

6.1 Work intensification factors and impacts on health

The transport activity encompasses a set of demanding tasks that, quite often, compel the workers to face inherently contradictory instructions: drive safely, provide a service to passengers in the public space (and manage the unexpected in this relation with the public), meet the schedule, and ensure the profitability of the transport (e.g., number of passengers; number of services completed).

According to the findings, the work intensification factors do not have the same impact. The proposal to build a score to assess the simultaneous effect of different types of variables is, for that reason, questionable [42]. This is the reason why we chose to use logistic regressions; they estimate the differentiated probability of perceived impact of the work intensification risk factors on health.

The work intensification is a source of risk and pain, both physical and psychological. The interactions between physical constraints, such as vibrations, production norms, or meeting strict deadlines, make it more likely that physical health be affected by the work activity.

The studies carried out under the scientific scope of the activity-centered ergonomics reinforce the idea that the work intensification leaves little room for the workers to build operative modes capable of better preserving their health, i.e., to develop work experience [20, 56]. In fact, in the descriptive analysis of the results (cf. Table 2), it is noticeable that more than half of the workers declares feeling “lack of autonomy” (e.g., to decide how to do work by themselves –58.0%; to choose the breaks –64.8%).

The accumulation of physical and psychological constraints associated with the contact with the public are an additional source of work intensification and impact on health. An example thereto are the frequent interruptions, which contribute greatly for the generalized discouragement. It may be explained by the drivers’ perception of not having the time to work correctly, to make a work well done, as the interruptions cause delays and prevent the fulfilment of the service schedule established/imposed by the client. The literature also underlines how the work intensity can damage the working conditions and the performance of the activity itself: “the goals, the procedures that have to be followed, the available means, are constraints each worker has to take into consideration to optimize the activity, in order to preserve one’s physical and mental health as much as possible (. . .), but the urgency worsens the effects of such constraints” [42 p 201].

Another example that the study’s findings make particularly noticeable is the fact that the intense work situations significantly increase the perception that one is being exploited, with an impact in almost all the health problems previously addressed, either physical or psychological (cf. Table 7). The work intensification “takes time from the individuals and takes the time of the individuals” [35 p 205]. Working under such circumstances makes it virtually impossible for the workers to make use of their own requirements, experience and unique contribution to do a work well done. Hence, we are talking about an expropriation of the time a worker needs to make use of oneself at work, with highly impactful costs for the individual health.

6.2 The future of work within automated mobility scenarios: pursuing the sustainability

This study examined the sources of work intensification and their effects on road transport drivers’ perceived health, at the time the transport industry is going through a period of transition to automated vehicles. Indeed, in the EU context, the sector’s prospective evolution seems to be entirely monopolized by automated mobility solutions [57]. However, could automation systems be considered the solution for work intensification, diluting drivers’ health complaints? Or, on the contrary, as showed in 1995 in the automation of a rail system [58], will it pave the way to other risk factors in contexts of transport services (apparently) without workers?

Until fully autonomous vehicles become a reality, i.e., operating without human input, the role of the human driver will remain a key component of the system because so far even the highest automated driving systems rely on a back-up human driver who takes over when the technology reaches its limits or disconnects [13]. Hence, it is crucial to analyze what does contribute to the work intensification and use that analysis to improve the drivers’ working conditions, especially at this critical moment when the sector is testing new human –automation interface scenarios. Therefore, we cannot help but question how to develop at the same time mobility for all and work sustainability when the human work activity in transport seems to acquire the meaning of a “second-class component” of the driving system, or as an “adjusted variable” according to the rhythm of technological progress [59].

The approach to sustainable work involves, on the one hand, taking into account the effects of the working conditions [60]; and, on the other hand, ensuring that the development of the automated technologies goes hand-in-hand with the working population characteristics and the improvement of the working conditions.

Bearing this in mind, our findings support some recommendations in terms of working conditions and they are worth attention in the face of the expected transformations due to automation.

First, the development of automated driving should consider the current demands of this work activity in order to present solutions that assist the human worker instead of giving rise to new constraints [61]. For instance, automation is expected to contribute to the efficiency of the road transport, leading to an increase in the number of transport services and in the number of hours travelled per vehicle. Hence, it is fundamental to ensure that these prospective changes do not end up contributing to the work intensification (e.g., the exposure to extended working periods) that is already experienced by the professional drivers, as our results pointed out.

Second, the role of the driver when operating automated vehicles is one of the main challenges for both transport industry and ergonomics science. The results of our study highlight a highly demanding job, entailing increasing productions norms, conflicting tasks and strict deadlines. Therefore, in automated vehicles, where workers are expected to intervene, the human driver will guarantee a possible “double role”, both as a driver and as a supervisor (of the automation system) [62]. Will these situations double the tasks and work demands that the road transport workers must deal with? If so, we will be facing one of “ironies of automation” [14, 63], because rather than relieving human driver workload and vigilance, it might actually place greater demands on the worker [61].

Third, one of the main results of our research concerns the feeling of exploitation at work reported by the workers, with impact on almost all the health problems, either physical or psychological. Performing a job under these conditions, particularly in systems characterized by human-automation interfaces, may hinder the use of work experience and give rise to a feeling of “loss of control” over the work activity whereas the technology seems to acquire the domination in the work process. This aspect in the road transport work calls our attention for the need to deploy automated vehicles through a collaborative approach between the human agent and the technical agent (automation).

Taken together, these recommendations defined from our quantitative results could help designers, transport companies, transport authorities, policy-makers, and scientific community to develop automated vehicles, considering the drivers’ working conditions and the real needs that automation should meet to foster health-promoting work situations and prevent new sources of work intensification.

6.3 Study limitations

The major limitation of the study lies in the fact that our sample encompassed professional drivers from different subsectors in transport (e.g., bus drivers; truck drivers, taxicab drivers) with specific constraints in terms of working conditions. For instance, the need to perform long routes with trucks/lorries; with or without passengers/clients on board; to make manual work with loading and unloading goods to/from trucks; or helping people while transporting them (e.g., sick or older people). A quantitative methodology is consistent with this sectoral approach. However, another study limitation is that this analysis has not been complemented with a qualitative approach, which would allow the identification of the specificities of those constraints in each subsector. Lastly, even though we have organized sessions to return our results to the transport companies, it would be important to share these results with other strategic stakeholders such as trade unions and public authorities called up to intervene on the regulation of transport services, as well as on the working conditions and the occupational health of those providing these services.