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Article

The Fear of War Scale (FOWARS): Development and Initial Validation

by
Kinga Kalcza-Janosi
*,†,
Ibolya Kotta
†,
Eszter Eniko Marschalko
† and
Kinga Szabo
†
Applied Psychology Department, Faculty of Psychology and Educational Sciences, Babeş-Bolyai University, 400084 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Soc. Sci. 2023, 12(5), 283; https://doi.org/10.3390/socsci12050283
Submission received: 28 February 2023 / Revised: 20 April 2023 / Accepted: 21 April 2023 / Published: 4 May 2023
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Abstract

:
The emergence of the Ukraine-Russia war in 2022 led to fear, worry and anxiety among individuals, mostly in the immediate neighboring countries of Ukraine. The purpose of the present study was to develop the fear of war scale (FOWARS), aiming to fill the gap in the literature that currently is scarce in valid assessment tools for measuring the fear of war. The sample of the study consisted of N = 1131 participants (n = 670 for group A, for EFA and n = 461 for group B, for CFA). Hungarian speaking participants, mainly from Romania and Hungary. Exploratory factor analysis (EFA) evinced a two-factor model of the newly developed scale, and the final version fulfilled the criteria of the confirmatory factor analysis (CFA). The 13-items FOWARS has robust psychometric properties and proves to be appropriate for a fear of war assessment in the general population. The phenomenon is measured by two factors, namely experiential and physiological dimensions of fear. The scale is available in the present paper in two languages: English and Hungarian.

1. Introduction

The news of the Ukraine-Russia war in February 2022 (Kirby 2022) has emotionally impacted people living in many European countries in the first days of war. The prevention of the escalation of warlike circumstances in Europe mobilized many governments. Humanitarian help for Ukrainian civilians was highly activated especially in the immediate neighboring countries of Ukraine (e.g., Romania, Hungary, Poland, etc.), where the civilians fled for their lives (Council on Foreign Relations 2022; Preventing a Wider European Conflict n.d.). In the context of the COVID-19 pandemic in which fear played a major role (Ahorsu et al. 2020; Tzur Bitan et al. 2020; Luo et al. 2021; Stănculescu 2022), the emergence of this war continued to bring new threats into everyday life. War, as a crisis, formerly was presented in history and in literature as the most eventful period in a nation’s psychology, as fear can have a destructive effect on well-being and can alter life on a whole continent (Armstrong-Jones 1917).
According to the core definition of contemporary psychology (APA Dictionary of Psychology n.d.), fear is a “basic, intense emotion aroused by the detection of imminent, identifiable threat, involving an immediate alarm reaction that mobilizes the organism by triggering a set of physiological changes”. Fear as an emotion can be interpreted in the context of individual experiences to a stimulus or situation. The emotion itself is connected to subjective experience (personally interpreted threats), physiological reactions (autonomic nervous system’s reactions) and behavioral facets (e.g., expression of fear) (The Science of Emotion 2019; Meiselman 2016; Fernandez-Álvarez et al. 2022). It can potentially give a higher impact to negative information processing in everyday functioning, but especially in crisis situations, holding an adaptive role (Baumeister et al. 2001). Fear can be interpreted as a state or a trait, even in crime related circumstances (Gabriel 2003). Armed conflict can disrupt the livelihoods of daily living both on an individual and collective level. The fear of violence during armed conflict and the fear of the loved one’s life plays an important role in the phenomenon and demographic variables evince as important associative of fear (Williams et al. 2018). In a maladaptive perspective, fear can motivate avoidance behavior and can contribute to a prolonged stress reaction which exhausts the body’s resources (Ropeik 2004) and can lead to toxic stress (Murray 2017; Shern et al. 2016; Franke 2014). The emergence of war and the related crisis in society activates fear in people, regardless of their status or age. The phenomenon is not related to indicators of mental health; people without psychological issues can also react with fear to warlike circumstances or news related to a possible nuclear war (Buzan 2009). Society can be affected by the presence of this reaction (Lederer 2012). The possible threats related to a war can be interpreted not only in the context of life or death, but also from the perspective of economic and financial consequences (Lee and Andrade 2011; Coyne and Mathers 2011).
Literature presents many fear assessment scales, developed and validated in many different countries. Fear of COVID-19 (Ahorsu et al. 2020; Tzur Bitan et al. 2020; Luo et al. 2021; Kotta et al. 2021; Stănculescu 2022), fear of death (Loo and Shea 1996) and fear of pain (Carleton and Asmundson 2009) can be screened with valid instruments.
A marked scarcity is present on instruments validated to assess fear of war or warlike circumstances. Fear of nuclear war was recently identified even in countries which are far from war zones (Lybarger 2020). To our knowledge, there is only one scale measuring fear of nuclear war in undergraduate participants, published a few decades ago, which comprises Despair, Urgency, and Denial as subscales (Chandler 1991) and has no factors on physiological or experiential reactions related to fear.
However, a short seven item single-factor War Anxiety Scale (WAS) (Surzykiewicz et al. 2022) was recently elaborated in Polish describing the common symptoms of anxiety disorders based on DSM-5 criteria (e.g., dizziness, sleep problems, distress, lack of appetite, nausea, fatigue and shortness of breath).
While anxiety is a response to an imprecise or unknown threat, fear is a reaction to a specific, observable danger (Barlow 2002). Fear and anxiety feel alike as both produce a similar stress response and they often occur together; nevertheless, these terms are not interchangeable. Fear is an emotion caused by a danger in the environment, while anxiety is considered a mental health condition, most often linked to anxiety disorders.
The threat of a possible outbreak of a war may lead to a diffuse, unfocused anxiety, but with the outbreak of the Ukrainian-Russian War in 2022, this vague threat became a real danger that generated definite fear in many.
Considering the lack of ecologically sound assessment instruments on fear of war, the development of a new scale in a geographical area which is close to the conflict zone (western neighboring countries of Ukraine), can add value to the literature of fear and its measurement, especially on physiological and experiential level.

Objective of the Study

As presented above, war fear assessment tools are missing from the literature. The lack of ecologically sound, standardized and valid assessment instruments motivated this study. The aim was the development and validation of the fear of war scale (FOWARS). The fear of war in this paper is conceptualized as the appreciation of personally becoming a victim of war directly or indirectly. The scale can be used to measure fear as a state, or in case of repetitive use, fluctuations of fear in war-related circumstances.
The newly developed scale focuses on the experiential presence of fear (based on subjective appraisal) and the associated physiological reactions to a definite external threat (signs of autonomic nervous system’s reaction). The behavioral aspects of fear (e.g., nonverbal expression of fear) were not in the focus of the present study, because these are more exposed to cultural and context-based interpretations (Meiselman 2016).
The utility and importance of a valid and reliable scale for the assessment of fear of war can contribute to better screening and targeted interventions to prevent toxic stress in the context of war.

2. Materials and Methods

2.1. Participants

A number of N = 1131 participants, mostly females, most of them from Hungary and fewer from Romania (Transylvania), completed the scale. All participants’ first language was Hungarian and were adults aged over 18 years. Only participants from Hungary and Romania were included in the final dataset. The sample was heterogeneous in terms of education and residency. For statistical analysis, participants were divided into two groups, Group A and Group B. CFA was performed on Group B, while all other calculations were performed on Group A. The sociodemographic characteristics of participants and the descriptive statistics of other measured variables are presented in Table 1.

2.2. Instruments

Development of the Fear of War Scale (FOWARS)

After an initial extensive literature review of general and specific fear scales, researchers pooled possible relevant items. The items were formulated based on four scales which measure specific fear: nuclear war anxiety scale (Chandler 1991) was the only available scale focusing specifically on the topic of war; the fear of vaccines subscale of the COVID-19 vaccine hesitancy scale (Kotta et al. 2021) measures exhaustively the physiological component of fear; the fear of COVID-19 scale (Ahorsu et al. 2020) and surgical fear questionnaire (Jankovic et al. 2020) cover the experiential component of fear. Considering that none of the available scales measure the fear of war expressly, no items from the above scales were adapted without reformulation. For example: the item “I am most afraid of Corona” was rewritten into “I am afraid of the war”. Items with similar content were excluded. Emphasis was put on covering emotional experiential symptoms and frequent physiological symptoms of fear. Furthermore, items for measuring fear of nuclear war and fear of death and personal human losses were also formulated. Second, based on the suggestions of an expert group of health and clinical psychologists, 4 items were deleted. The final 16-item version was then applied as the pilot study indicated that no changes were needed in wording. The initial fear of war scale (FOWARS) included 16 items. These items were initially formulated in English based on the literature and translated by a professional translator into Hungarian and also reviewed by a clinical psychologist. The research team compared the two versions, discrepancies were discussed and resolved between the translators. The agreed Hungarian version was then translated back into the original language to ascertain the accuracy of translation. The final check was made by a group of experts, who concluded that the backward translation matched the original version. The protocol followed the standardized translation process. All items were rated on a 5-point scale. Answers included “1, strongly disagree,” “2, disagree,” “3, neutral” “4, agree” and “5, strongly agree”. Higher scores suggested the presence of a higher fear of war.
Depression, Anxiety and Stress Scale (Lovibond and Lovibond 1995). DASS-21 is a self-report scale designed to measure the negative emotional states of depression, anxiety and stress in the interval of the last two weeks preceding the query. The items were rated on a 4-point Likert scale from 0 (did not apply to me at all) to 3 (applied to me very much, or most of the time) (sample item, e.g., “I felt that I had nothing to look forward to”). The scale has three subscales, depression, anxiety and stress, each containing 7 items. A minimum of 0 and a maximum of 21 points were attainable on all subscales. The original scale has good total reliability declared in the literature for the use in both clinical and community settings (Henry and Crawford 2005; Severino and Haynes 2010; Tran et al. 2013).
The Cronbach alpha values intervals for the DASS-21 subscales in former studies were as follows: depression: α = 0.83–0.94, anxiety: α = 0.66–0.91, stress: α = 0.79–0.91 (Lee et al. 2019). In the present study, the Hungarian version of the scale was applied (Szabó 2010), and it had a high internal reliability. Cronbach’s α values for the depression, anxiety and stress subscales were 0.91, 0.85 and 0.90, respectively.
Intolerance of Uncertainty Scale (Carleton et al. 2007). The IUS-12 is the short version of the original 27-item IUS scale (Buhr and Dugas 2002) that was developed to measure intolerance of uncertainty: reactions to uncertainty, ambiguous situations and future (sample items “I always want to know what the future has in store for me.”, “I must get away from all uncertain situations.”). The IUS-12 demonstrated good psychometric properties (Fergus and Wu 2012; Bredemeier et al. 2018; Wilson et al. 2020). The protocol of the Hungarian translation of the scale followed the standardized translation process, namely the forward-backward method (Nejati et al. 2020). The items were rated on a 5-point Likert scale from 1 (“not at all characteristic of me”) to 5 (“entirely characteristic of me”). The total score ranges between 12–60 points. The internal consistency presented in the literature for the IUS-12 items was excellent (α = 0.91). In the present study, the alpha values for the Hungarian version of IUS-12 were 0.90.

2.3. Procedure

In an online structured survey, the sociodemographic of the participants and their responses covering study variables was recorded. Data collection took place in the spring of 2022 (10–20 March). The sample was recruited with online convenience sampling performed through social networks (e.g., Facebook). Informed consent was obtained from all participants for being included in the study. The data gathering time schedule was in the first weeks of war in the western neighboring countries of Ukraine (Romania and Hungary) and it is important to state that both countries were under Russian occupation in the past century. Moreover, the responses to the one-item measure fear of war confirmed that the phenomenon is relevant in the targeted sample.
Fear of war proved to be an important issue for the respondents, as 83.1% of them marked that they were afraid of the war.
In order to assure anonymity, no personal or e-mail-related identifiers were provided.

2.4. Data Analysis

In this cross-sectional design, a conventional sampling method was applied. The Z-score method of outlier detection was applied, values far from zero (generally between −3 and 3) were removed from the database (Tabachnick and Fidell 2013). A list-wise deletion approach was applied as the method of handling missing values: all cases with missing scores on any variable were excluded from the analysis. Based on (Williams et al. 2010), the final study sample size (Group A n = 670; Group B n = 461) was considered suitable for the statistical analyses required for scale validation (e.g., exploratory and confirmatory factor analysis).
The data distribution was checked based on (George and Mallery 2010) suggestions, and values between −2 and +2 for Skewness and Kurtosis were considered acceptable for normal univariate distribution.
Descriptive statistics, namely percentages for categorical variables and mean and standard deviations (M ± SD) for continuous variables, were provided.
Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to validate the final scale. For the principal axis factoring conducted on the 16 items, direct oblimin (DO) was chosen, because factors are allowed to be correlated, and oblimin allows the factors to not be orthogonal. Criteria for the identification of domains and retention of items was set as follows: factors with eigenvalues > 1.0, items with factor loading > 0.5, and the correlation matrix should show at least some correlations of 0.3 or greater (Pallant 2013). Furthermore, Kaiser–Meyer–Olkin (KMO) sample adequacy values between 0.8 and 0.9 were considered great (Field 2009).
The most frequently used fitting function for structural equation modelling, the maximum likelihood (ML) procedure, was used. Instead of the χ2 statistic for the likelihood ratio test that is overly affected by larger sample sizes (Vandenberg 2006), other fit indices are recommended as criterion for the acceptance or rejection of the model. The following guidelines were settled for interpreting the results of the model fit indices: GFI-goodness of fit index values 0.90 or higher indicate a well-fitting model; TLI-Tucker Lewis index, CFI-comparative fit index, NFI-normed fit index values close to or higher than 0.90–0.95 are acceptable, indicating a good model; SRMR-standardized root mean square residual values should be <0.08 and for parsimonious fit indices χ2/df the values are expected to be less than 5.0 for a good model fit (Hooper et al. 2008; Browne and Cudeck 1989).
Cronbach’s alpha values were calculated to check the internal consistency of the scale. Pearson correlation was calculated for evaluating the association of FOWARS with DASS-21 and IUS-12. Independent samples t test and one-way ANOVA were computed to check the sociodemographic differences in fear of war. Effect sizes (Hedges’s g for independent samples t test) were calculated. The alpha level was set at p ≤ 0.05.
Calculations were performed using version 23.0 of SPSS (statistical package for the social sciences) and SPSS and package 22. of AMOS.

3. Results

3.1. Exploratory Factor Analysis

The factor structure of the proposed FOWARS questionnaire was examined with principal axis factoring, direct oblimin (DO) rotation. A two-factor solution emerged. Based on Field’s (Field 2009) criteria regarding the identification of domains and retention of items, 13 items of the initial 16 items of the original scale were included. Three items (“I am afraid of the war.”, “I am afraid that the war may cost me my life.”, “I’m afraid that I might get hurt in the war.”) with similar factor loadings on both factors were eliminated. The item reduction does not affect the content validity of the scale as both subscales fully cover the construct to be measured. The 13 items are overall relevant and representative of the fear of war.
The remaining 13 items’ factor loadings were high. For the final model, the sample adequacy was excellent, KMO = 0.933. For Bartlett’s test of sphericity, χ2 (78) = 4490.63, p < 0.001, and the results were significant, indicating the model’s suitability for factor analysis. Two components had eigenvalues over Kaiser’s criterion of 1 and explained 61.77% of the variance of fear of war. Table 2 shows the factor loadings.
A 5-point Likert scale is provided for the respondents to indicate the extent to which the statements formulated in the scale are characteristic to them, with the minimum possible score of each question being 1 (“not characteristic of me at all”) and the maximum being 5 (totally characteristic of me”). A total score is calculated as the item scores mean. The higher score indicates higher self-reported war fear (score range 1–5). The two subscales are the experiential dimension of fear (items 1–7) and the physiological dimension of fear (items 8–13).

3.2. Reliability/Internal Consistency

The scale produced good and excellent internal consistencies in each of its subscales (see Table 2): experiential subscale α = 0.88 for Group A and α = 0.92 for Group B; physiological subscale α = 0.88 for Group A and α = 0.88 for Group B. The internal validity of the total scale is also excellent, α = 0.91 for Group A and α = 0.93 for Group B. The average variances extracted ranges were 12.61 for the experiential subscale and 49.17 for the physiological subscale.

3.3. Confirmatory Factor Analysis

A confirmatory factor analysis (CFA) was conducted next on the 13-item scale for the two-factor structure model (see Figure 1).
According to the results, the two-factor structure model is adequate, the model fit indices showing good fit: χ2 = 303.490, df = 64, p < 0.001, χ2/df = 4.742, CFI = 0.938, GFI = 0.910, TLI = 0.924, NFI = 0.946, SRMR = 0.044.

3.4. Construct Validity (Convergent Validity)

Convergent validity is an indicator of construct validity, meaning that, based on theoretical grounds, the newly developed scale correlates with other constructs that are expected to be close to the targeted variable (Boateng et al. 2018).
Both subscales showed a high correlation with the total score of the scale (experiential r (668) = 0.89, p ≤ 0.01 and physiological r (668) = 0.89, p ≤ 0.01) and the subscales were positively correlated with each other (r (668) = 0.57, p ≤ 0.01).
Significant correlations were found of FOWARS and its subscales with the depression, anxiety and stress subscales of DASS and IUS-12 scale. The Pearson correlation values are presented in Table 3.

3.5. Construct Validity (Differentiation by Groups)

Another indicator of construct validity is differentiation or comparison between groups. In order to examine whether the scale could discriminate between particular groups (Boateng et al. 2018), sociodemographic group differences were calculated for FOWARS and its subscales. The results of the One-Way analysis of Variances are presented in Table 4.
There were significant differences between participants based on gender, with males presenting lower levels of fear of war (moderate to large effect sizes). Similarly, differences based on country were also found, and the analysis showed that participants from Hungary had significantly higher levels of fear than participants from Romania, both on experiential and physiological levels (small effect sizes).

4. Discussion

Little is known about the prevalence and amplitude of the fear of war in the population of Ukraine’s neighboring countries. Motivated by the scarceness found in the literature on validated measurement instruments, in this study we aimed to develop and validate a fear of war scale (FOWARS) in an ecologically sound environment. Fear, as a reaction, can be interpreted as a state or as a disposition/trait (Gabriel 2003). If it is present for an extended period and it is associated with a lack of control over circumstances (e.g., war), it can contribute to the depletion of ego resources and to chronic or toxic stress (Murray 2017; Shern et al. 2016). These highlights from the literature put emphasis on the importance of a valid assessment tool for war related fear. The assessment of the phenomenon can help the purpose of better adaptation to everyday life. When facing fear, the tendency to prioritize the processing of negative information occurs. This preferential attention is specific to human information processing and has an impact on the decisions taken under the impact of fear (Baumeister et al. 2001; Lee and Andrade 2011).
FOWARS was inspired by four previously published scales, which measure fear related to health (Kotta et al. 2021; Ahorsu et al. 2020; Jankovic et al. 2020) and fear of nuclear war (Chandler 1991). The structure of the scale comprised physiological reactions and experiential reactions, in concordance with the basic definition of fear in psychology (APA Dictionary of Psychology n.d.). The final, validated version of the scale was established based on several widely recognized and recommended inclusion and exclusion criteria in statistical analysis. In this way, EFA and CFA revealed a robust two-factor structure for the 13 retained items, with 7 items linked to emotional experiential reactions and 6 items linked to physiological reactions. The data analysis revealed an adequate structural model of FOWARS. The high internal consistency of the subscales justified this two-dimensional approach as being reliable for the measurement of fear of war. The items of the scale were formulated to be easily understood and to be applicable to the general population.
Results showed that FOWARS has adequate convergent and concurrent validity. FOWARS scores were found to be positively associated with depression, anxiety and stress scores measured by the Dass-21 Scale (Lovibond and Lovibond 1995) and with the intolerance of uncertainty scores, measured by IUS-12 (Carleton et al. 2007) with moderate to high correlation coefficients.
The scale was found to be slightly sensitive to sociodemographic variables; differences were found based on gender and participants’ country; females and people from Hungary presented higher levels of war fear. No differences based on residency or education were found.

5. Conclusions

Instruments to assess psychological distress associated with war are lacking. FOWARS may help to determine those at an increased likelihood to experience fear of war. This is particularly important because fear of war as a vulnerability factor and is associated with adverse mental health outcomes (Poikolainen et al. 2004).
The development and the validation of this instrument relies on a robust methodology and all data suggest that this is a useful and valid instrument for professionals who would like to assess the fear of war in the general population. Moreover, in the context of war or danger of war, men and women traditionally assume different roles; therefore, fear reactions will most likely differ (Williams et al. 2018). Our results were in line with this, showing gender differences in fear of war; however, this needs further investigation in studies with a more balanced gender distribution.
The timing of data collection was optimal for investigating the phenomenon of fear of war, in an ecologically sound environment, namely in the neighboring countries of the Russia-Ukraine war. Data collection started a few days after the outbreak of the armed conflict. This strength, however, also implies some limitations imposed by a relatively short data collection period. The data was collected online by a convenience sampling method. Despite reaching a large sample size, males were underrepresented. This disproportionality in gender can seriously affect generalizability, especially due to the known gender differences in fear (Boehnke and Schwartz 1997). Due to the limitations of the non-random sampling method and the underrepresentation of male participants in our sample, further studies are required to confirm the measurement invariance of FOWARS across different socio-demographical groups (e.g., age, gender). Another limitation is linked to the lack of measurement of social desirability, which could bias the results. Future studies should focus on a test-retest methodology, validation in other cultures (e.g., more developed countries) and on testing FOWARS predictive validity compared to other multidimensional fear of war scales.
We recommend this tool to be applied in subsequent longitudinal studies, to further estimate the predictive validity of war fear. This scale is a valid, ecologically sound and reliable instrument for assessing fear of war. The FOWARS scale is the first two-factor structured scale which measures the fear of war, and adds to the literature a tool that can be used to measure a state of war fear (if applied once) or a disposition toward fear of war (if applied repeatedly, the stability in high scores could indicate fear as a trait or prolonged reaction). The scale can be useful for screening fear of war as a reaction and serve future psychological treatment options. Screening can be useful in clinical, but also in organizational contexts.
In conclusion, FOWARS is suitable to evidence the immediate and long-term impact of the war on the well-being of citizens in nearby countries. The availability of specific instruments such as FOWARS may foster the understanding of the amplitude of the phenomenon not only in indirectly affected regions and civilians, but even in refugees or Ukraine civilians who were relocated/who fled to other, more safe regions of the country. Hopefully, war-related measures will encourage the emergence of relevant studies on this topic.

Author Contributions

K.K.-J., I.K., E.E.M. and K.S. contributed to the study conception, design, material preparation and data collection. Data analysis was performed by K.K.-J. The first draft of the manuscript was written by K.K.-J. and I.K. All authors commented on previous versions of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The publication of this article was supported by the: Universitatea Babeș-Bolyai 2022 Development Fund of the Babes-Bolyai University Cluj-Napoca, Romania.

Institutional Review Board Statement

Study is in line with research ethical standards, and ethical approval was obtained from Babeș-Bolyai University (reference number 58TT/16.03.2022). All procedures followed were in accordance with the ethical standards of the Helsinki Declaration of 1975, as revised in 2000 (5).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Open Data: The information needed to reproduce all of the reported results is available at https://doi.org/10.6084/m9.figshare.19358408 for group A and https://doi.org/10.6084/m9.figshare.20237505 for group B.

Acknowledgments

We would like to express our deepest appreciation to all the participants who kindly participated in this study for donating their effort and time to help scientific research.

Conflicts of Interest

The authors declared no potential conflict of interest with respect to the research, authorship and/or publication of this article.

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Socsci 12 00283 g001 550
Figure 1. Factor structure of FOWARS (Group B, n = 461).
Figure 1. Factor structure of FOWARS (Group B, n = 461).
Socsci 12 00283 g001
Table
Table 1. Descriptive data of the participants.
Table 1. Descriptive data of the participants.
Group A (n = 670)Group B (n = 461)
Age (M ± SD) 18–71 (38.53 ± 11.56)18–72 (45.04 ± 12.79)
Gender Female622 (92.8%)419 (90.9%)
Male48 (7.2%)42 (9.1%)
CountryHu458 (68.4%)395 (85.7%)
Ro212 (31.6%)66 (14.3%)
Education level 10 grades/grade 10 or less8 (1.2%)14 (3%)
High school/baccalaureate173 (25.8%)130 (28.2%)
College, university304 (45.4%)222 (48.2%)
Master’s degree160 (23.9%)84 (18.2%)
Doctor’s degree25 (3.7%)11 (2.4%)
Residency Capital city259 (38.7%)162 (35.1%)
City294 (43.9%)208 (45.1%)
Village117 (17.5%)91 (19.7%)
DASS (M ± SD)Depression0–21 (6.54 ± 5.88)-
Anxiety0–20 (4.50 ± 4.57)-
Stress0–21 (8.46 ± 5.84)-
IUS (M ± SD) 12–60 (35.51 ± 10.82)-
FOWARS (M ± SD)Total scale1–5 (3.05 ± 0.88)1–5 (2.64 ± 0.94)
Experiential subscale 1–5 (3.79 ± 0.93)1–5 (3.34 ± 1.11)
Physiological subscale1–5 (2.19 ± 1.06)1–5 (1.84 ± 0.95)
Note: values represent frequency and percentage, unless indicated otherwise. n: number in subsample; M: mean, SD: standard deviation.
Table
Table 2. Summary of exploratory factor analysis (Group A, n = 670).
Table 2. Summary of exploratory factor analysis (Group A, n = 670).
ItemComponents
1.2.
1. Félek, mert tudom, hogy a háború emberi életekbe kerül. 1
(I am scared because I know war costs human lives.) 2		0.7830.498
2. Félek, hogy a háború hosszasan elhúzódik. 1
(I am afraid that the war will drag on for a long time.) 2		0.7770.502
3. Attól tartok, hogy a béketárgyalások eredménytelenek lesznek. 1
(I fear that the peace talks will be fruitless.) 2		0.7160.417
4. Félek attól, hogy a világ már nem lesz biztonságos hely. 1
(I am afraid the world will no longer be a safe place.) 2		0.7520.489
5. Kényelmetlenül érzem magam, ha a háborúra gondolok. 1
(I feel uncomfortable when I think of the war.) 2		0.7550.555
6. Aggódom a háború súlyos következményei (gazdasági, politikai stb.) miatt. 1
(I am concerned about the serious consequences of the war (economic, political, etc.).) 2		0.6670.433
7. Félek attól, hogy kitör a nukleáris háború. 1
(I am afraid that a nuclear war will break out.) 2		0.6790.451
8. Remegni kezdek, amikor arra gondolok, hogy ide is elér a háború. 1
(I start to tremble when I think the war reaches here, as well.) 2		0.4240.746
9. Izzad a tenyerem, ha arra gondolok, hogy a háború bennünket is elér. 1
(My palms sweat when I think the war will reach us too.) 2		0.4590.743
10. A szívem gyorsabban ver (pulzusom megnő) amikor arra gondolok, hogy nálunk is kitör a háború. 1
(My heart is beating faster (my heart rate is rising) when I think the war will break out in our country too) 2		0.4500.722
11. Alvászavarom van, mert aggódom, hogy ide is elér a háború. 1
(I have a sleep disorder because I am worried the war will get to us too.) 2		0.5810.803
12. Kiráz a hideg (libabőrös leszek), amikor arra gondolok, hogy nálunk is kitör a háború. 1
(It gives me the creeps (I get goose bumps) when I think the war will break out here too.) 2		0.5100.726
13. Felfordul a gyomrom (hányingerem, gyomoridegem van), amikor arra gondolok, hogy nálunk is kitör a háború. 1
(It makes me sick to the stomach (I have nausea, stomach upset) when I think the war will break out here too.) 2		0.5220.725
Eigenvalues6.3921.639
% of variance49.16712.605
α0.8880.883
α total scale0.912
Note: extraction method: principal axis factoring. Rotation method: oblimin with Kaiser normalization; 1 Hungarian, 2 English; component 1: experiential subscale, component 2: physiological subscale; average variance extracted was 61.77.
Table
Table 3. Correlation between FOWARS, DASS-21 and IUS-12 (Group A, n = 670).
Table 3. Correlation between FOWARS, DASS-21 and IUS-12 (Group A, n = 670).
VariableMSDSK1.2.3.4.5.6.
1. FOWARS3.050.88−0.115−0.534 1
2. Experiential subscale3.790.93−0.8780.3180.89 *** 1
3. Physiological subscale2.191.060.681−0.4960.89 ***0.59 *** 1
4. Depression6.545.880.719−0.5960.57 ***0.49 ***0.53 ***1
5. Anxiety4.504.571.1530.6880.64 ***0.47 ***0.68 ***0.70 ***1
6. Stress8.465.840.241−0.9770.65 ***0.57 ***0.58 ***0.76 ***0.73 ***1
7. Intolerance of uncertainty35.5110.820.079−0.6670.61 ***0.57 ***0.52 ***0.63 ***0.57 ***0.63 ***
Notes *** indicates p < 0.001; M: mean; SD: standard deviation; S: Skewness; K: Kurtosis.
Table
Table 4. Sociodemographic group differences for FOWARS scale and subscales (Group A, n = 670).
Table 4. Sociodemographic group differences for FOWARS scale and subscales (Group A, n = 670).
Variable FOWARS TotalExperiential SubscalePhysiological Subscale
M (SD)M (SD)M (SD)
GenderMale (n = 48)2.41 (0.86)3.10 (1.08)1.60 (0.81)
Female (n = 622)3.10 (0.87)3.84 (0.90)2.24 (1.06)
t (df)−5.31 (668)−5.36 (668)−5.13 (60.22)
p<0.001<0.001<0.001
Hedges’s g0.790.810.61
CountryRomania (n = 212)2.87 (0.86)3.63 (0.92)1.98 (0.99)
Hungary (n = 458)3.14 (0.88)3.86 (0.93)2.29 (1.07)
t (df)−3.59 (668)−2.90 (668)−3.52 (668)
p<0.001<0.001<0.001
Hedges’s g0.310.250.30
ResidencyCapital city (n = 259)3.07 (0.88)3.81 (0.94)2.21 (1.03)
City (n = 294)3.01 (0.89)3.75 (0.96)2.15 (1.04)
Village (n = 117)3.11 (0.88)3.79 (0.84)2.27 (1.13)
F (df)0.67 (2, 667)0.51 (2, 667)0.59 (2, 667)
p0.5080.5970.555
Educational level10 grades/grade 10 or less (n = 8)2.73 (0.78)3.41 (0.72)1.93 (1.07)
High school/baccalaureate (n = 173)3.04 (0.94)3.71 (1.00)2.22 (1.09)
College, university (n = 304)3.10 (0.89)3.82 (0.94)2.27 (1.07)
Master’s degree (n = 160)2.99 (0.80)3.79 (0.82)2.06 (0.98)
Doctor’s degree (n = 25)2.97 (0.87)3.82 (1.06)1.98 (0.99)
F (df)0.78 (4, 665)0.50 (4, 665)1.52 (4, 665)
p0.5360.7340.194
Notes: n: number in subsample; M: mean; SD: standard deviation; t: t-test value; F: F-ratio; p: probability; df: degrees of freedom.
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Kalcza-Janosi, K.; Kotta, I.; Marschalko, E.E.; Szabo, K. The Fear of War Scale (FOWARS): Development and Initial Validation. Soc. Sci. 2023, 12, 283. https://doi.org/10.3390/socsci12050283

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Kalcza-Janosi K, Kotta I, Marschalko EE, Szabo K. The Fear of War Scale (FOWARS): Development and Initial Validation. Social Sciences. 2023; 12(5):283. https://doi.org/10.3390/socsci12050283

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Kalcza-Janosi, Kinga, Ibolya Kotta, Eszter Eniko Marschalko, and Kinga Szabo. 2023. "The Fear of War Scale (FOWARS): Development and Initial Validation" Social Sciences 12, no. 5: 283. https://doi.org/10.3390/socsci12050283

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