Skip to main content

Quality of life among residents of Gaza, Palestine: the predictive role of mental distress, fear of COVID-19, and social support

Abstract

Background

Living under siege and deteriorated health, social, educational, and economic conditions and isolation with scarce opportunities to fulfil basic needs and aspirations affect the civil population's mental health and perceived quality of life. In this cross-sectional investigation, we explored the consequences of mental distress, fear of COVID-19, and social support for QoL in the Gaza strip.

Methods

Nine hundred seventy nine (32.9% males; 67.1% females; mean age was 35.2 years; s.d. = 11.4) adults were recruited in the Gaza strip. We used the Fear for COVID-19 scale (FCS-19), The WHOQOL-BREF Scale, Berlin Social Support Scale (BSSS), Depression Anxiety and Stress Scale (DASS). Pearson correlation coefficient was computed to assess relationships between quality of life, fear of COVID19, mental distress, and social support; a hierarchical regression analysis was used to assess the association between QoL as the dependent variable and demographic variables and fear of COVID19, mental health, and social support as the independent variables.

Results

QoL was positively associated with perceived emotion, instrumental, and support seeking. Depression, anxiety, stress, and fear of COVID19 were negatively associated with quality of life. Gender was significantly associated with lower QoL. The study highlighted that the level of fear of COVID-19 was negatively influencing individuals' quality of life (QoL). This fear was negatively associated to psychological distress, gender, place of residence, and family type. Lower-educated and poorer participants had lower QoL scores. Conversely, female gender was notably linked to a lower QOL. The hierarchical regression confirmed that COVID-19 was an added burden for the Palestinian population. The fear of COVID-19 term added a 6.2% variance in QoL. In the final analysis, all predictors were statistically significant, with the fear of COVID-19 term recording a higher contribution of 22.5%, followed by depression term with 21.5%, perceived emotional 18.5%, income at 15.4%, and perceived instruments at 14.8% towards QoL.

Conclusions

Practitioners and policymakers must consider the severe violation of human rights when developing psychosocial programs to intervene in the COVID-19 crisis.

Peer Review reports

Introduction

COVID-19 has swept through every country globally, particularly in crisis zones with limited resources and capacities [1,2,3,4]. The Gaza Strip, one of the world's most densely inhabited areas, is located on the Mediterranean Sea's south-eastern side, with 2 million people living in a 365-square-kilometre territory [5]. Being overcrowded with few resources coupled with a 16-year blockade by Israel and going population has exacerbated the deterioration of health, social, educational, and economic conditions, as well as the identity of Gazans [6,7,8]. As a result, people in Gaza suffer from a high unemployment rate [9, 10], poverty, poor infrastructure [10, 11], and a fragile health system [12]. They also experience suffering from the Israeli-imposed restrictions on access to agricultural land and fishing waters [13].

Armed conflicts have a negative influence on people's social determinants of mental health and well-being [14, 15], and affects their ability to meet their basic needs such as health, economic, social, and educational demands [16,17,18]. According to several studies, the quality of life in the occupied Palestinian territory (oPt) was found to be among the lowest of any population in the world, including the physical and psychological [19,20,21], and environmental domain [19].

The healthcare system in Gaza Strip is already overburdened and has deteriorated significantly as a result of repeated rounds of violence with Israel in 2008, 2012, and 2014, 2023 the Great March of Return demonstrations, and the overall situation of unrest [22, 23]. On Friday, May 10, 2021, an Israeli escalation occurred while the oPt was still coping with a surge of coronavirus cases in Gaza, with the number of active cases exceeding 60% in April 2021. During the fighting, follow-up on COVID-19 preventative measures, vaccination and testing have been severely hampered. Moreover, the central testing facility and the single vaccination centre in northern Gaza were damaged [24]. This situation makes Gaza weak and fragile in responding effectively to the global crisis of the COVID-19 pandemic [4].

Since the Coronavirus outbreak, most governments worldwide have taken quick actions to halt the spread of the virus [25,26,27]. In Gaza, the Palestinian Authority implemented several restrictions, including travel restrictions, and social isolation, as many stayed at home and many employees worked from home [22, 28, 29].

Several studies have addressed the impact of the COVID-19 pandemic, including its effect on the mental health of several groups of people in fragile and conflict-affected settings [30,31,32,33,34,35]. Following COVID-19 infection, there is evidence of increased levels of indirect effects of COVID-19 on general mental health, such as posttraumatic stress in hospitalized patients or health providers, depression, anxiety [36], acute panic, obsessive behaviours, paranoia, fear, and anger [37, 38] as well as negative symptoms impacting overall mental health. The COVID-19 pandemic has had a global psychosocial impact, creating mass fear of “corona phobia”, economic burdens, and financial losses [32, 39]. As a result, during the pandemic, families in Gaza have encountered several problems that have harmed their well-being, including domestic violence, conflict, and divorce. Studies have shown that the most affected groups were young, female, married, and not well-educated [39, 40].

A study by Vujčić and colleagues (2021) assessed the mental health impact of COVID-19 on the adult population in Serbia during the state of emergency and lockdown. Out of 1057 participants, high rates of depression (28.9%), anxiety (36.9%), and stress (38.1%) were reported. Factors such as uneasiness from COVID-19 news, helplessness, perceived likelihood of death, and COVID-19 symptoms were associated with higher mental health symptoms. Smoking, student status, age, and socioeconomic status also played a role [41].

Another study in Serbia examined mental health among healthcare workers during the COVID-19 pandemic. Results showed that resilience and capacity for mentalizing were linked to depression, anxiety, and stress levels. Higher resilience and hypermentalizing were associated with lower mental health symptoms, while hypomentalizing was linked to higher symptoms. Socioeconomic status also influenced mental health [42, 43].

Social support is essential to an individual's well-being and plays a vital role in crisis management [44,45,46,47,48], either by supporting avoidance strategies or by encouraging a treatment strategy [49].

Established studies demonstrate that social support is a moderating variable in the association between the reaction to stress and psychological distress [50,51,52,53,54,55,56]. “Social support is” social interactions or relationships that provide individuals with actual assistance or include individuals in a social system who are believed to provide care, love, or a sense of connection to a social group of value.” [57,58,59]. Individuals seeking social support increase their social resources by offering empathy or decreasing their feelings of loneliness [60,61,62].

In contrast, lack of social support and feelings of social isolation are the most important predictors of psychological illnesses such as posttraumatic stress after exposure to crises or traumatic events [63,64,65,66]. Reavell and Fazil [42] found that high mental health problems were linked to increased susceptibility to injury, while social support was crucial in reducing symptoms of traumatization and depression. Furthermore, in a study on Palestinian adolescents, Al-Sheikh and Thabet [63] found that overall traumatic events were negatively correlated with social support. Similarly, Labrague and Santos [47] and Pietrzak et al. [60] showed that higher social support is linked with lower anxiety levels related to the COVID-19 pandemic and can buffer against the onset and maintenance of posttraumatic stress disorder (PTSD) symptoms and other mental health problems over time.

According to the previous literature review, we sought to explore the consequences of mental distress and COVID-19-related burdens in a society characterized by ongoing violence and political instability and the role of social support on the deterioration of quality of life (QoL). Our leading hypotheses were that QoL was associated with higher social support (H1), while QoL would deteriorate as a result of mental distress (depression, anxiety, and stress) (H2). Furthermore, fear of COVID-19 would be negatively associated with QoL (H3), mainly in the population with lower socioeconomic status (H4). Finally, we explored gender differences, hypothesizing that women's QoL may have been more affected during the pandemic (H5). Ultimately, our study aimed to explore the predictors of the quality of life in the Gaza strip during the COVID-19 pandemic.

Methods

This study adhered to the guidelines of the Declaration of Helsinki.

Study design and population

Approval was granted by the Ethics Committee of Stellenbosch University (Date: 7–12-2020/No: REC-2020–17479) and the Helsinki committee (Palestinian Health Research Council) (Date: 1–6-2020\ No: PHRC\HC\702\20). The Ethics Committee of Stellenbosch University and the Helsinki committee (Palestinian Health Research Council) approved the procedure for verbal informed consent. We ensured that each participant had the right to decline participation and withdraw from the study. The privacy of the participants was protected, and their names and any identifiable information were kept confidential.

Data were collected through an online questionnaire using Google forms with a consent form. The questionnaire link was sent online on social media and papers via CBOs in Access Restricted Areas (ARAs). It was conducted from January 2021 to April 2021. The general population of the Gazan adults who fulfilled the inclusion criteria and agreed to participate in the study were included using purposive convenience and snowball sampling techniques (1000 adults) (100% responses).

Gazans of both sexes aged 18 years or older who use social media, live in restricted access areas and are willing to give informed consent were included. Those not living in Gaza or under 18 were excluded from the study.

Most individual participants included in the study provided written informed consent. However, we obtained verbal consent from [28] uneducated participants who were too old to provide written consent.

Participants

The participants included 322 men (32.9%) and 657 women (67.1%). The mean age was 35.2 years (s.d. 11.4). Of the total, 19.5% were from the North Gaza governorate, 36.5%, 16.5%, 18%, and 9.5% from the Gaza governorate, the central area governorate, Khan Younis governorate, and Rafah governorate, respectively (see Table 1).

Table 1 Socio-demographic data of the study sample (N = 979)

Measures

Demographic information

The socio-demographic variables were collected, including age, sex, marital status, area of residency, education, monthly income, and occupation.

Fear for COVID-19 scale, FCS-19 [67]

This scale was developed by Ahorsu and colleagues (2020). COVID-19 and its consequences can create a sense of fear, worry, and anxiety worldwide. The Fear of COVID-19 Scale (FCV-19S) has been validated in a sample of 717 Iranian adults. The items of the FCV-19S were constructed based on an extensive review of existing scales on fears, expert evaluations, and participant interviews. A panel reviewed the items and seven items with acceptable corrected item-total correlation (0.47 to 0.56) were retained and further confirmed by significant and strong factor loadings (0.66 to 0.74). Reliability values were acceptable; internal consistency (α = 0.82) and test–retest reliability (ICC = 0.72). FCS-19 is a reliable and robust instrument for assessing fear of COVID-19 among the general population.

The WHOQOL-BREF Scale [68]

The WHOQOL-BREF is a 26-item instrument consisting of four domains: physical health (7 items), psychological health (6 items), social relationships (3 items), and environmental health (8 items). It also contains QOL and general health items. Each item is scored from 1 to 5 on a Likert-type scale. The physical health domain includes mobility, daily activities, functional capacity, energy, pain, and sleep items, while the psychological domain includes self-image, negative thoughts, positive attitudes, self-esteem, mentality, learning ability, memory concentration, religion, and mental status. The social relationships domain contains personal relationships, social support, and questions related to sexual activity. Finally, the environmental health domain covers financial resources, safety, health and social services, living physical environment, opportunities to acquire new skills and knowledge, recreation, general environment (noise, air pollution, etc.), and transportation. Cronbach's alpha displayed good reliability of 0.91.

Depression Anxiety and Stress Scale (DASS) is a 21- items scale that assesses the emotional states of depression, anxiety and stress. The depression scale assesses dysphoria, hopelessness, devaluation of life, self-deprecation, lack of interest, anhedonia and inertia, while the anxiety scale measures autonomic arousal, skeletal muscle effects, situational anxiety, and subjective experience of anxious affect. The stress scale is sensitive to levels of chronic non-specific arousal. It assesses difficulty relaxing, nervous arousal, and being easily upset/agitated, irritable / over-reactive and impatient [69]. The scale's internal consistency was calculated using Cronbach's alpha and was 0.92.

Berlin Social Support Scale (BSSS)

The BSSS is a set of six scales to measure cognitive and behavioural aspects of social support [70]. The first social support dimension includes the perceived available support as the degree to which help from others is available. Secondly, the need for support is how social support is important to respondents in stressful situations. Third, support-seeking is the frequency or range of support from others that the respondent seeks. Actual support comprises the actual amount of support received from others. Provided support is a scale filled out by those who provide support to the respondent. Finally, protective-buffering support is a new construct protecting close others from bad news. This scale is filled out by the person receiving and providing support. In our scales, only support receivers were administered with the scale. Cronbach's alpha showed excellent reliability of 0.93.

Data analysis

Statistical analysis was performed using Statistical Package for the Social Sciences (SPSS V25). Descriptive statistics were expressed by mean and Standards deviation. Frequencies and percentages are calculated and tabulated.

Hierarchical regression analysis was utilized to examine the relationship between quality of life (QoL) as the dependent variable and demographic factors (e.g., age, gender), as well as fear of COVID-19, mental health, and social support as independent variables. Significance was established at *p < 0.05 and ** p < 0.01, indicating the statistical robustness of the findings.

Results

In total, 1000 individuals filled out the questionnaire in this study. Twenty-one questionnaires had more than 20% missing data and thus were excluded from the study. The analysis was restricted to the remaining 979 respondents. The characteristics of the study population are shown in Table 1. In Table 2, we reported the descriptive statistics of all the measures used in the study.

Table 2 Descriptive statistics of the study measures

Pearson's correlation coefficient was computed to assess the relationship between quality of life and the following variables: Gender, Age, Income, educational level, place of residence, type of family, Depression, Anxiety, Stress, Fear of COVID, perceived emotional support, Perceived instrumental support, Need For Support, Support Seeking.

The correlational analysis showed that QOL was positively associated with perceived emotion, instruments, and support seeking. Depression, anxiety, stress, and fear of COVID were negatively associated with high quality of life. The results also indicated that higher income and educational level were significantly associated with higher QOL. In contrast, gender was significantly associated with lower QOL (See Table 3 for details).

Table 3 Correlation between the study variables

Hierarchical regression analysis was conducted to identify the predictors of QOL. Four different models were examined to understand which predictor explains the variance. Table 4 summarizes four models, all of which were significant.

Table 4 Hieratical Regression with QoL as a dependent variable

The first model with an Adjusted R square of 0.113 suggests that gender, Age, Income, Educational level, residence, place of residence and type of family account for 11.3% of the variance in self-rated QOL.

In the second model, we introduced depression, anxiety, and stress as dependent variables; the results indicate a noticeable improvement, where the Adjusted R-square value of 0.336 suggests that model 2 accounts for 33.6% of the variability.

In Model 3, Fear of COVID-19, the Adjusted R-value increased from 0.336 to 0.398. Such results suggest that model 3 can account for 39.8% of the variance in self-rated QOL by sample subjects. However, not all the variables in model 3 were significant.

In Table 4, we reported the specifics regarding each regression model and the associated residuals. For better illustration, it shows the coefficients of the significant variables included in the models. Nine variables in model 3 were significant, with one variable, Anxiety, which did not impact QOL.

In Model 4, Perceived emotional, perceived instruments, Need for support, Support seeking, the results indicate a significant increment, where the adjusted R-square value of 0.481 suggests that model 4 accounts for 48.1% of the variability.

When all models were examined, Fear of COVID-19 was the best predictor of QOL by explaining 22.5% of the total variance explained. Depression was the second, explaining 21.5% of the variance. Perceived emotional support was the third predictor, explaining 18.5% of the total variance. Income was the fourth predictor, explaining 15.4% of the variance. Perceived instruments was the fifth predictor by explaining 14.8% of the total variance explained.

Discussion

This study aimed to investigate the predictors of the quality of life during the COVID-19 pandemic in the Gaza strip. We examined the association between QOL, demographic data, fear of COVID-19, psychological distress, and social support. We found that the participants reported a moderate quality of life during the COVID-19 pandemic, which was positively associated with social support and income and educational level and negatively associated with psychological distress, gender, place of residence, and family type.

Social support was positively associated with quality of life, as supported by previous studies that found that a high level of social support was associated with a high level of quality of life [71,72,73,74,75,76,77]. Social support might improve people's quality of life during uncertainty, including during infectious disease outbreaks [78,79,80]. In the case of the Gaza Strip, social networks usually support individuals living in poverty and under siege [81]. Gaza is a collectivistic society, and large families can mitigate the effect of limited individual resources but even provide socio-emotional resources that can help conserve good functioning and a subjective sense of QoL despite the deterioration of living conditions [81].

Furthermore, the study findings show that psychological distress (depression, anxiety, and stress) was negatively associated with QoL. [82,83,84] (H2). Examining the relationship between psychological distress and QoL during the COVID19 outbreak among health workers, Fino and colleagues [53] found that quality of life was negatively associated with depression, anxiety, and stress with minor to medium effects. Similar findings were found in other studies that targeted the general population [76, 85,86,87], children, and adolescents [88,89,90,91,92]. Regarding the Gaza context, living under siege affects the civil population's mental health and perceived QoL, mainly in conditions of isolation with scarce opportunities to fulfil basic needs and aspirations (92a; 92b). Also, the COVID-19 isolation policies imposing social distancing and 'stay at home orders contributed to deteriorating the QoL of people and increasing stress and depressive reactions. Losing social support might have contributed to diminishing QoL and exacerbating mental health conditions among Gazans.

Furthermore, lower-educated and poorer participants had lower QoL scores which are in keeping with previous research [93,94,95] (H4). Education is a strategic dimension of QoL in Palestinian society, reaching a literacy level of up to 98% [96]. Despite the scarcity of resources, many Palestinian families believe education is pivotal in improving life circumstances by providing work opportunities and meaningfulness. On the other hand, lower education is associated with lower life satisfaction, even during the pandemic [97]. Few studies have estimated the relationship between the level of family income and QoL, especially during crisis times. In the current study, lower-income participants reported a lower level of QoL. This result was consistent with the findings of other studies [72, 98,99,100,101] which reported that family income was the most important factor affecting people's QOL (the low income has been associated with worse QoL). In Gaza, the economic deterioration has affected most Palestinian families. During the COVID-19 outbreak, the economic isolation and crisis worsened and contributed to an ulterior decline in QoL [22].

Our study also found that gender was associated negatively with QoL (H5). This result is consistent with evidence that socio-demographic factors significantly predict QoL in general people. Seemingly, women living under challenging conditions were more affected than their male counterparts.

Finally, the hierarchical regression confirmed that COVID-19 might have been an added burden for the Palestinian population (H3). The fear of COVID-19 term added a 6.2% variance in QoL. In the final analysis, all predictors were statistically significant, with the fear of COVID-19 term recording a higher contribution of 22.5%, followed by depression term with 21.5%, perceived emotional 18.5%, income at 15.4%, and perceived instruments at 14.8% towards QoL.

Our work provides a unique picture of the Gaza population QoL during the pandemic, shedding light on the burdens of disrupted living conditions among populations affected by ongoing social suffering, conflict and military violence.

Limitations of the study

The sample distribution was unbalanced because the data were collected through social media. For example, the percentage of women in the sample was twice that of men; the percentage of the elderly was small compared to young people, in addition to the sample's high social and educational status.

One constraint to be aware of is the utilization of adapted instruments. Although they underwent Arabic validation, none of them were specifically validated in a Palestinian context, except for the fear of COVID-19 scale. The instruments' trustworthiness may be questioned due to the lack of validation. Nevertheless, the Arabic adaptations of the measures can ensure a certain level of credibility, having been verified in related cultures.

Another limitation concerns the two different ways of data collection strategy that could have created a bias in the data analysis. However, we must consider that people with lower socioeconomic and educational backgrounds could have less confidence in dealing with technologies and find it more appropriate pencil and paper procedures. We are at risk of generalizing from the results, given these limitations. Due to the cross-sectional nature of our research design, we must consider our work exploratory and non-generalizable.

Conclusion

The study's findings can contribute to understanding the role of fear of COVID- 19, psychological distress, and social support in the people's quality of life during the pandemic in the Gaza strip. The study displayed the vital role of the variables (fear of COVID-19, depression, perceived emotional, income, and perceived instrumental social support) towards QOL of Gazan people during the COVID-19 pandemic. The study is among the first to examine the combined psychosocial consequences of the COVID-19 pandemic and the stresses of living in the Gaza strip on quality of life. To this extent, the results may help mental health professionals understand better the pandemic's mental health consequences when working with clients who present with psychological distress. Further research can include intervention studies to improve the quality of life under conditions of uncertainty, including in war-affected areas.

The COVID pandemic has shown an urgent need for Gaza to lift the more than one-decade military block that constrains the population in the small area of Gaza. Practitioners and policymakers must consider the severe violation of human rights when designing psychosocial interventions in the COVID-19-related mental health crisis [102]. If human rights violations are not recognized, the population's mental health will remain at risk of deterioration.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

ARAs:

Access Restricted Areas

BSSS:

Berlin Social Support Scale

CBOs:

Community-based organizations

DASS:

Depression Anxiety and Stress Scale

FCS-19:

Fear for COVID-19 scale

Opt:

Occupied Palestinian territory

PTSD:

Posttraumatic stress disorder

QoL:

Quality of Life

References

  1. ESCAP, U, UPU, U, P, U, &World Health Organization (WHO). How COVID-19 is changing the word: a statistical perspective. 2020. How COVID-19 is changing the world: A statistical perspective, Volume I - UNICEF DATA. Accessed 15 Mar 2022.

  2. Ibn-Mohammed T, Mustapha KB, Godsell J, Adamu Z, Babatunde KA, Akintade DD, … & Koh, SC. A critical analysis of the impacts of COVID-19 on the global economy and ecosystems and opportunities for circular economy strategies. Res Conserv Recycl. 2021;164:105169.‏

  3. Jackson JK. Global economic effects of COVID-19. Congressional Research Service. ‏2021.

  4. Palestine PF, Abuzerr S. The impact of environmental pollution on public health in light of the COVID-19 pandemic in fragile and conflict settings: reflections from the Gaza Strip. 2020.

  5. Palestinian Central Bureau of Statistics (PCBS). Palestine in figures. Press release, Ramallah, Palestine. 2022. http://pcbs.gov.ps/site/507/default.aspx. Accessed 15 Apr 2022.

  6. Barber BK, Spellings C, McNeely C, Page PD, Giacaman R, Arafat C … & Mallouh MA. Politics drives human functioning, dignity, and quality of life. Soc Sci Med. 2014;122:90–102.‏

  7. Hammad J, Tribe R. Social suffering and the psychological Impact of structural violence and economic oppression in an ongoing conflict setting: The Gaza Strip. J Community Psychol. 2020;48(6):1791–810.

    Article  PubMed  Google Scholar 

  8. UNICEF State of Palestine Humanitarian Situation Report 4 (Jan. – Dec. 2021). 2021. https://www.un.org/unispal/document/unicef-state-of-palestine-humanitarian-situation-report-4-jan-dec-2021/. Accessed 2 May 2022.

  9. OCHA. Humanitarian needs overview OPT Dec 2021. 2022. https://www.ochaopt.org/content/humanitarian-needs-overview-2022. Accessed 12 May 2022.

  10. United Nations Relief and Works Agency (UNRWA). Occupied Palestinian Territory Emergency Appeal. 2022. https://reliefweb.int/report/occupied-palestinian-territory/occupied-palestinian-territory-emergency-appeal-2022. Accessed 4 May 2022.

  11. United Nations Office for the Coordination of Humanitarian Affairs occupaied Palestinian territories (OCHA oPT). 53 per cent of Palestinians in Gaza live in poverty, despite humanitarian assistance. (2018). 53 per cent of Palestinians in Gaza live in poverty, despite humanitarian assistance | United Nations Office for the Coordination of Humanitarian Affairs - occupied Palestinian territory (ochaopt.org). Accessed 4 May 2022.

  12. Klingsbo D. The Right to Health: Israel's obligations in the occupied Palestine during the COVID-19 pandemic.‏ 2021.

  13. Oxfam. Reviewing six years of the Gaza reconstruction mechanism and the dire water situation in the Gaza Strip. 2021. https://www.oxfam.org/en/research/still-treading-water. Accessed 5 May 2022.

  14. Batniji R, Van Ommeren M, Saraceno B. Mental and social health in disasters: relating qualitative social science research and the Sphere standard. Soc Sci Med. 2006;62(8):1853–64.

    Article  PubMed  Google Scholar 

  15. Tol WA, Kohrt BA, Jordans MJ, Thapa SB, Pettigrew J, Upadhaya N, de Jong JT. Political violence and mental health: a multi-disciplinary review of the literature on Nepal. Soc Sci Med. 2010;70(1):35–44.

    Article  PubMed  Google Scholar 

  16. Barber BK, McNeely CA, El Sarraj E, Daher M, Giacaman R, Arafat C … & Abu Mallouh M. Mental suffering in protracted political conflict: Feeling broken or destroyed. PLoS One. 2016; 11(5):e0156216.‏

  17. Barber BK, McNeely C, Allen C, Giacaman R, Arafat C, Daher M, … & Belli RF. Whither the “children of the stone”? An entire life under occupation. J Palestine Stud. 2016;45(2):77–108.‏

  18. Bseiso RA, Thabet AAM. The relationship between siege stressors, anxiety, and depression among patients with cancer in Gaza Strip. Health Sci J. 2017;11(2):499.

    Google Scholar 

  19. Hammoudeh W, Hogan D, Giacaman R. Quality of life, human insecurity, and distress among Palestinians in the Gaza Strip before and after the Winter 2008–2009 Israeli war. Qual Life Res. 2013;22(9):2371–9.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Mataria A, Giacaman R, Stefanini A, Naidoo N, Kowal P, Chatterji S. The quality of life of Palestinians living in chronic conflict: assessment and determinants. Eur J Health Econ. 2009;10:93–101.

    Article  PubMed  Google Scholar 

  21. Ziadni M, Hammoudeh W, Rmeileh NM, Hogan D, Shannon H, Giacaman R. Sources of human insecurity in post-war situations: The case of Gaza. J Hum Secur. 2011;7(3):1–16.

    Google Scholar 

  22. Abuhabib A, Abu-Aita S, Procter C, Al-Smeri I. Unique situation of Gaza Strip dealing with COVID-19 crisis. Int J Infect Dis. 2020;100:149–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Mills D, Wispelwey B, Muhareb R, Gilbert M. Structural violence in the era of a new pandemic: the case of the Gaza Strip. Lancet (London, England). 2020.

  24. OCHA. Response to the escalation in the oPt. Situation report NO.1 (21–27 May 2021). 2021. https://www.ochaopt.org/content/response-escalation-opt-situation-report-no-1-21-27-may-2021. Accessed 25 May 2022.

  25. De Bruin Y, Lequarre AS, McCourt J, Clevestig P, Pigazzani F, Jeddi MZ, … & Goulart M. Initial impacts of global risk mitigation measures taken during the combatting of the COVID-19 pandemic. Safety Sci. 2020;128:104773.‏

  26. Khanna RC, Cicinelli MV, Gilbert SS, Honavar SG, Murthy GV. COVID-19 pandemic: Lessons learned and future directions. Indian J Ophthalmol. 2020;68(5):703.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Ren X. Pandemic and lockdown: a territorial approach to COVID-19 in China, Italy and the United States. Eurasian Geogr Econ. 2020;61(4–5):423–34.

    Article  Google Scholar 

  28. Alser O, AlWaheidi S, Elessi K, Meghari H. COVID-19 in Gaza: a pandemic spreading in a place already under protracted lockdown. East Mediterr Health J. 2020;26(7):762–3.

    Article  PubMed  Google Scholar 

  29. Altaher AM, Elottol AE, Jebril MA, Aliwaini SH. Assessment of awareness and hygiene practices regarding COVID-19 among adults in Gaza, Palestine. New Microbes New Infections. 2021;41:100876.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Abuzerr S, Zinszer K, Shaheen A, et al. Impact of the coronavirus disease 2019 pandemic on the Palestinian family: a cross-sectional study. SAGE Open Med. Epub ahead of print Mar 16 2021. https://doi.org/10.1177/20503121211001137.

  31. El-Khodary B, Alshawamreh S, Salah MA, Hamada A, Alhendawi B, Alhabil M, … & Wadi EA. The relationship between stress, trait emotional intelligence and mental health amongst Gaza's basic-year medical students during the COVID-19 outbreak. Middle East Curr Psych. 2021;28(1):1–9.‏

  32. El-Zoghby SM, Soltan EM, Salama HM. Impact of the COVID-19 pandemic on mental health and social support among adult Egyptians. J Commun Health. 2020;45:689–95.

    Article  Google Scholar 

  33. Ghaleb Y, Lami F, Al Nsour M, Rashak HA, Samy S, Khader YS … & Ramzi SR. Mental health impacts of COVID-19 on healthcare workers in the Eastern Mediterranean Region: a multi-country study. J Publ Health. 2021;43(Supplement_3): iii34-iii42.‏

  34. Ghandour R, Ghanayem R, Alkhanafsa F, Alsharif A, Asfour H, Hoshiya A, et al. Double burden of COVID-19 pandemic and military occupation: Mental health among a Palestinian University community in the West Bank. Ann Glob Health. 2020;86(1):1–11.

    Google Scholar 

  35. Shehada AK, Albelbeisi AH, Albelbeisi A, El Bilbeisi AH, El Afifi A. The fear of COVID-19 outbreak among health care professionals in Gaza Strip, Palestine. SAGE Open Med. 2021;9:20503121211022988.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Sharma K, Saji J, Kumar R, Raju A. Psychological and anxiety/depression level assessment among quarantine people during COVID19 outbreak. J Drug Deliv Therapeut. 2020;10(3):198–201.

    Article  CAS  Google Scholar 

  37. Roy D, Tripathy S, Kar SK, Sharma N, Verma SK, Kaushal V. Study of knowledge, attitude, anxiety & perceived mental healthcare need in Indian population during COVID-19 pandemic. Asian J Psychiatr. 2020;51:102083.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Torales J, O’Higgins M, Castaldelli-Maia JM, Ventriglio A. The outbreak of COVID-19 coronavirus and its impact on global mental health. Int J Soc Psychiatry. 2020;66(4):317–20.

    Article  PubMed  Google Scholar 

  39. Asmar IT, Naseef H, Al-Shami N, Jaghama MK, Abukhalil AD, Karsh AA, et al. Impact of COVID-19 pandemic on the psychological status of Palestinian adults in the West Bank, Palestine; a cross-sectional study. Open Psychol J. 2021;14(1):227–37.

    Article  Google Scholar 

  40. Jahan F, Al Zadjali NM, Siddiqui M, Moqbali SA. Mental health status among health care workers in primary care exposed to COVID-19 pandemic in North Batinah, Oman. Eur J Mol Clin Med. 2021;8(3):1268–80.

    Google Scholar 

  41. Vujčić I, Safiye T, Milikić B, Popović E, Dubljanin D, Dubljanin E, … & Čabarkapa M. Coronavirus disease 2019 (COVID-19) epidemic and mental health status in the general adult population of Serbia: A cross-sectional study. Int J Environ Res Public health. 2021;18(4):1957.

  42. Reavell J, Fazil Q. The epidemiology of PTSD and depression in refugee minors who have resettled in developed countries. J Ment Health. 2017;26(1):74–83.

    Article  PubMed  Google Scholar 

  43. Safiye T, Gutić M, Dubljanin J, Stojanović TM, Dubljanin D, Kovačević A, … & Milidrag A. Mentalizing, Resilience, and mental health status among healthcare workers during the COVID-19 pandemic: a cross-sectional study. Int J Environ Res Publ Health 2023;20(8):5594.

  44. Chu PS, Saucier DA, Hafner E. Meta-analysis of the relationships between social support and well-being in children and adolescents. J Soc Clin Psychol. 2010;29(6):624–45.

    Article  Google Scholar 

  45. DeLongis A, Holtzman S. Coping in context: the role of stress, social support, and personality in coping. J Pers. 2005;73(6):1633–56.

    Article  PubMed  Google Scholar 

  46. Helgeson VS, Lopez L. Social support and growth following adversity. Handbook of adult resilience. 2010;309–330.‏

  47. Labrague LJ, de los Santos JAA. COVID-19 anxiety among front-line nurses: Predictive role of organizational support, personal resilience and social support. J Nurs Manage. 2020;28(7):1653–61.

    Article  Google Scholar 

  48. Taylor SE, Welch WT, Kim HS, Sherman DK. Cultural differences in the impact of social support on psychological and biological stress responses. Psychol Sci. 2007;18:831–7.

    Article  PubMed  Google Scholar 

  49. Burnell KJ, Coleman PG, Hunt N. Falklands War veterans’ perceptions of social support and the reconciliation of traumatic memories. Aging Ment Health. 2006;10(3):282–9.

    Article  CAS  PubMed  Google Scholar 

  50. Ajrouch KJ, Reisine S, Lim S, Sohn W, Ismail A. Perceived everyday discrimination and psychological distress: does social support matter. Ethn Health. 2010;15(4):417–34.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Çivitci A. The moderating role of positive and negative affect on the relationship between perceived social support and stress in college students. Educ Sci: Theor Pract. 2015;15(3):565–73.

    Google Scholar 

  52. Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 1985;98:310–57.

    Article  CAS  PubMed  Google Scholar 

  53. Fino E, Bonfrate I, Fino V, Bocus P, Russo PM, Mazzetti M. Harnessing distress to boost growth in frontline healthcare workers during COVID-19 pandemic: The protective role of resilience, emotion regulation and social support. Psychol Med. 2021;53(2):1–3.

    Article  Google Scholar 

  54. Lepore SJ, Evans GW, Schneider ML. Dynamic role of social support in the link between chronic stress and psychological distress. J Pers Soc Psychol. 1991;61(6):899.

    Article  CAS  PubMed  Google Scholar 

  55. Prado G, Feaster DJ, Schwartz SJ, Pratt IA, Smith L, Szapocznik J. Religious involvement, coping, social support, and psychological distress in HIV-seropositive African American mothers. AIDS Behav. 2004;8(3):221–35.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Yu H, Li M, Li Z, Xiang W, Yuan Y, Liu Y, … Xiong Z. Coping style, social support and psychological distress in the general Chinese population in the early stages of the COVID-19 epidemic. BMC Psych. 2020;20(1):1–11.‏

  57. Gottlieb BH. Social support in adolescence. In: Adolescent stress. 2017;281–307.

  58. Hobfoll E, Stockes P. The Process and Mechaniced of social support. In: Duck SW, Hay DF, Hobfoll SE, Ickes B, Montgomery B, editors. The handbook of research in personal relationship. London: Wiley; 1988. p. 497–517.

    Google Scholar 

  59. Veronese G, Pepe A, Diab M, Abu Jamei Y, Kagee A. Social support, resilience, and mental health in a low-intensity warfare context: the effects of siege on university students in Gaza. J Ment Health. 2022;31(3):383–91.

    Article  PubMed  Google Scholar 

  60. Pietrzak RH, Johnson DC, Goldstein MB, Malley JC, Southwick SM. Psychological resilience and post deployment social support protect against traumatic stress and depressive symptoms in soldiers returning from operations enduring freedom and Iraqi freedom. Depress Anxiety. 2009;26(8):745–51.

    Article  PubMed  Google Scholar 

  61. Prati G, Pietrantoni L. Optimism, social support, and coping strategies as factors contributing to posttraumatic growth: a meta-analysis. J Loss Trauma. 2009;14(5):364–88.

    Article  Google Scholar 

  62. Tedeschi RG, Calhoun LG. Posttraumatic growth: conceptual foundations and empirical evidence. Psychol Inq. 2004;15(1):1–18.

    Article  Google Scholar 

  63. Al-Sheikh NA, Thabet AA. Post-traumatic stress disorder due to war trauma, social and family support among adolescent in the Gaza strip. J Nurs Health Sci. 2017;3(2):1.

    Google Scholar 

  64. Hager FW. Links between telecommuting, social support and mental well-being among teleworkers. ‏2018.

  65. McCabe CT, Watrous JR, Galarneau MR. Trauma exposure, mental health, and quality of life among injured service members: Moderating effects of perceived support from friends and family. Mil Psychol. 2020;32(2):164–75.

    Article  Google Scholar 

  66. Smith BN, Wang JM, Vaughn-Coaxum RA, Di Leone BA, Vogt D. The role of post deployment social factors in linking deployment experiences and current posttraumatic stress disorder symptomatology among male and female veterans. Anxiety Stress Coping. 2017;30(1):39–51.

    Article  PubMed  Google Scholar 

  67. Ahorsu DK, Pramukti I, Strong C, Wang HW, Griffiths MD, Lin CY, Ko NY. COVID-19-related variables and its association with anxiety and suicidal ideation: Differences between international and local university students in Taiwan. Psychol Res Behav Manag. 2021;14:1857–66. https://doi.org/10.2147/PRBM.S333226.

    Article  PubMed  PubMed Central  Google Scholar 

  68. Ohaeri JU, Awadalla AW. The reliability and validity of the short version of the WHO Quality of Life Instrument in an Arab general population. Ann Saudi Med. 2009;9(2):98–104.

    Article  Google Scholar 

  69. Lovibond PF, Lovibond SH. The structure of negative emotional states: comparison of the Depression Anxiety Stress Scales (DASS) with the beck depression and anxiety inventories. Behav Res Ther. 1995;33(3):335–43.

    Article  CAS  PubMed  Google Scholar 

  70. Schulz U, Schwarzer R. Social support in coping with illness: The Berlin Social Support Scales (BSSS). Diagnostica. 2003;49:73–82.

    Article  Google Scholar 

  71. Levkovich I, Shinan-Altman S, Essar Schvartz N, Alperin M. Depression and health-related quality of life among elderly patients during the COVID-19 pandemic in Israel: a cross-sectional study. J Prim Care Commun Health. 2021;12:2150132721995448.

    Article  Google Scholar 

  72. Liu C, Lee YC, Lin YL, Yang SY. Factors associated with anxiety and quality of life of the Wuhan populace during the COVID-19 pandemic. Stress Health. 2021;37(5):887–97.

    Article  PubMed  PubMed Central  Google Scholar 

  73. Ng, CG, Mohamed, S, See, MH, Harun, F, Dahlui, M, Sulaiman, AH, … & Taib, NA. Anxiety, depression, perceived social support and quality of life in Malaysian breast cancer patients: a 1-year prospective study. Health Qual Life Outc. 2015;13(1):1–9.‏

  74. Ratajska A, Glanz BI, Chitnis T, Weiner HL, Healy BC. Social support in multiple sclerosis: Associations with quality of life, depression, and anxiety. J Psychosom Res. 2020;138:110252.

    Article  PubMed  Google Scholar 

  75. Shrestha JS, Shrestha A, Sapkota A, Sharma R, Shrestha S, Shestha S, Gautam M. Social support, quality of life and mental health status in breast cancer patients. Cancer Rep Rev. 2017;1(2):1–5.

    Google Scholar 

  76. Whatley AD, DiIorio CK, Yeager K. Examining the relationships of depressive symptoms, stigma, social support and regimen-specific support on quality of life in adult patients with epilepsy. Health Educ Res. 2010;25(4):575–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. White RG, Van Der Boor C. Impact of the COVID-19 pandemic and initial period of lockdown on the mental health and well-being of adults in the UK. BJPsych Open. 2020;6(5):e90.

    Article  PubMed  Google Scholar 

  78. Behar J. Social support: Theory, research and applications. Soc Sci Med. 1986;22(12):1369–70.

    Article  Google Scholar 

  79. Li F, Luo S, Mu W, Li Y, Ye L, Zheng X, … & Chen X. Effects of sources of social support and resilience on the mental health of different age groups during the COVID-19 pandemic. BMC Psych. 2021;21(1):1–14.‏

  80. Wu SFV, Young LS, Yeh FC, Jian YM, Cheng KC, Lee MC. Correlations among social support, depression, and anxiety in patients with type-2 diabetes. J Nurs Res. 2013;21(2):129–38.

    Article  PubMed  Google Scholar 

  81. Veronese G, Diab M, Abu Jamei Y, Saleh S, Kagee A. Risk and protection of suicidal behavior among Palestinian university students in the Gaza Strip: an exploratory study in a context of military violence. Int J Ment Health. 2021;50(4):293–310.

    Article  Google Scholar 

  82. An Y, Yang Y, Wang A, Li Y, Zhang Q, Cheung T, … & Xiang YT. Prevalence of depression and its Impact on quality of life among frontline nurses in emergency departments during the COVID-19 outbreak. J Affect Disord. 2020; 276:312–315.‏

  83. Suryavanshi N, Kadam A, Dhumal G, Nimkar S, Mave V, Gupta A, … Gupte N. Mental health and quality of life among healthcare professionals during the COVID‐19 pandemic in India. Brain Behav. 2020;10(11):e01837.‏

  84. Zhang HH, Zhao YJ, Wang C, Zhang Q, Yu HY, Cheung T, … & Xiang YT. Depression and its relationship with quality of life in frontline psychiatric clinicians during the COVID-19 pandemic in China: a national survey. Int J Biol Sci. 2021;17(3):683.‏

  85. Eren I, Erdi Ö, Şahin M. The effect of depression on quality of life of patients with type II diabetes mellitus. Depress Anxiety. 2008;25(2):98–106.

    Article  PubMed  Google Scholar 

  86. Ma YF, Li W, Deng HB, Wang L, Wang Y, Wang PH, … & Xiang YT. Prevalence of depression and its association with quality of life in clinically stable patients with COVID-19. J Affect Disord. 2020;275:145–148.‏

  87. Sainsbury K, Mullan B, Sharpe L. Reduced quality of life in coeliac disease is more strongly associated with depression than gastrointestinal symptoms. J Psychosom Res. 2013;75(2):135–41.

    Article  PubMed  Google Scholar 

  88. Fazeli S, Zeidi IM, Lin CY, Namdar P, Griffiths MD, Ahorsu DK, Pakpour AH. Depression, anxiety, and stress mediate the associations between internet gaming disorder, insomnia, and quality of life during the COVID-19 outbreak. Addict Behav Rep. 2020;12:100307.

    PubMed  PubMed Central  Google Scholar 

  89. Freire T, Ferreira G. Health-related quality of life of adolescents: Relations with positive and negative psychological dimensions. Int J Adolesc Youth. 2018;23(1):11–24.

    Article  Google Scholar 

  90. Ravens-Sieberer U, Kaman A, Erhart M, Devine J, Schlack R, Otto C. Impact of the COVID-19 pandemic on quality of life and mental health in children and adolescents in Germany. Eur Child Adolesc Psych. 2021;31:1–11.

    Google Scholar 

  91. Ravens-Sieberer U, Kaman A, Erhart M, Otto C, Devine J, Löffler C, et al. Quality of life and mental health in children and adolescents during the first year of the COVID-19 pandemic: results of a two-wave nationwide population-based study. Eur Child Adoles Psych. 2021;32:1–14.

    Google Scholar 

  92. Ravens-Sieberer U, Kaman A, Otto C, Adedeji A, Devine J, Erhart M, Napp AK, Becker M, Blanck-Stellmacher U, Löffler C, Schlack R, Hurrelmann K. Mental health and quality of life in children and adolescents during the COVID-19 pandemic-results of the copsy study. Deutsches Arzteblatt Int. 2020;117(48):828–9.

    Google Scholar 

  93. Adib-Hajbaghery M, Ahmadi M. Health related quality of life, depression, anxiety and stress in patients with beta-thalassemia major. Iranian J Pediatr Hematol Oncol. 2015;5(4):193.

    CAS  Google Scholar 

  94. Ansari Sh, Baghersalimi A, Azarkeivan A, Nojomi M, Hassanzadeh RA. Quality of life in patients with thalassemia major. Iran J Ped Hematol Oncol. 2014;4(2):57–63.

    PubMed  PubMed Central  Google Scholar 

  95. Kaheni S, Yaghobian M, Sharefzadah GH, Vahidi A, Ghorbani H, Abderahemi A. Quality of life in children with β-thalassemia major at center for special diseases. Iran J Ped Hematol Oncol. 2013;3(3):108–13.

    CAS  PubMed  PubMed Central  Google Scholar 

  96. Salama A. Discuss the relationship between unemployment and level of education in Palestine. The Annals of the University of Oradea. Econ Sci. 2017;26(1):171–80.

    Google Scholar 

  97. Veronese G, Pepe A, Jaradah A, Murannak F, Hamdouna H. Quality of life and determinants of parents’ school satisfaction in war contexts: A mixed-method exploratory study in Palestine. SAGE Open. 2015;5(4):2158244015608422.

    Article  Google Scholar 

  98. Jones AM, Wildman J. Health, income and relative deprivation: Evidence from the BHPS. J Health Econ. 2008;27(2):308–24.

    Article  PubMed  Google Scholar 

  99. Kusek JW, Greene P, Wang SR, Beck G, West D, Jamerson K, … & Level, B. Cross-sectional study of health-related quality of life in African Americans with chronic renal insufficiency: The African American Study of Kidney Disease and Hypertension Trial. Am J Kidney Dis. 2002;39(3):513–524.‏

  100. Lemos CF, Rodrigues MP, Veiga JR. Family income is associated with quality of life in patients with chronic kidney disease in the pre-dialysis phase: a cross sectional study. Health Qual Life Outcomes. 2015;13(1):1–9.

    Article  Google Scholar 

  101. Tan Z, Shi F, Zhang H, Li N, Xu Y, Liang Y. Household income, income inequality, and health-related quality of life measured by the EQ-5D in Shaanxi, China: a cross-sectional study. Int J Equit Health. 2018;17(1):1–10.

    Article  Google Scholar 

  102. Diab M, Veronese G, Jamei YA, Hamam R, Saleh S, Kagee A. Community work in the ongoing crisis context of Gaza: Integrating a public health and human rights approach. Australian New Zealand J Fam Ther. 2018;39(3):320–30.

    Article  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Author information

Authors and Affiliations

Authors

Contributions

All authors contributed to the study’s conception and design. Material preparation, data collection and analysis were performed by [Suhayla Jalala], [Guido Veronese], [Marwan Diab], [Yasser Jamei], [Rawya Hamam], and [Ashraf Kagee]. The first manuscript draft was written by [Suhayla Jalala], and all authors commented on previous versions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Marwan Diab.

Ethics declarations

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Stellenbosch University (Date: 7–12-2020/No: REC-2020–17479) and the Helsinki committee (Palestinian Health Research Council) (Date: 1–6-2020\ No: PHRC\HC\702\20).

Written Informed consent was obtained from most individual participants included in the study. However, because we had [5] uneducated participants, we obtained verbal consent from them as they are too old to go back to their parents and ask for it in writing like little children. The Ethics Committee of Stellenbosch University and the Helsinki committee (Palestinian Health Research Council) both approved verbal informed consent procedure.

Each participant in the study was given the right to decline participation and withdraw from the study. Moreover, we pledged to protect the participants' privacy; thus, their names and any revealing data were not disclosed.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jalala, S.S., Veronese, G., Diab, M. et al. Quality of life among residents of Gaza, Palestine: the predictive role of mental distress, fear of COVID-19, and social support. BMC Psychol 12, 152 (2024). https://doi.org/10.1186/s40359-024-01642-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40359-024-01642-8

Keywords