The Conditional Probability for Human Error Caused by Fatigue, Stress and Anxiety in Seafaring

Abstract

Human error caused by the interaction and effect of fatigue, stress and anxiety in seafarers is the subject of this research. The human element is a major part of the maritime system. We used Bayesian networks to predict human error in maritime affairs by analysing interactions between people, technology, organisational and environmental factors which make up the specificity of the maritime system. Bayesian networks are graphical structures developed to represent the conditional dependencies among a number of variables and to make conditional conclusions related to the selected variables. Through the analysis of psychic causes such as stress, fatigue, anxiety and so on, the model can produce graphic diagrams indicating which rank on which type of vessel at which seafarers age contributes to an increase in conditional probability of human error. The contribution of the paper is to find the worst combinations of influencing variables that can lead to an increase in the risk of human error. The results show a significant level of fatigue and stress in all officers (engine and nautical), regardless of the type of vessel they serve. A strong presence of anxiety is also reported in all surveyed officers, with a higher degree between engine officers.

1. Introduction

Rapid development of marine technologies has resulted in major changes and increased challenges for mariners in view of acquiring new knowledge and skills as well as the pressure they need to handle trying to transfer goods over the seas as fast as possible. In their living and working environment, these changes occur at a much faster rate than the human body is able to follow. Any such change requires adjustment, and if that adjustment is difficult or impossible, it inevitably encourages stress.

1.1. Research Background

Among the risk factors affecting the occurrence of illness or accidents on board are fatigue, stress and anxiety, which, alone or in combination with other factors, can lead to human error. Human error, or a chain human error, is a common cause of maritime accidents. Fatigue also causes misjudgement in the management and performance of certain activities on board, and affects the health of seafarers and their working ability. According to the International Maritime Organization (IMO), fatigue is defined as “a reduction in physical and/or mental capability as the result of physical, mental or emotional exertion, which may impair nearly all physical abilities including strength, speed, reaction time, decision making, or balance” [1].

Living and working conditions are usually divided into the workplace, the social environment and the personal sphere. This concept is not applicable on board, as the vessel represents the seafarer’s living and working environment at the same time. While at sea, he or she is essentially a crew member, a role that cannot be changed. For instance, an officer remains an officer both during his/her service and free time. Psychological theories claim that, in order to preserve mental health, it is necessary to change the role after some time, but this is not possible on board and can lead to frustration [1,2,3,4].

An additional factor that complicates work on board is the disturbed circadian rhythm due to work in shifts/watches. The circadian rhythm is a natural internal process that regulates the sleep–wake cycles and is repeated approximately every 24 h. Although the circadian rhythms are endogenous, e.g., having no obvious cause, they adjust to the external environment, the so-called time givers. The latter may include the light, temperature, food, physical activity, etc.

In a work rhythm such as the on-board watchkeeping rota system 6:6 and 4:8, the capacity for the organism recovery and sleep are intermittent and often insufficient. When working at night in the watch system 6:6 (from midnight to 6 a.m.) and 4:8 (from midnight to 4 a.m.), the seafarers experience increased sleepiness and the sleep episodes are shorter [2,3].

The circadian rhythm is the essential natural cycle of physical, mental and behaviour changes that the human body goes through in a 24 h cycle. The rhythm and organisation of work on board—the work in shifts or watch rotas—are often at odds with the circadian rhythm. The sleep rhythm is disrupted depending on the type of trade and the related organisation of work in watches. This results in the intermittent sleep on board. The deprivation of sleep is strongly associated with sleepiness during the daytime and reduced working performance. It is particularly important to underline that, in seafaring environments, the loss of sleep is cumulative over the periods of navigation.

The disruption of the circadian rhythm due to work in shifts, along with the stress, chronic lack of sleep and fatigue are just some of the factors whose complex interrelations affect the life and work of seafarers. One of the consequences is a higher probability of human error [2].

1.2. The Importance of Human Error

Human error is the subject of research in almost every industry and profession of our times. There have been many studies dealing with factors that may result in human errors. Accidents prove that human error in maritime, road or air traffic may have very serious and long-term effects, ranging from the loss of human life to environmental threat. The research studies attempt to define all the factors and their combinations that affect the accident possibility [1,2,3,4]. The marine system is a human-based system, and human errors play an important role in accidents and casualties as well [5,6].

1.3. Literature Review

In the 2019 Annual Overview of Marine Casualties and Incidents, the European Maritime Safety Agency (EMSA) reported that over the 2011–2018 period 230 vessels were lost; there were 23,073 casualties and incidents, involving 7694 persons injured. During this period, 426 accidents resulted in a total of 696 lives lost. Human action represented 65.8% of the accident events. A total of 65% of the contributing factors were related to shipboard operations and 24.9% to shore management [7].

Predicting human error in the context of human-to-machine or human-to-human interaction reveals important information concerning the reliability of the whole system [8,9]. Regardless of the cutting-edge marine technologies, computerisation, automation, high level of accommodation comfort and advanced communications, human error remains an important issue in seafaring and maritime affairs. Numerous research studies have shown that serious sea accidents have been caused by human errors due to fatigue, various psychological states and disruption of the circadian rhythm [1,2,3,4,5,6].

One of the ways of reducing maritime accidents is the assessment of the risk of accident occurrence by means of various modelling methods. This research makes use of the Bayesian networks, one of the possible models designed to assess the likelihood of human errors in complex systems. The possibility of forecasting human errors in the marine environment has been studied as well [8,10,11,12,13]. A number of studies indicate direct or indirect human errors as a major cause of maritime accidents, which raises many unanswered questions about the best ways of preventing catastrophic human errors in the maritime context [14].

1.4. Goal of This Research

Based on the produced model results and performed analysis, the goal of this research has been to determine which combinations of the variables are most likely to result in human error. The model created for the purpose of the research is able to show how and in which ratio the variables affect human errors given the rank aboard the vessel, the type of vessel and the respondent’s age, under conditions of fatigue, anxiety and stress.

Since it is not possible to accurately calculate the risk of such events, this study makes use of a method that allows the combination of expert thinking and statistical data in order to indicate the probability of human error occurrence affected by psychological factors.

2. Materials and Methods

With regard to the context of this study, the experts/respondents are seafarers with more than two years of navigation experience.

Bayesian networks have been selected as a method for creating the model as they can provide assessments even in case of incomplete sets of information and, during the assessment process, they can equally use the data obtained through analysis and/or with the help of experts. With the aid of Bayesian networks, it is possible to recognise the most essential causes leading to human errors and to analyse connections acting among them. The combination of mathematical logic and expert opinions is used in the creation of Bayesian networks. The latter allow the incorporation of expert knowledge when designing these models. In cases where it was necessary to use an expert assessment for the validation of the variables, Bayesian networks proved useful when processing incomplete information on the contributing factors [10,11,12,13].

Bayesian networks are graphical structures developed to represent the conditional dependencies among a number of variables (attributes) and to make conditional conclusions related to the selected variables [15]. A Bayesian network is a probabilistic graphical model that represents the conditional relations among random variables and their conditional dependencies [16]. Furthermore, a Bayesian network can be defined as a directed acyclic graph (DAG), consisting of the nodes representing the variables and the edges representing the conditional dependencies [17]. Every edge has its beginning and end (arrow). The nodes are random variables showing the states—but not necessarily the event, as is the case in the decision tree models [18]—and the factors contributing to the main problem. The edges represent direct influences [18] and determine an independent assumption that connects the nodes [8,9,18].

In order to design a Bayesian network, it is necessary to define the nodes (variables), possible values that an individual node may receive, connections among the nodes and values of the conditional dependencies in the nodes. Relations among parent nodes and child nodes imply that for calculating the child’s probability distribution it is necessary to know certain probabilities of the parents. Every node in the network has its joint probability, thus defining a Bayesian network by structure and values [19].

In this study, the values needed for creating a Bayesian network were obtained through a questionnaire completed by 61 seafarers in 2020. The questions on the amount of stress, anxiety and other issues related to psychological states were responded to by using a scale from 1 to 10, with 1 indicating the lowest and 10 indicating the highest values for a specific state. For example, on the scale from 1–10, for the amount of anxiety which the respondents experienced on the last voyage: 3 means that anxiety was low, 5 means middle and 7 being quite high.

Twelve experts participating in the workshop constructed the network and assigned values to the conditional probability tables. The experts were seafarers, maritime professionals and experts in Public Health: medical and psychologists. The making of BBN framework for human error in maritime accident is presented in Figure 1.

The mode values of the expert-assigned values were entered in the conditional probability tables SMILE (structural modelling, interface, and learning engine) and GeNie GUI (graphical network interface) to create and quantify the Bayesian network [20].

The technique developed by Van der Gaag was used for allocating the conditional values within the network as this technique allows a fast and simple allocation of values to several hundreds or thousands of conditional probabilities of expert thinking [21].

The method used for allocation of values was the probability scale, as shown in the Figure 2. A probabilistic scale is a horizontal or vertical line with numerical values. The values offered to the experts were: (0.1, 0.25, 0.5, 0.75, 0.9).

Description of the value allocation scale:

• 0.10—very unlikely (almost impossible)
• 0.25—unlikely
• 0.5—half-half
• 0.75—likely
• 0.90—very likely (almost certain)

3. Results

The results of the research consist of two parts. In the first part, the results of the survey of 61 seafarers were processed and analysed, on the basis of which the model variables and parameters within the network were made. The paper analyses the influences of the function/rank of the respondents on the vessel, the age of the respondents and the type of vessel on the mental states of seafarers. The observed mental states included fatigue, anxiety and stress are presented in Appendix A.

The data used in the paper were obtained through the statistical analysis of the survey results of 61 seafarers aged 18–65, of which 22 were deck officers, 11 masters, 22 engineer officers, 1 chief engineer and 5 other crew members/ratings, with regard to their age as presented in

Table 1. Age of the respondents.

Age of Respondents	Number of Experts
18–25	12
26–35	23
36–55	25
36–55	1

:

On their last voyage, the experts were employed on various types of vessels. Out of a total of 61, 8 seafarers served on yachts, 4 on special types of vessels, 31 on cargo ships, 3 on passenger-cargo ships and 15 on passenger ships. Figure 3 shows the reported rates of fatigue, anxiety and stress among deck officers on different types of vessels.

Figure 3 shows that the highest values of anxiety and stress were reported by seafarers serving as deck officers on passenger ships, while the highest value of fatigue was reported among the deck officers on yachts.

Furthermore, according to the results of the survey questionnaire, the greatest fatigue among the masters is present at the age of 36–55 years. Masters do not indicate significant states of anxiety. Somewhat higher rates of anxiety were reported among the masters on passenger ships and yachts, aged from 26 to 55. The comparative results regarding fatigue, anxiety and stress among the masters on passenger ships and yachts are presented in Figure 4.

The analysis of data obtained from the engine officers produced fatigue, anxiety and stress rates that are worse than in deck officers. Engine officers aged 26–55 serving on cargo and passenger ships show a very high level of stress and nervousness. Engineers aged 36–55 report considerably higher values of fatigue than their younger peers. The results of the survey analysis show a significant level of fatigue and stress in all engine officers, regardless of the type of vessel they serve. A strong presence of anxiety is also reported in all surveyed engineering officers (Figure 5).

3.1. Creation of the Model

The input variables of the model, whose values are obtained through the analysis of the results produced by the questionnaire, include “Function/Rank on board”, “Type of vessel” and “Age”. The first part of the model reveals their influence on the “General intensity of fatigue”, “Anxiety” and “Stress and nervousness”. Values for the tables of conditional probabilities have been obtained from experts and through logical inference.

“Anger”, “Control over important matters” and “Confidence in one’s own abilities” are external variables that have been inserted into the model in such a way that they may significantly alter the model’s end results. The variable “Anger” has been included as an emotion that may lead to agitation in persons who have poor control over situations due to increased fatigue, accumulation of personal problems or insufficient experience. Anger is the input variable and it is isolated to present its strength and impact. While Anger is an independent variable, both Anger and Fatigue are reunited by the Agitation variable, ultimately influencing human error in the end.

The variable Concentration refers to a person’s ability to direct psychic energy towards a stimulus from the environment. In order to obtain the values of conditional probabilities for this variable, we have observed the effects of the General intensity of Fatigue, Anxiety and Stress and nervousness. The values of the variable Concentration have been obtained through the results produced by the research, based on the responses in the questionnaire. These values are presented in Figure 6 (see the description of the model’s variables in

Table 2. Description of the variables.

Name of the Variable	Description	State of Variables
Function on board	Refers to the actual rank on board regardless of the certificate of competence he/she holds	- Master - Deckofficer - Engineofficer - Crewmember - Chiefengineer
Age of the respondent	Respondents’ age divided into 4 categories	Age 1—from 18 to 25 Age 2—from 26 to 35 Age 3—from 36 to 55 Age 4—from 56 to 65
Type of vessel	According to the basic categorisation of vessels, regarding their purpose or type of cargo	- Cargo - Passenger - Cargopass. - Special - Yacht
Anger	Current state of agitation due to an event or provocation	- Yes - No
General intensity of fatigue	Average feeling of tiredness based on a personal estimation of a crew member	- Standard - Increased
Anxiety	Refers to an average feeling of worry, restlessness and tension, which a crew member experiences on board (chest pain, permanent concern, bad mood, irrational fears, inability to sleep well, etc.)	- Standard - Increased
Stress and nervousness	Refers to occurrence of increased heart and lung function, increased muscle tension, increased mental activity, mental tension and restlessness	- Yes - No
Control over irritation	Ability to control tensions, stressful situations and negative reactions to stressful situations	- Yes - No
Agitation	A state of current unrest caused by an event	- Yes - No
Feeling of inability to handle things	A feeling of overwhelming psychic load	- Yes - No
Concentration	Person’s ability to direct psychic energy towards a stimulus from the environment (focus)	- Good - Poor
Control over important matters	Refers to a personal perception of one’s own psychic abilities over a period of time	- Yes - No
Confidence in one’s own abilities	Perception of one’s own psychic and physical abilities	- Yes - No
Incapacitated	Refers to a person who, for various psychic and/or physical reasons, does not feel fully capable of controlling the vessel	- Yes - No
Personal condition	Overall psychic and physical state of a person who controls the vessel	- Good - Poor
Human error	Refers to the probability of human error that may lead to a marine accident with various consequences	- Yes - No

).

3.2. Results of the Model/Simulation

The model shows that the rate of conditional probability for the last (root) node is 70:30. When setting the variables Fatigue, Stress and Anxiety to value 100%, the probability of human error increases by 11%. The combination of the nodes Anger and Agitation increases the likelihood of human error by 4%. The node Fatigue set at 100% increases the probability of human error by 2%, Stress increases it by 7% and Anxiety by 4%. The combination of Anger, Stress, Fatigue and Anxiety indicates an increase in conditional probability by 11%, while the combination of Anger, Stress and Fatigue indicates an increase in conditional probability of human error by 7%.

The model shows the combinations of factors that reduce concentration and disrupt physical and mental homeostasis, thus increasing the likelihood of human errors.

Through the analysis of psychic causes, such as stress, fatigue, anxiety, and so on, the model can produce simple graphic diagrams indicating which rank on which type of vessel at which age contributes to an increase in conditional probability of human error.

According to the model presented in Figure 7, the most adverse combinations resulting in human errors are detected in deck officers aged 18–25 engaged on passenger ships, when these seafarers are affected by the variables Stress and nervousness (77%), Anxiety (75%) and Fatigue (76%). In the event of presence of all three states in the deck officers aged 18–25 engaged on passenger ships, the calculated conditional probabilities for the occurrence of human error amount to 81%. In such a case, human error can be further adversely affected by poor concentration, thus increasing the likelihood of human error to 83%.

The intensity of red colour is proportional to the rate of the variables’ sensitivity. The selected variable is considerably influenced by the variables in red colour, and the strength of influence can be observed by the colour’s intensity. As it can be noticed, the selected variable is strongly affected by the variables Type of vessel, Respondent’s age, Rank on board, Concentration, Personal condition, Feeling of inability to handle things, Control over important matters, Confidence in one’s own abilities and Incapacitated. Detailed values of sensitivity for each variable are shown in

Table 3. Values obtained through examination of sensitivity by selecting the variable Human error.

Variable	Max. Sensitivity	Min	Avg
Control over important matters	0.173	0	0.086
Confidence in one’s own abilities	0.131	0	0.065
Incapacited	0.121	0	0.028
Concentration	0.051	0	0.012
Function on board	0.045	0	0.009
Feeling of inability to handle things	0.028	0	0.012
Type of vessel	0.025	0	0.007
Personal condition	0.024	0	0.006
Age of the respondent	0.024	0	0.005
Stress and nervousness	0.012	0	0.01
Anger	0.01	0	0.005
Agitation	0.007	0	0.002
Control over irritation	0.007	0	0.003
Anxiety	0.005	0	0
Fatigue	0.004	0	0

.

In both cases, the variables indicate the expected sensitivity to the selected variables. The variables revealing a considerable sensitivity in both cases are the input variables, i.e., Type of vessel, Respondent’s age and Rank on board. When targeting the variable Human error, the highest level of sensitivity is indicated by the variables Control over important matters, Confidence in one’s own abilities and Incapacitated as presented in Figure 8.

The variables presenting lower sensitivity also influence the end result to a certain extent. For instance, the variable Fatigue, when set at maximum value, makes the end variable Human error increase by 2%, which is a significant change. The sensitivity analysis actually shows that the level of fatigue can be considerably influenced if a person has the capacity and possibility to overcome fatigue, i.e., control his/her psychic state and be aware of it.

Another examination of sensitivity was performed by selecting the variable Concentration (Figure 9). The produced results indicate that the selected variable is mostly affected by the variables Type of vessel, Respondent’s age, Rank on board, Stress and nervousness, Fatigue and Anxiety.

4. Discussion

This study brings an analysis of the influence of fatigue, stress and anxiety on the possibility of human error occurrence in the seafaring environment under various circumstances. It has long been sought to anticipate the possibility of human error and the circumstances that would lead to it, in order to prevent accidents in such systems. It is important to assess the effects of human error during the early stages of the system and to prevent them as much as possible [5,6,7,8,9].

The research concept is divided into two parts: the data obtained through the voluntary questionnaire were analysed and then used for model simulation in Bayesian networks. The model’s validity was confirmed through the sensitivity analysis performed with the aid of the programming language Genie. This method makes use of the logarithmic expression of the authors. This program can produce a number of derivates of the posterior probabilities of all nodes within a Bayesian network, which provide indications of importance of the network parameters [20,21]. The method allows a graphic display of the most influential variables on the targeted (selected) variable. As an example, this paper presents the targeting of the variable Human error.

The relevant literature and other sources contain similar research studies that used machine learning techniques and machine anticipation of human error, which requires a multi-disciplinary approach [8,10,11,12,13]. Bayesian networks and models used in this research are also used in medicine for making decisions and forecasting the process course and the illness outcome (given the symptoms, the network can be used to compute the probabilities of the presence of various diseases) [21,22].

The results obtained through the analysis show that respondents have well distinguished different notions of mental states because anxiety and nervousness have significantly different outcomes. Most respondents stated that they were more significantly exposed to stress compared to feelings of anxiety. A high degree of anxiety was recorded in a significantly smaller number of respondents than stress, and it should be taken into account that the knowledge and ability of experts to distinguish nervousness from anxiety has not been researched.

The results of the analysis of statistical data of 61 respondents in this study reveal that seafarers employed on passenger ships, merchant ships and yachts show a high intensity of fatigue. On average, the greatest fatigue is present in yacht deck officers, which is expected given the small number of crew members and the dynamics of tasks. When the intensity of fatigue is observed in all respondents regardless of occupation, then the data indicate that the greatest feeling of fatigue is present on special-purpose vessels and the least on passenger cargo ships. Stress and anxiety are significantly present in seafarers who keep watch and have the highest mean values for deck officers on passenger ships. Deck officers show a higher intensity of fatigue at the age of 36–55 years than officers in other working periods of life. An alarmingly high level of anxiety was recorded among deck officers on passenger ships aged 36–55, and from 18–25 years, followed by deck officers on cargo ships aged 26 to 36.

In our study, the most unfavourable combinations that lead to human error were found in deck officers aged 18–25 employed on passenger ships, when they are influenced by the variables Stress and nervousness (77%), Anxiety (75%) and Fatigue (76%). In the event that all three conditions are present in deck officers aged 18–25 employed on passenger ships, the conditioned probability of human error amounts to 81%. In this case, human error can be further intensified by poor concentration, increasing the probability of human error to 83%.

Fatigue can be defined as a complex reaction of the body, i.e., the condition of muscles, internal organs or the central nervous system, where the previous physical activity and/or mental process, in the absence of sufficient rest, results in insufficient cellular capacity to maintain the original level of activity due to insufficient and/or poor sleep and job complexity. In case of this type of fatigue, the latter can be partially or completely cured by sufficient amount of time for rest and relaxation and quality sleep [1,4,23,24,25].

Fatigue and sleepiness are often used as synonyms, but they differ because sleepiness will always end in a sufficient amount of sleep, while this is not the case with fatigue. Physical fatigue occurs after a long period of physical activity and causes weakness and decreased endurance. Mental fatigue is mainly the result of psychological stress and emotional exhaustion, or a great burden on the personal capacities of the individual. It can be caused, for example, by long working hours. In particular, disorders in sleep–wake cycles and circadian rhythms, which occur in jet lag and shift work, result in irregular work and sleep and reduce the amount and quality of sleep between work cycles [1,2,23,24,25]. Mental fatigue occurs gradually and insidiously, and can occur as cognitive impairment, resulting in decreased efficiency and other mental symptoms that can increase feelings of fatigue and drowsiness [2,24]. The International Maritime Organization (IMO) defines fatigue as “a decrease in physical and/or mental ability as a result of physical, mental or emotional exertion, which can impair almost all physical abilities including strength, speed, reaction time, decision-making process or balance”. The most common causes of fatigue known to seafarers are lack of sleep, poor quality of rest, stress and excessive workload [1,25,26]. The ability of an individual seafarer to adequately cope with the requirements of such a demanding profession depends on the state of the physical and mental health of each individual [27].

Individuals are constantly in a situation to make choices. Every one of our behaviours is a choice, and every choice, no matter how small, strengthens the sense of control and self-efficacy. Individuals who are less proactive will have less faith in their ability to achieve the desired result, which leads to feelings of helplessness and contributes to the worsening of disorders from the depressive circle. Research has shown that perceived self-efficacy is associated with psycho-social functioning, including work performance, academic achievement, perseverance and health functioning. An important role is also played by the locus of control, in which people with an internal locus of control have a feeling that their life events are under personal control, unlike people with an external locus of control, who believe that events cannot be controlled [28].

Burnout at work is directly correlated with reduced work performance [29]. Withdrawal from a stressful situation, as one of the defence mechanisms, implies taking sick leave and/or leaving work [29,30,31]. However, it is obvious that, owing to the nature of their work at sea, seafarers cannot leave their job “instantly and straight away” and that such awareness contributes to the deterioration of their mental state.

Although anxiety, as an accompanying feeling of stress, sometimes protects us from threatening situations in an attempt to establish homeostasis, if it is prolonged, it can result in psychological stress that affects the daily and overall functioning of the individual [32]. Feelings of greater emotional exhaustion, greater cynicism and a feeling of less efficiency in work performance lead to increased anxiety. The latter exhausts an individual emotionally, and consequently leads to faster burnout.

A person with a higher score on the neuroticism scale may develop feelings of dissatisfaction and deficits in functioning, regardless of the environmental demands. An elevated score on the neurosis scale is characterised by intensified anxiety and tension, concern and vulnerability, and general feelings of agitation that are disproportionate to the circumstances in a person’s life. They impair a person’s quality of life and can cause difficulties in almost any area of their life, and in establishing and maintaining productive relationships either at work or in private life, but they are still not strong enough to incapacitate a person in his/her daily functioning [33,34]. People with high neuroticism are often self-critical and sensitive to other people’s criticism [35].

Anxiety affects concentration and the ability to remember, and it reduces self-confidence, which can have an indirect effect on the power of reasoning [36].

When targeting the variable Human error, our respondents presented the highest level of sensitivity in the variables Control over important matters, Confidence in one’s own abilities and Incapacitated.

According to the study conducted by Italian researchers, a higher level of anxiety and a lower satisfaction were reported by the engine officers and ratings than the deck officers. Deck and engine officers show a higher level of self-control than the engine ratings. This is in line with our research revealing a pronounced sensibility precisely in these variables, which may eventually lead to human error [37].

The term emotional exhaustion includes physical, emotional and behavioural symptoms. Stressful events or continuous challenges in an individual’s life, especially long-lasting ones, lead to a state of emotional exhaustion or fatigue. Emotional symptoms include anxiety, apathy, depression, feelings of hopelessness, feelings of helplessness or captivity, irritability, lack of motivation and nervousness [38].

According to various authors [3,26,37,38], it is evident that emotional exhaustion increases with the number of working hours per day, subjective feeling of a lack of sleep, sense of responsibility for organising work in officer occupations, separation from family and—very importantly, as it can be moderated—with insufficient support from superiors on the ship itself or in the management ashore. In the mentioned studies, emotional exhaustion was increased on average by 10.8%: it was detected in 10.7% of officers, in 4.5% of lower crew ranks and in 25.0% of galley staff.

An alarmingly high level of anxiety was recorded among deck officers on passenger ships aged 36–55, and from 18–25 years, followed by deck officers on cargo ships aged 26 to 36.

Stress is caused by any internal or external stimulus that exceeds the total capacity of the individual. Given the exposure and severity of events, the long-term psychological stress results in changes in homeostasis, life-threatening effects and death [39].

Similar research has shown that psychological stress on board occurs more in higher education or specialised secondary education graduates and significantly more in the age groups 35–44 and 45–54. According to this research, the occurrence of psychological stress was mostly influenced by work in the environment requiring increased strain on vision and vibration. In addition, it has been found that depression occurs more often at sea than on land, that emotional instability is also affected by improper work and rest regimes due to changing time zones, and disrupted regular sex life [40]. How early psychological stress appears can be seen from the research of the same authors, conducted on Lithuanian and Latvian seafarers, where 57.5% of Latvian seafarers and 46.1% of Lithuanian seafarers experienced the occurrence of psychological stress on average 2.7–2.8 months from the start of the voyage [41].

Our research has produced interesting data for deck officers employed on yachts where a decrease in stress and nervousness with the number of years of life is recorded, while, on cargo ships, stress and nervousness are present throughout the entire seafaring life. We assume that motivational factors have the influence on the above results because it is easier to motivate seafarers for shorter tasks (as a rule, yachting is a seasonal activity), compared to the positions of seafarers in the merchant navy. Accordingly, the research conducted on Danish maritime officers and petty officers highlights the length of stay at home and level of responsibility and challenge as work motivators, while the main demotivating factors include the absence from home, human resources management of the shipping company and regulatory requirements [42].

5. Conclusions

Compared to the vast majority of occupations on land, the profession of a seafarer has special features that should not be neglected, primarily the fact that they live and work in a closed and isolated environment that a seafarer cannot leave instantly and straight away, regardless of events and circumstances.

In all jobs, including maritime occupations, it is evident that management responsibility is more often associated with higher levels of stress. It is important to consider the specific features of these occupations and perform a variety of research in order to reduce emotional exhaustion among seafarers, preserve their mental and physical health and, consequently, reduce human error and increase safety. Raising the seafarers’ mental strength and greater self-control can be achieved, in part, through education and training of leadership skills, through improvement of communication skills, by providing greater institutional and corporate support to seafarers and adjusting sleep–wake cycles not only to work requirements but, if and when possible, to individuals.

The results of various studies show that most of the stress stems from work tasks and the work environment, and basically lies at the psycho-social level of the problem.

Bayesian networks can help predict the risk of human error on board—in this case, the human error due to fatigue, stress and anxiety. The model can be applied and extended, as appropriate, to other psychological factors that increase or decrease the possibility of human error. It is applicable in all areas of navigation and on all types of vessels, depending on the input components. The Bayesian network constructed for this paper allows visualisation of the combination of the worst influencing factors for mental condition across relevant categories, dividing seafarers by age, type of vessel and role on board. Using the obtained results, it is possible to improve the psychological condition of seafarers on board by introducing certain measures such as increasing the number of hours of sleep, reducing working hours and workload, improving living spaces and shortening the time spent on the vessel. The results obtained indicate the significance of the project for the safety and efficiency of seafarers and suggest expanding future research to include a larger pool of subjects to be evaluated across a greater range of relevant categories. In order to enhance the quality of model creation, future models need to involve more seafarers older than 56 and a larger number of chief engineers.