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The power of emotion regulation: how managing sadness influences depression and anxiety?

BMC Psychology volume 13, Article number: 38 (2025) Cite this article

Abstract

Background

Emotions are a fundamental part of life and play a critical role in shaping individuals’ experiences Effectively regulating emotions in socially appropriate ways is essential for navigating life successfully. This study investigated the impact of seven sadness regulation strategies on depression and anxiety and examined the mediating role of ER in the relationship between sadness regulation and depression and anxiety.

Method

A cross-sectional design was employed with 350 participants (144 men, 206 women) aged 18 to 35.

Results

Regression analyses showed that sadness regulation strategies significantly predict both depression and anxiety. For depression, the model explained 18.6% of the variance (F (7,342) = 11.140, p < 0.001), with cognitive reappraisal, religious coping, and seeking support negatively associated, while rumination was positively associated. For anxiety, the model explained 19% of the variance (F(7,342) = 11.484, p < 0.001), with rumination and substance use linked to lower anxiety levels, while other strategies showed no significant associations. Mediation analyses highlighted emotion regulation critical role, with sadness regulation influencing depression indirectly through ER (β = -0.024, 95% CI [-0.040, -0.009]) and accounting for 3.6% of the variance. Sadness regulation also had a direct (β = -0.037, p < 0.001) and indirect effect on anxiety through emotion regulation, explaining 6.1% of the variance.

Conclusion

These findings underscore the importance of adaptive sadness and emotion regulation strategies in mitigating depression and anxiety, offering valuable insights for therapeutic interventions.

Peer Review reports

Background

Depression and anxiety are among the most prevalent mental health disorders globally, affecting millions of people worldwide. According to [1], more than 300 million people suffer from depression, while anxiety disorders impact approximately 284 million individuals worldwide [2]. Depression and anxiety are leading contributors to the global burden of psychological disorders and significantly impairing quality of life across psychological and physical domains [1, 3].

Emotions are a fundamental part of life and play a critical role in shaping individuals’ experiences [4, 5]. Effectively regulating emotions in socially appropriate ways is essential for navigating life successfully. Emotion regulation (ER) refers to the intrinsic and extrinsic processes and strategies individuals use to monitor, evaluate, and modify their emotional responses [6]. ER has been shown to enhance psychological and emotional functioning [7, 8], contributing to improved mental health [7], physical health [7, 9], and work performance [10]. However, ER can be challenging, as individuals often struggle to manage negative emotions such as anger, fear, and sadness throughout their development, from early childhood to adulthood [11].

The profound effect of negative emotions on individuals’ lives is well-documented [12]. Nevertheless, differences in emotion regulation highlight the need for further research into the psychological and behavioural factors influencing the effectiveness of adaptive strategies for reducing negative emotions [13, 14]. Notably, studies emphasize the importance of examining emotions individually, as each emotion has unique psychological consequences [4]. Understanding the characteristics and contextual factors of specific emotions can provide greater insight into whether particular ER strategies are helpful or harmful in regulating those emotions [13, 15, 16].

One negative emotion that warrants individual exploration is sadness. Sadness is a basic emotion that people experience frequently throughout their lives [17]. It occurs when people lose something that is personally or perceived to be valuable [18, 19]. Sadness is particularly important because of its strong correlation with anxiety and depression. understanding how individuals manage sadness can provide critical insights into the broader systems of emotion regulation and its effects on mental health [20]. Sadness regulation (SR), a component of emotion regulation [21], plays a crucial role in both internalizing and externalising psychopathologies [22, 23]. Research consistently demonstrates that deficits in ER and SR are predictive of the onset and persistence of anxiety and depression disorders [24,25,26].

Globally, depression and anxiety affect individuals of all ages and ethnic backgrounds [1, 3]. These two disorders are accompanied by the persistence of negative emotions, such as sadness along with difficulties in regulating these emotions [27]. Despite the growing body of research on emotion and sadness regulation, how specific strategies regulate sadness and, in turn, influence depression and anxiety remain unclear [28, 29]. While ER is linked to mental health outcomes, the distinct processes of sadness regulation and their unique contributions to mental health disorders have not been sufficiently investigated [30].

Naragon-Gainey, McMahon [31] identified ten common ER and SR strategies: (1) acceptance, (2) cognitive reappraisal, (3) rumination, (4) mindfulness, (5) behavioral and experiential avoidance, (6) avoidance, (7) expressive suppression, (8) distraction, (9) worry, and (10) problem-solving. The adoption and the effectiveness of these strategies depend on the context in which they are used. Habitual use of certain strategies can influence and sustain clinical depression and other emotional disorders. For instance, research highlights the link between depression and rumination, with rumination associated with longer durations of depressive episodes and a higher likelihood of recurrence [32,33,34]. In addition, individuals with heightened depressive symptoms are more likely to use expressive suppression and less likely to employ cognitive reappraisal [35, 36].

While various emotion regulation strategies, such as cognitive reappraisal and suppression, have been studied, there is limited understanding of their specific effect on sadness regulation and how these influence depression and anxiety [37]. Furthermore, the potential mediating role of overall emotion regulation in the relationship between sadness regulation and depression and anxiety has not been fully clarified. Addressing these gaps is essential for developing targeted interventions aimed at improving emotional well-being and reducing the burden of mental health disorders. Therefore, this study aimed to address the knowledge gap by investigating how sadness regulation strategies influence depression and anxiety, as well as testing the mediation role of emotion regulation on the relationship between sadness regulation and depression and anxiety.

Objectives

  1. 1.

    To investigate how different sadness regulation strategies predict depression and anxiety.

  2. 2.

    To examine the direct relationship between sadness regulation and depression and anxiety.

  3. 3.

    To test the mediation role of emotion regulation in the relationship between sadness regulation and depression and anxiety.

Hypotheses

  1. 1.

    Maladaptive sadness regulation strategies (e.g., suppression) will be positively correlated with depression and anxiety.

  2. 2.

    Adaptive sadness regulation strategies (e.g., cognitive reappraisal) will be a negatively associated with depression and anxiety.

  3. 3.

    Emotion regulation will mediate the relationship between sadness regulation and depression and anxiety.

By investigating these hypotheses, this study aimed to enhance the understanding of the sadness regulation strategies involved in mental health disorders and inform the development of targeted therapeutic approaches that more effectively address the regulation of sadness.

Method

Participants

This cross-cultural study was conducted in Yemen and involved students from different universities across the country. Universities were randomly selected from a comprehensive list to ensure to ensure board representation. At each university, participants were recruited using a random sampling method, drawing from the list of enrolled students. This approach aimed to generate a sample that was representative of the students’ population. The inclusion criteria were as follows: (1) participants had to be 18 years or older, (2) participate voluntarily with informed consent, and (3) provide complete responses to all questionnaires’ items. Individuals were excluded if (1) they were younger than 18 years old, or (2) had a diagnosed severe mental health condition. A total of 380 students were initially approached to participate in the study. During the screening process, 30 individuals were excluded: 10 participants for being under 18 years of age, and 10 due to incomplete survey responses or outliers. No participants were excluded for diagnosed severe mental health condition, as none reported such a diagnosis during screening. A total 10 questionnaires were not returned. The final sample included 350 participants, comprising 144 males and 206 females, with ages ranging from 18 to 35 years. Detailed demographic characteristics are presented in Table 1. This recruitment process ensured the inclusion of diverse and representative data while maintaining ethical and methodological rigor.

Table 1 Demographic characteristics for the samples
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Measures

Four main questionnaires were utilized in this study:

Adults’ Sadness Regulation Questionnaire (ASRS) [38]

The ASRS consists of 36 items across seven dimensions, assessing different sadness regulation strategies: religious coping, seeking social support, rumination, cognitive reappraisal, expressive suppression, substance use, and acceptance. Respondents rate each item on a Likert scale ranging from 1 (“Never do that”) to 7 (“Always do that”). The questionnaire has demonstrated good reliability, with Cronbach’s alpha values ranging from 0.66 to 0.89. In the current study, the Cronbach’s alpha was 0.80.

Beck Depression Inventory BDI-II [39]

The BDI-II is a widely used 21-item self-report scale that assesses the severity of depressive symptoms in adolescents and adults. Each item corresponds to a symptom of depression and is rated on a scale from 0 (symptom not present) to 3 (severe symptom). The total score ranges from 0 to 63, with higher scores indicating more severe depressive symptoms. The BDI-II has demonstrated high internal consistency, with Cronbach’s alpha coefficients ranging from 0.73 to 0.92, making it a reliable measure for both clinical and research purposes. The current study used a translated version of the BDI-II, which was translated and validated with a sample from Syria by [40]. In the current study, the Cronbach’s alpha was 0.87.

Manifest Anxiety Scale (MAS) [41]

The MAS is a psychological assessment tool widely used in both clinical and research settings to assess anxiety symptoms. It consists of 50 items designed to measure the level of manifest anxiety in individuals, focusing on aspects such as nervousness, worry, and somatic symptoms associated with anxiety. Respondents rate each item on a binary scale of “Yes” or “No”. The MAS has demonstrated strong test-retest reliability, with estimates ranging from 0.73 to 0.90. The current study utilised a translated version of the MAS, which had been previously translated and validated with a sample from Sudan by [42]. In this study, the Cronbach’s alpha was 0.71.

Emotion Regulation Questionnaire (ERQ) [43]

The ERQ is a self-report questionnaire designed to assess individual differences in the habitual use of two emotion regulation strategies: cognitive reappraisal and expressive suppression. It consists of 10 items, with participants responding on a seven-point Likert scale, ranging from “strongly disagree” (1) to “strongly agree” (7). The ERQ has demonstrated good reliability, with a Cronbach’s alpha value of 0.72. The current study utilised a translated version of the ERQ that was previously translated and validated with a sample from Egypt by [44]. In the current study, the Cronbach’s alpha was 0.71.

The low reliability values MAS and ERQ could be attributed to the fact that cross-cultural validations often show a variation in reliability scores compared to original samples. Cross-cultural studies usually show that instruments do not function equally across different populations [45].

Procedures

Ethical approval for data collection was granted by the Centre for Postgraduate Studies and Research at Sana’a University and the Universiti Malaya Research Ethics Committee (UMREC), with the reference number UM.TNC2/UMREC_2503. Data were collected using paper-based forms. Participants were informed that their participation was voluntary and that their data would be kept strictly confidential and used solely for research purposes. Before completing the questionnaires, participants were provided with an informed consent form through WhatsApp and email, which they were required to review and sign. After obtaining consent from all participants, the researchers distributed the questionnaire booklets. Lecturers assisted the researchers in facilitating the administration of the questionnaires to the participants during their classes. Each booklet included an instruction page, followed by sections for demographic data and the ASRS, BDI-II, MAS, and ERQ instruments. Completing the questionnaires took approximately 20-30 minutes. All questionnaires were administered in the Arabic language to ensure comprehension and accuracy.

Data analysis

The collected data were analysed using SPSS version 29. Descriptive statistics were utilised to analyse the demographic characteristics of the participants, identify outliers, and addressing missing values, providing a detailed overview of the sample’s composition. Multiple regression analysis was then performed to determine whether the use of sadness regulation strategies could predict levels of depression and anxiety. Additionally, mediation analysis was performed using the PROCESS macro for SPSS to explore both the direct and indirect effects of sadness regulation on depression and anxiety, with emotion regulation serving as a mediator. This approach enabled a more nuanced understanding of the relationships between these variables and the underlying mechanisms driving these associations.

Results

Demographic characteristics of participants

A total of 380 questionnaires were distributed to the sample, with 370 were returned, yielding a response rate of 97%. However, 10 cases were removed due to outliers and missing values, and 10 cases were excluded for not meeting the inclusion criteria, leaving 350 cases eligible for analysis.

Multiple regression analysis (ASRS strategies with depression)

Before conducting the multiple regression analysis, the assumptions of regression were tested. The result of the Durbin-Watson test was within the acceptable range of 1.5–2.5, demonstrating the independence of the residuals. The Cook’s distance for each observation was less than the required threshold of 1, indicating no outliers in the data set that could negatively affect the estimates of the coefficients. Additionally, no collinearity was found between the variables, as all the correlations were less than 0.70. Figure 1 shows the standardised predicted value against the standardised residuals, which was used to check that the variance of the residuals is constant.

Fig. 1
figure 1

Plot of standardised residuals against the predicted value

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Multiple linear regression was conducted to predict depression based on various sadness regulation strategies, including expressive suppression, substance use, rumination, religious coping, social support, acceptance, and cognitive reappraisal. The overall fit of the model was statistically significant, as indicated by the F-statistic (F(7,342) = 11.140, p < 0.001), suggesting that the model explains a significant portion of the variance in depression. The R-squared value of 0.186 further indicated that this model accounts for approximately 19% of the variance in depression, see Table 2.

Table 2 Model summary of sadness regulation strategies and Depression
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Additionally, Table 3 presents the coefficients and the results of the t-tests for the variables entered in the multiple regression. Most of the p-values were statistically significant and less than 0.05. The standardized coefficients indicated statistically significant negative relationships between religious coping, seeking emotional support, cognitive reappraisal, and depression. These results suggest that frequent engagement or use of adaptive strategies like religious coping, seeking emotional support, and cognitive reappraisal is linked with lower levels of depression, supporting the first hypothesis.

Table 3 Unstandardised and standardised coefficients of the variables in the multiple regression analysis
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On the other hand, rumination was positively and significantly associated with depression, (p < 0.05), indicating that individuals who ruminate more likely to experience depression, supporting the second hypothesis. Surprisingly, the correlations between substance use, expressive suppression, acceptance, and depression were not statistically significant, as the p-value was greater than 0.05. These non-significant findings could indicate that these strategies are less relevant to the depressive symptoms in the current sample or that their effects may depend on other unexamined factors such as frequency of use of strategies, context, or severity of sadness. Among the strategies that significantly correlated with depression, rumination had the highest coefficient, highlighting that rumination is a strong predictor of depression.

Multiple regression analysis (ASRS strategies with anxiety)

Multiple linear regression was conducted to predict anxiety based on sadness regulation strategies, including expressive suppression, substance use, rumination, religious coping, social support, acceptance, and cognitive reappraisal. The overall fit of the model was statistically significant, as indicated by the F-statistic (F(7,342) = 11.484, p < 0.001), indicating that the model explains a significant portion of the variance in anxiety. The R-squared value of 0.190 further highlighted that this model accounts for approximately 19% of the variance in anxiety, see Table 4.

Table 4 Model summary of sadness regulation strategies and anxiety
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Table 5 shows the coefficients and the results of the t-tests for the variables entered in the multiple regression. Some of the p-values were statistically significant and less than 0.05. The results showed that religious coping, seeking social support, expressive suppression, cognitive reappraisal, and acceptance did not significantly correlated with anxiety (P > 0.05), which does not support the first and the second hypotheses regarding anxiety. These results suggest that these regulation strategies did not have a significant impact on anxiety symptoms or that their effects are not strong enough to be detected in this sample, potentially due to cultural, contextual, as well as methodological factors, such as the appropriateness of the anxiety scale used. The selection of a measurement tool that better align with cultural and contextual characteristics of Yemeni participants might yield more accurate and meaningful results. Future research should explore these variables to enhance the validity of the findings.

Table 5 Unstandardised and standardised coefficients of the variables in the multiple regression analysis
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Interestingly, two strategies were negatively and significantly correlated with anxiety: rumination and substance use, as the p-values were less than 0.05. This result suggests that higher levels of substance use and rumination are associated with lower levels of anxiety. This contradictory finding for the substance use might reflect its temporary relief effect on anxiety, through it is maladaptive long-term.

Mediation analysis of sadness regulation on depression through emotion regulation

A mediation analysis was conducted to examine whether emotion regulation mediates the relationship between sadness regulation and depression. The indirect effect was tested using a bootstrapping estimation approach with 5,000 samples [46]. The analysis was performed using the PROCESS macro for SPSS (Version 4.2).

The results revealed a significant indirect effect of sadness regulation on depression through emotion regulation (β = −0.024, Boots = 0.008, 95% Botch [−0.040, −0.009]). This indicates that higher levels of sadness regulation are associated with lower levels of depression through their impact on emotion regulation. The direct effect of sadness regulation on depression was not significant (β = 0.027, SE = 0.021, t(347) = 1.305, p = 0.193), indicating that the relationship between sadness regulation and depression is fully mediated by emotion regulation.

The total effect of sadness regulation on depression was also not significant (β = 0.004, SE = 0.020, t(348) = 0.179, p = 0.858), implying no direct association between sadness regulation and depression when not accounting for the mediator. Overall, the mediation model explains 3.6% of the variance in depression, with emotion regulation acting as a significant mediator in the relationship between sadness regulation and depression (see Table 6; Fig. 2). These results suggest that emotion regulation fully mediates the relationship between sadness regulation and depression, underlining the importance of emotion regulation in reducing depression.

Table 6 Results of the mediating effect of emotion regulation on depression
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Fig. 2
figure 2

Standardised mediation effect of emotion regulation on depression

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Mediation analysis of sadness regulation on anxiety through emotion regulation

A mediation analysis was conducted to examine the effect of sadness regulation on anxiety through the mediator of emotion regulation. The results revealed a significant indirect effect of sadness regulation on anxiety through emotion regulation (β = 0.006, boots = 0.003, 95% botch [0.001, 0.011]). This suggests that higher levels of sadness regulation are associated with lower levels of anxiety through their effect on emotion regulation. The direct effect of sadness regulation on anxiety was also significant (β = −0.037, t(347) = −4.671, p < 0.001), indicating that sadness regulation has a direct negative association with anxiety.

The total effect of sadness regulation on anxiety was significant (β = −0.031, t(348) = −4.127, p < 0.001), highlighting a negative association between sadness regulation and anxiety (see Table 7; Fig. 3). The mediation model explains 6.1% of the variance in anxiety, with emotion regulation acting as a significant mediator in the relationship between sadness regulation and anxiety. These results suggest that emotion regulation partially mediates the relationship between sadness regulation and anxiety, underscoring the importance of emotion regulation in reducing anxiety. The direct effect suggests that sadness regulation independently reduces anxiety, while the indirect effect highlights the complementary role of emotion regulation in regulating anxiety. The relatively small effect size of the indirect pathway highlights that while emotion regulation plays an important role, other factors also contribute to anxiety reduction. These could include personality traits, external stressors, or other coping strategies not examined in this study.

Table 7 Results of the mediating effect of emotion regulation on anxiety
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Fig. 3
figure 3

Standardised mediation effect of emotion regulation on anxiety

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Discussion

This study aimed to examine the impact of sadness regulation strategies on depression and anxiety, with a particular focus on seven strategies—religious coping, seeking social support or emotional support, expressive suppression, substance use, rumination, acceptance, and cognitive reappraisal. Additionally, it investigated the mediating role of emotion regulation in those relationships.

The regression findings on the relationship between the sadness regulation strategies and depression and anxiety emphasise the significance of adaptive sadness regulation strategies, namely religious coping, social support, and cognitive reappraisal, in reducing depression. Religious coping showed a robust negative relationship with depression, aligning with literature suggesting that religious practices like prayer, Quran recitation, meditation, religious rituals, and finding meaning through faith can provide emotional comfort, promote resilience, and foster hope in individuals [47,48,49,50].

In Yemen, where Islam is deeply integrated into daily life, religious practices like prayer and Quran recitation, and communal rituals are widely viewed as effective strategies to regulate sadness and distress. These faith-based practices, embedded in cultural norms, offer comfort and resilience during challenging times. This finding highlights the importance of cultural context in understanding the effectiveness of sadness regulation strategies, especially those rooted in religious practices.

On the other hand, no significant relationship was found between religious coping and anxiety, suggesting that its benefits may primarily address emotional distress, such as sadness, rather than reducing anxiety. Variability in how individuals practice religious coping and its personal significance may dilute its impact [51]. Cultural factors and nature of religious practices may also contribute, as not all forms religious practices are equally effective for managing anxiety [52]. Additionally, stronger influences like social support or other coping strategies may reduce its effect.

Similarly, seeking social or emotional support was significantly associated with reduced depression. This finding is consistent with previous studies that emphasise the buffering effect of social support against depression and stress [53, 54]. In collectivistic cultures like Yemen, where family and community bonds are emphasised, seeking social support might provide a stronger emotional safety net than in more individualistic societies. The presence of robust social networks in such cultures may foster emotional well-being by reducing loneliness, providing practical help, and encouraging adaptive sadness regulation strategies [49, 55, 56]. Moreover, the findings demonstrated no significant correlation between seeking social or emotional support and anxiety. The lack of a significant association between anxiety and seeking social support may stem form personal traits like psychological resilience. Highly resilient individuals might find social support more effective in reducing anxiety, while those with lower resilience may not experience the same benefits [57].

Cognitive reappraisal significantly predicted reduced depression, aligning with studies highlighting its role in reframing sad situations and fostering psychological resilience [58,59,60]. Cognitive reappraisal may be particularly effective in managing depressive symptoms as it helps individuals interpret negative or sad events more positively, improve emotion regulation, and enhance problem-solving abilities [55], thereby reducing emotional distress. On the other hand, cognitive reappraisal was not significantly correlated with anxiety in this study, despite evidence supporting its anxiety-reducing effects [58]. This discrepancy may stem from differences in how cognitive reappraisal and anxiety were measured, cultural factors, or characteristics of the study population, anxiety severity, the use of alternative regulation strategies, or situational stressors [61].

Interestingly, rumination showed a significant positive association with depression, reflecting its maladaptive nature as sadness regulation strategy. This finding is consistent with prior research demonstrating that rumination fosters a cycle of negative thinking, which exacerbate depressive symptoms [62]. Unexpectedly, rumination was found to have a negative relationship with anxiety. This contradicting result might reflect cultural nuances in the perception of rumination. In Yemen, rumination could be viewed as reflective or problem-solving process rather than merely a repetitive focus on negative thoughts. This may lead to temporary reductions in anxiety, as individuals might feel a greater sense of control when engaging in reflective rumination [32].

This study also revealed non-significant relationship between expressive suppression and both depression and anxiety. While some studies have highlighted the detrimental effects of expressive suppression on emotional well-being, others have reported inconsistent results, particularly in cultural contexts where emotional restraint is valued [63, 64]. In Yemen, for example, expressive suppression may not be perceived as entirely maladaptive; instead, it could be viewed as a socially acceptable way of regulating emotions in public settings, thereby diluting its impact on metal health outcomes [65].

Substance use, often considered a maladaptive strategy, showed no significant relationship with depression. This finding could be influences by cultural factors, such as the widespread use of Khat in Yemen. Although Khat is classified as substance, its cultural normalization may reduce its perceived association with depression. Chewing Khat is a common practice, often used by individuals as a coping strategy for negative emotions when feeling sad. However, the significant negative relationship between substance uses and anxiety highlights the dual role of substance use as both a regulation strategy and a potential risk factor, depending on the context and individual differences [66,67,68].

Acceptance was not significantly associated with either depression or anxiety in this study. This result contrasts with findings from other cultural contexts, where acceptance has been linked to reduced emotional distress [46]. In Yemen, acceptance may sometimes be seen as avoidance or give up rather than as an active coping strategy, which may reduce its effectiveness. In other words, cultural differences in the perception of acceptance might influence its effectiveness [69].

With regard to mediation analyses, the findings provided deeper insights into the complex interplay between sadness regulation, emotion regulation, and depression and anxiety. Emotion regulation fully mediated the relationship between sadness regulation and depression, suggesting that individuals with better sadness regulation strategies are likely to experience enhanced emotion regulation, which, in turn, reduces depressive symptoms. This finding support theories that indicated effective sadness regulation helps individuals manage sadness and other emotions more effectively [43, 70].

In addition, the mediation analyses revealed a partial mediation effect of emotion regulation in the relationship between sadness regulation and anxiety. Interestingly, while sadness regulation directly reduced anxiety, the indirect effect through emotion regulation was positive. This unexpected finding suggests a complex relationship: while improved sadness regulation can enhance emotional awareness and control, increased emotional awareness may sometimes lead to higher anxiety in certain individuals [71, 72]. For example, individuals who are more attuned to their emotions might experience greater self-scrutiny or fear of judgment, leading to heightened anxiety despite improved overall regulation.

Potential confounding variables

Several factors could potentially influence the relationship between sadness regulation strategies and depression and anxiety. Although beyond the scope of this study, factors such as gender, trauma history, social support, psychological disorders, and socioeconomic status may influence the results. Despite using data screening, outlier removal, complete responses, and robust statistical analysis to reduce these effects, some residual residual confounding cannot be entirely eliminated. Future research should consider using experimental designs to more effectively isolate the effects of sadness regulation on depression and anxiety. The current study utilised the Manifest Anxiety Scale to assess anxiety. However, some findings on the correlations between sadness regulation strategies and anxiety contradicted existing literature. This discrepancy might be attributes to the scale’s limited suitability for the Yemeni context. Future research is encouraged to replicate this study using alternative anxiety measures that better align with the cultural and contextual characteristics of Yemeni participants to determine whether the observed correlations differ.

Implications and future directions

These findings have significant implications for mental health interventions. Therapeutic approaches should emphasise the influence of adaptive sadness regulation strategies, such as cognitive reappraisal, religious coping, and seeking social support, while also addressing the negative impact of maladaptive strategies like rumination. Moreover, culturally tailored interventions are essential, particularly in collectivist and religious contexts like Yemen. Future research should delve deeper into the non-significant results observed for expressive suppression and substance use. Longitudinal studies could provide greater clarity on the temporal effect off these strategies on depression and anxiety. In addition, the study highlights the need for culturally tailored assessment tools to capture the nuances of emotion regulation strategies. Thus, future research should further explore the cultural dimensions of sadness regulation and refine the sadness regulation scale to ensure its applicability across diverse populations. Additionally, future research should investigate cultural differences in sadness regulation and evaluate interventions in both clinical and non-clinical populations.

Limitations

Despite the contributions of the current study, several limitations should be addressed. First, there was no screening for depression or anxiety among the sample to diagnose whether the participants suffer from these conditions. Second, as this study was conducted on a sample from the general public, the results might not be applicable to those with clinically diagnosed depression or anxiety. Third, the current study’s results should be interpreted cautiously, as there are some findings that contradict existing literature. Fourth, this study is cross-sectional, which means it is impossible to examine the causal effect of sadness regulation on depression and anxiety. Fifth, self-reported data may be subject to bias, and the reliance on participants’ self-assessments could affect the accuracy of the findings. Finally, cultural differences were not considered, which may influence the generalizability of the results to other populations.

Conclusion

The current study examined the impact of different sadness regulation strategies on depression and anxiety, with a focus on the mediating role of emotion regulation. The findings highlighted that adaptive sadness regulation strategies, such as religious coping, seeking social support, and cognitive reappraisal, are significantly associated with lower levels of depression. However, rumination was positively and significantly associated with depression. Interestingly, expressive suppression and substance use did not show significant relationships with depression or anxiety, suggesting the complexity of these regulation strategies and their varying impact on mental health. Similarly, religious coping, seeking social support, expressive suppression, cognitive reappraisal, and acceptance did not correlate significantly with anxiety. These results suggest that these regulation strategies did not have a significant impact on anxiety symptoms or that their effects are not strong enough to be detected in this sample, potentially due to cultural, contextual, as well as methodological factors. The mediation analysis revealed that emotion regulation fully mediates the relationship between sadness regulation and depression. This finding underscores the critical role of emotion regulation as a mechanism through which adaptive sadness regulation strategies can reduce depressive symptoms. Additionally, the partial mediation effect of emotion regulation on the relationship between sadness regulation and anxiety highlights the complicated and sometimes contradictory dynamics between these variables. This study enhanced the understanding of the sadness regulation strategies involved in depression and anxiety and inform the development of targeted therapeutic approaches that more effectively address the regulation of sadness.

Data availability

The dataset from this study is not available in public repositories. However, it can be obtained from the corresponding author SZ upon reasonable request for reuse.

Abbreviations

ER:

Emotion Regulation

SR:

Sadness Regulation

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Acknowledgements

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Clinical trial

Clinical trial number: Not applicable, as this study was not conducted in a clinical setting.

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Authors and Affiliations

  1. Department of Psychology, Faculty of Art and Humanities, Sana’a University, Sana’a, Yemen

    Sumaia Mohammed Zaid

  2. Department of Educational Psychology and Counselling, University of Malaya, Kuala Lumpur, Malaysia

    Fonny Dameaty Hutagalung

  3. Fakulti Pengurusan, Pendidikan dan Kemanusiaan, University College of MAIWP International, Kuala Lumpur, Malaysia

    Harris Shah Bin Abd Hamid

  4. Department of kindergarten, Faculty of Education, Taiz University, Taiz, Yemen

    Sahar Mohammed Taresh

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Contributions

SZ and ST: Conceptualization, data collection, data analysis, and writing the main manuscript. FH and HB: Supervise and review methodology, data analysis, and manuscript writing.

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Correspondence to Sumaia Mohammed Zaid.

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Zaid, S.M., Hutagalung, F.D., Abd Hamid, H.S.B. et al. The power of emotion regulation: how managing sadness influences depression and anxiety?. BMC Psychol 13, 38 (2025). https://doi.org/10.1186/s40359-025-02354-3

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BMC Psychology

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