Latin American validation of an instrument to assess stress caused by a possible war originated from the current armed conflicts (War-Stress)

doi:10.21203/rs.3.rs-2613815/v1

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Latin American validation of an instrument to assess stress caused by a possible war originated from the current armed conflicts (War-Stress)

https://doi.org/10.21203/rs.3.rs-2613815/v1

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Introduction: Every armed conflict generates an uncomfortable and stressful environment, but there were no valid instruments to measure this in the Latin American population.

Objective: To validate, in Latin American, an instrument to assess stress due to a possible war originated from the current conflicts.

Methodology: This is a multicentric, instrumental study. It was based on a previous survey that measured stress, but we added some other questions according to the context of war. We sought previous and other suggested questions; then, expert judgment was carried out as well as a previous pilot test, virtual surveying, and psychometric analysis.

Results: The Kaiser-Meyer-Olkin index (KMO = 0,957) and the Barlett’s test (230039.3; df = 105; p = 0.000) were acceptable. Factor 1 (stress in the war context) explains 64,3%; and Factor 2 (stress due to external situations caused by the war), 75,9% of the variance. Confirmatory factor analysis yielded a nine-item model, grouped into two factors (χ2 = 312,08; df = 26; p = 0.001; RMR = 0.030; GFI = 0.960; CFI = 0,980; TLI = 0.980; and RMSEA = 0.070). The general Alpha (α = 0.935; 95% CI = 0.92 – 0.94), and Factor 2 (α = 0.955; 95% CI = 0.81 – 0.91) were good.

Discussion: We validated an instrument with excellent psychometric indicators. Through nine questions in two factors, it can measure stress effectively in the context of war. It is applicable to multiple scenarios.

Health sciences/Health occupations

Health sciences/Medical research

Stress

war

validation study

Latin America

mental health

armed conflicts

An event that few expected took place on the last days of February, 2022. This event shook politics and world peace. Since the first days, Russia has sent troops to its border with Ukraine (BBC News Mundo, n.d.), that week Russia invaded the Ukrainian territory and started a conflict that had not been seen for a long time (CNN, 2022). Prior to this, there have been less serious conflicts or conflicts that have been going on for a long time; for example, Israel is constantly at war with Palestine and other countries in the Middle East (Cyjon, 2021). Likewise, the United States is constantly in conflict with the Middle East and other countries (Aguado Romero et al., 2019). However, this last Russia-Ukraine conflict had a great impact because the United States and all its allies promised severe and drastic sanctions against Russia. On the other hand, China and its allies promised to help Russia if the United States or others interfered. Thus, the European Union established economic sanctions, diplomatic measures, and restrictions on Russian banks and the media (BOE.es - DOUE-Y-2022-70015 Marco Temporal relativo a las medidas de ayuda estatal destinadas a respaldar la economía tras la agresión contra Ucrania por parte de Rusia., n.d.; Medidas restrictivas de la UE contra Rusia por sus actos en Ucrania (desde 2014), n.d.).

This whole scenario made the world concerned about the possible consequences of the war, which, at the beginning, seemed to be a local problem, but then threatened to spread to all the world (BBC News Mundo, n.d.). This situation is concerning, especially when observing the constant bombings, the deployment of tanks and other weapons (Melguizo, 2022), as well as, the attack on places where there were nuclear power plants (Welle (www.dw.com), n.d.). All this revived horror scenes from past wars, where it has already been documented that the mental health of the population is damaged by the armed conflict and the economic and political consequences it brings (Caspe, 2018), not to mention the environmental and other types of damage (The Political Room, 2020).

For example, it was reported that there was more emotional distress, depressive symptoms, perceived stigma and anxiety-stress in Colombia after a conflict (Campo-Arias et al., 2017).

In other studies, the authors have found enuresis, fear, sadness, aggression, hyperactivity, inattention, adjustment disorders, depression, anxiety and post-traumatic stress (Cudris-Torres and Barrios-Núñez, 2018; Piñeros-Ortiz et al., 2021). Moreover, this is in addition to what is stated in the reviews carried out in tens of thousands of respondents in Asia, Europe and America, where it is evident that they suffer from anxiety, depression, poor quality of sleep and physical inactivity in these years of pandemic (Sepúlveda-Loyola et al., 2020). We can also mention the uncertainty of the disease, the problems generated by social distancing, isolation and quarantine (Hernández Rodríguez and Hernández Rodríguez, 2020). This is the reason why it is important to generate instruments to evaluate the stress generated by this conflict. Therefore, the objective of the research was to validate an instrument to evaluate the stress in Latin America caused by a possible war originated from the current armed conflicts.

We undertook an instrumental study in a Latin American population. A total of 2008 inhabitants from Latin America were surveyed during March and the first days of April, 2020. The main countries were the following: Colombia (448), Paraguay (383), Peru (342), Bolivia (238), Panama (180), Ecuador (161), Brazil (83), Mexico (63), Cuba (31), among others. Of the respondents, 1204 were female with an age range between 18 and 78; the median age was 26,8 (standard deviation: 9,7 years old).

The study was conducted in the context of the war between Russia and Ukraine. The surveys were administered from the second week of the conflict until the first days of April. We included those who were 18 or older, who resided in any country of Latin America when the survey was being administered, and that accepted to participate in the study. We excluded fewer than 200 responses because they did not meet the inclusion criteria or because they did not answer the totality of the questions that were formulated to measure stress.

In order to initiate the research, we generated a project; then, it was submitted for review to the ethics committee of Universidad Norbert Wiener, in Peru, which authorized the study (File number: 1647–2022). This project included a previous questionnaire that measured stress (Campo-Arias et al., 2015). It comprised ten questions and has been validated in the Latin American context. In addition, we collected questions from other sources (bibliographically and from experts) to complement the previous questions, knowing that the context was different from any other situation that generated stress for being in the middle of a war conflict and in a post-pandemic situation. The preliminary survey had 15 questions, all of them could be responded in a Likert-type format of five answers (from strongly disagree to strongly agree).

Then, we proceeded to upload the questions to Google Forms and the link was sent to the respondents. In this form, we always respected the right to answer the questions they wanted to answer; no personal or other sensitive data was asked, and the objective of the research and their rights were explained to them. Subsequently, they were asked if, having been informed about the research, they were willing to participate. Those who accepted proceeded to fill in the survey.

After completing the survey, we downloaded the answers through the Microsoft Excel program (version 2019), in which we proceeded to perform data quality control and filter by selection criteria. Finally, we started psychometric analysis.

Data analysis

Descriptive analysis and exploratory factor analysis (EFA) were executed through the FACTOR Analysis program (version 11,05). We analyzed the mean, standard deviation, skewness and kurtosis of the 15 items of the scale. Regarding the skewness and kurtosis coefficient, we took into account the value of +/- 2 (Pérez and Medrano, 2010). For EFA, we considered the Kaiser-Meyer-Olkin (KMO) coefficient and the Barlett’s test. Here is where the estimation of the unweighted least squares with Promin rotation method was taken into account (Lorenzo-Seva and Ferrando, 2006).

For confirmatory factor analysis (CFA), the AMOS statistical program (version 21) was used, with this we performed the structural equation modeling (SEM) and we could obtain the goodness-of-fit index (GFI), the Tucker-Lewis Index (TLI), the comparative fit index (CFI), the root mean square error of approximation (RMSEA) and the root mean square error (RMR). For the assessment, we followed the criteria proposed by Hu and Bentler (Hu and Bentler, 1999), who indicated that GFI, TLI and CFI should be higher than 0,9, as well as RMSEA should be lower than 0.08. Finally, we calculated the scale reliability and its respective confidence intervals through the SPSS software (version 25.) (Domínguez-Lara and Merino-Soto, n.d.).

The scores’ means were always lower than two, 31 of the 45 means were higher than 2,59 (taking into account that the score could range between zero and three), with a standard deviation ranging from 0,000–1,25. In the analysis of Aiken’s V, we could obtain the relevance, clarity and representativeness, which were good for the 15 items (ranging from 0,71 − 1,00, the values were higher than 0,80 in most of the cases). Thus, even the inferior limits had good values (ranging from 0,54 − 0,89, having values higher than 0,60 in most of the cases). This is why we considered that the 15 items of the initial scale had excellent values in regard to relevance, representativeness and clarity according to the expert judgment.

Preliminary analysis of the items

We performed a preliminary analysis of the 15 items of the War-stress scale. We analyzed the descriptive statistics (mean, standard deviation, skewness and kurtosis), in which there was evidence that Item 14 had the greatest average score and was the one that shows the highest variability (M = 3,13; SD = 1,34). Regarding skewness and kurtosis values, they did not exceed ± 1.5(1.5). In addition, communalities are > 0.30. Table 1

Exploratory Factor Analysis (EFA)

Table 2 shows EFA pertinence; it is justified through the values (acceptable) of the Kaiser-Meyer-Olkin index (KMO = 0,957) and the Barlett’s test (230039.3; df = 105; p = 0.000). We used the unweighted least squares method with Promin oblique rotation and parallel analysis was used to determine the factors. Items 2 and 3 were eliminated because there were factor loadings in both factors. Factor 1 (stress in the context of war) explains 64,26% of the variance and comprises Items 4, 5, 6, 7, 8, 9, and 10 with saturation values over 0,70. In addition, Factor 2 (stress due to external situations caused by the war) contributes 75,88% of the variance and includes Items 1, 11, 12, 13, 14, and 15, with saturations values over 0,50. Table 2.

Confirmatory factor analysis

Through CFA we could verify the internal structure of the War-Stress scale (Table 3). The results of the original model reported unsatisfactory goodness-of-fit indices. Hence, we proceeded to perform two respecifications through the technique of indices modification. First, we eliminated Items 10 and 12, but we could not achieve an adequate adjustment. In the second respecification, Items 1 and 15 were eliminated and a satisfactory factor structure model was obtained. The FIs show that the nine-item model with two underlying factors is adequate (χ2 = 312.08, df = 26, p = 0.001; RMR = 0.030; GFI = 0.960; CFI = 0.980; TLI = 0.980; and RMSEA = 0.070) (Fig. 1).

Reliability

The reliability of the general scale reported an excellent value (α = 0.935; 95% IC = 0.92–0.94). In addition, we could find good values for the Factor “Stress in the context of war” (α = 0.955; 95% IC = 0.95–0.95) and the Factor “Stress due to external situations generated by the war” (α = 0.902; 95% IC = 0.81–0.91). If we want to measure stress/no stress in a dichotomous way, it is suggested that we use the technique of terciles. For example, if we want to measure stress globally (with all the test questions), we should score each answer (1 = strongly disagree to 5 = strongly agree), so that each respondent would have a score that could vary between 9–45 points. Then, we would have a total score and those who have stress would be in the top tercile of scores, compared to those in the middle + low terciles. This same procedure can be done for each factor separately. Figure 2

The possibility of the outbreak of a war from the current conflict between two or more countries puts at risk the mental health of the population indirectly involved. Moreover, this can be added to the possibility that the countries of this population can be part of that large-scale diplomatic problem. In accordance with the above and in the context of the current war conflict between Russia and Ukraine, an instrument (War-Stress) was validated, using the collection of more than two thousand responses from residents of Latin America. The statistical analysis of War-Stress shows that it is a reliable instrument for quantifying stress in the context of a war conflict, as it has excellent psychometric indicators, both at the global scale level and at the level of each individual item. Optimal results were obtained in all phases of the evaluation of this instrument, in addition to having considered questions related to the global context of war crises and considering the current situation of armed conflict between the aforementioned countries.

Therefore, a scale is necessary to measure an important part of the mental health of the population in this type of context. There is literature showing that the psychological sphere is affected. For example, a study of the South Sudanese civil war found that the level of perceived needs predicted psychological distress (Ayazi et al., 2015). Furthermore, it has also been reported that the severity of psychopathological disorders in the context of war depends on the attrition of stress coping skills (T et al., 2017). Therefore, it would be important to administer the War-Stress scale to vulnerable individuals and groups, which will allow the identification of populations where resilience programs and strategies need to be implemented to avoid stress-associated diseases (Sanders et al., 2019). To this end, we should use short and well validated instruments, based on the stressors during conflicts (Wl et al., 2019), and on the different types of reactions that may arise (Abu-Kaf and Braun-Lewensohn, 2019; Chukwuorji et al., 2017).

We know that war conflicts per se have repercussions on mental health and generate situations of stress, anxiety or depression (Thompson et al., 2018). However, this should be added to the influence of the media, knowing that they generate anxiety and stress in several populations (Hoge et al., 2017; Lemieux et al., 2021; Sasaki et al., 2020). This factor is key to explore how people are exposed to the news and how their mental health is affected. Therefore, having a global picture on the subject can be useful to give recommendations on how to handle such information to avoid negative repercussions. Thus, it is recommended that the influence of the media or others on the mental health of the population in this type of context can be measured by means of questions or instruments.

Furthermore, this should be measured at the same time with post-traumatic stress, anxiety, depression and others related to stress, such as family history of psychiatric disorders, consumption of alcoholic beverages or drugs, as shown in a study of victims of the armed conflict in Colombia. That study showed that 12% of victims had polyvictimization associated with symptoms related to depression, anxiety and stress (Campo-Arias et al., 2017). Likewise, another study conducted in Yemen showed that 15–20% of the population experienced mild to moderate mental disorders such as depression, anxiety and post-traumatic stress disorder. In addition, 3–4% experienced severe mental disorders, such as psychosis or debilitating depression and anxiety (TOMADA and Reportage, n.d.). Also, in a bibliographic review, it was revealed that children who were exposed to armed conflicts had post-traumatic stress syndrome (Kithama, n.d.). In regard to psychopathology, it was observed in a study that intrapsychic determinism of a mental disorder is a cause of the immersion of the human being in violence (Venegas Luque et al., 2017). All these references make us see the need to measure populations globally, since the mental sphere is influenced globally, in addition to the need to measure the repercussions on work, study, family and community as well.

The study has an intrinsic limitation, since it does not have a random sample that would have allowed for more extrapolation of the results. However, this limitation is partial, as it is more important to have a large population in this type of validation study, with diverse realities and a good number of respondents for each question (taking into account that, in the end, there were more than 133 responses for each final question in around ten Latin American countries). This can give us the confidence that we can count on an instrument that had an adequate validation process, and is recommended that it can be used in diverse populations, and simultaneously with other scales and questions that measure mental health globally.

Based on the above, it is concluded that a nine-item instrument was validated to assess the stress perceived in the context of a war conflict. This scale has two factors and had excellent psychometric values obtained in the validation process.

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Table 1

Preliminary analysis of the War-Stress scale’s items
Variables	M	SD	Skewness	Kurtosis	h
Item 1	2.809	1.172	-0.075	-1.002	0.578
Item 2	2.799	1.198	0.052	-0.943	0.580
Item 3	2.687	1.147	0.070	-0.887	0.636
Item 4	2.445	1.055	0.301	-0.547	0.592
Item 5	2.470	1.087	0.292	-0.639	0.613
Item 6	2.440	1.068	0.317	-0.611	0.623
Item 7	2.440	1.056	0.319	-0.562	0.627
Item 8	2.457	1.089	0.301	-0.696	0.640
Item 9	2.500	1.121	0.279	-0.746	0.590
Item 10	2.536	1.154	0.296	-0.785	0.610
Item 11	2.940	1.298	-0.077	-1.148	0.579
Item 12	2.991	1.277	-0.148	-1.110	0.601
Item 13	2.928	1.268	-0.112	-1.112	0.622
Item 14	3.125	1.342	-0.210	-1.163	0.598
Item 15	2.777	1.177	0.027	-0.908	0.652
Note: M = Mean; SD = standard deviation; S = Skewness coefficient; K = kurtosis coefficient, h = Communality

Table 2

Exploratory factor analysis of the items of the War-Stress scale. Note: F1: stress in a context of war; F2: stress due to external situations caused by the war
Items	F1	F2
1. Thinking that I’m affected because this war might occur unexpectedly.		0.522
4. Not being able to handle my personal problems in this context of war.	0.920
5. Things not going well in this context of war.	0.882
6. Not being able to face the things I have to do in this context of war.	0.971
7. Being unable to control the difficulties in my life in this context of war.	0.970
8. Being unable to have this situation under control in this context of war.	0.891
9. Getting angry for not being able to control this situation.	0.723
10. Feeling that the difficulties are piling up so much that I can’t overcome them.	0.706
11. The decisions the politicians make		0.963
12. The decisions made by the international organizations (UN, NATO, etc.)		0.998
13. The situation shown by the media.		0.935
14. This situation getting out of control and a major war breaking out.		0.930
15. What is said in the streets/my country about the possibility of the outbreak of a war.		0.608
Interfactors correlation
F1	1
F2	0.702**	1

Note: F1: stress in a context of war; F2: stress due to external situations caused by the war

In this context of imminent war, I feel stressed about…
Thinking that I’m affected because this war might occur unexpectedly.
Being unable to control what happens in this context of war.
Being more nervous or stressed than usual due to this context of war.
Not being able to handle my personal problems in this context of war.
Things not going well in this context of war.
Not being able to face the things I have to do in this context of war.
Being unable to control the difficulties in my life in this context of war.
Being unable to have this situation under control in this context of war.
Getting angry for not being able to control this situation.
Feeling that the difficulties are piling up so much that I can’t overcome them.
The decisions the politicians make
The decisions made by the international organizations (UN, NATO, etc.)
The situation shown by the media.
This situation getting out of control and a major war breaking out.
What is said in the streets/my country about the possibility of the outbreak of a war.

Table 3

*Goodness-of-fit indices of the factor models of the War-Stress scale.*
Goodness-of-fit index	Original	Model 1	Model 2
Goodness-of-fit index	(13 items)	(11 items)	(9 items)
CMIN	1618.57	849.01	312.08
DF	64	43	26
P	0000	0.000	0.000
CMIN/DF	25.29	19.74	12.00
RMR	0.090	0080	0.030
GFI	0.880	0920	0960
CFI	0940	0960	0980
TLI	0930	0950	0980
RMSEA	0110	0.100	0.070

There is NO Competing Interest.

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Latin American validation of an instrument to assess stress caused by a possible war originated from the current armed conflicts (War-Stress)

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Abstract

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Introduction

Methodology

Data analysis

Results

Preliminary analysis of the items

Exploratory Factor Analysis (EFA)

Confirmatory factor analysis

Reliability

Discussion

References

Tables

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