Introduction
The eruption of conflict and war not only disrupts societal harmony but also deeply impacts the mental well-being of individuals particularly those residing in conflict zones [1, 2]. The onset of war in Gaza on October 7, 2023, alarmed communities and international entities about the impact of war on the health and well-being of individuals in Gaza. However, those residing in the near areas have also under the same e pressure and negative impact of War, in particular, students in West Bank. The literature asserted that wars, which are man-created situations, do jeopardize people’s physical, psychological, and social health [3]. There are direct and indirect negative effects on the well-being and welfare of people. Amongst are the young people whom mainly at their university years and seems to be affected and struggle to compromise between their paternalistic and academic duties and responsibilities.
While university students are all at risk for psychosocial and academic distress in normal situations [4, 5], war would add to their struggle and might compromise their well-being if they lack appropriate skills. Anxiety, depression, and stress are multi-faceted and multi-factorial phenomena. While anxiety and depression are found to affect individuals’ physical and mental well-being [6], resilience has been reported to serve as a buffering factor for their adaptation [7] Particularly, a qualitiative study examined how the conflict in Yemen impacted the lived experience of health workers and their coping capacities found that during the political conflict times in Yemen, resilience was found to buffer the impact of conflict-related stressors and reverse the negative effect of exposure to violence [8]. In the context of Palestine, some studies have provided valuable insights into the psychological well-being of various demographic groups amidst the protracted conflict. For instance, a recent study assessed the prevalence of depression, and anxiety symptoms and coping mechanisms among Palestinian university students during the times of current political violence in Palestine after October 7, 2023 [9]. Beside, a systematic review and meta-analysis estimated that in post-conflict environments almost one in ten people (9.1%) have a moderate of severe mental illness at any one time; more than one in five people (22.1%) have depression, anxiety disorder, post-traumatic stress disorder, bipolar disorder, or schizophrenia, and they alarming rates of psychological distress among youth exposed to chronic violence and political instability [10]. This infers that there is a need to address the magnitude of the negative effect of wars on mental well-being while, assessing the level of personal capability or resilience to adapt and manage mental health needs.
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Several studies emphasized War’s negative effect on university students’ health and well-being. For instance, a study conducted by Yousef et al. [11] revealed significant psychological distress among Syrian university students during the war period in Syria. In Palestine, Shawahna et al. [12] reported high anxiety and depression levels among medical students, while Canetti et al. [13] found a connection between exposure to political violence and elevated levels of anxiety and depression in Palestine. In addition, Goncharuk-Khomyn et al. [14] addressed the psychological status among foreign students in Ukraine and found a decrease in the level of students’ satisfaction with the quality of dental and medical education considering the impact of the war in Ukraine. The profound impact of the War in Gaza also affects the residents of the West Bank due to Israeli Occupation restrictions.
The literature addressed the psychological status of nursing students who were found to be distressed and overwhelmed academically and psychologically [15]. Consequently, and during the War times similar to the October 7th War against Gaza, it is expected that nursing students would suffer further psychosocial distress and disturbances. Therefore, the current outbreak of war in Gaza heightened concerns about the mental health and well-being of undergraduate nursing students. Individuals, globally, have witnessed the extensive scenes and stories of bloodshed in Gaza. Such an effect is expected to be severely magnifying the effect on Palestinians in other territories outside Gaza. Of those the nursing students who feel responsible for providing all support and care to their sisters and brothers. The struggle in Palestine is been for decades; however, it is extensively been observed during the past few years due to political conflicts. This study sheds light on anxiety, depression, and stress among nursing students at Al-Quds University, and investigates their resilience level. The purpose is to assess the moderation effect of resilience on the relationship between anxiety, depression, stress, and the sociodemographic and personal characteristics of nursing students in West Bank. The specific aims are:
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To assess the status of anxiety, depression, stress, and resilience levels among nursing students among nursing students in West Bank.
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To assess the moderation effect of resilience on the relationship between anxiety, depression, and stress and the sociodemographic and personal characteristics of nursing students in West Bank.
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To investigate differences in levels of anxiety, depression, stress, and resilience concerning sociodemographic and personal characteristics among nursing students in West Bank.
In term of research hypotheses in this study we have three main hypotheses as following:
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Hypothesis 1 (H1)
The war that started on October 7 in Palestine has a significant positive impact on levels of anxiety, depression, and stress among undergraduate nursing students at Al-Quds University.
Hypothesis 2 (H2)
There is a significant difference in the levels of anxiety, depression, and stress based on demographic factors (e.g., sex, age group, income, marital status, year of study, cumulative GPA) among undergraduate nursing students at Al-Quds University during the war.
Hypothesis 3 (H3)
Resilience significantly moderates the relationship between war-related stress and the psychological outcomes (anxiety, depression, and stress) among undergraduate nursing students at Al-Quds University, such that higher resilience reduces the negative psychological impacts.
Methods
Design
A cross-sectional descriptive design was employed to describe the Level of Anxiety, Depression, Stress, and Resilience During the War that Started on October 7, 2023, in Palestine Among Undergraduate Nursing Students at Al-Quds University using self-administered questionnaire. Data were collected between March 20, 2024, and April 20, 2024.
Setting
Data was collected from nursing students at Nursing department of the Faculty of Health professions, Al-Quds University in Jerusalem in Palestine. This department award Bachelors’ degree in Nursing. Al-Quds University (AQU) is a collegiate research university that currently offers more than 120 undergraduate and postgraduate programs, taught through its fifteen degree-granting faculties that cover the main scientific disciplines such as medicine, life, and natural sciences, business and management, arts and humanities, law and jurisprudence, engineering, and social sciences. In term of nursing department, there are 10 faculty members with assisstant professor degree who teach students. It consists of two floors containing 10 teaching rooms, in addition to three laboratories for clinical training and one simulation center. Finally, an international training center affiliated with the American Heart Association (AHA) grants Basic Life Support (BLS) and Advanced Cardiovascular Life Support (ACLS) awards these certificates to students before graduation.
Population
The target populations of this study are nursing students. the access population are nursing students in Al Quds university. Therefore, according to the admission and registration office at Al-Quds University, the number of nursing students is 1200 enrolled in the first, second, third, and fourth academic years.
Sample and sampling
The sample size for this study is 325 nursing students, 325 questionnaires were distributed among nursing students at Al-Quds University, and the responses were 325, questionnaires valid for statistical analysis, which means that the rate of response was 100%. We used a convenience sampling technique in collecting the data.
Data were collected via an online survey through students’ emails, What’s app groups, and facebook messenger groups. The time frame for data collection was between March 20, 2024, and April 20, 2024 through an online survey, nursing students were asked to rate each item based on perception toward stress, anxiety, depression, and resilience. Nursing students completed the English version of the questionnaire without needing translation. All nursing education programs in Palestine are in English.
Inclusion criteria
The inclusion criteria of the participants were as follows:
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1st, 2nd, 3rd, and 4th years regular and upgrading nursing students who were registered at Al-Quds University.
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Nursing students who agreed to participate in this study during the period of data collection.
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Exclusion criteria
The exclusion criteria were as follows:
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Students who are enrolled in nursing programs at other universities, except AQU.
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Nursing Students who were not registered this semester at the University.
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Non-nursing students from AQU.
Data Collection
After obtaining the ethical approvals from the research ethics committee at Al-Quds University, the data collected from the students in the online survey were anonymous, and no identifiers or personal information were collected or stored. Informed consent and a statement explaining the purpose of the study and the participants’ rights regarding voluntary and confidential participation were included in the email invitation to students. The participants were assured that data would be used only for research purposes and that their privacy and confidentiality would be protected. A consent form from the nursing students was obtained after fully discussing all research issues. The confidentiality and anonymity of the received data have been completely secured.
Instruments
The instrument for data collection was a questionnaire which comprises four sections.
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Demographic questionnaire
The researchers developed the demographic questionnaire including demographic variables of the nursing students like age, sex, Academic year, income level, and marital status.
Depression anxiety stress scale (DASS-21)
To assess the level of anxiety about the war in Gaza, which consists of 7 items, adopted from DASS 21. And to assess the level of depression about the war in Gaza, which consists of 7 items, adopted from DASS 21 which was developed by Lovibond and Lovibond [16] in 1995.
Anxiety and depression were measured by the English version of the DASS-21. This instrument has three domains: depression, anxiety, and stress subscales. It is composed of 21 items, seven items for anxiety, seven items for stress, and seven items for depression. In this study, the levels of anxiety and depression were examined. We used a stress scale related to war. The participants rated their levels on a 0–3 scoring system, with a range of 0–21 for each subscale. According to the scoring system of the DASS-21 scale, each total score is multiplied by 2 to get the final score for each anxiety and depression score. Higher scores indicate higher symptom frequency and severity. Regarding the scoring system of both anxiety and depression levels, there are five severity levels; normal, mild, moderate, severe, and extremely severe.
The dimensional rather than categorical conceptualization of psychological pathology is the foundation of the DASS-21. The premise upon which the DASS-21 was developed (and which was supported by the research results) is that the variations in depression, anxiety, and stress experienced by normal people and clinical populations are, in essence, differences of degree. DASS21 scale is valid and reliable and has been widely used in many published works [17‐21].
The war-related stress scale
To assess the level of stress about the war in Gaza, which consists of 21 items, adopted from the War-related stress scale [22].
The stress scale consists of 21 items that can be further divided into three factors: (1) society-related stressors (8 items); (2) person-related stressors (7 items) and (3) security-related stressors (6 items). The first factor, society-related stressors, consists of items related to the functioning of the country (management of the economic and migration crisis, sufficiency of energy sources, etc.). The second factor, person-related stressors, covers items directly related to a person’s life (e.g., worries about the future, personal functioning, social relationships, and quality of life). The third factor, security-related stressors, contains items regarding safety issues (e.g., personal safety, potential escalation of the conflict, or nuclear threat). Vargová, Jozefiaková [22] who developed the original instrument recommended and invited researchers to modify the scale, tailoring it to specific cultural, geographical, and temporal contexts, therefore, we made a small change to item number five in society-related stressors (original item “Concern about the war moving to the EU or the world” changed to “Concern about the war moving to the West Bank or Jerusalem”) as the war started on Gaza strip to tailoring it to specific cultural, geographical, and temporal contexts of the war here in Palestine 2024. Each participant responded in a format with seven response options (ranging from 1 = No concerns/difficulties to; 7 = Great concerns/difficulties). The stress instrument is valid and reliable, and the content validity of each item is assessed. The list, along with other validated scales, was administered to a representative sample of the Slovak population (effective N = 1851). Exploratory factor analysis, confirmatory factor analysis, convergent validity analysis and network analysis were carried out to determine the optimal scale (long and short form) focused on war-related stressors. In addition, the three-factor model had sufficient psychometric properties (TLI = 0.95; RMSEA = 0.06, 95%CI [0.06, 0.07]; SRMR = 0.02) and was well-interpretable in terms of clarity of the factors. Items with high cross-loadings (> 0.40) were categorized into a factor that was more similar content-wise [22]. Furthermore, the reliability statistics for this study were high with Cronbach’s Alpha of 0.95 for the 21 stress items.
The brief resilience scale (BRS)
was used to assess the nursing student’s resilience about the war in Gaza, which consists of six items on a 5-item Likert scale from Strongly disagree (1), disagree (2), neutral (3), Agree (4), Strongly agree (5)). A higher score means a high level of resilience with this scoring system (giving a range from 6 to 30). adopted from the Brief Resilience Scale.
The Brief Resilience Scale (BRS), developed by Smith, Dalen [23], was the only measure included in the aforementioned systematic review whose aim was assessing individuals’ ability to recover from stressful circumstances. The BRS has also been translated to Dutch [24], its scores showing adequate reliability (α = 0.83; Intraclass Correlation Coefficient [ICC] = 0.94), and to Malaysian [25] with adequate psychometric properties as well (α = 0.93). The BRS scores showed adequate reliability (internal consistency α = 0.83, and test-retest ICC = 0.69). Confirmatory factor analyses showed that the Spanish version of the BRS is mono-factorial (χ2 /df = 2.36; SRMR = 0.036; GFI = 0.980; CFI = 0.984; IFI = 0.984; RMSEA = 0.067). They also showed adequate evidence of the scores’ convergent, concurrent, and predictive validity. The Spanish version of the BRS is a reliable and valid means to assess resilience as the ability to bounce back [26]. In term of Confirmatory factor analyses, all items displayed statistically significant (p < .05) factor loadings above 0.40 on the general factor and were all in the expected direction. In addition, in terms of Exploratory factor analysis, both the eigenvalue criterion and the scree plot indicated a one-factor solution that accounted for 61.20% of the total variance, with item loadings ranging from 0.59 to 0.88 [27].
The reliability statistics for this study tools were as follows; the Cronbach Alpha of the anxiety 7 items was 0.84, for depression was 0.86, for stress 21 items 0.95, and for resilience was 0.86.
Data analysis
After collecting the data, it was analyzed using SPSS software version 27.0. Testing the assumptions regarding the moderation effect including normality, linearity, Homoscedasticity, and Independence all assumptions met, as long the skewness less than one. and the differences based on the sociodemographic characteristics were assessed using an independent t-test and One-way analysis of variance (ANOVA). In addition, the Pearson correlation was used to detect any association between resilience and anxiety, depression, and stress. Two steps hierarchical regression analysis used to test the moderation effect of resilience at alpha 0.05.
Results
Demographic characteristics of the participants
A total of 325 nursing students participated in this study. The analysis (see Table 1) showed that females accounted for 62.5% (n = 203). Most participants were between 21 and 23 years 46.8% (n = 152). A significant proportion were single (82.2%). Regarding the academic year, fourth-year students comprised the majority of them 46.2% (n = 150). Most students were regular 88.9% (n = 289), and over half of participants cumulative averages (53.2% (n = 173) ranged from 80 to 89%. Around one-third of participants, income levels spanned from 4851 or more 30.2% (n = 98). See Table 1.
Table 1
Description of demographic characteristics of Nursing students (N = 325)
Demographic variable | N | % | |
|---|---|---|---|
Sex | Male | 122 | 37.5% |
Female | 203 | 62.5% | |
Age | 18–20 years | 120 | 36.9% |
21–23 years | 152 | 46.8% | |
24–26 years | 21 | 6.5% | |
27 and above years | 32 | 9.8% | |
Marital status | Single | 267 | 82.2% |
Married | 58 | 17.8% | |
Academic year | First-year | 65 | 20.0% |
Second year | 57 | 17.5% | |
Third year | 53 | 16.3% | |
Fourth year | 150 | 46.2% | |
Type of Study | Regular | 289 | 88.9% |
Upgrading | 36 | 11.1% | |
Cumulative Average | 60-69% | 18 | 5.5% |
70-79% | 103 | 31.7% | |
80-89% | 173 | 53.2% | |
90% & above | 31 | 9.5% | |
Income Level | 1850–2850 | 88 | 27.1% |
2851–3850 | 87 | 26.8% | |
3851–4850 | 52 | 16.0% | |
4851 and more | 98 | 30.2% | |
Variables of the study
The analysis showed that the majority of the participants were experiencing extremely severe anxiety levels (43.7%, n = 142), while 25.5% (n = 83) were experiencing extremely severe depression and 14.5% (n = 47) were experiencing high stress levels compared to 60% (n = 195) of the students were at their normal resilience level. See Table 2.
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Table 2
Descriptive statistics of nursing students’ psychological status (N = 325)
Psychological Trait | N | % |
|---|---|---|
Anxiety | ||
Normal | 32 | 9.8 |
Mild | 11 | 3.4 |
Moderate | 86 | 26.5 |
Severe | 54 | 16.6 |
Extremely Severe | 142 | 43.7 |
Depression | ||
Normal | 50 | 15.4 |
Mild | 25 | 7.7 |
Moderate | 101 | 31.1 |
Severe | 66 | 20.3 |
Extremely Severe | 83 | 25.5 |
Stress | ||
Low Stress | 157 | 48.3 |
Moderate Stress | 121 | 37.2 |
High Stress | 47 | 14.5 |
Resilience | ||
Low resilience | 129 | 39.7 |
Normal resilience | 195 | 60.0 |
High resilience | 1 | 0.3 |
Differences in psychological status concerning socio-demographics
In terms of anxiety, using one-way ANOVA, the results revealed that there was a statistically significant difference in anxiety concerning the age group (F 3, 321 = 2.83, p = .038). Post-hoc comparisons using the Bonferroni test revealed that the mean score for the age group of those between 18 and 20 years (M = 1.17, SD = 0.66) was significantly lower than those at the age of 21–23 years (M = 1.35, SD = 0.66), and 24–26 years (M = 1.53, SD = 0.63). In addition, there was statistically significant difference in anxiety in relation to academic year (f3, 321 = 3.557, p = .015). Post-hoc comparisons using the Bonferroni test revealed that the mean score for the second-year students (M = 1.17, SD = 0.59) was significantly lower than the fourth-year students (M = 1.43, SD = 0.66). On the other hand, other sociodemographic factors were not significantly related or different in terms of anxiety.
In terms of depression, using one-way ANOVA, the results revealed that there were statistically significant differences in depression based on academic year (f3, 321 = 2.939, p = .033). Post-hoc comparisons using the Bonferroni test revealed that the mean score for the third-year students (M = 1.28, SD = 0.80) was significantly lower than fourth-year students (M = 1.55, SD = 0.66). On the other hand, other sociodemographic factors were not significantly related or different in terms of depression.
In terms of stress, using one-way ANOVA, the results revealed that there were statistically significant differences in stress based on cumulative average (f3, 321 = 5.642, p < .001). Post-hoc comparisons using the Bonferroni test revealed that the stress mean score for the cumulative average of 60-69% (M = 2.38, SD = 1.27) was significantly lower than the cumulative average of 70-79% (M = 3.14, SD = 1.26), and cumulative average of 80-89% (M = 3.38, SD = 1.34), and cumulative average of 90% and above (M = 3.90, SD = 1.57). Furthermore, post-hoc comparisons using the Bonferroni test revealed that the stress mean score for the cumulative average of 70–79% (M = 3.14, SD = 1.26), was significantly lower than the cumulative average of 90% and above (M = 3.90, SD = 1.57).
In addition, by using one-way ANOVA, the results revealed that there were statistically significant differences in the stress based on monthly income (f3, 321 = 4.408, p = .005). Post-hoc comparisons using the Bonferroni test revealed that the stress mean score for the monthly income of 2851–3850 (M = 3.04, SD = 1.22) was significantly lower than the monthly income of 4851and above (M = 3.70, SD = 1.40. Moreover, post-hoc comparisons using the Bonferroni test revealed that the stress mean score for the monthly income of 1850–2850 (M = 3.22, SD = 1.40) was significantly lower than the monthly income of 4851 and above (M = 3.70, SD = 1.40. In addition, post-hoc comparisons using the Bonferroni test revealed that the stress mean scores for the monthly income of 3851–4850 (M = 3.09, SD = 1.33) were significantly lower than the monthly income of 4851 and above (M = 3.70, SD = 1.40). On the other hand, other sociodemographic factors were not significantly related or different in term of stress.
Finally, in terms of resilience, by using an independent sample t-test, the results revealed that there were statistically significant differences in the resilience based on sex (t323 = 2.994, p = .003). Knowing that males have higher resilience mean scores (M = 3.06, SD = 0.35) than females (M = 2.93, SD = 0.41) indicates higher resilience in males than females. On the other hand, other sociodemographic factors were not significantly related or different in term of resilience. Table 3 demonstrates the differences in psychological status based on socio-demographics.
Table 3
Differences of psychological status in relation to nursing students’ socio-demographic factors (N = 325)
Variable | Anxiety | Depression | Stress | Resilience | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
M ± SD | F/t | p | M ± SD | F/t | P | M ± SD | F/t | P | M ± SD | F/t | p | ||
Sex | Male | 1.31 ± 0.64 | 1.36 ± 0.65 | 3.15 ± 1.44 | 3.06 ± 0.348 | ||||||||
Female | 1.29 ± 0.68 | 0.138 | 0.890 | 1.47 ± 0.74 | -1.340 | 0.181 | 3.39 ± 1.31 | -1.509 | 0.132 | 2.93 ± 0.41 | 2.994 | 0.003* | |
Age | 18–20 years | 1.17 ± 0.66 | 1.32 ± 0.74 | 3.16 ± 1.29 | 2.91 ± 0.42 | ||||||||
21–23 years | 1.35 ± 0.66 | 1.46 ± 0.71 | 3.36 ± 1.40 | 3.01 ± 0.38 | |||||||||
24–26 years | 1.53 ± 0.63 | 1.53 ± 0.56 | 3.65 ± 1.44 | 3.04 ± 0.33 | |||||||||
≥ 27 years | 1.41 ± 0.62 | 2.833 | 0.038* | 1.62 ± 0.54 | 2.032 | 0.109 | 3.27 ± 1.36 | 0.926 | 0.429 | 3.00 ± 0.35 | 1.877 | 0.133 | |
Academic year | First year | 1.22 ± 0.75 | 1.39 ± 0.72 | 3.09 ± 1.28 | 2.89 ± 0.38 | ||||||||
Second year | 1.17 ± 0.58 | 1.30 ± 0.69 | 3.13 ± 1.40 | 2.93 ± 0.40 | |||||||||
Third year | 1.18 ± 0.57 | 1.28 ± 0.80 | 3.33 ± 1.47 | 2.98 ± 0.42 | |||||||||
Fourth year | 1.43 ± 0.65 | 3.557 | .015* | 1.54 ± 0.65 | 2.939 | 0.033* | 3.44 ± 1.34 | 1.346 | 0.259 | 3.03 ± 0.38 | 2.144 | 0.095 | |
Cumulative Average | 60-69% | 1.29 ± 0.54 | 1.30 ± 0.61 | 2.38 ± 1.27 | 3.00 ± 0.33 | ||||||||
70-79% | 1.28 ± 0.57 | 1.53 ± 0.66 | 3.14 ± 1.25 | 2.99 ± 0.37 | |||||||||
80-89% | 1.32 ± 0.73 | 1.39 ± 0.73 | 3.38 ± 1.34 | 2.97 ± 0.40 | |||||||||
≥ 90% | 1.21 ± 0.61 | 0.299 | 0.826 | 1.37 ± 0.76 | 1.137 | 0.334 | 3.90 ± 1.56 | 5.642 | 0.001* | 2.91 ± 0.46 | 0.331 | 0.803 | |
Income Level | 1850–2850 | 1.23 ± 0.57 | 1.39 ± 0.63 | 3.22 ± 1.40 | 3.03 ± 0.39 | ||||||||
2851–3850 | 1.31 ± 0.63 | 1.40 ± 0.72 | 3.04 ± 1.22 | 2.94 ± 0.39 | |||||||||
3851–4850 | 1.29 ± 0.73 | 1.31 ± 0.62 | 3.09 ± 1.32 | 3.03 ± 0.40 | |||||||||
≥ 4851 | 1.36 ± 0.724 | 0.635 | 0.593 | 1.54 ± 0.78 | 1.466 | 0.224 | 3.70 ± 1.39 | 4.408 | 0.005* | 2.93 ± 0.38 | 1.556 | 0.200 | |
Testing the moderation effect of resilience
To examine the association among the variables of the study, Pearson r was used. The analysis showed that there was a statistically significant negative correlation between resilience and anxiety (r = − .211**, p < .001), and a significant negative correlation with depression (r = − .262**, p < .001). while, no significant correlation was found between resilience and stress (r = − .099, p > .05). therefore, the moderation effect of resilience developed for depression and anxiety.
In terms of depression, to examine the moderation effect of resilience on the relationship between sociodemographics (age, sex, cumulative average, and income) and depression, a two-step multiple hierarchical regression analysis was performed. In Block 1, demographic characteristics were entered, and in Block 2, resilience was entered. The decision for order of entry was based on the assumption that adding resilience would show a significant improvement in the depression. We ordered the entry of the variables regarding their logically determined priority depending on the literature [28‐31] and what the bivariate correlation showed between the variables of the model, supported by the researchers’ scientific judgment.
The analysis (see Table 4) showed that model 1 which included demographic factors explained 3.7% (R2 = 0.0.037) of the variance in depression (Table 4). In this model, age and sex were significant predictors for depression, and the model was significant (F4, 320 = 3.064, p = .017). The analysis showed age and sex were positively associated with depression (β = 0.120, p = .002), (β = 0.171, p = .043), respectively. After the entry of resilience in model 2, the total variance explained by the model was increased to 10.5% (R2 = 0.105) and the model was also significant (F5,319 = 7.464, p < .001). The variables in step 2 explained an additional 6.8% of variance in depression. The R2 value of 0.105 indicates that 10.5% of the variation in the relationship between sociodemographics and depression is related to the moderation effect of resilience with an increase of 6.8%. In model 2, resilience has a negative association with depression (β = − 0.474, p < .001), while age remained significantly and positively predicting depression (β = 0.133, p = .002). The analysis revealed that resilience negatively moderated the relationship between sociodemographics and depression.
Table 4
Two steps multiple hierarchal examining resilience moderating effect on the relationship between sociodemographic and personal characteristics and depression (N = 325)
Variables | Model 1 | Model 2 | |||
|---|---|---|---|---|---|
β | P- value | Β | P- value | ||
Age | 0.120 | 0.008 | 0.133 | 0.002 | |
Sex | 0.171 | 0.043 | 0.116 | 0.156 | |
GPA | − 0.070 | 0.210 | − 0.073 | 0.178 | |
Income | 0.036 | 0.302 | 0.026 | 0.438 | |
Resilience | − 0.474 | < 0.001 | |||
Model | R2 | Adj R2 | R2change | F | p |
1 | 0.037 | 0.025 | 3.064 | 0.017 | |
2 | 0.105 | 0.091 | 0.068 | 7.464 | < 0.001 |
In terms of anxiety, to examine the moderation effect of resilience on the relationship between sociodemographics (age, sex, cumulative average, and income) and anxiety, a two-step multiple hierarchical regression analysis was performed. In Block 1, demographic characteristics were entered, and in Block 2, resilience was entered. The decision for order of entry was based on the assumption that adding resilience would show a significant improvement in anxiety. We ordered the entry of the variables regarding their logically determined priority depending on the literature [28‐31] and what the bivariate correlation showed between the variables of the model, supported by the researchers’ scientific judgment.
The analysis (see Table 5) showed that in model 1 which included demographic factors explained 2.3% (R2 = 0.0.023) of the variance in depression (Table 5). In this model, although age was a significant predictor for depression, the whole model was not significant (F4, 320 = 1.91, p = .109). After the entry of resilience in model 2, the total variance explained by the model was 7.2% (R2 = 0.072) and was significant (F5,319 = 4.93, p < .001). The variables in step 2 explained an additional 4.9% of variance in anxiety.
Table 5
Two steps multiple hierarchal examining resilience moderating effect on the relationship between sociodemographic and personal characteristics and anxiety (N = 325)
Variables | Model 1 | Model 2 | |||
|---|---|---|---|---|---|
Β | P- value | β | P- value | ||
Age | 0.101 | 0.017 | 0.112 | 0.007 | |
Sex | 0.033 | 0.674 | − 0.010 | 0.902 | |
GPA | − 0.018 | 0.730 | − 0.020 | 0.693 | |
Income | 0.032 | 0.334 | 0.024 | 0.456 | |
Resilience | − 0.375 | < 0.001 | |||
Model | R2 | Adj R2 | R2 change | F | P |
1 | 0.023 | 0.011 | 0.023 | 1.909 | 0.109 |
2 | 0.072 | 0.057 | 0.048 | 4.930 | < 0.001 |
In model 1, age was a significant predictor of anxiety (p < .05), but the whole model was not significant. The analysis showed age was positively associated with anxiety (β = 0.112, p = .007). In model 2, resilience has a negative association with anxiety (β = − 0.375, p < .001). The analysis revealed that resilience negatively moderated the relationship between sociodemographics and anxiety.
Discussion
The effect of war on nonhumans is well-reported and documented. However, during war times, certain population are under very particular effect, and the consequences of war may impact their wellbeing and functionability. In the West Bank, part of the Palestinian territory, nursing students are assumed to take responsibility and function psychologically and socially normally during wartime in Gaza that started on October 7, 2024. This study is testing whether resilience would enable nursing students to manage their psychological disturbances. We found that a significant portion of nursing students are suffering from mild to moderate levels of anxiety, while almost a quarter of them are suffering from moderate to severe levels of depression. an alarming note was related to war-stress. It was found that almost 40% of students are suffering from moderate to severe war stress levels. Such findings could be related directly to their experience of the war scene that comes from Gaza and could also reflect an accumulated effect of hardiness and occupational-related factors that include social, psychological, economic; and traveling issues. Nursing students feel, in general, that they have responsibilities towards their brothers and sisters in Gaza and they are not willing to assist. Their frustration and their incapability to assist might explain their depression and high levels of stress. Such secondary traumatic effects of war may also be due to the closeness to Gaza and Israeli occupation practices in the West Bank. In general, the results of the study are in line with previous reports that either being a primary or secondary victim, war would create great levels of stress, anxiety, and depression. The study by Chudzicka-Czupała, Grabowski [32] also found significant levels of depression, anxiety, and post-traumatic stress among populations in Ukraine, Poland, and Taiwan during the 2022 Russo-Ukrainian war, highlighting the widespread psychological impact of armed conflicts. However, in this study, nursing students had lower score than other international studies [33]. This could be related to a long-living experience under the strict rules and oppression of the Israeli occupation. On the other hand, almost 40% of the nursing students showed a low level of resilience. This could explain why we need to test the moderation effect of resilience on the levels of depression, anxiety, and stress. previous literature did confirm that resilience would have positive effect of psychological health and wellbeing of individuals. This study is endorsing a pioneer situation in which the resilience effect is tested due to effect of occupation and during the war time.
Resilience is assumed to enable individuals to manage their psychological distress and presume their function; given the individualized experiences and intensity of the event [34]. In this study, we found that resilience did have a positive effect on depression and anxiety, but not stress. The main sociodemographic factors that seems to play a significant role to enhance the effect of resilience in age. Older students were more resilient and did improve the positive effect of resilience on depression and anxiety. In other words, older students with higher levels of resilience did have lower depression and anxiety scores than younger ones. While, sex, which might be assumed to be a significant factor, had to significant effect. The results of this study go in two directions. The first one is the effect of age and resilience on depression and anxiety, and the other is the negative effect of sex on resilience. This may conclude that both male and female nursing students are suffering equally the effect of war regardless of the cultural socioeconomic or biological makeup factors of males and females. this could be related to the fact that they are all nursing students, and being in the health field exposes them all to the same level of trauma. However, their age was a significant one assuming that older nursing students have more experience and are expected to have more skills and experience to manage stressful life event. The results of this study are supporting previous report of the positive effect of resilience [35, 36]. Nevertheless, not significantly affecting stress levels would enable us to conclude that resilience is more useful when it comes to more personalized psychological disturbances than a specific one such as war stress. this is one pioneer finding of this study and adds to the body of knowledge.
However, limitations exist within this study. The novelty of the research field and data accessibility constraints may limit the depth of analysis and comparison with existing literature. Moreover, the temporal restrictions of the study design could hinder a comprehensive understanding of evolving mental health dynamics during prolonged conflict situations.
Conclusion
This study offers valuable insights into the mental health status of undergraduate nursing students in Palestine during the war that started on October 7, 2023. The results indicated that resilience is one of the pivotal moderators that may buffer anxiety and depression. The findings underscore the need for targeted interventions to address the diverse mental health needs of this population, considering the complex interplay of individual, demographic, and contextual factors. Future research should continue to explore these dynamics and evaluate the effectiveness of interventions promoting mental well-being during conflict.
Recommendations
The findings of this study underscore the need for comprehensive mental health support and interventions for individuals affected by war and conflict situations, particularly among vulnerable populations such as students and those from low-income backgrounds.
Providing accessible and culturally sensitive mental health services, promoting resilience-building strategies, and addressing the socioeconomic determinants of mental health should be prioritized to mitigate the long-term psychological consequences of war and conflict. For instance, as the results revlead that males have higher resilience than females, this suggest a more focused intervdentions should be targeted to female sex groups more than males. Furthermore, efforts should be made to raise awareness about mental health issues, integrate mental health services with other areas of healthcare, and enhance the capacity and resources of community mental health teams. Ultimatly, addressing the root causes of conflict and promoting peace and stability are crucial for safeguarding the mental well-being of affected populations.
We recommend that stakeholders and policymakers allocate sufficient budgets, implement effective training methods, and provide adequate time to promote the mental well-being of nursing students and other university students. The resources required will vary depending on the specific interventions, available support, and institutional settings, making flexible and well-structured planning essential for success.
Implcation for nursing practice
This study highlights the need for targeted mental health support systems within universities, especially for nursing students, who are vulnerable to stress, anxiety, and depression during conflict. Counseling services, peer support groups, and psychological first aid training could be made more accessible, offering students resources to manage mental health issues before they escalate. Ultimatly, since resilience was found to moderate the levels of anxiety and depression among nursing students, implementing resilience-building interventions, such as stress management workshops, mindfulness practices, and emotional regulation training, could be incorporated into nursing curricula. These implications suggest that fostering resilience and providing mental health support can enhance the well-being of nursing students, eventually contributing to a more prepared and mentally resilient future nursing workforce.
Acknowledgements
We would like to thank all nursing students who participated in this study and for their welcoming and support during data collection. Additionally, we would like to acknowledge Philadelphia University In Jordan for encouraging this study.
Declarations
Ethics approval and consent to participate
The Scientific and Ethical Research Committee at the Al-Quds University was addressed (RESC/2024-38). All the participants were assured that participation in the study was voluntary. Data collection was initiated after obtaining ethical approval for the study. Procedures were strictly aligned with applicable standards and laws, including the Declaration of Helsinki. Informed consent to participate was obtained from all of the participants in the study. A self-reported questionnaire was used to collect data.
Consent for publication
Not applicable.
Clinical trial number
Not applicable.
Competing interests
The authors declare no competing interests.
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