Psychological trauma and post-traumatic growth in parents of children with sickle cell disease

TL;DR

This study explores the psychological trauma and post-traumatic growth experienced by parents of children with sickle cell disease in Saudi Arabia.

Contribution

The study provides insights into trauma and growth among caregivers of children with sickle cell disease in Al-Ahsa, Saudi Arabia.

Findings

Mothers reported higher trauma levels than fathers.

Higher family income and education were linked to lower trauma scores.

Online participants showed higher trauma and post-traumatic growth compared to phone interviewees.

Abstract

Sickle cell disease (SCD) is a hereditary blood condition characterized by abnormal hemoglobin, leading to chronic hemolysis and vaso-occlusive complications. Caregivers of children with SCD often experience significant distress, akin to post-traumatic stress disorder (PTSD). This study aimed to measure the degree of trauma and post-traumatic growth among parents (caregivers) of children with SCD in the Kingdom of Saudi Arabia. A total of 294 primary caregivers were recruited for this study, through direct phone calls and online outreach using contact information obtained from their primary treating physician in Maternity and Children Hospitals and the Hereditary Blood Diseases Center in Al-Ahsa. Inclusion criteria required caregivers not to be receiving professional mental health care and to have a child with SCD below the age of 18. Results indicate that caregiver gender significantly affected IESR scores, with mothers reporting higher scores than fathers. Family income had a significant effect on IESR as well. In terms of education level, higher-educated caregivers were less likely to experience severe trauma. Significant differences emerged between online and phone interview participants, with online respondents reporting higher post-traumatic growth and higher trauma levels. This study represents a crucial step in understanding the challenges faced by caregivers of children with SCD in Al-Ahsa, Saudi Arabia. However, the study has limitations, including a substantial portion of the sample being from a single clinic and a cross-sectional design.

Full text

Introduction

1

Sickle cell disease (SCD) is a hereditary blood condition passed down from parents to children in an autosomal recessive pattern. It is characterized by the presence of an abnormal type of hemoglobin in affected individuals. Hemoglobin, a protein found in red blood cells, is responsible for transporting oxygen throughout the body. SCD affects this process of oxygen transportation to organs and tissues [1].

Individuals with SCD can present clinically with chronic hemolysis, increased susceptibility to infections, and vaso-occlusive complications, often requiring medical care [2]. Symptoms such as paleness and fatigue due to hemolytic anemia occur in all significant forms of SCD. The lifespan of red cells in HbSS patients is estimated to be around 17 days, compared to 120 days in healthy individuals [3,4]. Sickled cells can become sticky as they flow through small blood vessels, occluding these vessels and resulting in sharp pain. This pain can occur anywhere in the body, but the most common sites are the chest, arms, and legs [5,6].

Children with SCD get admitted to hospitals for various reasons. The most common cause of admissions worldwide is the acute painful crisis [7,8]. However, in developing countries, infections remain the top cause of admission [8].

SCD affects millions globally, with a high prevalence among descendants of sub-Saharan Africa, Spanish-speaking regions of the hemisphere (South America, the Caribbean, and Central America), Saudi Arabia, India, and Mediterranean countries such as Turkey, Greece, and Italy [9]. Studies have shown that SCD is a comparatively common genetic disorder in Saudi Arabia, with a range of 2 %–27 % in the carrier state and up to 1.4 % in the disease state [9]. Moreover, caregivers of children with chronic diseases generally experience high levels of distress that can lead to dysregulation of the hypothalamic-pituitary-adrenal axis and reduce their life span [10]. Given the significant impact of SCD on quality of life and the frequent hospitalizations due to various crises and complications, it is unsurprising that studies report that four out of ten caregivers experience emotional distress due to their child having SCD [11].

Furthermore, due to some lethal complications of SCD, it can be assumed that a caregiver of a child with the disease may experience elements of post-traumatic stress disorder (PTSD). PTSD can result from extremely stressful, distressing, or frightening events and is characterized by nightmares and flashbacks related to the event, accompanied by feelings of isolation, guilt, and irritability [12].

PTSD is clinically diagnosed using specific diagnostic criteria. These include exposure to the traumatic event (TE), involuntary memories of the TE, distressing dreams related to the TE, flashbacks of the TE, intense psychological and physiological reactions to cues symbolizing the TE, avoidance of stimuli related to the TE, and negative alterations in arousal, mood, and cognitions related to the TE [13].

Some studies have demonstrated the psychological impact of SCD on affected children and their parents. For instance, a study conducted in France, including SCD children and their parents, showed the presence of PTSD in SCD children and their parents similar to the findings found in cancer survival children and their families [14].

In addition, psychological challenges are widespread among the public, and studies indicate that levels of depression are particularly elevated among caregivers of children with cancer [15,16].

To the best of our knowledge, there are very few studies on PTSD among parents of children with SCD globally, with no study done in the region. This creates a knowledge gap in the literature regarding this issue. So, this study aims to measure the degree of trauma among caregivers (i.e., parents) of children affected with SCD, as well as post-traumatic growth. We plan to collect data through two methods, i.e., phone calls and online questionnaires, to identify any significant difference between them, especially after the COVID era when everything is being done with the least amount of friction and connection.

Finally, this study will evaluate the factors contributing to the degree of trauma (i.e., rate of admission, level of income, level of education) as PTSD in caregivers may affect the quality of care, causing more suffering in SCD patients and daily life disturbances. This study may help policymakers in the Kingdom of Saudi Arabia to identify the most vulnerable group and design supporting programs. Although this study sample is limited to the eastern region of Saudi Arabia, the results can be generalized globally due to the similarity in disease presentation and burden.

Methods

2

This study was conducted in accordance with the ethical standards outlined in the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) under the ethical approval number 64-EP-2021.

Sample

2.1

This study involved 294 caregivers of children with sickle cell disease in the period between 2021 and 2022. The caregivers were conveniently invited to the study by their primary treating hematologist. After verbal consent was obtained, their contact numbers were sourced from the databases of the Maternity and Children Hospital and the Hereditary Blood Diseases Centre in Al-Ahsa. The primary caregivers were eligible to participate in this study if they had a child with SCD. Exclusion criteria included parents who were receiving mental health care services or if their child was above 18 years of age.

Procedures

2.2

Prior to participation, all participants were provided with detailed information about the study objectives, procedures, potential risks, and benefits. Informed consent was obtained from all participants before any data collection commenced. Participants were assured of their anonymity and confidentiality. A structured interview was conducted with 142 caregivers over the phone, while 151 caregivers participated through an online Google form questionnaire. The two methods were used to identify any significant difference between them, especially after the COVID-19 era, when reduced contact became more common in contemporary research practices. The response rate for the phone calls was 80 %. Each phone call took 22–27 min to answer all the questions. Demographic information included questions about the level of education of the primary caregiver, age, family income, and the type of therapy coverage.

An Arabic version of the Impact of Events Scale-Revised, developed by Daniel Weiss and Charles Marmar and translated and validated by Ali (2022), was used to diagnose PTSD according to DSM-IV [17]. The primary caregivers were asked to rate the presence of each of the 22 statements related to PTSD on a 4- scale ranging from "not at all" [0] to "extremely" [4]. Questions were formulated to be related to the sickle cell disease of their child to ensure assessment of SCD-related PTSD. For example, item 1 asked whether there was any reminder that brought back feelings about the disease or the treatment of the child. Total IES-R scores range from 0 to 88, with higher scores representing a high probability of PTSD presence.

An Arabic version of the Post-traumatic growth inventory developed by Lawrence Calhoun and Richard Tedeschi and translated and validated by Al-Nasah, was also used to assess the growth and self-improvement a person undergoes after trauma [18]. The participants were asked if they experienced 21 different items related to growth on a 6-point scale ranging from "I did not experience this as a result of my crisis" [0] to "I experienced this change to a very great degree as a result of my crisis" [5]. A high total score indicates that the person has undergone a positive change.

Data management and statistical analyses

2.3

The data was stored in Excel sheets and reviewed. Then, it was analyzed using the statistical package SPSS, release 26 (SPSS Inc., Chicago, IL). All analyses were performed with two-sided tests; p < 0.01, and p < .05 were considered significant. In demographic data such as gender distribution and family income, descriptive statistics such as frequencies, mean, median, standard deviation, minimum, and maximum values were used, as well as in IES-R dimensions and PTGI. ANOVA test was also used to analyze the differences between the mean scores of IES-R and PTGI scales of demographic data, such as the different family income groups. Tukey's HSD test was used to see the significance of the means of different groups of demographics in relation to IES-R score. Pearson correlation coefficient was used to examine the relationship between the three dimensions of IESR (intrusion, avoidance, and hyperarousal) and the five dimensions of post-traumatic growth in the PTGI (Relating to others, New possibilities, Personal strength, Spiritual change, and an Appreciation of life), as well as the relationship between PTSD, demographics, and illness-related variables.

Results

3

The overall sample was composed of 294 caregivers. The details of the sociodemographics are shown in Table 1a, Table 1ba, b 49.2 % of the responses were gathered online, while 50.8 % came from phone interviews. Mothers were the primary caregivers in 54.4 % of the sample, while fathers were 44.9 %, and others were barely 0.6 %. Regarding the education level, 24.7 % of the caregivers were below secondary school, 35.8 % had completed secondary school, and 39.6 % had a university degree. Most of the caregivers were in an age group between 41 years and 50 years (40.8 %). Most of the sample had a family income from 8000 to 12000 SR (32.3 %) and an income of less than 5000 SR (29.4 %).Table 1aSociodemographic data of the caregivers of children with sickle cell disease (n = 315).Table 1aCharacteristicsNo.%Primary caregiver Mother17254.4 Father14244.9 Others20.6Educational level Below secondary school7824.7 Secondary school11335.8 University degree12539.6Age of the caregiver 20–30288.9 31–4011837.3 41–5012940.8 51–604113Age of the partner 20–30196 31–4010834.2 41–5014044.3 51–603812 Single parent113.5Family income (by Saudi Riyal) Less than 5K9329.4 5K–7K5216.5 8K–12K10232.3 13K–16K4714.9 More than 16K227Therapy payment Fully covered29493 Cash contribution227Chronic disease Sickle cell disease4414.0 One chronic disease5116.2 Multiple chronic disease268.3 Multiple chronic disease including Sickle cell disease278.6 None16853.3Mental disorder Yes227 No29493Substance use Smoking6821.5 Morphine20.6 None24677.8Number of children 1 child4413.9 Two6520.6 Three6119.3 Four6119.3 Five288.9 More than 55718Do you attend your child appointments? Always27687.3 Sometimes3912.3 No10.3Do you think that you receive family support for your child's disease? Yes15348.4 A little8928.2 No7423.4Do you have a relative with the same disease? Yes26182.6 No5517.4Table 1bCharacteristics of the children with sickle cell disease (n = 315).Table 1bCharacteristicsNo.%Gender Male22771.8 Female8928.2The age of the child when they're informed with the diagnosis. Birth to 2 years18859.5 3–6 years10432.9 6–9 years175.4 10–13 years72.2Having a complication of SCD Multiple complications185.7 One complication6821.5 No complications23072.8History of surgeries Multiple surgeries61.9 One surgery7724.4 No surgeries21166.98Hospital admissions because of SCD? Once12038 Twice299.2 Three times4915.5 Four times247.6 Five times92.8 More than 5 times8526.9Does the child have another hereditary disease? G6PD deficiency6319.9 Thalassemia247.6 None22972.5

In terms of the differences between the phone calls and the online questionnaires, the results in Table 2, Table 3 indicated significant differences in the mean of PTG scores between them, with online participants having higher mean score (M = 63.09 ± 27.99) than phone calls participants (M = 36.12 ± 25.24), p < 0.001. Similarly, trauma levels, as measured by IES-R, were significantly higher in the online group (M = 12.32 ± 13.24) compared to the phone calls group (M = 9.15 ± 10.46), p = 0.023.Table 2. Independent samples t-test comparing the means of IESR scores between online and phone interview data collection modes.Table 2. Independent samples t-test for the means of IESR score95 % Confidence Interval of the DifferenceMode of CollectionNMean ± SD of IESR scorep-value. (2-tailed)t-statisticdfMean DifferenceLowerUpperOnline14212.32 ± 13.240.0232.292913.180.445.91Phone Interviews1519.15 ± 10.46Table 3Independent samples t-test comparing the means of PTGI scores between online and phone interview data collection modes.Table 3. Independent samples t-test for the means of PTGI score95 % Confidence Interval of the DifferenceMode of CollectionNMean ± SD of PTGI scorep-value. (2-tailed)t-statisticdfMean DifferenceLowerUpperOnline14263.09 ± 27.990.0008.6729126.9820.8533.09Phone Interviews15136.12 ± 25.24

Table 4 shows the impact of event score among the primary caregivers consisting of mothers, fathers, and, in some children, other individuals who took care of them. It includes information on the mean, standard deviation, 95 % confidence intervals for the mean, ANOVA results, and Tukey's HSD test results. The average score for mothers (n = 158) was 13.10 (SD = 13.09), with a 95 % confidence interval ranging from 11.11 to 15.23. For fathers (n = 134), the average score was 7.81 (SD = 9.8), with a 95 % confidence interval ranging from 6.13 to 9.48. The gender of the caregiver had a significant effect on the total score of the IESR scale F [2,291] = 7.63, p = 0.001. Moreover, the Tukey HSD post-hoc analysis results indicated a significant mean difference in IES scores between mothers and fathers (Mdiff = 5.36, SE = 1.37, p < 0.001).Table 4ANOVA results comparing the means of IESR scores among different primary caregivers (mother, father, others), and Tukey's HSD test results.Table 495 % Confidence Interval for Mean ANOVAPrimary CaregiverNMean ± SD of IESR scoreLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsMother15813.10 ± 13.0911.1115.237.6330.001vs. Father: p = 0.000Father1347.81 ± 9.86.139.48vs. Others: p = 0.962Others210.00 ± 11.31−91.65111.65vs. Mothers: p = 0.923Total29410.70 ± 11.969.3312.08*The mean difference is significant at the 0.05 level.

Regarding the income level, the average score of the IES was the highest for the lowest income range (less than 5000 SR), with a mean of 16.17. The average score decreases as income increases, with the lowest mean score of 5.73 for the income range of 13000–16000 SR. Moreover, Table 5 shows that the results of an ANOVA test revealed a significant difference in the IES score between the means of the income categories F(4, 289) = 9.442, p < 0.001. Pairwise comparisons of the means using Tukey HSD revealed significant differences between families with less than 5000SR income and almost all of the other categories. More specifically, those who had a family income of less than 5000 SR (M = 16.17, SD = 14.65), had significantly higher average IES scores than those who had a family income of 8000 SR to 12000 SR (M = 8.30, SD = 8.18, p < .001), 13000 to 16000 (M = 5.73, SD = 8.50, p p < .001), and those who had an income that was more than 16000 SR (M = 5.81, SD = 7.51, p = 0.002).Table 5ANOVA results comparing the means of IESR scores among different family income groups, and Tukey's HSD test results.Table 595 % Confidence Interval for Mean ANOVAFamily incomeNMean ± SD of IESR scoreLower BoundUpper BoundF-valuep-valueTukey's HSD Test Resultsless than 5000 SR8416.17 ± 14.6512.9919.359.44. 000Vs 5000 to 7000 SR: p = 0.391Vs 8000 to 12000 SR: p = 0.000Vs 13000 to 16000 SR: p = 0.000Vs More than 16000 SR: p = 0.0025000 to 70005012.58 ± 13.338.7916.37Vs 8000 to 12000 SR: p = 0.198Vs 13000 to 16000 SR: p = 0.029Vs More than 16000 SR: p = 0.1488000 to 12000 SR948.30 ± 8.186.629.97Vs 13000 to 16000 SR: p = 0.722Vs More than 16000 SR: p = 0.89313000 to 16000455.73 ± 8.503.188.29Vs More than 16000 SR: p = 1.000More than 16000215.81 ± 7.512.399.23Vs 13000 to 16000 SR: p = 1.000Total29410.70 ± 11.969.3312.08*The mean difference is significant at the 0.05 level.

In terms of the education level, the detailed descriptive statistics are presented in Table 6. The mean scores for IESR were highest for those with below secondary school education (M = 15.89), followed by secondary school education (M = 11.09), and lowest for those with a university degree (M = 7.60). The ANOVA test showed a statistically significant difference in the mean scores of IESR based on level of education F (2,291) = 10.993, p < .001. The Tukey HSD test further showed that the mean score for those with a university degree was significantly lower than those with below secondary school education (p < .001) and secondary school education (p = 0.024).Table 6ANOVA results comparing the means of IESR scores among different levels of education of the primary caregiver, and Tukey's HSD test results.Table 695 % Confidence Interval for Mean ANOVALevel of Education of the primary care giverNMean ± SDLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsBelow secondary school6515.89 ± 14.7112.2519.5410.9930.000Vs Secondary School p = 0.024Secondary School10711.09 ± 11.398.9113.28Vs University Degree: p = 0.060University Degree1227.60 ± 9.685.869.33Vs Below secondary school: p = 0.000Total29410.70 ± 11.969.3312.07*The mean difference is significant at the 0.05 level.

Regarding the effect of the child having a complication of SCD on the parent's IESR scores, the results in Table 7 shows that the mean IESR score of parents who their child had one complication (15.88) was similar to those who had a child with multiple complications (15.00). On the other hand, parents with a child who did not experience any complications had the lowest mean score (8.91). As a result, it was clear that the effect of complications on the parents' IESR score is significant F(2,291) = 9.782, p < .001.Table 7ANOVA results comparing the means of IESR scores based on having complications of SCD (one complication, no complications, multiple complications), and Tukey's HSD test results.Table 795 % Confidence Interval for Mean ANOVAHaving a complication of SCDNMean ± SD of IESR scoreLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsHad one complication6015.88 ± 13.1912.4819.299.78. 000Vs No complications: p = 0.000No complications2168.90 ± 11.257.4010.42Vs Multiple complications: p = 0.084Multiple complications1815.00 ± 10.279.8920.11Vs Had one complication p = . 957Total29410.70 ± 11.969.3312.08*The mean difference is significant at the 0.05 level.

Regarding the history of surgeries in Table 8, the mean IESR score for parents of children who had multiple surgeries (11.00) was higher than that of those who did not have surgeries (9.36) but lower than that of those with at least one surgery (14.35). Moreover, the Anova results showed that surgeries significantly affect the mean IESR score (F = 5.041, p = .007).Table 8ANOVA results comparing the means of IESR scores based on the history of surgeries (at least one surgery, no surgeries, multiple surgeries), and Tukey's HSD test results.Table 895 % Confidence Interval for Mean ANOVADoing surgeriesNMean ± SD of IESR scoreLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsHad at least one surgery7714.35 ± 12.5311.5117.205.040.007Vs Didn't have a surgery: p = 0.005Didn't have a surgery2119.36 ± 11.587.7910.94Vs Had multiple surgeries: p = 0.940Had multiple surgeries611.00 ± 8.991.5720.40Vs Had at least one surgery p = 0.781Total29410.70 ± 11.969.3312.08*The mean difference is significant at the 0.05 level.

In terms of having another hereditary disease, the results in Table 9 revealed that parents whose child had thalassemia had the lowest mean IESR score (8.76), followed by parents whose child did not have another hereditary disease (10.07), and parents whose child had G6PD (13.78). However, the ANOVA table indicated that the differences in the means between the groups were not statistically significant F(2,291) = 2.524, p = 0.082.Table 9ANOVA results comparing the means of IESR scores based on the child having other hereditary diseases (G6PD, none, Thalassemia), and Tukey's HSD test results.Table 995 % Confidence Interval for Mean ANOVAThe child having other hereditary diseasesNMean ± SD of IESR scoreLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsG6PD5813.78 ± 13.4210.2517.302.520.082Vs None: p = 0.090None21510.07 ± 11.508.5211.61Vs Thalassemia: p = 0.881Thalassemia218.76 ± 11.413.5713.95Vs G6PD: p = 0.224Total29410.70 ± 11.969.3312.08

Regarding the effect of admission rate, the results in Table 10 show that the mean IESR score for all participants was (M = 10.7041 ± 11.95687). Participants who had their children admitted to the hospital more than five times had the highest mean IESR score (17.0845), while those who had their children admitted only once had the lowest mean score (5.5169). Furthermore, the results of the ANOVA test indicated a statistically significant difference between the means of IESR scores for different admission rates F(5,288) = 10.688, p < .001. In Tukey's HSD test, the differences were statistically significant for all comparisons except for the comparison between twice and three times hospital admissions and between five times and more than five hospital admissions.Table 10ANOVA results comparing the means of IESR scores based on the frequency of hospital admissions due to SCD, and Tukey's HSD test results.Table 1095 % Confidence Interval for Mean ANOVAFrequency of Hospital admissions because of SCDNMean ± SDLower BoundUpper BoundF-valuep-valueTukey's HSD Test ResultsOnce1185.52 ± 7.714.116.9210.688. 000Vs Twice: p = 0.390Vs Three times: p = 0.005Vs Four times: p = 0.013Vs Five times: p = 0.276Vs More than five times: p = 0.000Twice299.93 ± 13.094.9514.91Vs Three times: p = 0.927Vs Four times: p = 0.792Vs Five times: p = . 933Vs More than five times: p = 0.042Three times4512.49 ± 11.569.0215.96Vs Four times: p = 0.996Vs Five times: p = 0.999Vs More than five times: p = 0.252Four times2313.91 ± 8.6210.2017.64Vs Five times: p = 1.000Vs More than five times: p = 0.840Five times814.13 ± 10.065.7122.54Vs More than five: p = 0.980More than five times7117.08 ± 14.8113.5820.59Vs Five times: p = 0.980Total29410.70 ± 11.969.3312.08*The mean difference is significant at the 0.05 level.

Table 11 shows the descriptive statistics of the IES-R and PTGI scores and their subscales. The mean score for IES-R was 10.70, indicating that the caregivers experienced some level of stress related to their role as caregivers. The IES-R subscales included intrusive thoughts, avoidance, and hyperarousal. The mean scores for these subscales were 3.96, 3.55, and 3.19, respectively. On the other hand, the mean score for PTGI was 49.21, indicating that caregivers also experienced some level of post-traumatic growth. PTGI is composed of five subscales. They relate to others, new possibilities, personal strength, spiritual change, and appreciation of life. The mean scores for these subscales were 14.22, 10.18, 11.67, 5.86, and 7.28, respectively.Table 11. Mean and standard deviation (SD) of IESR and PTGI scores, including the subscales.Table 11. CharacteristicsMean ± SDIESPTSD_intrusive thoughts3.96 ± 4.17PTSD_Avoidance3.55 ± 4.56PTSD_Hyperarousal3.19 ± 3.86Total IES score10.7 ± 11.96PTGIT scorePTGI_ Relating to others14.22 ± 10.05PTGI_ New Possibilities10.18 ± 8.31PTGI_ Personal Strength11.67 ± 6.54PTGI_ Spiritual Change5.86 ± 3.47PTGI_ Appreciation of Life7.28 ± 4.46PTGIT total score49.21 ± 29.75

In terms of the relationships between the three elements of PTSD (intrusion, avoidance, and hyperarousal), Table 12a shows that there were positively strong relationships between them. For example, the Pearson correlation coefficient of intrusive thoughts and avoidance was found to be strongly positive and statistically significant (r = . 849, p = 0.000). Similarly, the correlation of avoidance and hyperarousal was found to be as strongly positive and significant (r = . 849, p = 0.000). Moreover, the correlation of hyperarousal and intrusive thoughts was found to be stronger than the formers (r = . 855, p = 0.000).Table 12aPearson Correlation between the total scores of IESR and PTGI.Table 12aIES_RPTGIIES_RPearson Correlation10.328aSig. (2-tailed)0.000N294294PTGITPearson Correlation0.328a1Sig. (2-tailed)0.000N294294aCorrelation is significant at the 0.01 level (2-tailed).

In addition, the five dimensions of post-traumatic growth in the PTGI (Relating to others, New Possibilities, Personal Strength, Spiritual Change, and Appreciation of Life) were positively and strongly correlated (Table 12b). The strongest degree of positive correlation was seen between relating to others and openness to new possibilities (r = . 843, p = 0.000), followed by the positively strong correlation between openness to new possibilities and personal strength (r = . 807, p = 0.000). On the other hand, the weakest degree of positive correlation among them was detected between the spiritual change and appreciation of life (r = . 682, p = 0.000).Table 12bPearson Correlation between the subdivisions of the IESR scale.Table 12bPTSD_INTRUSIVE THOUGHTPTSD_ AvoidancePTSD_ HyperarousalPTSD_ Intrusive thoughtPearson Correlation10.849a0.855aSig. (2-tailed)0.0000.000N294294294PTSD_ AvoidancePearson Correlation0.849a10.849aSig. (2-tailed)0.0000.000N294294294PTSD_ HyperarousalPearson Correlation0.855a0.849a1Sig. (2-tailed)0.0000.000N294294294aorrelation is significant at the 0.01 level (2-tailed).

Finally, regarding the relation between the degree of the trauma score in the Impact of Event Scale (IES-R) and the post-traumatic growth in the Post-Traumatic Growth Inventory (PTGI), a Pearson correlation coefficient in Table 12c indicated a moderately positive correlation between them (r = . 328, p = 0.000).Table 12cPearson Correlation between the subdivisions of the PTGI scale.Table 12cPTGI_RTOPTGI_NPPTGI_PSPTGI_SCPTGI_AOLPTGI_ Relating to othersPearson Correlation10.843a0.751a0.704a0.684aSig. (2-tailed)0.0000.0000.0000.000N294294294294294PTGI_ New PossibilitiesPearson Correlation0.843a10.807a0.727a0.770aSig. (2-tailed)0.0000.0000.0000.000N294294294294294PTGI_ Personal StrengthPearson Correlation0.751a0.807a10.787a0.798aSig. (2-tailed)0.0000.0000.0000.000N294294294294294PTGI_ Spiritual ChangePearson Correlation0.704a0.727a0.787a10.682aSig. (2-tailed)0.0000.0000.0000.000N294294294294294PTGI_ Appreciation of LifePearson Correlation0.684a0.770a0.798a0.682a1Sig. (2-tailed)0.0000.0000.0000.000N294294294294294aCorrelation is significant at the 0.01 level (2-tailed).

Discussion

4

This study aimed to measure the level of trauma and its effects on primary caregivers of children with Sickle cell disease in AlAhsa, Saudi Arabia, using the IESR and PTGI scales and their relationship to each other.

It included 294 participants, with mothers accounting for 54.4 % of the sample and fathers accounting for 44.9 % (Table 1a). Regarding recruitment, most responses (50.8 %) were gathered through phone interviews, while (49.2 %) were collected through a direct online invitation after a verifying call. Most caregivers had a university degree, were between the ages of 41 and 50, and had a family income ranging from 8000 to 12000 SR (Table 1a). Regarding the health aspect of the caregivers, most were not suffering from chronic diseases and were not using mental health services (Table 1a).

Using the IERS and PTGI scales, our study revealed that the caregivers experienced some level of stress related to the event, i.e., their child's diagnosis and situation. Also, many caregivers experienced some level of post-traumatic growth as a result of their trauma, such as a shift in their priorities. Furthermore, the trauma may have had a profound impact on their spiritual beliefs and practices. In terms of PTSD elements (intrusive thoughts, avoidance, and hyperarousal), the mean scores were 3.96, 3.55, and 3.19, respectively, with positive correlations between all of them (Table 11, Table 12bb). Furthermore, it is worth mentioning that the highest positive correlation was between hyperarousal and intrusive thoughts (r = . 855, p = 0.000) (Table 12b).

Regarding the relationship between IERS and PTGI, our research showed a moderately positive correlation (r = . 328, p = 0.000) (Table 12a). There are several studies discussing the effects of chronic diseases by their different phases (diagnosis, treatment, and late complications) on the traumatic experience of parents as caregivers for their children. For example, three studies have been conducted on parents of cancer survivor children showed that diagnosis and treatment of cancer can have traumatic effects on caregivers, which manifest in PTSD symptoms in the long run [[19], [20], [21]].

Furthermore, caregivers addressed intrusive thoughts and distress as reminders of the diagnosis and treatment of cancer [19]. These findings are consistent with our study regarding SCD. In terms of studies on SCD in children and caregivers, intrusive thoughts, which has the highest mean score in our study, have been shown to worsen the consequences of vasoccclusion, increasing children's feeling of pain and causing doctors to prescribe analgesics inadequately instead of providing psychological support [22], (Table 11).

Our study has found many factors affecting the IERS score. First, the gender of the caregiver had a significant effect on the total score of the IESR scale, with a higher average score (13.17) among mothers (Table 4). Such a finding is consistent with what has been found in the literature that mothers are more prone to Post-traumatic Stress Syndrome (PTSS) early in the disease and PTSD later [1]. In their study of caregivers of children with epilepsy, Carmassi et al. discovered that 13.3 % of mothers developed PTSD while only 4.5 % of fathers did. When the diagnosis threshold was lowered, 43.3 % of mothers had partial PTSD compared to 25 % of fathers [23]. These differences between mothers and fathers can be explained by the fact that males and females have different coping mechanisms; however, in other studies, lower household income and higher disease-related costs were found to be associated with a higher prevalence of PTSD among fathers [24].

Second, the IESR's average score was highest for the lowest income range (less than 5000 SR) (Table 5). This finding is consistent with many studies' findings that low income and high illness-related expenses are important contributors to caregivers' degree of distress [25]. Moreover, it was found that fathers were primarily affected by these factors [24].

Third, in terms of the effect of education level on IERS score, it is safe to assume that education is a protective factor since the mean scores for IESR were highest for those with less than secondary school education (Table 6). Moreover, a study conducted in Egypt on 96 caregivers found that higher professional status and education levels were negatively associated with PTSS prevalence [26].

Fourth, we discovered that parents of children with Sickle cell disease, who had higher rates of admission, had higher trauma scores (Table 10). There is no data on the rate of admissions and the prevalence of PTSD; however, many studies correlated the hospital's length of stay and PTSD. For example, in burn victim children and transplant candidates, the length of hospital stay was correlated with PTSS and PTSD in their caregivers [27]. The length of stay effect could be a confounder for many other findings in our data, such as the higher IESR scores among parents of children who underwent multiple surgeries or had multiple complications.

Finally, our findings suggest that the method of data collection can influence participants' levels of post-traumatic growth (PTG) and the trauma degree. When compared to phone calls, online participants reported significantly higher levels of PTG (P < 0.001) and trauma (P = 0.023) (Table 2). In light of the testimonies of the data collectors, these differences must be attributed to a variety of factors extending beyond the mere convenience and privacy associated with online questionnaires. They reported frequent instances of grief and tears during phone calls, along with repeated requests for clarifications regarding terms like "numb feelings.". Therefore, researchers in trauma-related research should exercise caution and seek a source to verify the accuracy of the collected data.

Despite the fact that we put every effort into coming up with reliable and generalizable data, our study has a few limitations. Firstly, although we tried to enrol participants from different canters, most of the caregivers were following the hematology clinic at the MCH hospital in Alahsa City. Secondly, and due to its nature, this is a cross-sectional study that is prone to a recall bias and a limited ability to deduce a temporal relationship between PTSD elements, PTGI elements, and sociodemographic factors. So, a follow-up study is recommended to confirm the temporal relationship. Finally, 294 participants were enough for most of the measured factors. However, the raw data showed promising important factors that were not statistically significant due to the lack of sufficient participation and institutional support for the research team.

However, to the best of our knowledge, no local similar studies have explored the degree of distress among caregivers of children with SCD. So, our study aimed to measure the effect of Sickle cell disease in children in AlAhsa, Saudi Arabia, on their caregivers in order to identify the most vulnerable group and provide a well-designed intervention to improve their quality of life.

Conclusion

5

In conclusion, similar to parents of children with cancer, caregivers of children with SCD experienced intrusive thoughts and distress. Several sociodemographic factors influenced the level of trauma experienced by caregivers. Mothers exhibited higher levels of trauma compared to fathers, possibly due to differences in coping mechanisms. Education level appeared to be a protective factor, with higher education levels associated with lower trauma scores. The study also revealed a correlation between the child's rate of hospital admissions and caregiver trauma scores. Longer hospital stays were associated with increased distress among caregivers, suggesting the need for support during hospitalization. While the study provides valuable insights, it has limitations, including a limited sample from a specific clinic and a cross-sectional design. Future research should consider longitudinal studies to establish temporal relationships.

CRediT authorship contribution statement

Ali Alsaad: Writing – review & editing, Supervision, Investigation, Conceptualization. Abdullah Alghanim: Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Conceptualization. Mohammed Aldawood: Writing – review & editing, Writing – original draft, Validation, Supervision, Project administration, Conceptualization. Ali Al Zaid: Writing – original draft, Investigation, Data curation. Hussain Aldehneen: Writing – original draft, Project administration, Investigation, Data curation. Rawan Aldrees: Writing – original draft, Data curation, Conceptualization. Ammar Alsalem: Writing – review & editing, Validation, Methodology, Investigation. Sami Albattat: Writing – review & editing, Resources, Funding acquisition, Data curation, Conceptualization. Abbas Al Mutair: Writing – review & editing, Supervision, Project administration, Methodology, Investigation, Formal analysis, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.