War, Torture and Trauma in Preadolescents from Gaza Strip. Two Different Modalities of PTSD

Introduction

In the last decade, armed conflicts and human rights violations have increased worldwide. Of particular severity are situations of ethnic cleansing that result in the forced displacement and extermination of thousands of people. Minors are the most vulnerable victims in these conflicts. Since October 2023, following an attack by Hamas, the State of Israel launched an assault on the Gaza Strip and the West Bank, resulting in over 26,000 deaths by January 2024, with approximately half being children. Thousands of children have been injured, witnessed the murder of their relatives, had to leave their homes, and lacked basic supplies to survive. These events are currently under investigation by the International Court of Justice in The Hague as potential genocide. Understanding the psychological impact that previous attacks had on surviving children could aid in future psychological interventions for the new victims.

Preadolescents in war zones may face severe developmental impacts due to traumatic experiences, particularly related to torture, with limited specific studies in this age group (Dimitry, 2012). Existing research focuses on younger and older populations, revealing that children and adolescents are significantly affected by war situations (Barber, 2008). Mental health studies indicate that minors from war zones often exhibit pathologies such as posttraumatic stress disorder (PTSD), anxiety, and depression (Bronstein & Montgomery, 2011; Dimitry, 2012; Slone & Mann, 2016).

Determining factors influencing the effects include exposure level, age, gender, family factors, socio-economic adversity, coping strategies, belief systems, social support, and religiosity (Dimitry, 2012; Lustig et al., 2004; Richardson et al., 2021; Slone & Mann, 2016). Low social support is recognized as a PTSD risk factor (Bryant, 2019), and parental responses to trauma play a crucial role (Hiller et al., 2018). The relationship between social support and PTSD is intricate, with social support potentially buffering the effects of adverse childhood experiences (ACE), while ACE may negatively impact social support (Jones et al., 2018; Wang et al., 2021).

A meta-analysis focused on social support as a PTSD predictor found complex relations, varying based on types of traumatic events (Zalta et al., 2021). PTSD, associated with traumatic experiences, has faced criticism for diagnostic criteria (Manzanero et al., 2021; McNally et al., 2014). Some argue that PTSD is a cognitive pathology related to memory processes, where perceptions of traumatic memories predict posttraumatic stress symptoms (Brewin, 2001; Brewin et al., 1996; Manzanero et al., 2020; Manzanero & Morales-Valiente, 2024; McGuire et al., 2021).

Adolescents experiencing forced displacement due to combat, with traumatic events, may meet PTSD criteria (Panter-Brick et al., 2009). The association between PTSD and the number of traumatic experiences suggests a link between intensity, coping strategies, resilience, and the manifestation of traumatic pathology. Repeated exposure to traumatic events may erode resistance, leading to symptoms and psychological disorders.

Traumatic experiences’ effects extend beyond PTSD, encompassing psychosocial elements impacting the well-being and quality of life of child victims in war zones (Thabet & Thabet, 2016; Veronese et al., 2017).

The Case of the Gaza Strip

The whole Palestine region, and the Gaza Strip in particular, have undergone a persistent conflict for decades that has implied repetitive exposure to violence and war, and that have clearly eroded the psychological well-being, health, and quality of life of children population (D’Andrea et al., 2023; Manzanero et al., 2021; Massad et al., 2009; Shank et al., 2023; Shehadeh et al., 2015; Thabet et al., 2014, 2009; Thabet & Thabet, 2016; Thabet & Vostanis, 1999, 2000), adding urgency to the need to understand and address the implications of war-related trauma in this population.

In general, the severity of psychological disorders in minors exposed to war-related violence depends on the quantity of the traumatic events suffered (Thabet & Vostanis, 1999). In any case, there are important individual differences (Kolltveit et al., 2012; Punamaki, 2002) and resilient strategies (Betancourt et al., 2013; Tol et al., 2013). Several studies have found that girls in Gaza would be more vulnerable to war-related stressors than boys (Kolltveit et al., 2012; Panter-Brick et al., 2009; Thabet et al., 2014).

Also, there are many stressors that affect minors in war situations (Lustig et al., 2004). Most of the studies (Kadir et al., 2019) point out, among the most frequent, the lack of medical attention and diseases related to unsanitary conditions and lack of food, exposure to toxins (which increase the medium and long-term prevalence of cancer), environmental and meteorological factors, exposure to violence and extreme trauma (primary or secondary), social and geographical changes, and sexual assaults. APA (2000) defined extreme trauma as directly experiencing, witnessing, or learning about events that involve actual or threatened death or serious injury, or other threat to physical integrity.

Sometimes traumatic experiences in war situations correspond to what has been defined as torture (Kadir et al., 2019; Quiroga, 2009). According to Article 1 of the Convention against Torture and Other Cruel, Inhuman or Degrading Treatment or Punishment (UNCAT), adopted by the United Nations’s General Assembly in its 39/46 resolution of December 10^th, 1984, “torture” shall be understood as any act by which severe pain or suffering, whether physical or mental, is intentionally inflicted on a person in order to obtain information or a confession from him or a third party, to punish him for an act he has committed, or is suspected of having committed, or to intimidate or coerce that person or others, or for any reason based on any type of discrimination, when said pain or suffering is inflicted by a public official or another person in the exercise of public functions, at his instigation, or with his consent or acquiescence. Article 2 specifies that in no case may exceptional circumstances, such as a state of war or threat of war, internal political instability or any other public emergency, be invoked as a justification for torture.

In addition, sexual assaults have been reported in war situations against minors on numerous occasions (Kadir et al., 2019). In the case of Palestine, the Public Committee Against Torture in Israel (PCATI) documented, during 2005-2012, 60 cases of sexual abuse (4% of all files in this period), 36 reports of verbal sexual harassment, either directed toward Palestinian men and boys or toward family members, and 35 reports of forced nudity; 15% of the attacks were against minors (Weishut, 2015).

Context and Objectives of Current Study

On July 8^th, 2014, the Israeli Army launched an attack against the population of Gaza Strip that lasted 51 days, causing the death of 2,251 people, 551 of them children, 299 women and 64 unidentified. During the conflict, 11,231 Palestinians were injured, including 3,436 children. This attack caused the destruction of infrastructures, particularly water supplies and sewerage, while the destruction of dwellings left more than 500,000 people homeless. During this time, 118 UNRWA (United Nations Relief and Works Agency for Palestine Refugees in the Near East) installations were damaged, including 83 schools and 10 health centers. In total, over 12,600 housing units were totally destroyed and almost 6,500 sustained severe damage. Almost 150,000 additional housing units sustained various degrees of damage and remained inhabitable. The conflict led to a massive displacement crisis in Gaza, with almost 500,000 persons internally displaced at its peak. Approximately 50,000 of them took refuge in UNRWA schools. Other people found refuge with family or friends, in overcrowded conditions and lack of essential resources (UNRWA, 2014).

Consequently, this study assessed exposure to traumatic events and posttraumatic symptoms in preadolescents from the Gaza Strip between December 30th, 2014, and May 17th, 2015. The study’s objectives were: (1) to determine the prevalence of exposure to traumatic events among male and female children aged 11 to 13 living in the Gaza Strip, and (2) to examine the symptoms of traumatic stress in these children.

Method

Participants

A total of 521 preadolescents (11-13 years old) from the Gaza Strip (Palestine) with a mean age of 11.62 years (SD = 0.73), 225 girls (43.2%) and 296 boys (56.8%), participated in the study. They resided in five areas of the Gaza Strip: Rafah, Khan Yunis, Wustah, Gaza City, and North Gaza. All of them attended UNRWA elementary schools.

Material

The assessment is based on the application of the Harvard Trauma Questionnaire (HTQ1) developed by the Harvard Program in Refugee Trauma (Mollica et al., 1992). The sections I to IV from Iraqi Version-Arabic of Harvard Trauma Questionnaire (HTQ; Shoeb et al., 2007) allows to obtain information about the effects of war in the participants:

• First section enumerates 39 traumatic events in a yes/no question.
• Second section include 35 yes/no questions about torture experiences.
• Third section measures physical effects of war (injury and starvation), composed by three items with several types of responses depending on the information requested.
• Fourth section measures psychological symptoms of trauma and is composed of 44 items that evaluate the severity or intensity of the symptoms on a 4-point Likert scale (1 = not at all, 2 = a little, 3 = quite a bit, and 4 = extremely). The first 16 items aim to measure PTSD symptoms according to DSM-IV criteria, with a threshold of 2.5 or higher. The other 28 items quantify what the authors name “refugee specific”, which evaluates the impact that the traumatic events could have had on their perception of their own daily life. The overall scale of section 4 also considers a threshold value of 2.5 or higher.

Procedure

For the purpose of this study, the UNRWA schools in the Gaza Strip were asked in writing by the Department of Psychology of the Al-Azhar University-Gaza for their collaboration in the application of the HTQ trauma questionnaire. When approval was obtained, psychologists who work with the families went to the schools to meet the children and their parents. The purpose of the study was explained, and the children’s parents were asked for their consent to apply the test. The instruments were applied in individualized interviews by psychologists from UNRWA schools between December 2014 and May 2015, several months after the Israeli army carried out attacks on the Gaza Strip from July until august 2014.

Data Analysis Techniques

The first perspective of data analysis explored variables one by one or relationships of couples of variables. To do that, data exploration and analysis used several tools, based on the research questions to answer. Cronbach’s alpha was calculated to get scale reliability measured. Analysis of variance (ANOVA) and chi-squared (χ²) were used to test statistically significant differences, and eta-squared (η²) to assess effect size.

The second perspective of data analysis explored large or complete set of assessed variables. For that, multidimensional scaling (MDS) was used to permit 3D dimensionality reduction (Nguyen & Holmes, 2019) and data visualization (Walny et al., 2019) of complex data. Specifically, classic metric MDS was used. Those graphs reflect data distribution, so it is possible to see, for example, if people with and without PTSD are somehow grouped. Interesting visual groupings are analyze using machine learning (ML), also called data science (DS), tools to check group arrangements beyond apparent visual arrangement. That way, evidence (or a lack of it) is obtained to support those groupings. Support vector classifier (Vapnik, 1998) (SVC), multivariate logistic regression (MLR), and k-means (Yadav & Sharma, 2013) nearest centroid classifier (Levner, 2005) (KM-NCC) are used to get global support. Additionally, one-way ANOVA (group comparison) and η² are used to detect the most relevant variables, differentiating identified groupings.

Additional data analysis ML techniques are used, providing additional insights through its different data analysis perspective. “(…) machine learning enables more rigorous exploration, and holds the potential to advance theory formation in developmental psychology and other fields. Machine learning is an umbrella term for methods that learn patterns from data through automated model build” (Van Lissa, 2023, p. 2). Although ML methods are still a novelty in psychological research, its use is growing fast in all areas of psychological research (Orrù et al., 2020), as educational psychology (Levy et al., 2020; Luan and Tsai, 2021), clinical psychology (Dwyer et al., 2018), and social psychology (Kumar et al., 2019). Because these techniques used here are still not very widely known, they are shortly described in a foot note2.

Samples with missing data were removed for DS analysis, implying a reduction of 8.6% of data samples. Data imputation using average values decreases data variability (Hastie et al., 2009), making groupings identification difficult. To prevent higher values bias being favored in algorithm training, Likert type items were rescaled from [1, 2, 3, 4] values to [-1.5, -0.5, 0.5, 1.5]3.

Ethical Information

Children’s participation in the study was voluntary and approved by their family members or caregivers. All the children and their families who participated in the study had the necessary psychological support. This study was part of the research project about the assessment of psychological trauma in vulnerable refugees and asylum seekers (children and women), and was approved by Ethic Committee from [masked institution]. It was endorsed by UNHCR-Spain and declared of interest to the European Union, and it was possible thanks to the collaboration of the UNRWA schools. After the attacks of the summer of 2014 the UNRWA’s Community Mental Health Programme assisted refugees in the Gaza Strip, asserted that children who could present physical and psychological needs were adequately cared for. They collectively support children and families, not only through individual and group counselling, but targeted interventions aimed at enhancing psychosocial resiliency and well-being. Along the armed conflict, UNRWA provided humanitarian assistance (including non-food-items, food, water, psycho-social support) to internally displaced persons in 90 of 156 UNRWA school buildings, with the remaining school buildings either unsafe or damaged. On 23rd August, 2014, a record-high of 292 959 internally displaced persons were counted in 85 UNRWA school buildings (UNRWA, 2014).

Results

The results are reported by grouping the responses of the participants to the four sections of the questionnaire applied in “traumatic war events”, “torture experiences”, “physical effects”, and “mental health”. Also, two more sections were added, “sexual abuse” and “posttraumatic stress disorder”.

Traumatic War Events

The results of the participants are reported separately on the questions raised about the experience of events related to the war, and in a different section of those situations that go beyond combat situations and can be considered torture according to the UNCAT (1984). The Cronbach’s alpha of the section in this sample was .844.

Table 1 shows the traumatic situations to which the preadolescents were exposed in order from highest to lowest frequency. As can be seen, the majority witnessed the destruction of residential areas and religious sites and were confined to try to protect themselves from bombings and violence. A large number of preadolescents were exposed to fighting and witnessed the presence of corpses. About half of the children studied had to leave their homes and witness chemical attacks. Around 40 % of their friends or family were injured as a result of the fighting and shelling, were forced to internally displace in the Gaza Strip to underserved areas, and witnessed some people being injured. Around a third of the minors witnessed deaths, executions of civilians, and lacked shelter to protect themselves from the war. About 20 percent lost friends in violent deaths and their property was destroyed. Around 10 percent or less witnessed their homes being searched, suffered the disappearance of friends and the violent death of a relative, were victims of complaints that put them at risk of death, and were searched on occasion.

The evaluated preadolescents suffered an average of 10.77 traumatic events throughout the 51 days of the war. No statistically significant differences were found in the number of traumatic experiences according to gender, F(1, 519) = 1.559, p = .212, η² = .003; age, F(2, 518) = 1.690, p = .186, η² = .006; or the place of residence, F(4, 516) = 1.261, p = .284, η² = .010.

Torture Experiences

This section collects the data found from the responses of the evaluated preadolescents to the questions related to experiences that could be considered torture, cruel, inhuman or degrading treatment or punishment (see Table 2).

Forty preadolescents (7.68%) reported having been tortured while being held. Around a quarter of the preadolescents evaluated reported that they witnessed torture and a fifth that such torture, arrests, or executions were against relatives. Between 8 and 9 percent were forced to destroy their property or to expose someone, putting their lives at risk. Some 30 teenagers were used as human shields, forced to cause physical harm to other people, taken prisoner, or witnessed sexual assaults and rapes. Around 25 children had suffered the kidnapping of relatives or friends, and 13 were themselves kidnapped or taken hostage.

As can be seen in Table 2, 16 minors (3.07%), 10 girls and 6 boys, were sexually assaulted. Most of the sexual assaults occurred against younger children; 10 children were 11 years old, 4 were 12 years old, and 2 were 13 years old. Even more minors witnessed sexual abuse and rape, this event being reported by 29 minors (5.57%), 14 girls and 15 boys.

Physical Effects

Seventy-seven preadolescents (14.8%) were physically harmed, 35 (6.7%) informed about physical injuries due to nearby explosions, and 47 (9.03%) about serious physical injury from combat situation. No statistically significant differences were found based on gender or age. Nor were statistically significant differences found for “serious physical injury from combat situation” based on gender, age or residence.

Due to the confinement and food shortages, and due to supply problems during the 51 days of attacks on the Gaza Strip, 233 children (44.72%) suffered from “food and drinking water shortages”, and 36 (6.9%) reported having suffered “starvation” that resulted in a weight loss of between 0 to 15 kg. (M = 4.50, SD = 3.31). Statistically significant differences were found for “lack of water and food” as a function of age, χ²(2, N = 521) = 6.737, p < .05, and gender, χ²(4, N = 521) = 4.275, p < .05, with boys and younger ones being the most affected. No statistically significant differences were found in starvation based on gender or age.

Asked about medical care, 196 preadolescents (37.69%) informed that they suffered from diseases without being able to access to medical care or medicine because of war.

Mental Health Effects

Table 3 shows the data collected regarding some aspects related to the mental health of the preadolescents evaluated, ordered from highest to lowest frequency. The Cronbach’s alpha of the section in this sample was .96. Considering the symptoms that the evaluated preadolescents present, we found that 137 (26.29%) would have PTSD. No statistically significant differences were found according to age, χ²(2, N = 521) = 2.933, p = .231; gender, χ²(1, N = 521) = 0.028, p = .867; or the place of residence, χ²(4, N = 521) = 2.715, p = .607.

DS techniques were used to analyze data distribution and variable relationships. MDS were used to reduce dimensionality from 44 dimensions data points (psychological variables) to its equivalent 3 dimensions (3D) data points. The 3D points obtained were plotted as a 3D scatterplot graph (Figure 1). PTSD diagnose presence or absence is shown through color.

In this case, two aspects are especially useful for a better understanding of symptoms: data distinguishability and data distribution. Data distinguishability tells us if we can distinguish, separate, psychological data considering PTSD diagnoses. This graph visualizes the war effects in psychological variables and PTSD. Data distribution in each group shows individual differences both on participants meeting and not meeting PTSD DSM criteria.

Data can be visually distinguished based on PTSD diagnoses. Data distribution is also different based on PTSD condition. So, the effect of war, torture, and the rest of traumatic experiences, show among participants how psychological state move away (towards the upper area) from psychological well-being. It can be seen, as per Figure 1 shows, how red data points (PTSD) have displaced from what can be considered a preserved psychological health as shown by green data points (no PTSD).

To get beyond what graphically appears to be the case and get classification quality measured, SCV and LR were used, scoring its correct classification degree from psychological data to PTSD diagnoses. Both models used all 44 psychological variables as predictor variables, and PTSD diagnoses (absence or presence) as target variable. In both cases 60% of data were used to train the model and 40% was used to test it. A 50 folds cross validation process was done to calculate average accuracy.

SVC models shown an average accuracy of .84. LR models shown a similar average accuracy of .83. Both models were able to classify well, so adolescents with and without PTSD can be correctly classified to that level of accuracy. The effect of mental health state as per PTSD disease is clearly recognizable at the detailed level of psychological variables.

Data distribution shows greater variability among PTSD (red points) compared to no PTSD (green points). In this analysis, PTSD points have an average distance to its centroid a 6.4% higher than no PTSD points. Figure 1 shows how individual differences increase in PTSD condition. These individual differences show different ways of traumatic experience. These reaction differences could be linked to traumatic experiences and show difference among protection/risk factors, as social support.

To dig deeper on PTSD data variability, we reduced all variables linked to trauma to one value. The same was done with physical condition and psychological variables. Each participant dataset was, then, reduced to a three-dimensional (3D) point, each value corresponding to each variable group (trauma, physical condition, and psychological variables). This 3D points are graphically represented in Figure 2.

This transformation showed a fit of R² = .68, with p < .01. This fit is not very high, so the graphic can suggest insights, but they are in clearly need, at the end, of hypothesis testing and effect size analysis to get back to a high level of confidence.

Figure 2 suggests two modalities of PTSD. In order to check how these two distinguishable modalities are distributed for PTSD diagnosed participants, a k-means clustering model with all 44 psychological variables to get two categories was trained and used to classify all PTSD participants in one of the two categories. That information was added, producing Figure 3.

Figure 3 suggests two modalities linked to PTSD severity. Non PTSD cases are located at a central area, having PTSD cases at two sides. It looks like the closer cases (red points) have less severe PTSD, while the more distant cases (blue points) have a more severe PTSD. This hypothesis was tested, and its results corroborated it: F (0.999, 1, 115) = 14.193, p < .05/44 (Bonferroni adjusted), η² = .110, corresponding to a medium size effect. PTSD severity was calculated as the average over the 16 items linked to PTSD DSM diagnosis.

It was not observed any relation of PTSD modalities to sex, F(0.999, 1, 115) = .260, p = .611, or age, F(0.999, 1, 115) = .252, p = .617.

Once the two PTSD modalities can be distinguished, it is relevant to know what variables, beyond those used to diagnose PTSD, best distinguish both modalities. Table 4 shows the six variables having statistically significant differences and showing largest effect sizes.

With the exception of the first one, related to executive functions (HTQ/IV item 22), the rest (HTQ/IV items 31, 34-37) are linked to social aspects: trust, unable to help other, feeling ashamed or humiliated (both social emotions), or feeling as a jinx. Based on that, it looks like having a socially preserved modality and a socially weakened modality. Average responses to those items per modality are shown at Figure 4.

Those items are related with interpersonal difficulties and, in a lesser degree, with affect dysregulation, two of the three clusters featuring complex PTSD (CPTSD) (Hyland et al., 2017). HTQ part IV item 27 has been identified as the one at HTQ differencing both syndromes (Elklit, 2014). There was a significantly statistical difference between the two as expected, but its effect size was smaller than the items selected.

There is a constantly wide distance between average responses by both modalities, preserved across all six items. Considering prevalence, socially preserved modality was 57.3% of PTSD cases. Socially weakened modality represented a 42.7%.

Due to its relation to PTSD severity, having a classification criteria could be useful for both future research and practical purposes. A NCC model was trained for the identification of PTSD modalities. A 100 folds cross validation process was done to calculate an average accuracy. A 75% of data were used to train the model, and the rest of 25% was used to test it (accuracy_average = .89; accuracy_best = 1.0). Confusion matrix, shown at Table 5, also shows very good classification performance.

Modalities, socially preserved (sp) and socially weakened (sw) have their centroids for items 22, 31, 34, 35, 36, and 37 calculated for each PTSD modality is as follows:

When a person assessed with the HTQ, the score at those items is used to calculate its Euclidean distance to each centroid.

The two modalities are the two possible values of y ̂∈{sp,sw} So, the final decision maid corresponds to the shortest distance.

Beyond classification, other psychological variables showed statistically significant differences and medium or large effect sizes. Table 6 list them.

All Table 6 variables show higher scores for socially weakened modality.

The diagnosis of PTSD was strongly related to the number of traumatic experiences suffered, F(1, 519) = 82.364, p < .001, η² = .137. The mean number of traumatic experiences for preadolescents with PTSD was 14.28 (SD = 4.91), while for those who were not diagnosed with PTSD the mean was 9.52 (SD = 5.39) traumatic experiences.

Thabet and Vostanis (1999) stated a relation between number of traumatic events and PTSD severity. In order to get some insights about this, Figure 5 was done adding information about the number of experienced traumatic events to Figure 1.

Average experienced traumatic events were 10.77, as mentioned before. That is why 10 or less traumatic events are shown with one color, and 11 or more traumatic events are shown in a different color, separating data points below or above average value.

A distribution pattern can be seen in which data points tend to distribute in the following order, from bottom to top: 1) non-PTSD children having experienced 10 traumatic events or lesser (blue points), 2) non-PTSD children having experienced more than 10 traumatic events (green points), 3) PTSD children having experienced 10 traumatic events or lesser (orange points), and 4) PTSD children having experienced more than 10 traumatic events (red points). This trend in distribution is compatible with the idea of repeated traumatic events progressively impacting on children mental health state.

Analyzing the diagnosis of PTSD based on the type of traumatic experience suffered, we found that 12 types of traumatic events seem to play an important role in the development of this pathology. Table 7 shows the data of the factors that were significant, after applying the Bonferroni correction, ordered from highest to lowest frequency for the cases in which it was found that they had suffered the traumatic experience.

Discussion

The study found that all evaluated preadolescents experienced traumatic events during the 51-day war, with no significant differences based on gender or place of residence. Most witnessed the destruction of residential areas and religious sites, were exposed to fighting, lost their homes, and witnessed chemical attacks. Many sought shelter indoors or were internally displaced to underserved areas in the Gaza Strip. Numerous teenagers witnessed injuries, deaths, and violent events involving friends and family. Approximately 15% of preadolescents aged 11 to 13 suffered physical injuries during the war, affecting individuals of all ages and genders across the Gaza Strip. The impact of the war was widespread, with half of the adolescents experiencing a lack of food and clean water, and around 7% facing starvation, highlighting the extensive destruction reported by UNRWA (2014). The effects of malnutrition in adolescents could have serious long-term effects (Khoroshinina, 2005).

Data reveals that a significant number of preadolescents suffered attacks that according to the Geneva Convention could be considered torture against children and must be persecuted (O’Donnell & Liwski, 2010). When directly asked, 28.21% of the evaluated preadolescents reported witnessing torture, with 18.81% indicating that the torture, arrests, or executions affected family members. Moreover, 7.68% of the preadolescents reported personal experiences of torture during detention. Additionally, 6.74% were compelled to physically harm someone, 6.73% experienced imprisonment, and 5.76% were used as human shields. Disturbingly, 3.07% of preadolescents, comprising 10 girls and 6 boys, reported being sexually assaulted, while 5.57% witnessed sexual abuse and rape. The reported data, aligning with findings from other studies (Kadir et al., 2019), is likely underestimated due to the cultural taboo surrounding sexuality in this population. The stigma attached to such incidents, impacting the family’s honor and the victim, often leads to concealment of such experiences (Abu-Odeh, 2010; Weishut, 2015).

The study revealed that 26.29% of preadolescents experienced PTSD, aligning with findings in previous research indicating high resilience levels among this age group, facilitating recovery over time (Planellas et al., 2020). Despite concerns about potential malingering for protection, the data in this study fall within the lower band of the PTSD variation observed in various global studies, suggesting a nuanced interaction between resilience and motivation (Steel et al., 2009).

Characteristics such as gender, age, and place of residence did not influence the presence of PTSD in the evaluated population. Instead, the determining factor was the number of traumatic experiences, with a higher number correlating with an increased likelihood of suffering from PTSD. Specific traumatic experiences, such as the disappearance of a friend, lack of medical care, forced displacement, and exposure to combat situations, appeared to play a more significant role in PTSD development than others.

Distinct patterns of distribution and classification were identified for both psychological variables and PTSD diagnoses. Preadolescents with and without PTSD were clearly distinguishable through various techniques, revealing a discernible trend from fewer to more traumatic events and from no PTSD diagnosis to PTSD diagnosis when graphing data from psychological variables.

Two PTSD modalities emerged: socially preserved and socially weakened. The primary variables distinguishing them were linked to social relationships, influencing the effectiveness of social support and indicating a more severe form of PTSD. The socially weakened modality was characterized by feelings of being unable to make daily plans, eroded executive function, lack of trust in others, powerlessness to help others, shame and humiliation from traumatic events, and a sense of being a jinx to oneself and one’s family—indicating eroded social relations, emotions, and trust. All six variables exhibited more severe scores in cases associated with the socially weakened modality.

The socially weakened modality demonstrated more severe psychological conditions across various variables: a) affected memory processes, including poor memory and being informed of actions the child could not remember (for a better understanding, see the Continuous accessibility model of memory by Manzanero & Morales-Valiente, 2024), b) poor physical condition, involving exhaustion, bodily pain, and a feeling of tightness in the chest, c) negative thoughts related to social cognition, such as feeling isolated in suffering, perceiving a lack of understanding from others, and sensing hostility from others, d) negative emotions linked to social survival, self-blame, and depression-related hopelessness, and e) an affected self-concept, manifesting as a sense of being split into two people with one observing the actions of the other.

Conclusions

The study reveals significant psychological impacts on preadolescents in the Gaza Strip following the attacks, emphasizing the prevalence of post-traumatic symptoms affecting emotional well-being and daily functioning. The findings underscore the urgent need for psychological support in communities affected by such traumatic events. Similar to other research, 26.29% of preadolescents were found to suffer from PTSD, aligning with the notion of their generally high resilience. The study acknowledges the potential for over reporting due to malingering but notes that the prevalence falls within the lower range observed in various studies.

Data analysis techniques provided insights into the relationship between psychological variables, PTSD, and the number of traumatic events experienced. Clear patterns emerged in the distribution and classification of these variables, allowing for the differentiation of preadolescents with and without PTSD. The analysis also identified two PTSD modalities: socially preserved and socially weakened. The socially weakened modality exhibited more severe psychological conditions across various dimensions, including memory processes, physical well-being, thoughts, emotions, and self-concept. The study proposes a classifier system (NCC) for further research and potential applications in understanding and treating PTSD. Whether those two modalities correspond to PTSD and CPTSD is not clear from data and needs additional research.

Understanding the effects of past wars on preadolescents in Gaza and distinguishing between different types of PTSD could facilitate comprehension of the current Israeli attacks on Palestine (Gaza and the West Bank). It can also aid in determining the type of intervention needed to minimize the impact on the mental health of Palestinian youth, enhancing their resilience through social support.