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

, H.B. Usluer

1,2

, A. Akturan

& B.E. Efiloğlu

Piri Reis University, Istanbul, Turkey

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

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 sobering—but 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.

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

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

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 Code

Item Content (Turkish)

English Translation

Factor 1:

Psychological

Well-being and

Adaptation

VAR00005

Gemide kendimi yalnız

hissediyorum.

I feel lonely on the ship.

VAR00006

Gemide bulunmaktan

mutlu değilim

I am not happy being on

the ship.

VAR00008

Denize çıkmadan önceki

halime göre daha sinirli

bir yapıya sahibim

I have a more irritable

temperament compared

to before going to sea.

VAR00011

Gemide uyku düzenimi

ayarlayamıyorum

I cannot regulate my

sleep pattern on the

ship.

VAR00014

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.

VAR00015

Gemide sefer süresi

uzadıkça yaşanan

tartışmalar da artıyor.

As the voyage duration

increases, arguments on

the ship also increase.

VAR00018

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.

VAR00020

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

VAR00004

Gemideki çok

ulusluluktan

kaynaklanan kültür farkı

beni olumsuz etkiliyor.

The cultural differences

arising from

multinationality on the

ship negatively affect

me.

VAR00009

Tanımadığım insanlarla

bir arada yaşamak beni

tedirgin ediyor.

Living together with

people I don’t know

makes me

uncomfortable.

VAR00010

Çalıştığım insanlarla bir

arada yaşamak beni

olumsuz etkiliyor.

Living together with the

people I work with

negatively affects me.

VAR00012

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.

VAR00013

Gemideki insanlara karşı

güvensizlik yaşıyorum.

I experience distrust

towards people on the

ship.

VAR00017

Gemideyken sağlık

problemlerim artıyor.

(Mide bulantısı, ağrı,

ateş basması vb.)

My health problems

increase while on the

ship. (Nausea, pain, hot

flashes, etc.)

VAR00019

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

VAR00001

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.

VAR00002

Seferden döndükten

sonra karadaki hayata

alışmakta zorlanıyorum.

I have difficulty

adapting to life ashore

after returning from a

voyage.

VAR00003

Denizde kaldıkça

iletişim gücümü

kaybediyorum.

I lose my

communication skills the

longer I stay at sea.

VAR00007

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 (α =

0.904), Factor 2 (α = 0.854), and Factor 3 (α = 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.

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 (α = 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

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

I feel lonely on the ship.

1 2 3 4 5

I am not happy being on the ship.

1 2 3 4 5

I have a more irritable temperament

compared to before going to sea.

1 2 3 4 5

I cannot regulate my sleep pattern on the

ship.

1 2 3 4 5

I no longer want to work on the ship, but my

financial concerns prevent this.

1 2 3 4 5

As the voyage duration increases, arguments

on the ship also increase.

1 2 3 4 5

I think I frequently encounter people with

mental health problems on the ships I work

on.

1 2 3 4 5

I think working in a profession far from

shores negatively affects my mental health.

1 2 3 4 5

The cultural differences arising from

multinationality on the ship negatively affect

me.

1 2 3 4 5

Living together with people I don’t know

makes me uncomfortable.

1 2 3 4 5

Living together with the people I work with

negatively affects me.

1 2 3 4 5

I cannot adapt to the meal schedule on the

ship, and being hungry makes me angry.

1 2 3 4 5

I experience distrust towards people on the

ship.

1 2 3 4 5

My health problems increase while on the

ship. (Nausea, pain, hot flashes, etc.)

1 2 3 4 5

I have difficulty tolerating problems

(personal) experienced on the ship.

1 2 3 4 5

Being away from land for a long time

negatively affects my relationships with my

family.

1 2 3 4 5

I have difficulty adapting to life ashore after

returning from a voyage.

1 2 3 4 5

I lose my communication skills the longer I

stay at sea.

1 2 3 4 5

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