Psychosocial and Clinical Predictors of Depression, Anxiety, and Stress Among Breast Cancer Patients in Iraq: A Multivariate and Path Modeling Analysis
Conditions: Breast Cancer, Psychological Distress, Depression Anxiety Disorder, Stress (Psychology)
Sponsor: Hameed Adnan Hameed

Study Protocol and Statistical Analysis Plan 
 
Official Title of the Study: 
Psychosocial and Clinical Predictors of Depression, Anxiety, and Stress Among Breast 
Cancer Patients in Iraq: A Multivariate and Path Modeling Analysis 
 
Unique Protocol ID: BC-Psychology-2025 
 
NCT Number: (To be assigned by ClinicalTrials.gov) 
 
Date of Document: July 28, 2025 
 
Sponsor-Investigator: 
 Hameed Adnan Hameed 
(University of Al-Maarif College of Pharmacy) 
 
Collaborator: 
Anbar Cancer Center – Ministry of Health, Iraq 
 
 
 
 
 
 
 
 
 
 

Psychosocial and Clinical Predictors of Depression, Anxiety, and Stress 
Among Breast Cancer Patients in Iraq: A Multivariate and Path 
Modeling Analysis” 
1-Introduction 
Cancer is one of the most pressing global health concerns. It is stated that there will be four 
million new breast cancer cases in 2030. World Health Organization (1). Anticipate that 
cancer numbers will increase significantly, especially in low- and middle-income 
countries(2). Beyond the physical and financial burdens, cancer is now widely recognized 
for its profound psychological toll. Emotional distress, such as depression, anxiety, 
insomnia, and anger, has been identified as a 'silent comorbidity' that can impact treatment 
adherence, recovery outcomes, and overall quality of cancer patients. 
Breast cancer is the most commonly diagnosed cancer among women globally including 
the Middle East and Iraq. According to the Iraqi Ministry of Health (3). More than 5,000 
new breast cancer cases are diagnosed annually, representing over 21% of total new cancer 
diagnoses in the country(2,3). Unfortunately, due to poor access to screening programs, 
and limited public awareness, most patients are diagnosed at advanced stages, particularly 
in underserved regions such as Al-Anbar (4). These patients are at greater risk of 
experiencing severe psychological consequences due to uncertain prognosis, aggressive 
treatment protocols, and social isolation (5) 
Previous research in Al-Anbar has focused on breast cancer patients (4) Largely focused 
on pharmacological and economic variables, without exploring behavioral and emotional 
factors such as sleep quality, emotional regulation (e.g., anger), use of sedatives, or support 
systems. In the broader Middle Eastern context, recent literature from Jordan, Egypt, and 
Iran has emphasized the need for Integrated psychosocial evaluation in oncology practice, 
showing how untreated distress can Exacerbate the overall disease burden (6)(7)(8))(9,10) 
A recent study conducted across inpatient and outpatient oncology settings in Jordan 
reported that 23.4% of cancer patients exhibited depressive symptoms. In comparison, up 
to 37.6% showed signs of severe anxiety, particularly among inpatients and patients with 
advanced-stage disease. However, the antidepressant treatment was prescribed for only 

15.5% of patients with depression or anxiety (11). These findings highlight A major unmet 
need in clinical care and reinforce the importance of early screening and targeted 
psychosocial support in cancer patients.  
In Iraq, mental health services incorporation into oncology care remains substantially 
inadequate. Mental health professionals are scarce in most oncology centers, and 
psychological screening is not routinely performed during cancer diagnosis or follow-up. 
Cultural stigma surrounding mental illness may also contribute to the underreporting of 
emotional symptoms and poor help-seeking behavior. According to a 2023 WHO-EMRO 
report, less than 15% of patients in Iraq received psychological support, even though 
studies consistently demonstrate a high rate of undiagnosed mood disorders in this group 
of patients (12). 
The present study aims to examine the psychosocial, clinical, and economic correlations of 
depression, anxiety, and stress among breast cancer patients in Al-Anbar city. Applying a 
multidimensional analytic approach, including multivariate linear and logistic regression, 
ROC analysis, and path modeling. This study explains how individual, emotional, and 
treatment-related factors interact to shape mental health outcomes. The findings are 
intended to guide more culturally sensitive and systemically integrated psychological 
interventions for cancer patients in Iraq and the region. 
 
 
 
 
 
 
 

2-Materials and Methods 
2-1 Study design 
This is a cross-sectional observational study that was conducted between January and May 
2025 in Al-Anbar Oncology Centre, Al-Anbar, Iraq. 
2-2 Study population and sampling technique 
The study population consisted of all patients diagnosed with breast cancer who attended 
the Al-Anbar Oncology Centre in Al-Anbar, Iraq, between January 5th and May 30th, 
2025.. Patients diagnosed with breast cancer at any stage and who provided informed 
consent to participate were included in the study. 
2-3 Sample Size Calculation 
The sample size was calculated using the standard formula for cross-sectional studies, with 
the following parameters: a 95% confidence level, a 5% margin of error, and an expected 
prevalence of psychological distress of 50% to yield the largest possible sample size. Based 
on these assumptions, the minimum required sample size was estimated to be 384 
participants. To enhance the statistical power and compensate for potential non-response 
or incomplete data, a larger sample was targeted. Consequently, a total of 500 breast cancer 
patients were enrolled in the final analysis, exceeding the minimum requirement. 
2-4 Questionnaire tool and data extraction 
Patients’ data were collected from medical records (demographics data, medication use 
history, and clinical profile). Cost data was obtained from the finance department at the 
center. Financial data included all available direct medical costs, such as treatment and 
physician visits. Moreover, patients were contacted to estimate the indirect cost associated 
with breast cancer therapy. A validated assessment tool, the Generalized Anxiety Disorder 
7-item (GAD-7) and the Patient Health Questionnaire (PHQ-9) were used to assess anxiety 
and depression [Spitzer et al., 2006; Kroenke et al., 2001]. The patients were asked to 
determine the degree of applicability of each item (question) on a 4-point Likert scale. The 
participants' responses varied from 0 to 3, with 0 denoting "Not at all" and 3 denoting 
"Nearly every day." Nine elements comprise the PHQ-9 instrument. Items are scored on a 
scale of 0 to 3, resulting in a total score that ranges from 0 to 27. A total score of 0–4 
indicates minimal depression, 5–9 mild depression, 10–14 moderate depression, 15–19 
moderately severe depression, and 20–27 severe depression. Seven elements comprise the 

GAD-7 instrument. Items are scored on a scale of 0 to 3, resulting in a total score that 
ranges from 0 to 21. Mild anxiety is indicated by a total score of 5–9, moderate anxiety by 
10–14, and severe anxiety by 15–21.  
 
2-5 Ethical approval 
Ethical approval for this study was obtained from the Ministry of Health, Anbar Health 
Directorate, and the Al-Anbar Cancer Centre, Iraq (Approval No. 1060, dated January 28, 
2025). 
For any further inquiries, the ethical committee can be contacted via the official email: 
anbarcancercenter@gmail.com. 
The study was conducted by the ethical standards of the Declaration of Helsinki. 
2-6 Data Analysis 
Data was analyzed using IBM SPSS Statistics version 26. Descriptive statistics (mean, 
standard deviation, frequency, and percentage) were used to summarize demographic and 
clinical variables. The Kolmogorov-Smirnov test was applied to assess the normality of 
continuous variables, and due to non-normal distribution, non-parametric tests were used. 
 
Bivariate analyses included Spearman’s correlation coefficient to evaluate associations 
between psychological outcomes (depression, anxiety, stress) and continuous predictors 
such as sleep quality, cost, and number of children. The Kruskal-Wallis H test was 
employed 
to 
examine 
differences 
in 
distress 
levels 
across 
cancer 
stages. 
 
Categorical associations were evaluated using Pearson’s Chi-square test. Binary logistic 
regression analysis was conducted to identify predictors of severe anxiety. Additionally, 
multivariate linear regression models were constructed for each psychological outcome 
(PHQ-9, GAD-7, stress), and multicollinearity was assessed using the Variance Inflation 
Factor(VIF). 

 
Receiver Operating Characteristic (ROC) curve analysis was used to assess the predictive 
accuracy of stress scores for severe anxiety, with Area Under the Curve (AUC) interpreted 
based on conventional thresholds. Conceptual path modeling was used to explore potential 
indirect relationships between stress and anxiety, mediated by sleep disturbance and 
impaired daily performance. 
All tests were two-tailed, and a p-value of less than 0.05 was considered statistically 
significant. 
3 - Results 
A total of 500 breast cancer patients were included in the final analysis. Descriptive 
statistics revealed a high prevalence of psychological distress within the sample, with 
elevated scores in depression, anxiety, and stress domains. 
Spearman correlation analysis revealed strong positive associations between sleep 
difficulty and psychological outcomes: depression (r = 0.85), anxiety (r = 0.77), and stress 
(r = 0.85), all statistically significant at p < 0.001. Use of sedatives was also significantly 
correlated with elevated distress scores (r > 0.90 across models). 
Kruskal-Wallis tests demonstrated statistically significant differences in mean ranks of 
depression, anxiety, and stress across cancer stages (p < 0.01), with higher distress in 
patients with advanced-stage disease. 
Multivariate linear regression identified the following as significant predictors of 
psychological distress: 
- PHQ9_Total: β = 0.42, p < 0.001 
- Anger: β = 2.08, p < 0.001 
- Cancer Stage: β = 0.92, p = 0.0014 
Psychological support was not a significant predictor (p = 0.606). 
Binary logistic regression showed that PHQ9 and anger significantly predicted severe 
anxiety, with odds ratios of 1.32 and 1.27, respectively (p < 0.001). Stage of disease also 
emerged as a significant factor in anxiety prediction. 

Receiver Operating Characteristic (ROC) curve analysis yielded an Area Under the Curve 
(AUC) of 0.74 for stress in predicting severe anxiety, indicating a fair level of 
discriminative ability. 
Finally, conceptual path analysis demonstrated that the relationship between stress and 
anxiety was primarily indirect, mediated through sleep disturbance and daily performance 
impairment. The direct path from stress to anxiety was negligible (r = –0.01), suggesting a 
mediated mechanism of action. 
Table 1. Descriptive Statistics of Study Variables 
Variable 
N 
Minimum 
Maximum 
Mean 
SD 
Total Cost 
500 
80 
34785 
3721.69 
4456.79 
PHQ9_Total 
500 
1 
27 
17.99 
6.11 
GAD7_Total 
500 
1 
21 
12.79 
3.81 
Cancer Stage 
500 
0 
4 
2.52 
1.09 
Children 
500 
0 
5 
2.53 
1.63 
Metastatic 
500 
0 
1 
0.36 
0.48 
Stress Level 
500 
0 
4 
2.64 
0.79 
The descriptive characteristics of the study variables are presented in Table 1. 
Depression and anxiety scores were moderately high, while stress levels were also 
elevated. Treatment cost showed substantial variability across participants. 
 
Table 2. Spearman Correlation Matrix Among Study Variables 
Variable 
PHQ9_Total GAD7_Total 
Stress 
Level 
Sleep 
Difficulty 
Sleep 
Satisfaction 
Total 
Cost 

PHQ9_Total 
1.00 
0.79 
0.66 
0.85 
0.49 
-0.11 
GAD7_Total 
0.79 
1.00 
0.65 
0.77 
0.62 
-0.10 
Stress Level 
0.66 
0.65 
1.00 
0.85 
0.55 
-0.12 
Sleep 
Difficulty 
0.85 
0.77 
0.85 
1.00 
0.48 
-0.08 
Sleep 
Satisfaction 
0.49 
0.62 
0.55 
0.48 
1.00 
-0.09 
Total Cost 
-0.11 
-0.10 
-0.12 
-0.08 
-0.09 
1.00 
Spearman correlation coefficients between psychological outcomes and sleep-related 
variables are shown in Table 2. Strong positive correlations were observed between 
depression, anxiety, stress, and sleep difficulty. 
 
Table 3. Kruskal–Wallis Test for Differences Across Cancer Stages 
Variable 
Chi-square (H) 
df 
P-value 
Stress Level 
31.092 
3 
<0.001 
PHQ9_Total 
14.762 
3 
0.002 
GAD7_Total 
19.705 
3 
<0.001 
The Kruskal–Wallis test results (Table 3) indicate significant differences in depression, 
anxiety, and stress levels across cancer stages (P < 0.05). 
. 
Figure 1. Chi-square (H) Values for Stress, Depression, and Anxiety 

 
Figure 1 shows the Chi-square (H) values for stress, depression, and anxiety. Stress 
exhibited the highest value (H = 31.09), followed by anxiety (H = 19.71) and depression 
(H = 14.76), all indicating significant differences across groups (P < 0.05). 
 
Table 4. Multiple Regression Analysis of Factors Associated with Depression, Anxiety, 
and Stress among Patients 
Outcome 
Predictor 
B 
T 
P-value 
VIF 
R² 
Depression 
(PHQ-9) 
Use of 
Sedatives 
4.842 
10.817 
<0.001 
1.766 0.702 
 
Sleep 
Difficulty 
4.52 
11.221 
<0.001 
4.866 
 
 
Sleep 
Satisfaction 
0.364 
2.01 
0.045 
1.021 
 
 
Children 
0.075 
0.626 
0.532 
1.039 
 
 
Total Cost 
7.5E-5 
2.209 
0.028 
1.022 
 
31.092
14.762
19.705
Stress Level
PHQ9_Total
GAD7_Total

 
Metastatic 
-0.13 
-0.408 
0.684 
1.048 
 
Anxiety 
(GAD7) 
Use of 
Sedatives 
4.064 
12.807 
<0.001 
1.766 0.615 
 
Sleep-related 
Worry 
1.521 
6.193 
<0.001 
3.655 
 
 
Sleep 
Satisfaction 
0.539 
1.886 
0.060 
4.866 
 
 
Children 
0.205 
1.889 
0.060 
1.039 
 
 
Total Cost 
3.0E-5 
1.246 
0.213 
1.022 
 
 
Metastatic 
0.203 
0.896 
0.371 
1.048 
 
Stress 
Level 
Use of 
Sedatives 
1.856 
29.413 
<0.001 
1.766 
— 
 
Sleep-related 
Worry 
0.149 
3.048 
0.002 
3.655 
 
 
Children 
0.037 
1.705 
0.089 
1.039 
 
 
Metastatic 
0.084 
1.865 
0.063 
1.048 
 
 
Total Cost 
3.4E-6 
0.711 
0.477 
1.022 
 
 
The results of the multiple regression analysis are summarized in Table 4. Use of 
sedatives and sleep-related worry were significant predictors of stress, depression, and 
anxiety scores. 
Table 5: Binary Logistic Regression – Predicting Severe Anxiety 
Predictor 
Odds Ratio (OR) 
95% CI 
P-value 
Depression (PHQ-
9) 
1.32 
1.18 – 1.56 
<0.001 

Anger 
1.27 
1.11 – 1.49 
0.002 
Stress Level 
1.14 
1.03 – 1.35 
0.017 
Psychological 
Support 
0.54 
0.33 – 0.91 
0.021 
Cancer Stage  
0.61 
0.33 – 0.87 
0.049 
 
Binary logistic regression (Table 5) showed that depression, anger, and stress 
significantly increased the odds of severe anxiety, while psychological support and 
advanced cancer stage were protective. The corrected model (Table 6) confirmed these 
associations. 
Table 6. Logistic Regression Predicting Severe Anxiety (Corrected Model) 
Predictor 
Coef. (β) 
Std. Error 
z-value 
p-value 
95% CI 
(Lower – 
Upper) 
PHQ9_Total 
0.42 
0.06 
6.92 
<0.001 
0.30 – 0.53 
Anger 
2.08 
0.48 
4.36 
<0.001 
1.14 – 3.02 
Psych Support 
-0.18 
0.34 
-0.52 
0.606 
-0.84 – 0.49 
Cancer Stage  
0.92 
0.29 
3.20 
0.0014 
0.36 – 1.48 
 
This table presents the corrected logistic regression model for predicting severe 
anxiety. PHQ9_Total and anger were significant positive predictors, while 
psychological support did not show a significant protective effect in 
the adjusted model. 
 
Figure 2. ROC Curve for stress predicting severe anxiety. 
 

 
 
The ROC curve (Figure 2) illustrates the predictive value of stress scores for severe 
anxiety, with an AUC of 0.74 (p < 0.001), indicating fair discriminative accuracy. 
 
Figure 3. Conceptual Path Model illustrating stress–anxiety relationships. 
 

 
 
The conceptual path model illustrates the indirect relationship between stress and anxiety, 
mediated by sleep disturbance and impaired daily functioning, with β coefficients 
indicating the strength of associations. 
 
 
4- Discussion 
The present study provides a comprehensive psychosocial profile of breast cancer patients 
in Al-Anbar, Iraq, highlighting significant associations between psychological distress, 
sleep disturbance, disease stage, economic burden, and emotional regulation. The results 
of our study reveal that depression and anxiety levels were remarkably high among breast 
cancer patients, with strong correlations to sleep-related variables and the use of sedative 
medications. These findings are consistent with previous studies from Iraq and neighboring 
countries, which emphasize the underrecognized psychological morbidity among cancer 
patients (13). 

Specifically, the elevated stress levels observed in our study appear closely tied to poor 
sleep quality and increased reliance on sedatives. This pattern is consistent with findings 
from Iranian oncology research, where 66.8% of cancer patients reported poor sleep quality 
(PSQI > 5), strongly associated with symptoms of anxiety and depression (14) 
Similarly, (14) Demonstrated that more than one‑third of cancer patients experienced 
subjective sleep disturbances, with 6.1% relying on sedative medication. These findings 
highlight disrupted sleep as a key contributor to psychological distress in oncological care 
and support the growing understanding that impaired sleep quality may serve as a potential 
clinical indicator of emotional dysregulation in cancer care. 
However, other studies have reported conflicting results. For example, (15) found that 
while sleep disturbances were prevalent among cancer patients, they were not consistently 
associated with heightened anxiety or depression. Such discrepancies may be explained by 
differences in patient populations, cancer types, cultural factors, and methodological 
variations across studies. 
The results of the current study revealed that advanced cancer stage was significantly 
associated with increased levels of psychological distress, particularly anxiety and 
depression. After adjusting for stage coding, regression models confirmed that advanced 
cancer stage predicted elevated anxiety scores (β = 0.92, p = 0.001), which aligns with 
previous findings from oncology populations in the region(16). This association may 
reflect the psychological impact of disease severity, poor prognosis, increased treatment 
burden, and concerns about disease progression and its potential complications. 
Furthermore, Kruskal-Wallis analysis confirmed significant differences in mean ranks of 
depression, anxiety, and stress across cancer stages (H = 14.76 to 31.09, p < 0.01). These 
findings are supported by evidence from Iran and neighboring countries, where patients 
with stage III and IV breast cancer reported higher rates of emotional distress compared to 
the early stages of the disease (14). The increased psychological vulnerability in advanced 
stages underscores the need for stage-specific psychosocial interventions in cancer care 
protocols 

Interestingly, total treatment cost showed a weak but statistically significant inverse 
correlation with psychological distress variables (e.g., PHQ-9_Total: r = –0.11, p = 0.017). 
Although initially counterintuitive, this finding may reflect a perceived sense of security 
or access to higher-quality care among patients with greater financial capacity. Similar 
interpretations were reported in recent findings from Turkey, where patients with access to 
private sector services and higher financial resources exhibited lower levels of 
psychological distress despite elevated treatment costs, suggesting that financial ability 
may buffer emotional burden through enhanced control and perceived care quality (17). 
As for psychological support, logistic regression models from this study suggested a 
protective effect (OR = 0.54), though this was not statistically significant in the adjusted 
model (p = 0.606). The lack of significance may be attributed to limited availability or 
underutilization of structured psychological services in the region, a challenge frequently 
reported in Iraq and across low-resource Middle Eastern settings. (18,19). Nonetheless, 
the direction of effect emphasizes the urgent need to integrate psychosocial support into 
routine oncology care. 
Among all predictors examined, depression (PHQ9_Total) and anger emerged as the 
strongest independent predictors of severe anxiety in both logistic and linear regression 
models (β = 0.42 and 2.08, respectively, p < 0.001). These findings support prior research 
indicating that depressive symptomatology often precedes or co-occurs with anxiety in 
cancer patients, especially when emotional regulation is compromised (11) 
Although anger remains an underexplored emotional construct in oncology, its relevance 
is gaining traction. In Iraq, sociocultural norms that discourage emotional expression, 
combined with the psychological toll of cancer, may intensify internalized anger, 
contributing to emotional dysregulation. This perspective is supported by findings from the 
national report, which highlighted elevated psychological distress among cancer patients 
and emphasized the role of suppressed emotions in shaping anxiety and avoidance 
behaviors (20). 
These findings emphasize the significance of addressing emotional dysregulation, 
particularly in patients presenting with overlapping symptoms of depression and anxiety. 

This suggests that psychological screening tools should incorporate anger-related items to 
facilitate the early identification of high-risk cases. 
The conceptual path model derived from the dataset suggests that stress influences anxiety 
primarily through indirect mechanisms, notably sleep disturbance and impaired daily 
functioning. While the direct association between stress and anxiety was minimal (r = –
0.01), robust indirect effects were observed via sleep problems (r = 0.74) and functional 
impairment (r = 0.77). These findings are consistent with regional studies from Egypt and 
Oman, highlighting sleep disturbance and fatigue as key mediators of psychological 
distress in oncology patients. (Al-Habsi et al., 2021; Gabra & Hashem, 2021; Hendy et 
al., 2025). 
This structure reinforces theoretical frameworks such as the Transactional Model of Stress 
and Coping, where maladaptive emotional responses (e.g., stress) translate into clinical 
outcomes (e.g., anxiety) through sleep and functional capacity mediators. Similar models 
have been proposed in Jordanian studies (24),Though the present model uniquely 
incorporates performance and anger as variables of interest, adding depth to the 
psychosocial profile. 
The inclusion of psychological support and its weak inverse association with anxiety (r = 
–0.07) further suggests that strengthening emotional resources could buffer the transition 
from stress to anxiety. This model may therefore serve as a foundational structure for 
targeted interventions in Iraqi cancer care systems, particularly in resource-limited settings. 
5- Clinical Implications 
The findings of this study underscore the urgent need to integrate routine psychological 
screening and targeted psychosocial interventions into oncology care for breast cancer 
patients in Iraq. The strong associations between stress, sleep disturbances, sedative use, 
and emotional dysregulation highlight the importance of early detection and management 
of psychological distress to improve treatment adherence and quality of life. Implementing 
multidisciplinary care models that include mental health professionals, sleep management 
programs, and culturally tailored counseling may mitigate the adverse psychological 
impact observed in advanced-stage patients. These results also suggest the necessity of 

training healthcare providers to recognize and address hidden emotional symptoms, 
thereby promoting holistic cancer care in low-resource settings. 
 
 
 
6-Conclusion 
This study highlights the multifactorial nature of psychological distress among breast 
cancer patients in Al-Anbar, Iraq. Depression, anxiety, and stress were significantly linked 
to sleep disruption, sedative use, disease stage, and emotional dysregulation. Advanced 
cancer stage emerged as a key predictor of heightened anxiety and depression. These 
findings emphasize the need to integrate psychosocial assessment and targeted 
interventions into oncological care, particularly in low-resource settings, to mitigate 
psychological morbidity and improve quality of life in this population. 
 
 
 
 
 
 
 
 
 
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