39
1 INTRODUCTION
The well-being of seafarers has increasingly become a
critical area of concern in maritime research due to the
unique psychological stressors inherent in their
profession. Seafarers face prolonged isolation,
demanding work conditions, and restricted access to
mental health resources, which collectively contribute
to heightened psychological distress [16] [21] [22].
Despite these challenges, research on seafarers' mental
health remains fragmented, and there is a notable lack
of standardized psychological assessment instruments
tailored to this occupational group. Without robust
measurement tools, understanding and addressing
seafarers’ psychological well-being remains limited
[22], hindering the development of targeted
Development of a New Instrument for Measuring
Psychological Factors Specific to the Activity
of Seafarers
A. Arslan
1
, H.B. Usluer
1,2
, A. Akturan
1
& B.E. Efiloğlu
1
1
Piri Reis University, Istanbul, Turkey
2
Galatasaray University, Istanbul, Turkey
ABSTRACT:Researchers are increasingly recognizing the importance of seafarers' psychological well-being in
maritime contexts, reflecting the profound mental health challenges associated with life at sea. Seafarers endure
extended periods of isolation, demanding work schedules, and restricted access to psychosocial support, all of
which contribute to elevated levels of anxiety, depression, and fatigue. Although these issues are well-
documented, the field lacks a standardized psychological assessment tool specifically designed for this
occupational group. Existing instruments, such as the Psychological General Well-Being Index (PGWBI) and the
Symptom Checklist-90 (SCL-90), offer limited insight into the unique stressors faced by seafarers. Consequently,
this paper advocates for the development of a psychometrically sound, occupation-specific psychological scale to
assess seafarers’ mental health.
Based on a comprehensive literature review, the study identifies core psychological constructs relevant to
seafaring, including occupational stress, isolation, resilience, job satisfaction, and mental health symptoms. The
proposed methodology encompasses a multi-phase approach, involving construct identification, item
development, scale validation through exploratory and confirmatory factor analyses, and pilot testing with a
representative sample of seafarers. Cultural and contextual sensitivity is emphasized throughout, acknowledging
the diversity of maritime crews.
The development of this specialized tool is crucial for improving mental health interventions, enhancing
operational safety, and supporting the long-term well-being of maritime personnel. A validated instrument
would enable maritime organizations, researchers, and policymakers to systematically evaluate psychological
risks, implement timely support mechanisms, and foster healthier work environments. Furthermore, it holds the
potential to inform policy reforms and occupational health practices, ensuring that seafarers receive the targeted
mental health care they require. In doing so, this research aims to valorise the importance of psychology in
maritime affairs in order to promote sustainable workforce well-being across the global maritime industry.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 19
Number 1
March 2025
DOI: 10.12716/1001.19.01.05
40
interventions. Existing literature identifies common
mental health issues among seafarers, including
anxiety, depression, and chronic fatigue [1]. These
psychological stressors are often exacerbated by
operational demands, social isolation, and insufficient
coping mechanisms. Additionally, the COVID-19
pandemic has intensified these challenges, further
underscoring the urgent need for systematic
assessment tools [2]. While several studies have
explored psychological risks in maritime work, most
rely on general mental health indices that may not fully
capture the distinct stressors faced by seafarers [3].
Psychosocial factors, such as work environment, crew
relationships, and cultural diversity, further shape
seafarers' psychological resilience [4]. Research
highlights that mental health and job satisfaction are
interlinked [24], influencing both personal well-being
and operational efficiency [5]. Jiang et al. [23] report
that the annual incidence of mental illness among
seafarers is 3.9% per 100,000 individuals. Recent
epidemiological work paints a soberingbut far less
extreme—picture. Long‑run mortality analyses
indicate that suicide has historically represented about
6 % of all seafarer deaths (1 011/17 026 deaths,
1960‑2009). Contemporary insurer records from Gard
[25] show a slightly higher share, 11 % of 427 crew
deaths between 2019 and 2023. In survey data the
problem manifests earlier in the causal chain: a global
study of 1 572 seafarers found that 20 % reported
suicidal ideation in the preceding two weeks. These
figures underscore the urgency of systematic
assessment while avoiding the implausible claim that
one‑third of all seafarers take their own lives. [26].
However, the absence of a specialized psychological
assessment tool limits the ability to systematically
evaluate these factors and implement meaningful
workplace interventions.
Given these gaps, this paper underscores the
pressing need to develop a psychometrically sound
instrument to assess seafarers' psychological well-
being. Such a tool would enable more accurate
evaluations of mental health risks, inform intervention
strategies, and ultimately enhance the welfare and
operational effectiveness of maritime workers. The
following sections explore the significance of
measuring seafarers' psychology, the absence of
appropriate instruments, and the essential components
required to develop a valid and reliable assessment
tool.
2 THE IMPORTANCE OF MEASURING
PSYCHOLOGICAL FACTORS SPECIFIC TO THE
ACTIVITY OF SEAFARERS
Seafarers experience a distinct set of occupational
stressors, including extended work hours, social
isolation, and demanding physical environments.
These factors can lead to severe psychological
stressors, including anxiety, depressive symptoms,
and chronic fatigue, each of which affects both personal
well-being and maritime operational safety [1] [3].
Thus, measuring seafarers' psychological health is vital
for improving individual outcomes and ensuring
efficient maritime operations.
Existing studies highlight the correlation between
psychological factors and maritime safety. For
example, the Psychological General Well-Being Index
(PGWBI) has been employed to evaluate mental health
in seafarers, revealing high incidences of anxiety,
depression, and sleep disorders [1]. Similarly, Carrera
et al. [2] emphasize that workload stressors
significantly contribute to seafarers' psychological
strain, reinforcing the necessity for assessment
methods tailored to this workforce. Addressing these
psychological parameters is crucial for mitigating
chronic fatigue and reducing mental health-related
safety risks at sea. Furthermore, research by McVeigh
et al. [5] identifies occupational predictors of perceived
stress and job satisfaction, demonstrating that certain
work-related and personal factors strongly influence
mental health outcomes. Understanding these
variables through systematic psychological
assessments can facilitate timely interventions,
enhance retention in the maritime workforce, and
prevent job-related psychological deterioration [6].
The COVID-19 pandemic has further amplified
seafarers’ psychological challenges, exacerbated social
isolation and increasing uncertainty in maritime
operations [7] [8]. These evolving stressors highlight
the importance of adaptive and comprehensive mental
health assessment tools that can track emerging
psychological risks. In addition to mental health
outcomes, seafarer psychology directly influences job
performance. Studies suggest that fatigue-related
psychological stress is a leading contributor to human
error in maritime operations, increasing the likelihood
of accidents [9]. Therefore, a standardized
psychological assessment instrument could serve as a
preventive tool, allowing maritime organizations to
implement targeted interventions and enhance overall
safety.
Despite the clear need for systematic psychological
assessments, the maritime industry lacks standardized
evaluation methods specifically designed for seafarers
[2]. Existing tools often fail to account for seafarers’
unique occupational context, necessitating the
development of specialized instruments that capture
the nuances of maritime mental health.
2.1 The Absence of Instruments to Measure Psychological
Factors in Seafaring
While understanding of maritime workers'
psychological difficulties has expanded, the absence of
standardized psychological assessment instruments
remains a major research gap. Current studies
acknowledge that while general mental health
measures such as the PGWBI and the Symptom
Checklist (SCL-90) have been applied to maritime
populations, they lack the specificity required to
address the unique stressors of seafaring [1] [10].
Carrera et al. [2] note that existing assessment
methodologies often fail to capture seafarers’ dynamic
work conditions, including fluctuating stress levels
due to voyage duration, environmental factors, and
cultural diversity aboard ships. McVeigh et al. [5]
further argue that psychological instruments designed
for general occupational settings do not adequately
address the complexities of maritime work. These
findings indicate a pressing need for tailored tools that
can assess psychological resilience, occupational stress,
and the broader psychosocial environment of seafarers.
41
Additionally, region-specific studies emphasize the
importance of contextual sensitivity in psychological
assessment. For instance, Ekawati [11] explores
Indonesian seafarers' psychosocial risks, highlighting
the need for instruments that consider cultural and
geographical variations. Similarly, research by Nittari
et al. [3] identifies key contributors to seafarers' mood
disorders, including social isolation and long work
shifts, stressing the importance of developing
specialized assessment tools. Without reliable
psychological measurement tools, maritime
organizations lack the necessary data to implement
effective mental health strategies. The absence of
standardized assessment instruments not only limits
research advancements but also hinders industry-wide
efforts to improve mental health support systems for
seafarers.
2.2 Developing A Sound and Valid Instrument For
Psychological Factors In Seafaring
A comprehensive psychological assessment tool for
seafarers must consider multiple dimensions,
including occupational stressors, mental health
symptoms, and coping mechanisms. A valid
instrument should incorporate factors such as
isolation, job satisfaction, fatigue, and interpersonal
relationships, all of which significantly impact
seafarers' psychological well-being [5] [10]. The
development of such an instrument should follow
established psychometric methodologies, including
exploratory and confirmatory factor analyses, to
ensure reliability and validity [13]. Additionally,
integrating existing frameworks, such as the SCL-90
and PGWBI, into the scale's design could enhance its
applicability to maritime settings while addressing
specific occupational stressors [1] [3].
Recent studies emphasize the role of workplace
interventions in mitigating psychological distress. For
instance, Ekawati [11] highlights the need for
psychosocial training tailored to seafarers, suggesting
that assessment tools should measure both mental
health symptoms and resilience factors. Similarly,
research on organizational support structures indicates
that job satisfaction and psychological well-being are
closely linked, reinforcing the importance of including
workplace satisfaction metrics in the instrument [17].
The ongoing evolution of the maritime industry,
coupled with emerging mental health challenges,
necessitates the development of a standardized
psychological assessment tool. By systematically
evaluating seafarers' mental health, such an instrument
would provide valuable insights for both researchers
and maritime organizations, ultimately enhancing the
well-being, safety, and efficiency of seafarers
worldwide.
Seafarers' psychological welfare constitutes a
critical factor for both personal health outcomes and
operational safety in maritime environments.
However, the absence of standardized assessment
tools limits the ability to identify and address mental
health risks effectively. Developing a specialized
instrument tailored to seafarers' unique occupational
challenges is imperative for advancing research,
informing interventions, and fostering a supportive
maritime work environment. A validated
psychological scale would serve as a crucial tool for
improving seafarers' mental health, thereby
contributing to safer and more sustainable maritime
operations.
3 METHODOLOGY
The development of a seafarer psychology scale
necessitates a comprehensive, multi-phase
methodological approach designed to address the
unique psychological challenges faced by maritime
workers. This methodology encompasses the
identification of relevant psychological constructs,
instrument design, scale validation, and pilot testing to
ensure applicability within the seafaring context. The
resulting instrument aims to provide a reliable and
valid measure of the distinctive psychological
experiences and challenges encountered by seafarers,
addressing a significant gap in existing psychological
assessment tools.
3.1 Identification of Constructs
The first phase of scale development included a
systematic literature review to identify psychological
constructs specifically relevant to the seafaring
environment. Extensive review of maritime
psychology literature revealed numerous stressors and
psychological challenges unique to seafarers, including
elevated levels of occupational stress, anxiety,
depression, and burnout [5] [2] [13]. McVeigh et al. [5]
highlighted that the maritime industry presents
distinctive stressors that significantly impact mental
health, including heavy workloads, prolonged
separation from family, and psychosocial challenges
inherent to life at sea. Additional research identified
various factors influencing seafarers’ mental health,
such as occupational demands, psychosocial work
environments, and limited access to mental health
resources [10][8] [1].
Based on this literature, we identified key
constructs for measurement, including job stress,
psychological well-being, adjustment to maritime life,
and resilience. These constructs were selected based on
established frameworks from previous studies [2] [8].
To enhance ecological validity and ensure relevance to
the target population, we supplemented the literature
review with qualitative insights obtained through
focus groups and interviews [4] [12]. Specifically, we
adapted items from existing psychological scales to the
seafaring context and conducted focus group sessions
with 12 experienced captains currently on active duty.
Additionally, we interviewed three psychologists
specializing in seafarer mental health to gain expert
perspectives on the psychological challenges unique to
this population.
3.2 Scale Development
The second phase focused on developing scale items
that effectively measure the identified constructs. We
employed a mixed-methods approach, utilizing both
Likert-scale items for quantitative assessment and
open-ended questions to capture qualitative data. This
approach aligns with methodologies demonstrated in
42
previous studies on seafarers’ mental health
assessment [14][1][15].
Item development prioritized clarity, conciseness,
and contextual relevance to the seafaring environment,
enhancing response validity. The scale structure was
designed to facilitate differentiation between specific
psychological states, including anxiety, depression,
and job satisfaction levels. This approach is consistent
with existing literature on measurement tools for
assessing mental health and well-being among
seafarers [2][12][6].
The initial item pool consisted of 53 items, which
were subsequently refined to 36 items following
preliminary pilot testing. This refinement process
incorporated feedback from the pilot study
participants, allowing for necessary revisions to
enhance the scale’s psychometric properties.
Furthermore, we integrated feedback mechanisms
within the pilot study to validate user experience and
identify potential areas for improvement, ultimately
enhancing the instrument’s reliability and utility [16]
[17].
3.2.1 Sample 1: Validation Process and Results
3.2.1.1 Sample Characteristics.
The initial validation sample (Sample 1) consisted
of 150 seafarers recruited through convenience
sampling via the authors’ professional networks. The
online survey remained active for four months. The
demographic profile of Sample 1 revealed a significant
gender imbalance, with males comprising 87.2% (130
respondents) and females 11.4% (17 respondents) of
the sample. The age distribution was concentrated in
the middle age ranges, with 47.7% (71 respondents)
aged 31-45 years, 35.6% (53 respondents) aged 18-30
years, 12.8% (19 respondents) aged 46-65 years, and
2.7% (4 respondents) aged 66 years and above.
Regarding marital status and family structure,
43.0% (64 respondents) were single, 37.6% (56
respondents) were married, and 17.4% (26
respondents) were widowed or divorced.
Additionally, 59.1% (88 respondents) reported having
no children, while 37.6% (56 respondents) had
children. The professional profile revealed a
hierarchical structure within the maritime industry,
with positions distributed as follows: Captain (26.2%,
39 respondents), Chief Engineer (15.4%, 23
respondents), Trainee (12.1%, 18 respondents), Second
Officer (11.4%, 17 respondents), Third Officer (8.7%, 13
respondents), and First Officer (6.7%, 10 respondents).
The experience distribution showed a bimodal
pattern: 0-5 years (28.2%, 42 respondents), 11-15 years
(20.1%, 30 respondents), 16-20 years (20.1%, 30
respondents), 6-10 years (16.8%, 25 respondents), 21-25
years (8.7%, 13 respondents), and 26+ years (2.7%, 4
respondents). When asked about the most challenging
ship types to work on, respondents identified Tankers
(32.2%, 48 respondents), Container ships (18.8%, 28
respondents), Bulk carriers (14.1%, 21 respondents),
Dry cargo vessels (12.1%, 18 respondents), Military
vessels (6.7%, 10 respondents), and LNG/LPG carriers
(5.4%, 8 respondents). The distribution of ship types
where respondents spent most of their careers included
Bulk carriers (24.8%, 37 respondents), Dry cargo
vessels (23.5%, 35 respondents), Tankers (20.1%, 30
respondents), Container ships (13.4%, 20 respondents),
and Military vessels (7.4%, 11 respondents).
3.2.1.2 Exploratory Factor Analysis
Following data collection from Sample 1, we
employed EFA to uncover the fundamental
dimensionality of the assessment tool. The ‘minimum
residual’ extraction method was used in combination
with an ‘oblimin’ rotation to allow for correlated
factors. Prior to conducting the EFA, we assessed the
suitability of the data for factor analysis using Bartlett’s
Test of Sphericity and the Kaiser-Meyer-Olkin (KMO)
Measure of Sampling Adequacy.
Bartlett’s Test of Sphericity yielded a chi-square
value of 2523 (df = 171, p < .001), confirming the
factorability of the correlation matrix as it deviated
significantly from an identity matrix. The overall KMO
value was 0.933, well above the recommended
threshold of 0.6, confirming the sampling adequacy for
factor analysis. The fact that the individual KMO
values of the items ranged between 0.860 and 0.965
supports the suitability of the data for factor analysis.
The EFA results revealed a three-factor solution that
best represented the fundamental framework of the
scale. The factor loadings matrix showed clear patterns
of item loadings on the three factors:
Factor 1 included 11 items (S, M, N, Q, E, J, O, G, P,
D, R) with factor loadings ranging from 0.418 to
0.809
Factor 2 included 5 items (H, I, C, L, K) with factor
loadings ranging from 0.477 to 0.895
Factor 3 included 3 items (B, A, F) with factor
loadings ranging from 0.404 to 0.816
The three-factor solution explained 55.0% of the
total variance, with Factor 1 accounting for 25.7%,
Factor 2 for 18.2%, and Factor 3 for 11.0% of the
variance. The inter-factor correlation matrix indicated
moderate to strong correlations between the factors:
Factor 1 and Factor 2 (r = 0.716), Factor 1 and Factor 3
(r = 0.533), and Factor 2 and Factor 3 (r = 0.510). These
correlations support the use of an oblique rotation
method and suggest that the factors represent related
but distinct constructs.
3.2.1.3 Factor Structure and Scale Items
Based on the content analysis of the scale items, the
three factors identified in the exploratory and
confirmatory factor analyses were named as follows:
1. Psychological Well-being and Adaptation (Factor
1): This factor encompasses items related to
emotional and psychological responses to seafaring
life, including feelings of loneliness, unhappiness,
irritability, sleep disturbances, and overall negative
impacts on mental health.
2. Interpersonal and Environmental Challenges
(Factor 2): This factor includes items related to
difficulties in adapting to the social and physical
environment on ships, such as multicultural
challenges, discomfort with living among strangers,
food adaptation issues, trust concerns, and health
problems.
3. Social Isolation and Communication Difficulties
(Factor 3): This factor comprises items related to the
impact of prolonged separation from land and
43
family, difficulties in maintaining communication
skills, and challenges in readjusting to life ashore.
Table 1 presents the complete list of items for each
factor in the final version of the Seafarer Psychology
Scale.
Table 1. Factors and Items of the Seafarer Psychology Scale
Factor
Item Content (Turkish)
English Translation
Factor 1:
Psychological
Well-being and
Adaptation
Gemide kendimi yalnız
hissediyorum.
I feel lonely on the ship.
Gemide bulunmaktan
mutlu değilim
I am not happy being on
the ship.
Denize çıkmadan önceki
halime göre daha sinirli
bir yapıya sahibim
I have a more irritable
temperament compared
to before going to sea.
Gemide uyku düzenimi
ayarlayamıyorum
I cannot regulate my
sleep pattern on the
ship.
Artık gemide çalışmak
istemiyorum fakat
maddi kaygılarım
bunun önüne geçiyor
I no longer want to work
on the ship, but my
financial concerns
prevent this.
Gemide sefer süresi
uzadıkça yaşanan
tartışmalar da artıyor.
As the voyage duration
increases, arguments on
the ship also increase.
Çalıştığım gemilerde ruh
sağlığı bozuk insanlarla
sıklıkla karşılaştığımı
düşünüyorum.
I think I frequently
encounter people with
mental health problems
on the ships I work on.
Kıyılardan uzak bir
meslekte çalışmanın ruh
sağlığımı olumsuz
etkilediğini
düşünüyorum
I think working in a
profession far from
shores negatively affects
my mental health.
Factor 2:
Interpersonal
and
Environmental
Challenges
Gemideki çok
ulusluluktan
kaynaklanan kültür farkı
beni olumsuz etkiliyor.
The cultural differences
arising from
multinationality on the
ship negatively affect
me.
Tanımadığım insanlarla
bir arada yaşamak beni
tedirgin ediyor.
Living together with
people I don’t know
makes me
uncomfortable.
Çalıştığım insanlarla bir
arada yaşamak beni
olumsuz etkiliyor.
Living together with the
people I work with
negatively affects me.
Gemideki yemek
düzenine alışamıyorum
ve aç kalmak beni
sinirlendiriyor.
I cannot adapt to the
meal schedule on the
ship, and being hungry
makes me angry.
Gemideki insanlara karşı
güvensizlik yaşıyorum.
I experience distrust
towards people on the
ship.
Gemideyken sağlık
problemlerim artıyor.
(Mide bulantısı, ağrı,
ateş basması vb.)
My health problems
increase while on the
ship. (Nausea, pain, hot
flashes, etc.)
Gemide yaşanan
problemleri (kişisel)
tolere etmekte güçlük
çekiyorum.
I have difficulty
tolerating problems
(personal) experienced
on the ship.
Factor 3: Social
Isolation and
Communication
Difficulties
Uzun süre karadan uzak
kalmak, ailemle olan
ilişkilerimi kötü
etkiliyor.
Being away from land
for a long time
negatively affects my
relationships with my
family.
Seferden döndükten
sonra karadaki hayata
alışmakta zorlanıyorum.
I have difficulty
adapting to life ashore
after returning from a
voyage.
Denizde kaldıkça
iletişim gücümü
kaybediyorum.
I lose my
communication skills the
longer I stay at sea.
Gemide kurulan kısıtlı
iletişim beni daha içe
kapanık hale getirdi.
The limited
communication
established on the ship
has made me more
introverted.
3.2.1.4 Model Fit and Reliability
The model fit indices for the three-factor solution
indicated an acceptable fit to the data. The Root Mean
Square Error of Approximation (RMSEA) was 0.0769
(90% CI: 0.0651-0.0892), which is below the
recommended threshold of 0.08 for a reasonable fit.
The Tucker-Lewis Index (TLI) was 0.904, exceeding the
recommended threshold of 0.90 for a good fit. The
model chi-square test was significant (χ² = 270, df = 117,
p < .001), which is common in larger samples and does
not necessarily indicate poor fit when other indices
suggest adequate fit.
Reliability analyses were conducted to evaluate the
internal consistency of the scale and its subscales. The
overall scale demonstrated excellent reliability with a
Cronbach’s alpha of 0.941. The reliability statistics for
the individual factors were also strong: Factor 1 =
0.904), Factor 2 = 0.854), and Factor 3 = 0.828).
Item-level reliability statistics indicated that all items
contributed positively to the scale’s reliability, with no
substantial increases in Cronbach’s alpha if any item
were deleted (values ranging from 0.936 to 0.940).
These results from Sample 1 provided strong initial
evidence for the psychometric properties of the
seafarer psychology scale, supporting a three-factor
structure with good reliability and acceptable model
fit. Based on these findings, we proceeded to further
validate the scale with a second sample using
confirmatory factor analysis.
3.2.2 Sample 2: Confirmatory Analysis and
Convergent/Divergent Validity
3.2.2.1 Sample Characteristics
Following the exploratory factor analysis with
Sample 1, we sought to confirm the three-factor
structure with a larger, independent sample (Sample
2). This sample consisted of 221 maritime
professionals, with 95.02% male and 4.98% female
participants. The age distribution was similar to
Sample 1, with the majority aged 31-45 years (51.13%),
followed by 18-30 years (37.56%), 46-65 years (10.86%),
and 66 and above (0.45%). Regarding marital status,
56.11% were married and 43.89% were single, with
54.30% having no children and 45.70% having children.
The professional profile of Sample 2 included
Captains (21.72%), First Officers (16.74%), Second
Officers (13.57%), Second Engineers (10.86%), Third
Officers (9.95%), Chief Engineers (9.05%), and Trainees
(7.69%), among others. Years of offshore experience
ranged from 0-5 years (32.58%) to 26+ years (1.81%),
with the majority having 0-10 years of experience
(59.73%). Participants reported most experience with
Dry Cargo vessels (39.82%) and Tankers (26.70%),
while identifying Tankers (35.29%) and Dry Cargo
vessels (18.10%) as the most difficult ship types.
Notably, 84.62% of participants indicated they had
considered transitioning to onshore positions.
3.2.2.2 Confirmatory Factor Analysis
We conducted a confirmatory factor analysis (CFA)
to validate the three-factor structure identified in the
exploratory phase. The CFA model specified the three
factors with their respective indicators as identified in
the EFA. The factor loadings from the CFA showed
strong relationships between the indicators and their
respective factors, with standardized estimates ranging
from 0.572 to 0.853 for Factor 1, 0.601 to 0.834 for Factor
2, and 0.577 to 0.812 for Factor 3. All factor loadings
were statistically significant (p < .001), providing
strong support for the hypothesized factor structure.
44
The factor covariances indicated strong
relationships between the three factors, with
standardized estimates of 0.813 between Factor 1 and
Factor 2, 0.860 between Factor 1 and Factor 3, and 0.887
between Factor 2 and Factor 3. These high correlations
suggest that while the factors represent distinct
constructs, they are closely related aspects of seafarers’
psychological experiences.
The model fit indices for the CFA demonstrated a
good fit to the data. The Comparative Fit Index (CFI)
was 0.912, exceeding the recommended threshold of
0.90 for a good fit. The Tucker-Lewis Index (TLI) was
0.898, approaching the recommended threshold of
0.90. The Standardized Root Mean Square Residual
(SRMR) was 0.0516, well below the recommended
threshold of 0.08 for a good fit. The Root Mean Square
Error of Approximation (RMSEA) was 0.0797 (90% CI:
0.0697-0.0898), which is at the borderline of the
recommended threshold of 0.08 for a reasonable fit.
The chi-square test was significant (χ² = 394, df = 164, p
< .001), yielding a chi-square/df ratio of 2.40, which is
below the recommended threshold of 3.0 for a
reasonable fit.
3.2.2.3 Reliability Analysis
Reliability analyses for Sample 2 confirmed the
strong internal consistency of the scale. The overall
scale showed outstanding reliability with a Cronbach’s
alpha of 0.942 and McDonald’s omega of 0.897. The
mean score for the scale was 3.33. Item-level reliability
statistics indicated that all items contributed positively
to the scale’s reliability, with no substantial increases in
Cronbach’s alpha or McDonald’s omega if any item
were deleted (values ranging from 0.937 to 0.943).
Convergent and Divergent Validity
To establish convergent and divergent validity, we
examined correlations between our seafarer
psychology scale (Psiko) and three established
measures:
1. The Turkish version of the Work And Meaning
Inventory (WAMI) [18]
2. The Turkish version of the Multidimensional Work
Motivation Scale [19]
3. The Turkish version of the Perceived Stress Scale
(PSS) [20]
The correlation analysis revealed significant
relationships that supported both convergent and
divergent validity. The seafarer psychology scale
showed a significant positive correlation with the
Perceived Stress Scale (r = 0.223, p = 0.006), indicating
convergent validity as both measures assess stress-
related constructs. Conversely, the seafarer psychology
scale demonstrated significant negative correlations
with the Work And Meaning Inventory (r = -0.680, p <
.001) and the Multidimensional Work Motivation Scale
(r = -0.286, p < .001), providing evidence of divergent
validity as these scales measure distinct constructs
(meaning and motivation) that would be expected to
have inverse relationships with psychological distress.
Additional correlations between the validation
measures further supported the nomological network:
the Perceived Stress Scale was negatively correlated
with both the Work and Meaning Inventory (r = -0.221,
p = 0.006) and the Multidimensional Work Motivation
Scale (r = -0.478, p < .001), while the Work And Meaning
Inventory and the Multidimensional Work Motivation
Scale were positively correlated (r = 0.365, p < .001).
Descriptive Statistics
Descriptive statistics for Sample 2 (N = 221)
revealed the following patterns:
Perceived Stress Scale: Mean = 2.83 (SD = 0.501),
Median = 2.83, Range = 1.57-5.00
Work And Meaning Inventory: Mean = 2.98 (SD =
1.11), Median = 2.98, Range = 1.00-5.00
Multidimensional Work Motivation Scale: Mean =
3.66 (SD = 1.01), Median = 3.66, Range = 1.00-6.32
Seafarer Psychology Scale (Psiko): Mean = 3.17 (SD
= 1.13), Median = 3.30, Range = 1.00-5.00
The Shapiro-Wilk test indicated non-normal
distributions for the Perceived Stress Scale, Work And
Meaning Inventory, and Seafarer Psychology Scale (p <
.001), while the Multidimensional Work Motivation
Scale showed a normal distribution (p = 0.314).
4 CONCLUSION
The methodology for developing the seafarer
psychology scale represents a detailed and systematic
approach spanning multiple phases, from the
identification of relevant psychological constructs to
the validation and dissemination of the final
instrument. Through rigorous methodological
procedures, including comprehensive literature
review, qualitative insights from industry experts,
careful item development, and thorough validation
processes with two independent samples, we have
developed a psychometrically sound instrument
tailored to the unique psychological challenges faced
by seafarers.
The exploratory factor analysis with Sample 1 (N =
150) demonstrated a robust three-factor structure
explaining 55% of the variance, with excellent
reliability = 0.941). The confirmatory factor analysis
with Sample 2 (N = 221) validated this structure,
demonstrating good model fit and strong factor
loadings. The convergent and divergent validity
analyses established the scale’s relationship with
related constructs, supporting its construct validity
within the nomological network of psychological
measures.
This process, grounded in existing empirical
research and innovative methodological practices,
contributes significantly to enhancing understanding
and support of seafarers’ mental health and well-being
within their unique and challenging occupational
context. The resulting scale provides a valuable tool for
assessing psychological factors specific to the maritime
environment, addressing a significant gap in existing
psychological assessment measures for this specialized
population.
4.1 Outlook and Next Steps
The present two‑sample validation establishes factorial
validity and internal consistency, yet a fully
standardised psychological test requires broader
evidence. Our next phase (2025‑2026) will therefore
(i) draw a stratified random sample of 1 000
seafarers across vessel types and flag states to produce
45
stable norms and cut‑off scores; (ii) conduct test‑retest
and inter‑rater reliability studies over typical tour
lengths 90 days); (iii) examine predictive validity
against safety incidents and medical‑leave records; and
(iv) translate/adapt the SPS into at least five IMO
working languages, following ITC/APA guidelines for
cross‑cultural test adaptation. These steps will move
the SPS toward the full quality standards required of a
psychological test and will furnish maritime
organisations with an evidence‑based screening tool
for targeted mental‑health interventions.
ACKNOWLEDGMENT
The Authors gratefully acknowledge the support of
Galatasaray University, Scientific Research Support
Programme under grant number of SOA-2023-1163.
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APPENDIX A: ADMINISTRATION SHEET (READY
FOR PHOTOCOPYING OR E‑SURVEY)
Item
Statement
1 = Strongly
Disagree …
5 = Strongly
Agree
1
I feel lonely on the ship.
1 2 3 4 5
2
I am not happy being on the ship.
1 2 3 4 5
3
I have a more irritable temperament
compared to before going to sea.
1 2 3 4 5
4
I cannot regulate my sleep pattern on the
ship.
1 2 3 4 5
5
I no longer want to work on the ship, but my
financial concerns prevent this.
1 2 3 4 5
6
As the voyage duration increases, arguments
on the ship also increase.
1 2 3 4 5
7
I think I frequently encounter people with
mental health problems on the ships I work
on.
1 2 3 4 5
46
8
I think working in a profession far from
shores negatively affects my mental health.
1 2 3 4 5
9
The cultural differences arising from
multinationality on the ship negatively affect
me.
1 2 3 4 5
10
Living together with people I don’t know
makes me uncomfortable.
1 2 3 4 5
11
Living together with the people I work with
negatively affects me.
1 2 3 4 5
12
I cannot adapt to the meal schedule on the
ship, and being hungry makes me angry.
1 2 3 4 5
13
I experience distrust towards people on the
ship.
1 2 3 4 5
14
My health problems increase while on the
ship. (Nausea, pain, hot flashes, etc.)
1 2 3 4 5
15
I have difficulty tolerating problems
(personal) experienced on the ship.
1 2 3 4 5
16
Being away from land for a long time
negatively affects my relationships with my
family.
1 2 3 4 5
17
I have difficulty adapting to life ashore after
returning from a voyage.
1 2 3 4 5
18
I lose my communication skills the longer I
stay at sea.
1 2 3 4 5
19
The limited communication established on
the ship has made me more introverted.
1 2 3 4 5
1. Scoring instructions (place on the second page)
Scale structure
* Factor 1 Psychological Well‑being & Adaptation* (8 items:
5, 6, 8, 11, 14, 15, 18, 20)
* Factor 2 Interpersonal & Environmental Challenges* (7 items:
4, 9, 10, 12, 13, 17, 19)
* Factor 3 Social Isolation & Communication* (4 items: 1, 2, 3, 7)
Response format 1 = Strongly disagree … 5 = Strongly agree. No
items are reverse‑scored.
Sub‑scale scores Mean the items in each factor.
Total SPS score Mean of all 19 items (range 1‑5). Higher
values = greater psychological strain.
Interim interpretive bands (based on Sample 2, N = 221)
SPS mean Interpretation z‑approx.
< 2.0 Low distress < ‑1 SD
2.0 3.5 Moderate (typical) 1 SD +0.3 SD
> 3.5 High‑risk, flag for follow‑up > +0.3 SD
(Cut‑offs will be refined once a larger normative sample is available.)
2. Psychometric summary (page 3)
Statistic Total scale F1 F2 F3
Cronbach α 0.94 0.90 0.85 0.83
McDonald ω 0.90 0.88 0.84 0.80
KMO (overall) 0.93
CFA fit (Sample 2) CFI = 0.912; RMSEA = 0.080; SRMR = 0.052