1. Background
University students are one of the most important and dynamic groups in any society, usually aged 18 to 24. During their time at university, they typically have new experiences (1). Adapting to this changing era is a topic of constant interest for educational research. Depression is a common psychiatric condition among Iranian university students and deserves more attention. Depression is a set of symptoms that lead to changes in a person's mood, thoughts, and activities, including feelings of sadness and loss of interest, coupled with changes in sleep patterns, food intake, energy levels, and motivation, which impair personal and social functioning (2). According to the World Health Organization, depression is a leading cause of disability worldwide (3). A study by Auerbach et al. suggests that common health problems among students in developed countries account for 10 - 12 percent, making it one of the most important reasons for university expulsion, failures, and dropouts (4).
Shneidman was the first to use the term "mental pain" to describe intolerable psychological distress. He states that mental pain is a response to unmet basic needs such as being loved, having control, supporting self-image, avoiding shame, and feeling secure. When individuals do not feel self-consent, they cannot survive any longer (5). When these needs are not met, a combination of negative emotions such as guilt, shame, failure, humiliation, sadness, heartache, disappointment, and anger occur (6). A study by Meerwijk and Weiss (6) showed positive associations between executive functioning, depression, frustration, mental pain, and suicide. The results also showed that depression, despair, and suicide were positively associated with mental pain. A forward multiple linear regression model showed that mental pain, depression, and despair predicted 46% of the variance in suicide motivation. Studies have shown that patients with depression exhibit more emotional suppression, such as pain suppression, due to maladaptive emotion regulation; hence these patients report more pain (7).
Reviews have shown that people with depression tend to use maladaptive strategies of emotion regulation, such as rumination and catastrophizing, leading to anxiety, aggression, and other psychological symptoms (8). Some authors describe depression as a disorder of emotion regulation, resulting from dysfunction in emotion regulation (9). According to these theories, the signs and symptoms of depression are the result of a person's inability to regulate their emotions consistently and appropriately (10). Emotion regulation problems in cases such as mood and anxiety disorders are so noticeable that they are defined primarily on the basis of negative emotions (11). Emotion regulation is a process through which individuals adjust their conscious or unconscious motives to respond to various environmental demands (12). Maladaptive emotion regulation strategies, such as avoidance, are thought to increase the risk of emotional problems and psychological harm, whereas adaptive emotion regulation strategies, such as problem-solving, act as protective factors (13).
In other words, there is growing evidence that self-compassion is linked to mental health and serves as an important antidote to stress. Studies have shown that self-compassion is associated with reduced stress and depression (14). Neff et al. define self-compassion as “tolerance and suffering related to one’s experiences, a sense of compassion and kindness toward oneself, an understanding and open-minded attitude toward incompetence and failure of one’s goals and destinies, knowing that experience is a part of human life” (15). In a meta-analysis by Muris and Petrocchi, it was concluded that measures of self-compassion (self-kindness, the common human experience, and mindfulness) were negatively associated with psychopathology. These results indicate that self-compassion plays a protective role (16). On the other hand, the negative aspects of self-compassion (self-blame, isolation, excessive identification) are positively associated with mental health problems. Studies also show that self-compassion is negatively associated with depression (17), irrational beliefs (18), suicidal ideation, rumination, and self-injury (19).
Patients with chronic pain report higher levels of depression, fear, and anxiety (20). Anxiety triggers unwanted thoughts and worries that occupy working memory (21). Anxiety can be described as the result of persistent tension experienced throughout one's life. It is an emotional and physiological response to internal threats (such as dysfunctional thoughts) that can be neutralized. Anxiety is associated with specific physical symptoms and serves as a warning sign of imminent danger, preparing the individual to deal with it (22). High levels of pain-related anxiety lead to the avoidance of activities thought to exacerbate pain, often resulting in poor physical condition, behavioral problems, and reduced social contact, ultimately creating a vicious cycle. Some researchers have shown that localized pain and muscle activity can induce responses to stress and anxiety, indicating that the body's response to chronic anxiety and pain is almost the same (23).
Typically, college admission is a very important moment in life for talented and active young people. Most students face challenges such as integrating into a larger educational environment, adapting to new social and cultural situations, economic problems, lack of interest in education, separation from family, changes in daily life, academic difficulties, and dealing with new people in the academic environment. These challenges are stressful and can affect the performance and efficiency of the students (24).
2. Objectives
To date, no studies have been conducted on variables such as psychological pain, cognitive emotion regulation strategies, and depression in Iranian students. There is a need for research on the consequences of depression in a non-clinical population because, due to the high prevalence of depression and a wide range of mental health symptoms among students, they experience negative emotions such as anxiety, self-blame, blaming others, catastrophizing, lack of self-compassion, self-reported depression, and mental pain, as well as physical complaints.
3. Methods
3.1. Participants and Procedure
This cross-sectional study was approved by the medical ethics committee of Ahvaz Jondishapur University of Medical Sciences (IR.AJUMS.MEDICINE.REC.1400.072). The sample size consisted of 300 Iranian university students, including 147 males (M = 22.52, SD = 2.95) and 153 females (M = 20.70, SD = 1.87), aged 18 - 35 (mean age = 21). Participants were selected using cluster sampling. First, five colleges were randomly selected from three groups: Medicine, paramedicine, and midwifery. Then, two classes were randomly selected from each department.
The mean age (M) of the entire sample was 21.59 (SD = 2.62), and participants had graduated from an academic degree program (M = 13.70 years, SD = 1.87). Inclusion criteria included being a student at a public university and providing informed consent to participate in the study. Exclusion criteria included taking any psychiatric drugs, not completing the questionnaire, or having any vision and motor problems that would make participation difficult.
Participants were first briefed on the study's purpose, and after obtaining written consent, questionnaires were distributed. The researchers were two psychology master's students. The Soper formula was used to determine the sample size. Based on the anticipated effect size (f2) of the regression model (0.15), the desired statistical power level (0.8), the number of predictors (4), and the significance level (0.05), the desired sample size was determined to be 84 (25). To increase external validity and generalizability, the sample size was increased to 300 participants. Inclusion criteria included being a student and completing all the questionnaires. The exclusion criterion included not completing one or more questions and/or random responding.
3.2. Measures
3.2.1. Demographic Data
The demographic form included personal information, such as age, gender, academic level, and marital status.
3.2.2. Beck Depression Inventory (BDI-II)
To measure participants' symptoms of depression, we used the 21-item self-report Beck Depression Inventory (BDI-II) (26). The internal consistency of the BDI ranges from 0.73 to 0.92, with a mean of 0.86 (27). The BDI has demonstrated high internal consistency, with alpha coefficients of 0.86 and 0.81 for psychiatric and non-psychiatric populations, respectively (27). In Iran, the BDI has shown significant test-retest reliability (r = 0.64) and good convergent validity with the GHQ-28 (n = 209, r = 0.80) (28).
3.2.3. Orbach and Mikulincer Mental Pain (OMMP)
We used a questionnaire developed by Orbach and Mikulincer to assess the severity of mental pain (29). This 44-item questionnaire was first examined in Brazil, and nine subscales were approved. Participants rated each statement using a 5-point Likert Scale (1 = strongly disagree, 2 = disagree, 3 = agree to some extent, 4 = agree, 5 = strongly agree). The nine subscales include irreversibility, loss of control, narcissistic wounds/worthlessness, emotional flooding, freezing, self-estrangement, confusion, social distancing, and emptiness. The lowest test-retest coefficient for the nine subscales was 0.79, and the highest was 0.94. Good convergent validity has been reported for this questionnaire, as all its subscales have shown a significant correlation with anxious and depressive cognitions (r’s ranging from 0.26 to 0.64 for depression and 0.27 to 0.50 for anxiety), although this correlation was not reported for the social distancing subscale. In the study by Karami et al., the Cronbach's alpha for this scale and its subscales ranged between 0.61 (lowest for freezing) and 0.96 (highest for total). Its convergent validity was reported as 0.43 (30). In the present study, its Cronbach’s alpha was 0.96.
3.2.4. Cognitive Emotion Regulation Questionnaire (CERQ)
To investigate cognitive emotion regulation strategies, we used a 36-item questionnaire that participants answered using a 5-point Likert Scale (1: never, 5: always). This scale examines people's strategies for dealing with unpleasant life situations and includes the following: Self-blame, acceptance, rumination, putting into perspective, positive refocus, refocus on planning, positive reappraisal, catastrophizing, and blaming others. Cronbach’s alpha coefficients for the subscales across various populations ranged between 0.68 and 0.86, indicating good internal consistency (31). A study with the general adult population yielded test-retest correlations for subscales ranging between 0.48 (refocus on planning) and 0.65 (other-blame) (31). Its reliability in Iran was calculated using Cronbach's alpha, with values for the subscales ranging from 0.64 to 0.82 (32). In this study, the Cronbach’s alpha for the scale was 0.94.
3.2.5. Self-Compassion Scale–Short Form (SCS-SF)
The SCS-SF includes 12 items measuring the same six components of self-compassion as the SCS-LF. This scale uses a five-point Likert Scale (0 = ‘Almost never’ to 5 = ‘Almost always’). Its test-retest reliability was 0.92, and its convergent validity was 0.97 (33). The reliability in Iran, as calculated by Cronbach’s alpha, was reported to be 0.84. Its divergent validity was -0.38 (34). In the present study, the scale’s Cronbach’s alpha was 0.84.
3.2.6. Beck Anxiety Inventory (BAI)
In this research, we used a reliable questionnaire to assess the anxiety of participants, applicable to both adults and adolescents (35). This 21-item tool, presented on a 4-point Likert Scale, has been studied in many countries and languages, including German, French, Chinese, Spanish, Persian, Nepali, Icelandic, and others, and has shown sufficient reliability. Raw scores range from 21 to 84. Investigations across different populations, including clinical and non-clinical samples, have demonstrated high internal consistency (0.91 for both clinical and non-clinical) and test-retest reliability (0.66 for clinical and 0.65 for non-clinical) (35).
3.3. Data Analysis
Data were analyzed using SPSS-25 software. In the descriptive statistics section, the standard deviation, mean, and Pearson correlation were reported. In the inferential statistics section, linear regression analysis was employed using the forward multiple linear regression method.
4. Results
Data screening was performed prior to data analysis to identify any violations of normality. The scatter plot showed that the linearity assumption is valid for the independent and dependent variables. Variance inflation factors (VIFs) and tolerance coefficients were used to examine the multicollinearity assumption. Since the VIFs for the independent variables (mental pain, cognitive emotion regulation, self-compassion, and anxiety) were less than 5 and none of the tolerance values were less than 0.1, there was no multicollinearity among predictive variables. The results of the Durbin-Watson test indicated that the errors were independent. The assumption of normality of the data was tested using the Skewness and Kurtosis test, which showed that the assumption of normality in terms of gender was properly observed (36) (Table 1). The scatter plot showed that the variance of the dependent variable was constant for all values of the independent variables. Boxplots were used to identify 18 outliers, which were excluded from further analysis. Therefore, the final sample size for regression analysis was 300. Means, standard deviations, and Pearson's r correlations were calculated for all variables (Table 1).
Table 1. Means, Standard Deviations, and Group Comparison Using Independent t-tests
| Variables | Male | Female | Total | Kolmogorov-Smirnov (P-Value) | |||
|---|---|---|---|---|---|---|---|
| Mean ± SD | Skewness (Kurtosis) | Mean ± SD | Skewness (Kurtosis) | Mean ± SD | t (P-Value) | ||
| Anxiety | 50.82 ± 13.28 | 0.134 (0.463) | 53.56 ± 8.97 | -0.144 (0.926) | 52.30 ± 11.23 | -2.33 (0.02) | 0.177 (0.204) |
| Depression | 30.99 ± 9.57 | 0.839 (-0.177) | 30.96 ± 9.68 | 0.908 (-0.111) | 30.98 ± 9.61 | 0.02 (0.098) | 0.116 (0.200) |
| Maladaptive cognitive emotion regulation strategies | 41.56 ± 10.56 | -0.556 (-0.200) | 45.56 ± 9 | - 0.473 (0.917) | 43.60 ± 9.98 | -3.53 (<0.001) | 0.147 (0.098) |
| Adaptive cognitive emotion regulation strategies | 60.46 ± 18.96 | -0.156 (-0.632) | 68.28 ± 12.73 | -0.968 (0.350) | 64.45 ± 16.53 | -4.206 (< 0.001) | 0.125 (0.200) |
| Mental pain | 171.22 ± 32.09 | -0.918 (0.384) | 174.77 ± 29.34 | - 0.997 (0.315) | 173.03 ± 30.72 | - 1.021 (0.31) | 0.144 (0.115) |
| Positive self-compassion | 19.72 ± 5.05 | -0.064 (-0.208) | 19.78 ± 4.20 | -0.040 (0.519) | 19.75 ± 4.63 | -0.105 (0.916) | 0.148 (0.093) |
| Negative self-compassion | 16.56 ± 4.85 | 0.438 (-0.069) | 17.70 ± 4.32 | 0.498 (-0.036) | 17.14 ± 4.62 | - 2.150 (0.033) | 0.139 (0.146) |
Table 2 shows that the majority of participants were 26 - 29 years old, comprising 31% of the sample. In terms of gender, there were more females than males, accounting for 51% of the sample. Regarding marital status, the majority of participants were married. Additionally, most participants had graduated with a Bachelor's degree, making up 44% of the sample. The mean and standard deviation (SD) with the assumption of normality are given in Table 1.
Table 2.Demographic Characteristics of the Sample
| Demographic Variables | No. (%) |
| Age | |
| 18 - 21 | 50 (17) |
| 22 - 25 | 65 (22) |
| 26 - 29 | 81 (27) |
| 30 - 33 | 57 (19) |
| 34 and Higher | 47 (15) |
| Gender | |
| Male | 147 (49) |
| Female | 153 (51) |
| Marital status | |
| Married | 164 (54) |
| Single | 101 (33) |
| Widowed | 35 (13) |
| Education level | |
| Bachelor’s | 132 (44) |
| MSc | 93 (31) |
| PhD | 75 (25) |
As seen in Table 1, the mean (M) and standard deviation (SD) of the study variables are provided. Independent t-test results showed differences between male and female students in the components of anxiety, maladaptive cognitive emotion regulation strategies, adaptive cognitive emotion regulation strategies, and negative self-compassion. The observed skewness and kurtosis values for the variables in each group are within the range of (-2, 2), indicating that the variables are normal in terms of deviation and elongation and their distribution is symmetrical. Additionally, the results of the Kolmogorov-Smirnov test for all variables indicate that the assumption of normality is met. The summary of the forward multiple linear regression model is presented in Table 3.
Table 3.Summary of Forward Multiple Linear Regression Model Results on the Total Scores of Variables
| Variables | R | ΔR2 | Adjusted R | R Change | Std | F | P | DW |
|---|---|---|---|---|---|---|---|---|
| Mental pain | 0.683 | 0.467 | 0.465 | 0.467 | 7.035 | 260.675 | < 0.001 | 1.768 |
| Anxiety | 0.725 | 0.525 | 0.522 | 0.059 | 6.647 | 36.824 | < 0.001 | |
| Negative self-compassion | 0.731 | 0.532 | 0.530 | 0.010 | 6.591 | 6.074 | < 0.001 | |
| Positive self-compassion | 0.738 | 0.545 | 0.539 | 0.010 | 6.529 | 6.567 | < 0.001 | |
| Maladaptive cognitive emotion regulation strategies | 0.745 | 0.555 | 0.547 | 0.010 | 6.469 | 6.560 | < 0.001 | |
| Adaptive cognitive emotion regulation strategies | 0.751 | 0.564 | 0.555 | 0.009 | 6.417 | 5.735 | < 0.001 |
Table 3 shows a summary of the results. The analysis of variance for the same model also indicated significant overall model fit (ΔR2 = 0.56, P < 0.001). The Durbin-Watson test result of 1.768 suggests the independence of variables from each other.
As shown in Table 3, mental pain, cognitive emotion regulation, self-compassion, and anxiety accounted for 56% of the variance in depression. Mental pain level was the most significant predictor, explaining 46% of the variance in the depression score (β = -0.436, R2 change = 0.467). Anxiety (β = 0.211, R2 change = 0.059) and negative self-compassion (β = 0.082, R2 change = 0.010) were the next important predictors, together explaining 9% of the variance in the depression score. Positive self-compassion, maladaptive cognitive emotion regulation strategies, and adaptive cognitive emotion regulation strategies explained an additional 4% of the variance in depression. Specifically, positive self-compassion (β = -0.078, R2 change = 0.010) and adaptive cognitive emotion regulation strategies (β = -0.135, R2 change = 0.009) were significantly associated with lower depression scores.
As shown in Table 4, the results of the forward linear regression method on the total scores of the research variables indicate that mental pain (β = 0.436), anxiety (β = 0.211), negative self-compassion (β = 0.082), positive self-compassion (β = -0.078), maladaptive cognitive emotion regulation strategies (β = 0.210), and adaptive cognitive emotion regulation strategies (β = -0.135) are the strongest predictors of depression. These findings demonstrate that mental pain and anxiety are stronger predictors than the other variables. Table 5 provides a summary of the standard coefficients of each subscale of the research in relation to depression.
Table 4.The Results of Forward Linear Regression Method for the Relationship Between Total Score of Independent Variables and Depression
| Variables | B | SE | Β | t | P | Tolerance | VIF |
|---|---|---|---|---|---|---|---|
| Mental pain | 0.136 | 0.016 | 0.436 | 8.554 | < 0.001 | 0.575 | 1.740 |
| Anxiety | 0.168 | 0.035 | 0.211 | 4.784 | 0.002 | 0.762 | 1.312 |
| Negative self-compassion | 0.171 | 0.090 | 0.082 | 1.895 | 0.041 | 0.791 | 1.264 |
| Positive self-compassion | -0.163 | 0.096 | -0.078 | -1.703 | 0.042 | 0.703 | 1.423 |
| Maladaptive cognitive emotion regulation strategies | 0.203 | 0.058 | 0.210 | 3.517 | 0.002 | 0.416 | 2.403 |
| Adaptive cognitive emotion regulation strategies | -0.078 | 0.033 | -0.135 | -2.395 | 0.031 | 0.471 | 2.125 |
Table 5.The Results of Forward Linear Regression Method for the Relationship Between Subscales of Independent Variables and Depression
| Variables | B | SE | β | t | P | Tolerance | VIF | (DW) |
|---|---|---|---|---|---|---|---|---|
| Emptiness | 0.563 | 0.096 | 0.376 | 5.858 | < 0.001 | 0.205 | 3.343 | 1.94 |
| Other blaming | 0.460 | 0.114 | 0.164 | 4.054 | 0.024 | 0.749 | 1.334 | |
| Anxiety | 0.169 | 0.033 | 0.217 | 5.076 | 0.002 | 0.676 | 1.479 | |
| Positive refocus | - 0.388 | 0.099 | - 0.161 | - 3.930 | 0.025 | 0.729 | 1.371 | |
| Irreversibility | 0.326 | 0.094 | 0.194 | 3.462 | 0.003 | 0.390 | 2.561 | |
| Mindfulness | - 1.147 | 0.251 | - 0.240 | - 4.570 | < 0.001 | 0.445 | 2.247 | |
| Catastrophizing | 0.311 | 0.124 | 0.113 | 2.504 | 0.037 | 0.605 | 1.652 | |
| Self-compassion | - 0.294 | 0.082 | - 0.211 | 3.561 | 0.002 | 0.352 | 2.843 | |
| Isolation | 0.592 | 0.233 | 0.133 | 2.654 | 0.031 | 0.490 | 2.041 | |
| Social distancing/self-estrangement | 0.217 | 0.104 | 0.121 | 2.086 | 0.036 | 0.366 | 2.730 |
As shown in Table 5, the results of the forward multiple linear regression model on the subscales of mental pain, anxiety, self-compassion, and emotion regulation strategies indicate that emptiness and meaninglessness (β = 0.376, P < 0.001), other blame (β = 0.164, P = 0.024), anxiety (β = 0.217, P = 0.002), positive refocus (β = -0.161, P = 0.025), irreversibility (β = 0.194, P = 0.003), social distancing/self-estrangement (β = 0.121, P = 0.036), mindfulness (β = -0.240, P < 0.001), and isolation (β = 0.133, P = 0.031) are the strongest predictors of depression.
5. Discussion
The purpose of this study is to understand the impact of major depression in a non-clinical sample, focusing on the roles of mental pain, cognitive emotion regulation strategies, self-compassion, and anxiety. The results of the Pearson correlation coefficient showed a positive and significant correlation between mental pain and depression, consistent with previous studies (37-39).
Describing the results, we can say that individuals with high mental pain often act in a hostile, demanding, and critical manner towards themselves (40). They tend to reject their own thoughts, impulses, actions, and values, which can trigger the development of depression or exacerbate its symptoms. When faced with difficult situations, people experiencing severe mental pain usually feel isolated, ashamed of their flaws and feelings, and often try to hide their true selves. They may feel that they are the only ones suffering from incompetence and failure (41). As a result, they are more likely to suffer from depression, despair, and lower psychological pain tolerance. Mental pain is a significant source of their self-judgment, which in turn contributes to their inner suffering and distress.
On the other hand, the results showed a significant negative association between adaptive emotion regulation strategies and depression, and a significant positive association between maladaptive emotion regulation strategies and depression. These results are consistent with previous studies (42-44). People who find their emotions unbearable or cannot regulate negative emotions appropriately often experience more depression and psychological distress. In other words, those who use maladaptive strategies such as self-blame tend to have more negative feelings and thoughts related to events, leading to increased tension and depression (31).
The Pearson correlation coefficient also showed a significant negative correlation between the positive components of self-compassion and depression, and a significant positive correlation between the negative components of self-compassion and depression. These findings are consistent with previous studies (16, 17, 45). Mindfulness, related to self-compassion, helps individuals avoid forming pessimistic thoughts and mental ruminations (46). Since rumination is a significant component of depression and other negative emotional conditions, mindfulness and interventions that reduce rumination can decrease negative emotions and, consequently, depression.
Self-compassion also helps by normalizing negative events and recognizing that unpleasant experiences, suffering, and pain are common to humanity. This perspective helps individuals regulate their emotions and replace negative emotions with positive ones. High levels of self-compassion provide emotional resilience, protecting people from distressing events and depression. According to Leary et al., self-compassion plays a notable and supportive role in situations such as recalling past negative events, imagining negative events, and coping with negative emotions (47). Individuals with high self-compassion can accept their role in negative events, experience them fully, and understand their associated feelings. They are less likely to ruminate on negative events and face their mistakes with less negative emotion. At the core of depression is a distinct sense of loss of control, especially when confronted with challenges or potential threats. For these individuals, feelings of failure and weakness are symptoms of a perceived permanent inability to cope with inevitable negative events, accompanied by negative emotions (48, 49).
Healthy individuals tend to have more control over how they manage their lack of understanding and attribute these issues to temporary external or internal factors. In contrast, people with emotional disorders expect mistakes and failures when faced with threatening issues or challenges, indicating a chronic inability to cope with uncontrollable and unpredictable situations. This relates to their ability to react to negative emotions.
This study has several limitations that may affect the interpretation and generalization of the data. The equal numbers of boys and girls in the sample may have introduced some bias. Additionally, our data were obtained from a non-clinical population, so the results cannot be generalized to clinical populations. As a cross-sectional study, no causal correlations can be established. Furthermore, the use of self-reported questionnaires may have introduced bias due to social desirability, questionnaire length, and participants’ unconscious motivations. Consequently, the results may overestimate or underestimate the extent to which cognitive emotion regulation strategies are actually used. Future research should address questions about the correlation between mental pain, self-compassion, cognitive emotion regulation, symptoms of depression, and anxiety through other data sources such as interviews, judgments, or experimental studies. It is important to remember that no conclusions can be drawn about the direction of the effects. Future studies should use more balanced samples of boys and girls and replicate this research in a clinical sample that includes individuals with major depression and negative lifestyles.
