Cognitive emotion regulation strategies, empathy and compassion as predictors of anxiety and depressive symptoms in emerging adult university students

Ansiedad y Estrés, (2026), 32(2), 65-74
https://doi.org/10.5093/anyes2026a8
https://www.ansiedadyestres.es
Bibliography reference

Cognitive emotion regulation strategies, empathy and compassion as predictors of anxiety and depressive symptoms in emerging adult university students

INFO ARTICLE

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Received 2 February 2026
Accepted 7 June 2026

 

ABSTRACT

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Introduction: anxiety and depressive disorders are the most prevalent disorders worldwide. University emerging adults have higher rates of these disorders compared to the general population. This study aimed to examine the predictive role of cognitive emotional regulation strategies (CERS), empathy and compassion on anxiety and depressive symptoms in this population. Methods: a cross-sectional study was conducted with 362 university emerging adults. Participants completed self-report measures for anxiety and depressive symptoms, as well as for CERS, empathy, and compassion. Pearson correlations and hierarchical multiple linear regressions were used to study the relationship between variables and identify significant predictors of anxiety and depressive symptoms. Results: Higher levels of Self-blame, Catastrophising and Personal Distress predicted greater symptoms of anxiety and depression. Rumination was an additional specific predictor of higher levels of anxiety. Higher Planning predicted lower levels of both symptoms. Compassion was not a significant predictor in the regression models. Discussion: the findings highlight the significant contribution of specific maladaptive CERS strategies (Self-blame, Catastrophising, Rumination) and Personal Distress (empathy) as risk factors for internalising symptoms in emerging university adults, while Positive Refocusing acts as a protective factor. The results underline the importance of addressing specific CERS and the management of Personal Distress in psychological interventions for this population.

 

KEYWORDS

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anxiety
depression
cognitive emotion regulation strategies
empathy
compassion

Ansiedad y Estrés, (2026), 32(2), 65-74
https://doi.org/10.5093/anyes2026a8
https://www.ansiedadyestres.es
Bibliography reference

RESUMEN

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Introducción: Los trastornos de ansiedad y depresión son los más prevalentes a nivel mundial. Los adultos emergentes universitarios presentan tasas más elevadas de estos trastornos en comparación con la población general. El objetivo de este estudio fue examinar el papel predictivo de las estrategias de regulación cognitivo-emocional (CERS), la empatía y la compasión sobre los síntomas de ansiedad y depresión en esta población. Métodos: se llevó a cabo un estudio transversal con 362 jóvenes universitarios. Los participantes completaron cuestionarios de autoinforme sobre los síntomas de ansiedad y depresión, así como sobre las CERS, la empatía y la compasión. Se utilizaron correlaciones de Pearson y regresiones lineales múltiples jerárquicas para estudiar la relación entre las variables e identificar predictores significativos de los síntomas de ansiedad y depresión. Resultados: niveles más elevados de autoculpa, catastrofismo y angustia personal predijeron mayores síntomas de ansiedad y depresión. La rumiación fue un predictor específico adicional de niveles más elevados de ansiedad. Un mayor nivel de planificación predijo niveles más bajos de ambos síntomas. La compasión no fue un predictor significativo en los modelos de regresión. Discusión: los resultados ponen de relieve la contribución de ciertas CERS específicas y desadaptativas (autoculpa, catastrofismo, rumiación) y de la angustia personal (empatía) como factores de riesgo para los síntomas internalizantes en jóvenes universitarios, mientras que el reenfoque positivo actúa como factor protector. Los resultados destacan la importancia de abordar estas CERS específicas y la gestión del malestar personal en las intervenciones psicológicas dirigidas a esta población.

 

PALABRAS CLAVE

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Ansiedad
Depresión
Estrategias cognitivas de regulación emocional
Empatía
Compasión
 

Introduction

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Anxiety and depressive disorders affect millions of people worldwide, negatively impacting their quality of life and functioning (World Health Organization, 2022). General population prevalence estimates are around 4.0% for anxiety disorders and 3.8% for depressive disorders (GBD, 2022). However, within this overall picture, epidemiological studies have indicated that the emerging adult college student population has significantly higher prevalence rates of these disorders than the general population. According to the World Mental Health International College Student initiative, which surveyed students across several countries, approximately one-third (31-35%) of university students meet the diagnostic criteria for at least one mental disorder in the past 12 months, with anxiety and depressive disorders being the most prevalent (Auerbach et al., 2018; Racine et al., 2021). Furthermore, emerging adulthood could represent a critical window of vulnerability. A recent large-scale global meta-analysis indicated that while the peak age of onset for mental disorders is 14.5 years, 62.5% of all lifetime mental disorders emerge before the age of 25 (Solmi et al., 2022). This evidence places the university population at the core of the risk period for the consolidation of clinical symptoms.

This high prevalence coincides with a critical life transition stage, marked by a confluence of specific opportunities and stressors, such as high academic demands, increasing autonomy, reconfiguration of social networks, and economic and career pressures (Jankowiak et al., 2025; McCormick et al., 2024). In this complex scenario, it is crucial to investigate how individual resources operate to facilitate adaptation or, by contrast, increase vulnerability to psychopathology. Among these resources, cognitive emotional regulation strategies (CERS), empathy and compassion have received special interest from the scientific community (Iannattone et al., 2024; Kraft et al., 2023; Mu et al., 2025; Neff, 2023; Nguyen et al., 2025).

Emotional regulation refers to the processes and strategies by which individuals influence what emotions they have, when they have them, and how they experience and express them (Gross, 1998). CERS are commonly grouped into adaptive (e.g., Positive Reinterpretation, Planning or Acceptance) and maladaptive (e.g., Rumination, Catastrophizing or Self-blame) (Aldao et al., 2010). Furthermore, research has increasingly identified CERS as transdiagnostic factors, suggesting that the inability to switch flexibly from maladaptive to adaptive strategies is a central mechanism underlying the persistence of anxiety and depression symptoms (Sloan et al., 2017). Several studies have shown that the predominant use of maladaptive strategies is associated with higher levels of psychopathology (such as anxiety or depression), whereas adaptive strategies are generally associated with better mental health and well-being (Esteller Collado et al., 2023; Esteller-Collado et al., 2025; Garnefski & Kraaij, 2018; Muñoz-Navarro et al., 2022). In the university setting, recent evidence suggests that maladaptive strategies –in particular rumination, suppression and catastrophising– are not only very common, but also act as key mechanisms that maintain high levels of anxiety and depression among students (Moreno et al., 2024). Understanding which specific strategies differentially predict anxiety and depression in emerging adults university students could offer more precise therapeutic targets for psychological intervention in this population.

In parallel, interpersonal socioemotional skills such as empathy and compassion have also been found to be equally critical in this life period (Carrard et al., 2022; Gambin & Sharp, 2018; Jankowiak et al., 2025; Mu et al., 2025; Neff, 2023; Singer & Klimecki, 2014). Empathy, defined as a multidimensional response to others’ states (Davis, 1983), encompasses both cognitive (Perspective Taking and Fantasy) and affective (Empathic Concern and Personal Distress) domains. Its relationship to psychopathology is notably complex. While Empathic Concern is traditionally associated with prosociality and positive social cognition (Israelashvili et al., 2020), recent evidence suggests it may act as a double-edged sword (Wang et al., 2025). Specifically, high levels of empathic concern, if not coupled with adequate emotional regulatory resources, may lead to empathic over-identification and emotional exhaustion, potentially increasing vulnerability to internalizing symptoms. In contrast, Personal Distress (feeling overwhelmed by another’s negative emotions) has been more robustly and consistently associated with higher levels of anxiety and depression (Thoma et al., 2011). This association suggests that people experiencing high levels of personal distress may lack the self-regulatory controls needed to distinguish between their own emotions and those of others, a vulnerability that has consistently been linked to heightened emotional arousal and internalising symptoms (Fabi et al., 2019).

On the other hand, compassion –understood as sensitivity to one’s own and others’ suffering coupled with the motivation to alleviate it (Goetz et al., 2010; Strauss et al., 2016)– is postulated as a protective factor for mental health. Unlike the Personal Distress of empathy, compassion involves an action-oriented benevolent response that facilitates emotional resilience by down-regulating the physiological threat system and fostering a sense of safety (Singer & Klimecki, 2014). Compassion is a multidimensional construct comprising facets such as Kindness, Common Humanity, Mindfulness and Indifference. Consistently, research suggests that higher levels of the positive facets of compassion (Kindness, Common Humanity, Mindfulness) and lower levels of Indifference are associated with lower internalising symptomatology and greater well-being, possibly acting as a buffer against adversity and self-criticism (Kirby et al., 2017; López et al., 2018; Petrocchi et al., 2024; Pommier et al., 2020). In the university context, self-compassion has emerged as a key resource, as the ability to treat oneself with kindness during times of academic failure or stress acts as a critical buffer against pervasive self-criticism and ruminative patterns (Lee & Lee, 2022; Poots & Cassidy, 2020).

Despite established individual links between these constructs and mental health (Carrard et al., 2022; Kotera et al., 2021; Li et al., 2024; Petrocchi et al., 2024), integrative research examining their combined and differential predictive power remains scarce. While CERS represent internal cognitive mechanisms of distress management, empathy and compassion reflect the interpersonal dimensions of emotional processing. In the university context, a period defined by significant social reconfiguration, internal regulation and interpersonal sensitivity likely operate in tandem to determine psychological outcomes (Kayani et al., 2022). However, most studies examine these variables in isolation, leaving it unclear how they uniquely contribute to anxiety versus depression, whose cognitive and interpersonal underpinnings may significantly differ.

Taking all this into account, the aim of this study was to examine the relation and predictive role of CERS, empathy and compassion on anxiety and depressive symptoms in a sample of emerging adult university students.

Methods

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Sample and procedure

The present study follows a cross-sectional observational design. Data were collected between September 2025 and January 2026, using online methodology through the Lime Survey platform. The average time to complete the evaluation was approximately 30 minutes. Due to the observational characteristics of the study, the only exclusion criteria was age below 18 years of age. This study was submitted for approval by the Research Ethics Committee of the University of Valencia, thus guaranteeing compliance with ethical standards and integrity in the conduct of the study.

At the end of the data collection period, a total of 561 people had started the survey, but only 416 had completed it successfully (74.1% of those contacted). Participants who did not complete all the required questionnaires were excluded. Of the remaining 416 participants, those who reported not being university students (12.9%) were excluded as they were not the subject of this study. The final sample consisted of 362 subjects.

Instruments

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Measures of symptoms

Patient Health Questionnaire-9 (PHQ-9): The PHQ-9 was used to assess depressive symptoms (Kroenke et al., 2001). This scale consists of nine items based on the DSM-IV criteria for Major Depressive Disorder. The response format is a 4-point Likert-type scale (0=never; 3=almost every day). The maximum scale score is 27 points. The Spanish and validated version was used (Muñoz-Navarro, Cano-Vindel, Medrano, et al., 2017). A higher score on this scale indicates more severe symptoms of depression. The reliability of this instrument in the sample was good (?=.82).

Generalized Anxiety Disorder-7 (GAD-7): The GAD-7 was used to assess symptoms of generalized anxiety (Spitzer et al., 2006). The questionnaire consists of 7 items with a 4-point Likert-type response scale (0=never; 3=almost every day). The patient is asked to respond according to the frequency with which he/she has experienced a range of symptoms in the last two weeks, and the maximum score is 21 points. The Spanish and validated version was used (Muñoz-Navarro, Cano-Vindel, Moriana, et al., 2017). A higher score on this scale indicates more severe symptoms of depression. The reliability of this instrument in the sample was good (?=.81).

Measure of cognitive emotion regulation strategies

Cognitive Emotion Regulation Questionnaire-Short (CERQ-Short): this is a shortened version of the original CERQ, validated by Garnefski & Kraaij (2006). The CERQ-Short is composed of 18 items corresponding to 9 subscales, 5 for adaptive CERS (Positive Refocusing, Acceptance, Positive Reappraisal, Planning, and Putting into Perspective) and 4 for maladaptive ones (Rumination, Catastrophising, Blaming others, and Self-blame). The response scale is Likert-type with 5 anchor points (1=almost never; 5=almost always) and the results allow to obtain partial scores for the 9 subscales. The reliability of the different dimensions was acceptable in the sample (?=.73-.86).

Measure of empathy

Interpersonal Reactivity Index (IRI): The IRI (Davis, 1983) is a 28-item self-report instrument that measures cognitive and emotional aspects of empathy. The items are rated on a Likert-type scale (0=does not describe me well; 4=describes me very well). The questionnaire consists of four cognitive subscales: Fantasy, Perspective Taking, Empathic Concern and Personal Distress. The reliability of the different dimensions was acceptable in the sample (?=.70-.81).

Measure of compassion

The Compassion Scale (CS): is a short scale of 16 items (Pommier et al., 2020), with a 5-point Likert scale (1=Strongly Disagree; 5=Strongly Agree). This scale is composed of 4 dimensions: Kindness, Humanity, Mindfulness and Indifference. The reliability of the different dimensions was variable depending on the dimension (?=.55-.69).

Statistical analysis

Descriptive statistics were used to describe the sample, both at the socio-demographic level and for the study variables: symptoms (anxiety and depression), CERS, empathy dimensions, and compassion dimensions. Normality assumptions were tested using the Kolmogorov-Smirnov test and visual inspection of histograms of the distribution.

To analyze the relationship of CERS, empathy, and compassion with anxiety and depression, Pearson correlation analyses, and a set of hierarchical multiple linear regression models were performed. Predictors were entered using the Enter method in two successive steps. In Step 1, socio-demographic variables (gender and age) were included to control for their effect. In Step 2, the psychological variables (dimensions of CERQ, IRI, and CS) that showed significant bivariate correlations were entered simultaneously. This hierarchical approach allows for determining the incremental variance (?R2) explained by psychological factors above and beyond socio-demographic characteristics. The dependent variables were symptoms of anxiety and depression. In addition, due to possible multicollinearity between the independent variables, tolerance values and variance inflation factor (VIF) were studied. Tolerance values lower than .10 and VIF values higher than 10 usually indicate multicollinearity problems. Furthermore, in order to avoid possible bias due to distributions that did not meet normality assumptions, bootstrapping techniques were used to calculate accelerated bias-corrected 95% confidence intervals (BCa) with 1000 replicates. Results obtained using these intervals are considered significant when the interval does not include the value 0.

Data management and analysis was carried out using the IBM SPSS statistical software program (v.29) and R (4.3.3).

Results

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Sample description

The sample consisted of 362 individuals (see Table 1). The participants were predominantly women (78.4%), with a mean age of 20.4 years (SD = 6.0), indicating a population comprising mainly emerging adults. In terms of psychological distress, the sample exhibited non-clinically significant levels (<10) of anxiety (M = 8.2, SD = 4.2) and depression (M = 8.9, SD = 5.1), which is consistent with a general population sample. Regarding the CERS, participants reported greater use of adaptive strategies, notably Acceptance and Planning, compared to lower scores on maladaptive strategies such as Catastrophising or Blaming others. Similarly, in the dimensions of empathy and compassion, a profile was observed with high scores in Empathic Concern and Kindness, contrasting with comparatively lower levels of Personal Distress and Indifference. Table 1 shows a complete descriptive summary of the sample.

-- Insert Table 1 about here --

To evaluate the distributional properties of the variables, Kolmogorov-Smirnov tests were performed. Results indicated that all primary variables significantly deviated from a normal distribution (p < .001). Consequently, bootstrapping techniques (1000 replicates) were employed in the regression models to ensure the accuracy and stability of the parameter estimates and their respective confidence intervals.

Correlation analyses

Firstly, bivariate correlations between anxiety and depression symptoms and CERS were examined (Figure 1). As expected, a strong positive correlation was found between anxiety and depression symptoms (r = .718, p < .001). With regard to CERS, both anxiety and depression showed a similar pattern of correlation. Significant positive correlations (p < .01) were observed with maladaptive strategies: catastrophising (r = .467 for anxiety; r = .492 for depression), self-blame (r = .346 for anxiety; r = .418 for depression), rumination (r = .271 for anxiety; r = .231 for depression) and blaming others (r = .164 for anxiety; r = .187 for depression). Conversely, significant negative associations (p < .01) were found with the adaptive strategies of planning (r = -.190 for anxiety; r = -.175 for depression) and positive refocusing (r = -.137 for anxiety; r = -.138 for depression). Figure 1 provides a detailed overview of these correlations, as well as the scatter of the data and its distribution.

-- Insert Figure 1 about here --

Secondly, bivariate correlations between symptoms and the dimensions of empathy and compassion were examined (Figure 2). Regarding to empathy, personal distress exhibited the most robust positive correlation with both anxiety (r = .387, p < .001) and depression (r = .355, p < .001). The fantasy dimension also showed significant positive correlations with both symptoms (r = .170, p < .01 and r = .200, p < .001, respectively). Perspective taking showed a weak positive association only with anxiety symptoms (r = .124, p < .05), while it was not significant for depression. Regarding compassion, the kindness dimension showed slight but significant positive correlations with anxiety (r = .174, p < .001) and depression (r = .116, p < .05). Other dimensions, such as empathic concern, humanity, or indifference, did not show significant bivariate associations with the clinical symptomatology analyzed. Figure 2 provides a detailed overview of these relationships, including data scatter and distributions.

-- Insert Figure 2 about here --

Hierarchical regression analyses

Firstly, a hierarchical regression analysis was conducted with anxiety symptoms (Table 2). In Step 1, the sociodemographic variables (age and gender) were included, explaining 7.5% of the total variance (F(2, 359) = 15.78, p < .001). In Step 2, upon adding the psychological study variables, the model significantly increased its explanatory power, reaching 34.5% of the total variance explained (F(12, 349) = 16.88, p < .001). Following the inclusion of all variables and the use of bootstrapping, the predictors showing significant positive associations were gender (? = .459, 95% CI [.81, 2.55]), indicating higher levels of anxiety in women, self-blame (? = .074, 95% CI [.09, .43]), rumination (? = .076, 95% CI [.04, .32]), catastrophising (? = .087, 95% CI [.11, .49]) and personal distress (? = .059, 95% CI [.11, .34]). Conversely, planning acted as a significant negative predictor (? = -.080, 95% CI [-0.38, -0.04]).

-- Insert Table 2 about here --

Secondly, a hierarchical regression analysis was conducted with depression symptoms (Table 3). In Step 1, the sociodemographic variables (age and gender) were included, explaining 3.4% of the total variance (F(2, 359) = 7.36, p < .001). In Step 2, the addition of the psychological study variables significantly increased the model explanatory power, reaching 34.1% of the total variance explained (F(11, 350) = 17.98, p < .001). Following the inclusion of all variables and the use of bootstrapping, the predictors showing significant positive associations were self-blame (? = .090, 95% CI [.27, .64]), catastrophize (? = .107, 95% CI [.23, .68]), and personal distress (? = .072, 95% CI [.05, .36]). Conversely, planning acted as a significant negative predictor (? = -.098, 95% CI [-.41, -.02]).

-- Insert Table 3 about here –

In both models, the collinearity diagnostics indicated the absence of multicollinearity issues, with tolerance values above 0.57 and VIF below 1.76.

Discussion

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The aim of this study was to examine the relationship and predictive role of CERS, empathy and compassion on anxiety and depressive symptoms in a sample of emerging adult university students. The results of the hierarchical regression analyses indicated that, after controlling for the effect of sociodemographic variables –where female gender was significantly associated with higher levels of anxiety, but not depression– the inclusion of psychological variables in the models significantly increased the explained variance for both symptoms, reaching 34.5% for anxiety and 34.1% for depression. Specifically, the CERS dimensions of self-blame and catastrophising, as well as the personal distress of empathy dimension, emerged as shared risk factors for both types of symptoms, whilst the rumination dimension did so only for anxiety. On the other hand, the only adaptive CERS subscale that acted as a protective factor shared between both symptoms was planning. It should be noted that, contrary to what might be expected based on previous literature, the other dimensions of empathy and compassion did not show significant predictive power for either of the two symptoms.

Regarding to CERS, the findings of study are consistent with the transdiagnostic framework, which highlights the crucial role of maladaptive strategies in the development and maintenance of internalizing symptoms (Esteller-Collado et al., 2025; Moreno et al., 2024; Muñoz-Navarro et al., 2022; Sloan et al., 2017). The identification of Self-blame and Catastrophising as consistent predictors of both symptoms in emerging adults in university students reinforces the idea that these maladaptive strategies may be especially relevant for this population. In an academic and life context often characterised by evaluation, social comparison and future uncertainty, the tendency to blame oneself excessively for negative events and to cognitively magnify them can generate a cycle of emotional distress that is difficult to break (Jankowiak et al., 2025; McCormick et al., 2024; Moreno et al., 2024). Furthermore, the specific role of Rumination as a predictor of anxiety, but not of depression, in our sample is consistent with models linking repetitive negative thinking to the maintenance of anxiety and worry about future performance (Watkins, 2008).

With regard to adaptative CERS, Planning emerged as the only consistent protective factor for both anxiety and depressive symptoms. This finding is particularly relevant in the university context, as Planning involves a task-oriented cognitive approach, thinking about the steps to take and how to best handle a negative event (Garnefski & Kraaij, 2018). For emerging adults facing complex academic demands and the transition to autonomy, the ability to cognitively organize a response to stressors may provide a sense of agency and control that buffers against psychological distress (Jankowiak et al., 2025). Recent evidence supports the notion that such active, problem-focused strategies are crucial during the transition to higher education, as they help students transform overwhelming academic pressure into specific, manageable goals, thereby reducing the emotional burden associated with uncertainty (Sacchi & Dan-Glauser, 2021). The non-significance of other more adaptive strategies such as Positive refocusing or Acceptance could be due to the fact that their variance is shared with other more powerful predictors or that their protective role is less relevant than the negative effect of maladaptive strategies, something that has also been previously pointed out in the literature (Aldao & Nolen-Hoeksema, 2012)

With respect to empathy, the most remarkable result is the confirmation of Personal Distress as a significant predictor of internalising symptomatology, both anxious and depressive. This finding is in line with numerous studies that differentiate the effects of different dimensions of the IRI, pointing to Personal Distress as the dimension most consistently associated with negative mental health outcomes (Fabi et al., 2019; Thoma et al., 2011). Personal Distress reflects an aversive and self-centred affective response to the suffering of others, which can become overwhelming and interfere with one’s own well-being and ability to offer effective help (Elam et al., 2025). In the university context, where students are exposed to the difficulties of their peers, a high reactivity to Personal Distress may exacerbate one’s own vulnerability to anxiety and depression.

Perhaps the most unexpected finding of the study was the lack of predictive power of compassion. This contrasts with previous literature, which postulates compassion as an important protective factor for mental health (Etemadi Shamsababdi & Dehshiri, 2024; Kirby et al., 2017; Petrocchi et al., 2024). However, several theoretical and methodological factors may explain this outcome. Firstly, from a psychometric perspective, certain dimensions of the CS in our sample showed low internal consistency. This type of measurement error can significantly reduce regression coefficients and increase the number of false negatives. This suggests that the CS may not have captured the construct with sufficient enough in this specific university cohort to compete with more robustly measured variables, such as the CERS. Secondly, conceptually, compassion may overlap significantly with other predictors in the model. Compassion, particularly its facets of Kindness and Common Humanity, works by desactivating the physiological threat system and reducing self-criticism (Gilbert, 2020; López et al., 2018; Neff, 2023; Singer & Klimecki, 2014). In our study, the CERS of self-blame and catastrophising were such powerful predictors of distress that they may have “absorbed” the variance typically associated with the Kindness dimension of compassion. Finally, it is important to note that the compassion scale used in this study primarily assesses compassion directed towards others. Whilst interpersonal compassion is generally positive, evidence suggests that self-compassion –the ability to direct that kindness towards oneself– is the specific component most strongly linked to reduced anxiety and depression (Ferrari et al., 2019; Neff, 2023). In university students, interpersonal compassion without a corresponding level of self-compassion may even lead to emotional exhaustion, a phenomenon that aligns with the double-edged nature of empathy mentioned earlier (Wang et al., 2025). Therefore, our results may suggest that, in the university setting, interpersonal compassion alone may not be sufficient to protect against psychopathology if it is not accompanied by robust internal regulation strategies and self-compassion.

Clinical implications

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From a clinical perspective, these results have relevant implications for prevention and psychological intervention in university students and emerging adults. They suggest that therapeutic efforts should focus primarily on modifying maladaptive CERS, such as Self-blame, Catastrophising and Rumination, and on actively promoting adaptive strategies such as Planning. Techniques from cognitive behavioural therapy have been shown to be effective in addressing these cognitive patterns (Aldao et al., 2014; Esteller-Collado et al., 2025; Muñoz-Navarro et al., 2022). In addition, the intervention should pay specific attention to the management of empathic Personal Distress. This does not imply reducing empathy, but helping individuals develop a more regulated and less overwhelming response to the suffering of others, perhaps by encouraging differentiation between one’s own emotional states and those of the other, or by cultivating compassion as a more sustainable alternative to empathic distress (Singer & Klimecki, 2014).

Limitations

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This study has several limitations that should be considered. First, its cross-sectional design precludes establishing causal relationships between predictors and symptoms. Secondly, there is a significant psychometric limitation regarding the measure of compassion used. In this study, some dimensions of the CS showed low internal consistency (? = .55), which is below the generally accepted minimum threshold of .70. These low reliability coefficients can introduce significant measurement errors into the models. In ordinary least squares (OLS) regression, such errors can drastically reduce the regression coefficients, increasing the probability of Type II errors (false negatives). Therefore, the lack of significant predictive power observed in the dimensions of compassion should be interpreted with caution, as it may reflect these methodological limitations rather than a genuine absence of a relationship between compassion and psychological distress. Thirdly, there is a significant gender imbalance in our sample (75.4% women), which limits the generalizability of the findings. Although gender and age were included as control variables in the first step of the hierarchical regression models to isolate their influence, the overrepresentation of women may have skewed the estimated predictive power of sociodemographic factors. Consequently, the results regarding the role of gender in anxiety and depression should be interpreted with caution, and future studies should seek cohorts with greater gender balance to confirm whether these socioemotional mechanisms operate similarly in both sexes. Finally, several relevant contextual and sociodemographic variables were not assessed, which could affect the generalisability of the results. Although the sample focused on emerging university students, differences between specific academic years, fields of study, and participants’ financial circumstances (e.g. employment versus scholarships) were not taken into account. Furthermore, other potential confounding factors or moderating variables, such as recent stressful life events, perceived social support or history of mental health issues, were not controlled for via an initial assessment. Future research should adopt a more stratified sampling approach and include comprehensive socioeconomic and clinical profiles to better contextualise how these socio-emotional resources operate in different academic and personal circumstances.

Future Lines and Conclusions

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The limitations noted above open opportunities for future research. Longitudinal studies would be essential to analyse the directionality of the relationships found and to examine how these factors predict the evolution of symptoms over time. To address the gender and contextual imbalance in the sample, future studies should employ stratified sampling that encompasses different academic disciplines and socio-economic contexts, whilst controlling for recent stressful life events and clinical history. Furthermore, given the psychometric limitations of the compassion measure used here, it would be interesting to replicate these findings using instruments with greater internal consistency and to directly compare the protective role of interpersonal compassion versus self-compassion.

In conclusion, this study highlights the role of CERS and personal distress as key predictors of anxiety and depression symptoms in emerging university students. Specifically, a tendency towards self-blame, catastrophising and experiencing personal distress in response to others’ suffering emerged as a strong shared risk factor, whilst planning acted as the primary protective strategy for both symptoms. It is worth noting that rumination was identified as an additional specific predictor of anxiety. Contrary to expectations, the dimensions of compassion did not provide additional predictive value. These findings enhance our understanding of psychological vulnerabilities at this stage of life and suggest that mental health interventions in university settings should prioritise the reduction of maladaptive cognitive patterns, whilst promoting active, goal-oriented regulatory strategies, such as planning.

Funding Sources

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This work has not received funding from any public or private entity. The authors declare that they have no conflicts of interest.

Data Availability Statement

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For confidentiality reasons, the data from this study are not public. They can be made available on reasonable request.

CRediT authorship contribution statement

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GEC: Investigation, Methodology, Formal analysis, Visualization, Writing – original draft, Writing – review & editing. MOC: Investigation, Writing-review & editing. JGC: Supervision, Investigation, Writing – review & editing. RMN: Supervision, Investigation, Writing – review & editing.

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