Abstract

The aim of the present study was to assess the impact ofpast traumatic war experiences on preadolescents in theGaza Strip, which could be useful for psychologicalintervention with current and future child victims.Participants were 521 preadolescents from the UnitedNations Relief and Works Agency for Palestine Refugeesin the Near East (UNRWA) schools, aged 11 and 13 yearsold. Sections I to IV from the Iraqi Version-Arabic ofHarvard Trauma Questionnaire was used to assesstrauma experiences and Post-Traumatic Stress Disorder(PTSD). The results show that the preadolescents in theGaza Strip witnessed the destruction of their homes andthe murder of family members and friends. A quarter ofthe individuals assessed either suffered torture orwitnessed others undergoing it, including sexual assaults.Almost half of them experienced a lack of food and cleanwater. The traumatic and torture experiences seriouslyaffected preadolescents’ mental health as 26.29% met thecriteria for the diagnosis of PTSD. The data analysisrevealed two PTSD modalities, with the severity ofimpact depending on whether social implications wereinvolved. Further research is required to check whetherthese two modalities fit to PTSD and complex PTSD.Understanding the effects of past wars on preadolescentsin Gaza and distinguishing between different PTSD typescould enhance comprehension of the impacts of currentattacks on child victims. It can also aid in determining thetype of intervention needed to minimize the impact on themental health of Palestinian youth, enhancing theirresilience through psychological and social support.

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Keywords:
War Victims, Psychological Trauma,Children, Post-Traumatic Stress Disorder, SocialSupport

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Cite this article as Manzanero, A. L., Aroztegui, J.,Fernández, J., Guarch-Rubio, M., Álvarez, M. Á., ElAstal, S., and Hemaid, F. (2024). War, Torture andTrauma in Preadolescents from Gaza Strip. TwoDifferent Modalities of PTSD. Anuario de PsicologíaJurídica, 34(1), 1 - 12. https://doi.org/10.5093/apj2024a6

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Funding:
This paper is part of a research project onassessment of memories and psychological disordersassociated to trauma in refugees and victims of war,developed by the UCM Research Group on EyewitnessTestimony (ref. 971672), in the framework of the projectsfinanced by Santander-Universidad Complutense deMadrid (PR75/18-21661).

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Introduction

In the last decade, armed conflicts and human rightsviolations have increased worldwide. Of particularseverity are situations of ethnic cleansing that result inthe forced displacement and extermination of thousandsof people. Minors are the most vulnerable victims inthese conflicts. Since October 2023, following an attackby Hamas, the State of Israel launched an assault on theGaza Strip and the West Bank, resulting in over 26,000deaths by January 2024, with approximately half beingchildren. Thousands of children have been injured,witnessed the murder of their relatives, had to leave theirhomes, and lacked basic supplies to survive. These eventsare currently under investigation by the InternationalCourt of Justice in The Hague as potential genocide.Understanding the psychological impact that previousattacks had on surviving children could aid in futurepsychological interventions for the new victims.

Preadolescents in war zones may face severedevelopmental impacts due to traumatic experiences,particularly related to torture, with limited specificstudies in this age group (Dimitry, 2012). Existingresearch focuses on younger and older populations,revealing that children and adolescents are significantlyaffected by war situations (Barber, 2008). Mental healthstudies indicate that minors from war zones often exhibitpathologies such as posttraumatic stress disorder(PTSD), anxiety, and depression (Bronstein &Montgomery, 2011; Dimitry, 2012; Slone & Mann,2016).

Determining factors influencing the effects includeexposure level, age, gender, family factors, socioeconomic adversity, coping strategies, belief systems,social support, and religiosity (Dimitry, 2012; Lustig etal., 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 acrucial role (Hiller et al., 2018). The relationship betweensocial support and PTSD is intricate, with social supportpotentially buffering the effects of adverse childhoodexperiences (ACE), while ACE may negatively impactsocial support (Jones et al., 2018; Wang et al., 2021).

A meta-analysis focused on social support as a PTSDpredictor found complex relations, varying based ontypes of traumatic events (Zalta et al., 2021). PTSD,associated with traumatic experiences, has facedcriticism for diagnostic criteria (Manzanero et al.,2021; McNally et al., 2014). Some argue that PTSD is acognitive pathology related to memory processes, whereperceptions of traumatic memories predict post-traumaticstress symptoms (Brewin, 2001; Brewin et al.,1996; Manzanero et al., 2020; Manzanero & MoralesValiente, 2024; McGuire et al., 2021).

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

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

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The Case of the Gaza Strip

The whole Palestine region, and the Gaza Strip inparticular, have undergone a persistent conflict fordecades that has implied repetitive exposure to violenceand war and that have clearly eroded the psychologicalwell-being, health, and quality of life of childrenpopulation (D’Andrea et al., 2023; Manzanero et al.,2021; Massad et al., 2009; Shank et al., 2023; Shehadehet al., 2015; Thabet et al., 2014, 2009; Thabet & Thabet,2016; Thabet & Vostanis, 1999, 2000), adding urgencyto the need to understand and address the implications ofwar-related trauma in this population.

In general, the severity of psychological disorders inminors exposed to war-related violence depends on thequantity of the traumatic events suffered (Thabet &Vostanis, 1999). In any case, there are importantindividual differences (Kolltveit et al., 2012; Punamaki,2002) and resilient strategies (Betancourt et al., 2013; Tolet al., 2013). Several studies have found that girls in Gazawould 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 warsituations (Lustig et al., 2004). Most of the studies (Kadiret al., 2019) point out, among the most frequent, the lackof medical attention and diseases related to unsanitaryconditions and lack of food, exposure to toxins (whichincrease the medium and long-term prevalence ofcancer), environmental and meteorological factors,exposure to violence and extreme trauma (primary orsecondary), social and geographical changes, and sexualassaults. APA (2000) defined extreme trauma as directlyexperiencing, witnessing, or learning about events thatinvolve actual or threatened death or, serious injury, orother threats to physical integrity.

Sometimes, traumatic experiences in war situationscorrespond to what has been defined as torture (Kadir etal., 2019; Quiroga, 2009). According to Article 1 of theConvention against Torture and Other Cruel, Inhuman orDegrading Treatment or Punishment (UNCAT), adoptedby the United Nations’s General Assembly in its 39/46resolution of December 10th, 1984, “torture” shall beunderstood as any act by which severe pain or suffering,whether physical or mental, is intentionally inflicted on aperson in order to obtain information or a confessionfrom him or a third party, to punish him for an act he hascommitted, or is suspected of having committed, or tointimidate or coerce that person or others, or for anyreason based on any type of discrimination when saidpain or suffering is inflicted by a public official oranother person in the exercise of public functions, at hisinstigation, or with his consent or acquiescence. Article 2specifies that in no case may exceptional circumstances,such as a state of war or threat of war, internal politicalinstability or any other public emergency, be invoked asa justification for torture.

In addition, sexual assaults have been reported in warsituations against minors on numerous occasions (Kadiret al., 2019). In the case of Palestine, the PublicCommittee 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 sexualharassment, either directed toward Palestinian men andboys or toward family members and 35 reports of forcednudity; 15% of the attacks were against minors (Weishut,2015).

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Context and Objectives of the Current Study

On July 8th, 2014, the Israeli Army launched an attackagainst the population of the Gaza Strip that lasted 51days, causing the death of 2,251 people, 551 of themchildren, 299 women and 64 unidentified. During theconflict, 11,231 Palestinians were injured, including 3,436 children. This attack caused the destruction ofinfrastructures, particularly water supplies and sewerage,while the destruction of dwellings left more than 500,000people homeless. During this time, 118 UNRWA (UnitedNations Relief and Works Agency for Palestine Refugeesin the Near East) installations were damaged, including83 schools and 10 health centers. In total, over 12,600housing units were totally destroyed, and almost 6,500sustained severe damage. Almost 150,000 additionalhousing units sustained various degrees of damage andremained inhabitable. The conflict led to a massivedisplacement crisis in Gaza, with almost 500,000 personsinternally displaced at its peak. Approximately 50,000 ofthem took refuge in UNRWA schools. Other peoplefound refuge with family or friends in overcrowdedconditions and lack of essential resources (UNRWA,2014).

Consequently, this study assessed exposure to traumaticevents and posttraumatic symptoms in preadolescentsfrom the Gaza Strip between December 30th, 2014, andMay 17th, 2015. The study’s objectives were: (1) todetermine the prevalence of exposure to traumatic eventsamong male and female children aged 11 to 13 living inthe Gaza Strip, and (2) to examine the symptoms oftraumatic stress in these children.

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Method

Participants

A total of 521 preadolescents (11-13 years old) from theGaza 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 theGaza Strip: Rafah, Khan Yunis, Wustah, Gaza City, andNorth Gaza. All of them attended UNRWA elementaryschools.

Material

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

• First section enumerates 39 traumatic events ina yes/no question.

• Second section include 35 yes/no questionsabout torture experiences.

• Third section measures physical effects of war(injury and starvation), composed by three itemswith several types of responses depending onthe information requested.

• Fourth section measures psychologicalsymptoms of trauma and is composed of 44 items thatevaluate the severity or intensity of the symptoms on a 4-point Likert scale (1 = not at all, 2 = a little, 3 = quite abit, and 4 = extremely). The first 16 items aim to measurePTSD symptoms according to DSM-IV criteria, with athreshold of 2.5 or higher. The other 28 items quantifywhat the authors name “refugee specific”, whichevaluates the impact that the traumatic events could havehad on their perception of their own daily life. The overallscale of section 4 also considers a threshold value of 2.5or higher.

Procedure

For the purpose of this study, the UNRWA schools in theGaza Strip were asked in writing by the Department ofPsychology of the Al-Azhar University-Gaza for theircollaboration in the application of the HTQ traumaquestionnaire. When approval was obtained,psychologists who worked with the families went to theschools to meet the children and their parents. Thepurpose of the study was explained, and the children’sparents were asked for their consent to apply the test. Theinstruments were applied in individualized interviews bypsychologists from UNRWA schools between December2014 and May 2015, several months after the Israeli armycarried out attacks on the Gaza Strip from July untilAugust 2014.

Data Analysis Techniques

The first perspective of data analysis explored variablesone by one or relationships of couples of variables. To dothat, data exploration and analysis used several toolsbased on the research questions to answer. Cronbach’salpha was calculated to measure scale reliability.Analysis of variance (ANOVA) and chi-squared (χ2)were used to test statistically significant differences, andeta-squared (η2) to assess effect size.

The second perspective of data analysis explored a largeor complete set of assessed variables. Multidimensionalscaling (MDS) was used to permit 3D dimensionalityreduction (Nguyen & Holmes, 2019) and datavisualization (Walny et al., 2019) of complex data.Specifically, classic metric MDS was used. Those graphsreflect data distribution, so it is possible to see, forexample, if people with and without PTSD are somehowgrouped. Interesting visual groupings are analyze usingmachine learning (ML), also called data science (DS),tools to check group arrangements beyond apparentvisual arrangement. That way, evidence (or a lack of it)is obtained to support those groupings. Support vectorclassifier (Vapnik, 1998) (SVC), multivariate logisticregression (MLR), and k-means (Yadav & Sharma,2013) nearest centroid classifier (Levner, 2005) (KM-NCC) are used to get global support. Additionally, oneway ANOVA (group comparison) and η2 are used todetect the most relevant variables, differentiatingidentified groupings.

Additional data analysis ML techniques are used,providing additional insights through its different dataanalysis perspectives. “(…) machine learning enablesmore rigorous exploration and holds the potential toadvance theory formation in developmental psychologyand other fields. Machine learning is an umbrella term formethods that learn patterns from data through automatedmodel build” (Van Lissa, 2023, p. 2). Although MLmethods are still a novelty in psychological research, itsuse is growing fast in all areas of psychological research(Orrù et al., 2020), as educational psychology (Levy etal., 2020; Luan and Tsai, 2021), clinical psychology(Dwyer et al., 2018), and social psychology (Kumar etal., 2019). Because these techniques used here are stillnot very widely known, they are shortly described in afoot note2.

Samples with missing data were removed for DSanalysis, implying a reduction of 8.6% of data samples.Data imputation using average values decreases datavariability (Hastie et al., 2009), making groupingidentification difficult. To prevent higher values biasbeing favored in algorithm training, Likert-type itemswere rescaled from [1, 2, 3, 4] values to [-1.5, -0.5, 0.5,1.5]3.

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Ethical Information

Children’s participation in the study was voluntary andapproved by their family members or caregivers. All thechildren and their families who participated in the studyhad the necessary psychological support. This study waspart of the research project about the assessment ofpsychological trauma in vulnerable refugees and asylumseekers (children and women), and was approved by theEthic Committee from [masked institution]. It wasendorsed by UNHCR-Spain and declared of interest tothe European Union, and it was possible thanks to thecollaboration of the UNRWA schools. After the attacksof the summer of 2014 the UNRWA’s CommunityMental Health Programme assisted refugees in the GazaStrip, asserted that children who could present physicaland psychological needs were adequately cared for. Theycollectively support children and families, not onlythrough individual and group counselling, but targetedinterventions aimed at enhancing psychosocial resiliencyand well-being. Along the armed conflict, UNRWAprovided humanitarian assistance (including non-fooditems, food, water, psycho-social support) to internallydisplaced persons in 90 of 156 UNRWA schoolbuildings, with the remaining school buildings eitherunsafe or damaged. On 23rd August, 2014, a record-high of 292959 internally displaced persons were counted in85 UNRWA school buildings (UNRWA, 2014).

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Results

The results are reported by grouping the responses of theparticipants to the four sections of the questionnaireapplied in “traumatic war events”, “torture experiences”,“physical effects”, and “mental health”. Also, two moresections were added, “sexual abuse” and “posttraumaticstress disorder”.

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Traumatic War Events

The results of the participants are reported separately onthe questions raised about the experience of eventsrelated to the war, and in a different section of thosesituations that go beyond combat situations and can beconsidered torture according to the UNCAT (1984). TheCronbach’s alpha of the section in this sample was .844.

Table 1 shows the traumatic situations to which thepreadolescents were exposed in order from highest tolowest frequency. As can be seen, the majority witnessedthe destruction of residential areas and religious sites andwere confined to try to protect themselves frombombings and violence. A large number ofpreadolescents were exposed to fighting and witnessedthe presence of corpses. About half of the childrenstudied had to leave their homes and witness chemicalattacks. Around 40 % of their friends or family wereinjured as a result of the fighting and shelling, wereforced to internally displaced in the Gaza Strip tounderserved areas, and witnessed some people beinginjured. Around a third of the minors witnessed deaths,executions of civilians, and lacked shelter to protectthemselves from the war. About 20 percent lost friends inviolent deaths and their property was destroyed. Around10 percent or less witnessed their homes being searched,suffered the disappearance of friends and the violentdeath of a relative, were victims of complaints that putthem at risk of death, and were searched on occasion.

The evaluated preadolescents suffered an average of10.77 traumatic events throughout the 51 days of the war.No statistically significant differences were found in thenumber of traumatic experiences according togender, F(1, 519) = 1.559, p = .212, η2 = .003; age, F(2,518) = 1.690, p = .186, η2 = .006; or the place ofresidence, F(4, 516) = 1.261, p = .284, η2 = .010.

Torture Experiences

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

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Table 1

Children Who Experienced Different Types of Traumatic War Events, Ordered by Frequencies from Highestto Lowest

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Table 2

Children Who Experienced Different Types of Torture and Cruel, Inhuman, or Degrading Treatment, Ordered byFrequencies from Highest to Lowest

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Forty preadolescents (7.68%) reported having beentortured while being held. Around a quarter of thepreadolescents evaluated reported that they witnessedtorture and a fifth that such torture, arrests, or executionswere against relatives. Between 8 and 9 percent wereforced to destroy their property or to expose someone,putting their lives at risk. Some 30 teenagers were usedas human shields, forced to cause physical harm to otherpeople, taken prisoner, or witnessed sexual assaults andrapes. Around 25 children had suffered the kidnapping ofrelatives or friends, and 13 were themselves kidnappedor taken hostage.

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

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Table 3

Scores of Mental Health Symptoms, Ordered by Frequencies from Highest to Lowest

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Physical Effects

Seventy-seven preadolescents (14.8%) were physicallyharmed, 35 (6.7%) informed about physical injuries dueto nearby explosions, and 47 (9.03%) about seriousphysical injury from combat situation. No statisticallysignificant differences were found based on gender orage. Nor were statistically significant differences foundfor “serious physical injury from combat situation” basedon gender, age or residence.

Due to the confinement and food shortages, and due tosupply problems during the 51 days of attacks on theGaza Strip, 233 children (44.72%) suffered from “foodand drinking water shortages”, and 36 (6.9%) reportedhaving suffered “starvation” that resulted in a weight lossof between 0 to 15 kg. (M = 4.50, SD = 3.31).

Statistically significant differences were found for “lackof 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 instarvation based on gender or age.

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

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Mental Health Effects

Table 3 shows the data collected regarding some aspectsrelated to the mental health of the preadolescentsevaluated, ordered from highest to lowest frequency. TheCronbach’s alpha of the section in this sample was .96.Considering the symptoms that the evaluatedpreadolescents present, we found that 137 (26.29%)would have PTSD. No statistically significant differenceswere found according to age, χ2(2, N = 521) = 2.933, p =.231; gender, χ2(1, N = 521) = 0.028, p = .867; or theplace of residence, χ2(4, N = 521) = 2.715, p = .607.DS techniques were used to analyze data distribution andvariable 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 asa 3D scatterplot graph (Figure 1). PTSD diagnosepresence or absence is shown through color.

In this case, two aspects are especially useful for a betterunderstanding of symptoms: data distinguishability anddata distribution. Data distinguishability tells us if we candistinguish, separate, psychological data consideringPTSD diagnoses. This graph visualizes the war effects inpsychological variables and PTSD. Data distribution ineach group shows individual differences both onparticipants meeting and not meeting PTSD DSMcriteria.

Data can be visually distinguished based on PTSDdiagnoses. Data distribution is also different based onPTSD condition. So, the effect of war, torture, and therest of traumatic experiences, show among participantshow psychological state move away (towards the upperarea) from psychological well-being. It can be seen, asper Figure 1 shows, how red data points (PTSD) havedisplaced from what can be considered a preservedpsychological health as shown by green data points (noPTSD).

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Figure 1

Data Distribution per PTSD Diagnosis4

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

SVC models shown an average accuracy of .84. LRmodels shown a similar average accuracy of .83. Bothmodels were able to classify well, so adolescents withand without PTSD can be correctly classified to that levelof accuracy. The effect of mental health state as perPTSD disease is clearly recognizable at the detailed levelof psychological variables.

Data distribution shows greater variability among PTSD(red points) compared to no PTSD (green points). In thisanalysis, PTSD points have an average distance to itscentroid a 6.4% higher than no PTSD points. Figure1 shows how individual differences increase in PTSDcondition. These individual differences show differentways of traumatic experience. These reaction differencescould be linked to traumatic experiences and showdifference among protection/risk factors, as socialsupport.

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Figure 2

Data distribution per Variable Group, and PTSD Diagnosis5

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To dig deeper on PTSD data variability, we reduced allvariables linked to trauma to one value. The same wasdone with physical condition and psychologicalvariables. Each participant dataset was, then, reduced toa three-dimensional (3D) point, each valuecorresponding to each variable group (trauma, physicalcondition, and psychological variables). This 3D pointsare 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 suggestinsights, but they are in clearly need, at the end, ofhypothesis testing and effect size analysis to get back toa high level of confidence.

Figure 2 suggests two modalities of PTSD. In order tocheck how these two distinguishable modalities aredistributed for PTSD diagnosed participants, a k-meansclustering model with all 44 psychological variables toget two categories was trained and used to classify allPTSD participants in one of the two categories. Thatinformation was added, producing Figure 3.

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

It was not observed any relation of PTSD modalities tosex, 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 isrelevant to know what variables, beyond those used todiagnose PTSD, best distinguish both modalities. Table4 shows the six variables having statistically significantdifferences and showing largest effect sizes.

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Table 4

ANOVA Results and η2 Effect Size of Main Variables Distinguishing PTSD Modalities

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*p < .01/44 (Bonferroni adjusted).
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), orfeeling 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.

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Figure 4

Main Variables Distinguishing PTSD Modalities Average Values

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Those items are related to interpersonal difficulties and,in a lesser degree, with affect dysregulation, two of thethree clusters featuring complex PTSD (CPTSD)(Hyland et al., 2017). HTQ part IV item 27 has beenidentified as the one at HTQ differencing both syndromes(Elklit, 2014). There was a significantly statisticaldifference between the two, as expected, but its effectsize was smaller than the items selected.There is a constantly wide distance between averageresponses by both modalities, preserved across all sixitems. Considering prevalence, socially preservedmodality was 57.3% of PTSD cases. Socially weakenedmodality represented a 42.7%.Due to its relation to PTSD severity, having aclassification criteria could be useful for both futureresearch and practical purposes. A NCC model wastrained for the identification of PTSD modalities. A 100folds cross validation process was done to calculate anaverage accuracy. A 75% of data were used to train themodel, and the rest of 25% was used to test it(accuracyaverage = .89; accuracybest = 1.0). Confusionmatrix, shown at Table 5, also shows very goodclassification performance.

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Table 5

NCC Confusion Matrix7

Modalities, socially preserved (sp) and sociallyweakened (sw) have their centroids for items 22, 31, 34,35, 36, and 37 calculated for each PTSD modality is asfollows:μ→sp=(2.46,2.12,1.9,1.28,1.44,2.12)μ→sw=(3.27,3.11,2.84,2.35,2.7,3.11)When a person assessed with the HTQ, the score at thoseitems is used to calculate its Euclidean distance to eachcentroid.y^=argminm∈Mμ→m−x→The two modalities are the two possible values ofy ̂∈{sp,sw} So, the final decision maid corresponds to theshortest distance.Beyond classification, other psychological variablesshowed statistically significant differences and mediumor large effect sizes.

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Table 6 list them.

ANOVA Results and η2 Effect Size of Additional Variables with Medium to Large Effect Sizes per PTSD Modality

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All Table 6 variables show higher scores for sociallyweakened modality.The diagnosis of PTSD was strongly related to thenumber of traumatic experiences suffered, F(1, 519) =82.364, p < .001, η2 = .137. The mean number oftraumatic experiences for preadolescents with PTSD was14.28 (SD = 4.91), while for those who were notdiagnosed with PTSD t

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Figure 5

Data Distribution per PTSD Diagnosis and Number of Traumatic Events Suffered8

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Thabet and Vostanis (1999) stated a relation betweennumber of traumatic events and PTSD severity. In orderto get some insights about this, Figure 5 was done addinginformation about the number of experienced traumaticevents to Figure 1.Average experienced traumatic events were 10.77, asmentioned before. That is why 10 or less traumatic eventsare shown with one color, and 11 or more traumaticevents are shown in a different color, separating datapoints below or above average value.A distribution pattern can be seen in which data pointstend to distribute in the following order, from bottom totop: 1) non-PTSD children having experienced 10traumatic events or lesser (blue points), 2) non-PTSDchildren having experienced more than 10 traumatic events (green points), 3) PTSD children havingexperienced 10 traumatic events or lesser (orange points),and 4) PTSD children having experienced more than 10traumatic events (red points). This trend in distribution iscompatible with the idea of repeated traumatic eventsprogressively impacting on children mental health state.Analyzing the diagnosis of PTSD based on the type oftraumatic experience suffered, we found that 12 types oftraumatic events seem to play an important role in thedevelopment of this pathology. Table 7 shows the data ofthe factors that were significant, after applying theBonferroni correction, ordered from highest to lowestfrequency for the cases in which it was found that theyhad suffered the traumatic experience.

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Table 7

Percentages of preadolescents diagnosed with PTSD who had not suffered the traumatic event and who had, and values of χ2 forthe events that were significant.

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Discussion

The study found that all evaluated preadolescentsexperienced traumatic events during the 51-day war, withno significant differences based on gender or place ofresidence. Most witnessed the destruction of residentialareas and religious sites, were exposed to fighting, losttheir homes, and witnessed chemical attacks. Manysought shelter indoors or were internally displaced tounderserved areas in the Gaza Strip. Numerous teenagerswitnessed injuries, deaths, and violent events involvingfriends and family. Approximately 15% ofpreadolescents aged 11 to 13 suffered physical injuriesduring the war, affecting individuals of all ages andgenders across the Gaza Strip. The impact of the war waswidespread, with half of the adolescents experiencing alack of food and clean water and around 7% facingstarvation, highlighting the extensive destructionreported by UNRWA (2014). The effects of malnutritionin adolescents could have serious long-term effects(Khoroshinina, 2005).

Data reveals that a significant number of preadolescentssuffered attacks that according to the Geneva Conventioncould be considered torture against children and must bepersecuted (O’Donnell & Liwski, 2010). When directlyasked, 28.21% of the evaluated preadolescents reportedwitnessing torture, with 18.81% indicating that thetorture, arrests, or executions affected family members.Moreover, 7.68% of the preadolescents reported personalexperiences of torture during detention. Additionally,6.74% were compelled to physically harm someone,6.73% experienced imprisonment, and 5.76% were usedas human shields. Disturbingly, 3.07% of preadolescents,comprising 10 girls and 6 boys, reported being sexuallyassaulted, while 5.57% witnessed sexual abuse and rape.The reported data, aligning with findings from otherstudies (Kadir et al., 2019), is likely underestimated dueto the cultural taboo surrounding sexuality in thispopulation. The stigma attached to such incidents,impacting the family’s honor and the victim, often leadsto the concealment of such experiences (Abu-Odeh,2010; Weishut, 2015).

The study revealed that 26.29% of preadolescentsexperienced PTSD, aligning with findings in previousresearch indicating high resilience levels among this agegroup, facilitating recovery over time (Planellas et al.,2020). Despite concerns about potential malingering forprotection, the data in this study fall within the lowerband of the PTSD variation observed in various globalstudies, suggesting a nuanced interaction betweenresilience and motivation (Steel et al., 2009).

Characteristics such as gender, age, and place ofresidence did not influence the presence of PTSD in theevaluated population. Instead, the determining factor wasthe number of traumatic experiences, with a highernumber correlating with an increased likelihood ofsuffering from PTSD. Specific traumatic experiences,such as the disappearance of a friend, lack of medicalcare, forced displacement, and exposure to combatsituations, appeared to play a more significant role inPTSD development than others.

Distinct patterns of distribution and classification wereidentified for both psychological variables and PTSDdiagnoses. Preadolescents with and without PTSD wereclearly distinguishable through various techniques,revealing a discernible trend from fewer to moretraumatic events and from no PTSD diagnosis to PTSDdiagnosis when graphing data from psychologicalvariables.

Two PTSD modalities emerged: socially preserved andsocially weakened. The primary variables distinguishingthem were linked to social relationships, influencing theeffectiveness of social support and indicating a moresevere form of PTSD. The socially weakened modalitywas characterized by feelings of being unable to makedaily plans, eroded executive function, lack of trust inothers, powerlessness to help others, shame andhumiliation from traumatic events, and a sense of beinga jinx to oneself and one’s family—indicating erodedsocial relations, emotions, and trust. All six variablesexhibited more severe scores in cases associated with thesocially weakened modality.

The socially weakened modality demonstrated moresevere psychological conditions across various variables:a) affected memory processes, including poor memoryand being informed of actions the child could notremember (for a better understanding, see the Continuousaccessibility model of memory by Manzanero &Morales-Valiente, 2024), b) poor physical condition,involving exhaustion, bodily pain, and a feeling oftightness in the chest, c) negative thoughts related tosocial cognition, such as feeling isolated in suffering,perceiving a lack of understanding from others, andsensing hostility from others, d) negative emotions linkedto social survival, self-blame, and depression-relatedhopelessness, and e) an affected self-concept,manifesting as a sense of being split into two people withone observing the actions of the other.

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Conclusions

The study reveals significant psychological impacts onpreadolescents in the Gaza Strip following the attacks,emphasizing the prevalence of post-traumatic symptomsaffecting emotional well-being and daily functioning.

The findings underscore the urgent need forpsychological support in communities affected by suchtraumatic events. Similar to other research, 26.29% ofpreadolescents were found to suffer from PTSD, aligningwith the notion of their generally high resilience. Thestudy acknowledges the potential for over reporting dueto malingering but notes that the prevalence falls withinthe lower range observed in various studies.

Data analysis techniques provided insights into therelationship between psychological variables, PTSD, andthe number of traumatic events experienced. Clearpatterns emerged in the distribution and classification ofthese variables, allowing for the differentiation ofpreadolescents with and without PTSD. The analysis alsoidentified two PTSD modalities: socially preserved andsocially weakened. The socially weakened modalityexhibited more severe psychological conditions acrossvarious dimensions, including memory processes,physical well-being, thoughts, emotions, and selfconcept. The study proposes a classifier system (NCC)for further research and potential applications inunderstanding and treating PTSD. Whether those twomodalities correspond to PTSD and CPTSD is not clearfrom data and needs additional research.

Understanding the effects of past wars on preadolescentsin Gaza and distinguishing between different types ofPTSD could facilitate comprehension of the currentIsraeli attacks on Palestine (Gaza and the West Bank). Itcan also aid in determining the type of interventionneeded to minimize the impact on the mental health ofPalestinian youth, enhancing their resilience throughsocial support.

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The authors of this article declare no conflict ofinterest.

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Acknowledgments

To the psychologists and teachers of UNRWA whocollaborated in the study and dedicate their lives to thechildren of Palestine. To the children and their familieswho are victims of the conflict that still persists.Cite this article as: Manzanero, A. L., Aroztegui, J.,Fernández, J., Guarch-Rubio, M., Álvarez, M. A., ElAstal, S., & Hemaid, F. (2024). War, torture and traumain preadolescents from Gaza Strip. Two differentmodalities of PTSD. Anuario de Psicología Jurídica, 34,1-12. https://doi.org/10.5093/apj2024a6Funding: This paper is part of a research project onassessment of memories and psychological disordersassociated to trauma in refugees and victims of war,developed by the UCM Research Group on EyewitnessTestimony (ref. 971672), in the framework of the projects financed by Santander-Universidad Complutense deMadrid (PR75/18-21661).

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Notes

1. After data collection a new version of the HTQ adaptaedto DSM-5 has been developed (Berthold et al., 2019).
2. For each preadolescent, a large set of values is available(greater that 100), but it cannot be graphed being so manyvariables. Similar set of values, corresponding to twopreadolescents, should be near, due to its similarity.Diverging set of values, also corresponding to twopreadolescents, should be distant, due to its dissimilarity.MDS performs a dimensionality reduction preserving asmuch as possible the relative distances between allsamples, providing a 3D point to represent each set ofvalues of each preadolescent. This 3D points can now begraphed and explored to see its distributions andgroupings.SVC takes two groupings and build the best distinctioncriteria (a hyperplane) separating both groups. SVC istrained with classified samples (from the training set) anduses its classification labels to reduce classification error(supervised learning). The level of accuracy classifyingsamples from both groups in the testing dataset isassessed. If accuracy is high, the initially detectedgrouping get evidence support. Both groups are differentenough.MLR does the same as SVC in a different way.Coincidental results will add addition evidential supportof the differences between detected groups.KM-NCC does the same as SVC and MLR but with adifferent algorithm that uses unsupervised learning. KMNCC uses the training dataset to group by geometricalproximity. Then, distance to the centroid of each group isused for classification. Testing dataset is used to assessclassification accuracy. Again, coincidental quality ofclassification ends up supporting the visually detectedgroupings.
3. DS analyses were done using Python v3.8.8, ipythonv7.22.0, conda v4.10.1, numpy v1.19.5, scipy v1.6.2,statsmodels v0.13.5, pandas v1.2.4, scikit-learn v0.24.1,matplotlib v3.3.4 and plotly v5.4.0.ML code accessible at: https://github.com/javier/PTSD_Modalities.
4. All variables (traumatic events experienced, physicalcondition, and psychological variables) reduced to 3Dpoints through MDS and colored by PTSD presence orabsence.
5. Traumatic events experienced, physical condition, andpsychological variables, reduced to 1 value per variablegroup through MDS. Values obtained combined as 3Dpoints and colored by PTSD presence or absence. a)Initial view. b) Initial view rotated 45 degrees right. c)Initial view rotated 90 degrees right. Points colored byPTSD diagnosis.
6. Traumatic events experienced, physical condition, andpsychological variables, reduced to 1 value per variablegroup through MDS as in Figure 2. a) Initial view. b)Initial view rotated 45 degrees right. c) Initial viewrotated 130 degrees right. PTSD points are distinguishedby PTSD modality. Red and blue points correspond toboth PTSD modalities.
7. Many true positive (TP) and negative (TN) cases werecorrectly classified. Very few positive (FP) and negative(FN) cases were incorrectly classified. It was a very wellbalanced classifier, with TP and TN rates giving a b_acc= (TPR + TNR) / 2 = 1.0.
8. Same as Figure 1 highlighting the number of traumaticevents suffered for both PTSD and non-PTSD cases.

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