Emotions and Coping: “What I Feel about It, Gives Me More Strategies to Deal with It?”

Abstract

Background: Personal emotions and affects have been identified and studied in the context of pandemics, as well as coping strategies centered on emotional regulation or the balance between positive and negative emotions. Objectives: The objectives of this paper are to identify an emotion and affect structure in our sample and analyze the relationship of these dimensions with resilient coping in the context of the COVID-19 pandemic. Method: This study employed a cross-sectional design that involved a non-probabilistic sample with 598 participants over the age of 18, with 51.1% being female, and an average age of 40.73 years. First, the emotional structure was identified through principal component analysis (PCA). Secondly, a linear regression analysis was performed to investigate emotional dimensions as predictors of coping. Results: A valid and reliable emotional structure with four dimensions was identified. The regression model revealed that coping is positively associated with the active and positive dimension and negatively correlated with the negative and moral dimensions. Conclusions: Emotional dimensions are predictors of coping, with moral and negative dimensions having a negative effect, while active and positive dimensions have a positive effect. When designing interventions for coping strategies, multiple dimensions of emotions and affective states in people who are in vulnerable situations must be considered.

1. Introduction

Over time, in several traumatic events, e.g., due to human or natural causes, personal emotions have been widely addressed because they are crucial factors for understanding how people feel about and deal with these vulnerable situations [1,2,3]. In public health, some events have a massive impact on people’s behavior and emotions. In the initial stages, the COVID-19 pandemic contributed to the development of feelings of fear, anxiety, and insecurity [4,5].

Some authors [6] examined the emergence of emotions during the various phases of the pandemic. In the control phase, sadness increased and was accompanied by symptoms of anxiety. Anger did not increase in the same manner, particularly in the moments when social distance was imposed. During the lockdown and post-lockdown stages, there were fluctuations in both positive and negative affects.

Using a qualitative approach, Tang et al. [7] reported a transition in the emotional experiences felt, identifying fear and anxiety at the beginning, and a sense of comfort and gratitude after the lockdown phase. This study focused on a vulnerable population, the elderly, and emphasized that the transition from negative emotional experiences to positive emotional experiences was facilitated through the implementation of coping strategies.

Affective states of uncertainty, loneliness, worry, distress, low mood, and hopelessness were identified as relevant psychological responses during COVID-19 [8,9,10]. One aspect highlighted by these studies is the role of resilience and the practical implications of developing coping strategies to buffer the impact of the negative affective states that developed during the pandemic.

Vulnerability factors related to experiencing more negative affective states in stressful events have been linked to individual differences, such as perceived vulnerability to disease or threat anxiety proneness, and intolerance to uncertainty [4]. This vulnerability can also be related to personality traits, since individuals with high scores on the trait of neuroticism report more negative than positive emotions [11]. This finding is consistent with other studies that have also found that neuroticism was positively and significantly related to high anxiety during the COVID-19 pandemic [12].

Kumar and Tankha [11] also reported that individuals who were higher in emotional instability revealed poor sleep quality and reported more somatic concerns during the COVID-19 pandemic. Somatic concern represents an excessive focus on physiological symptoms and discomfort (e.g., palpitations, shortness of breath, fatigue, giddiness). Therefore, physiological mechanisms can also contribute to emotional experiences in COVID-19. These physiological symptoms are related to neural substrates, and they may also have a potential impact on coping strategies.

Adopting a multidisciplinary effort and a multifactorial perspective to understand anxiety and depression disorders, some authors [13,14] emphasize the importance of a translational perspective, which gives us the advantage of understanding how the neural substrates can be associated with emotional regulation and mood disorders [13,14,15,16]. The amygdala is crucial in normal emotional processing, and a prolonged stressful or threatening situation that causes an over-reaction of this structure provokes changes in its activity, increasing anxiety, hyperexcitability, depression, and leading to maladaptive emotional regulation [15]. Mood disorders are characterized by an alteration in the amygdala–hippocampal–prefrontal network, whereas the medium pre-frontal cortex is very important in the control of emotional processing [15].

In line with this, other authors [16] emphasize that fear responses can lead to more activation, anxiety, stress, or even psychiatric disorders and difficult emotional regulation. Higher-level cognitive structures (e.g., the prefrontal cortex) influence the amygdala and hippocampus, generating neurovisceral responses and governing heart rates. This cognitive structure is important for regulating emotions. Therefore, neural substrates involved in emotional processing, such as the amygdala for fear responses or the prefrontal cortex for cognitive regulation, enrich the understanding of how individuals navigate and regulate their emotions during traumatic events such as a pandemic [1,2,3,4] and, consequently, adopting a multifactorial perspective can be important for understanding resilient coping [13].

Social isolation, reduced contact with an individual’s social support, and lack of communication are also important factors to understand social vulnerability, leading to the experience of more negative emotions [17], and they are related to feelings of loneliness [18].

Regarding the role of coping strategies, some studies have focused on the mediating role of emotional perception in the context of public health safety, demonstrating that emotional perception is a critical mechanism for improving the sense of public health safety and decreasing risk perception. Therefore, perceiving positive emotions led the public to maintain a good psychological state during the pandemic, cope with situations, and increase their sense of public health safety, since their level of risk perception decreased [19].

According to Nui et al. [20], maladaptive emotional regulation is a risk factor, while an adaptative emotional regulation is a resilience factor that contributed to a decrease in the negative impact of the COVID-19 pandemic. Nui et al. [20] emphasized that emotion regulation means that cognitive and behavioral strategies are applied to modulate emotional responses. Emotion regulation strategies are maladaptive when they are associated with negative outcomes (e.g., more anxiety) and imply rumination, catastrophizing, and self-blame. Adaptive emotion regulation can involve the use of both problem-focused and emotion-focused strategies. Problem-focused strategies manage the stressor, whereas emotion-focused strategies manage the negative emotional feelings associated with the stressor.

Emotional regulation has also been studied as a strategy to deal with COVID-19 impacts on younger and older adults, and, in this process, it was found that acceptance, as an emotional regulation response, has beneficial affective outcomes for all (younger and older adults) when faced with an unpleasant and uncontrollable event [21,22]. Hofman et al. [23] define four interpersonal regulation strategies: enhancing positive affect (looking to others to increase positive emotions); perspective-taking (connecting with others as reminders not to worry); soothing (seeking others for comfort); social modeling (observing others’ ways of coping). These interpersonal regulation strategies were studied in context of the COVID-19 pandemic. The findings suggest that using the strategy to increase positive emotions is a potential mechanism for dealing with the pandemic’s effects on relationships, thereby increasing wellbeing. However, the soothing dimension and perspective-taking also presented positive correlations with the stress of COVID-19, indicating that people who have more difficulty regulating their emotions may need more comfort from others and may become dependent on others’ opinions [24]. Israelashvili [25] examined the specific role of positive versus negative emotions in an individual’s resilient coping associated with the COVID-19 pandemic and found that positive emotions are strongly linked with resilience in times of prolonged stress. This effect seems to be more evident among individuals who experience more negative emotions alongside their positive emotions.

Some authors [26] have also explored how people handle negative emotions using different coping strategies based on the search for information. Through a longitudinal study, they found that people who experienced fear, sadness, and anxiety looked for information more related to themselves and the virus (independent information), while the people who experienced fear, sadness, and anger looked for information from a collective perspective (interdependent information). Sun et al. [26] considered these coping strategies as cognitive ones, but different from problem-focused coping. They also identified disgust among the emotions experienced during COVID-19 but considered that they failed to identify a cognitive coping mechanism for this emotion, attributing it to its complexity, and related it to the threat of shame, which requires an emotion-coping strategy.

Polizzi and Lynn [27] developed a systematic and integrative review on the relation between emotion regulation and resilience, analyzing thirty-three articles. They concluded that emotional regulation is positively related to psychological resilience. Emotional regulation facilitates emotion and problem-focused coping, contributing to the development of psychological resilience. Some of the strategies found are cognitive reappraisal using positive affective states; suppression; and acceptance. In a recent study, Polizzi et al. [28] evaluated what we have learned from the pandemic context and identified coping strategies that seem to be efficient in studies developed during the COVID-19 pandemic: behavioral activation, acceptance-based coping, mindfulness practice, loving-kindness meditation; problem-focused and cognitive reappraisal.

Personal emotions and affects have been identified and studied in the context of pandemics, as well as coping strategies focused on emotional regulation and a balance between positive and negative emotions. However, the relationship between the categories of emotion (basic emotions; social emotions, self-conscious emotions, and moral emotions) and resilient coping has been less explored in the literature. For example, self-conscious emotions involve elaborated cognitive processes related to the notion of self and are intimately connected with psychopathology and vulnerable situations such as trauma [29]. A study developed by Lee et al. [30] found some of these emotions while examining unfinished business and self-blaming emotions among adults bereaved by a COVID-19 loss. The results revealed that participants reported experiencing grief reactions, such as regret, guilt, shame, and high to extreme levels of distress regarding their unfinished business. One of the limitations pointed out by the authors was the use of a single-item, binary response measure for self-blaming emotions. They encouraged future research to use a multi-dimensional measure for self-blaming emotions. An interesting study on public responses to two crises generated by COVID-19, which involved choosing between health and the economy, analyzed the emotional responses of anger, fear, and sadness on Twitter and justified the selection of these emotions because they are representative of basic emotions [31]. Hope is a well-documented social emotion in the context of COVID-19, leading to more resilience [32], and acting as a moderator in the relationship between the fear of COVID-19 and rumination [33].

The COVID-19 pandemic was considered an unpleasant and uncontrollable event, full of feelings of uncertainty [4,5] and a major threat, characterized by an “unknown threat affect” [34]. Accordingly, our study intends to also cover a range of affective states related to these attributions. Roca et al. [35] developed a qualitative study with the objective of registering the experiences of final-year nursing students who volunteered in COVID-19 health care and identifying their coping strategies. The students reported a category named emotions and feelings, revealing that in a context as emotionally complex as the pandemic, people experience a wide range of emotions and affective states.

In our literature review, some studies [25] make a major contribution to the objective of understanding the specific relationship between emotions and resilient coping, since the measures are identical to ours. However, emotions and affects are defined in advance in terms of their valence nature, whether positive or negative. The studies reviewed that relate emotions to coping strategies are, in general, focused on the fluctuations of negative and positive emotions [4,5,6] and on the transition from negative emotional experiences to positive emotional experiences [7]. They also identify negative affective states and coping strategies to buffer the impact of these emotions [8,9,10]. Adopting a multifactorial perspective to understand the relation between emotions and coping, some vulnerability factors and individual differences seem to be important for negative emotional experiences [4,11,12] and for understanding the neural mechanisms related to negative emotional responses or cognitive regulation [13,14,15,16], providing some interesting directions for future studies. The influence of social factors is also important [17,18]. Understanding specific coping strategies, whether maladaptive or adaptative, is also a relevant point [19,20,21,22,23,24,25,26,27,28].

The assessment of a wide range of personal emotions and affective states seems relevant because some of them have been less studied (e.g., moral emotions), and the majority of studies usually categorize emotions and affective states in terms of valence (negative and positive), particularly the studies related to coping strategies. This situation leads us to identify a gap in studies that explore diverse emotional dimensions and resilient coping during the pandemic.

Thus, considering the multidimensional nature of emotions, it seems important to identify a personal emotion and affect structure before analyzing the relationship between the obtained dimensions and resilient coping. Therefore, our study aims to bridge this gap by exploring the relationship between diverse emotional dimensions and resilient coping in the context of the COVID-19 pandemic.

2. Methods

2.1. Procedure

Our study is observational and was intended to collect data on emotions, affective states, and resilient coping in relation to the COVID-19 pandemic. The study and protocol were approved by the Ethics Committee and conducted in agreement with the Declaration of Helsinki for studies involving humans. After obtaining approval, we developed a questionnaire through an online platform to facilitate our data collection and dissemination. We adopted a cross-sectional design and defined an inclusion criterion for participation: participants should be at least 18 years old to participate.

Sample size was calculated a priori using G × Power 3.1.9.7^® software. In order to use regression analysis with four predictors (moral dimension, positive dimension, active dimension and negative dimension) and achieve a power of 0.90 at α = 0.05 to detect a small effect (f² = 0.15), a minimum sample of 108 participants was required.

A non-probabilistic sampling technique was conducted, namely, convenience and snowball sampling. Informed consent was obtained from all subjects involved in the study. The objectives of the research were explained, and the research team ensured the participants that the collected data would only serve for scientific purposes, adhering to the standards of anonymity and confidentiality.

In the data collection procedure, the use of a cross-sectional design did not allow us to stablish a causal relationship between variables; however, it allowed us to cover a wider range of participants, considering sociodemographic characteristics. For instance, our range of ages is from 18 to 90, so the emotional experiences reported are more diverse and could enrich our observational study. To base our data collection on self-reported measures is a limitation because people tend to answer according to social desirability in these types of measures. However, in the context of emotional experiences, the categorization (social or nonsocial) of the types of the emotions that people felt is also a valuable point of departure for working on adaptative coping strategies (e.g., reappraisal), since cognition is important for emotional experiences and regulation.

2.2. Participants

The sample included 598 participants: 51.1% were female and 48.5% were male. The average age of the respondents was approximately 41 years old (M = 40.73; SD = 11.48), with ages ranging from 18 to 90 years. A proportion of 62.2% of respondents were married or lived in a non-marital relationship, 10% were divorced, 26.9% were single, and 0.8% were widowed. Regarding their employment situation: 50% worked for others and did not mention their contract type, 8.4% were self-employed, 11.7% worked for others with a fixed-term contract, 1.8% worked for others as independent contractors, 2.8% were retired, 2.7% were unemployed, 11.5% were students, and 11% were in another situation.

2.3. Measures

A socio-demographic questionnaire was applied to respondents, including questions aimed at characterizing participants in terms of their sex, age, marital status, and employment situation.

Resilient coping (RC). This concept was measured using the brief resilient coping scale (BRCS) [36]. This version was validated for Portugal by Pais-Ribeiro and Morais [37]. The scale has four items (e.g., I look for creative ways to alter difficult situations; regardless of what happens to me, I believe I can control my reaction to it; I believe I can grow in positive ways by dealing with difficult situations; I actively look for ways to replace the losses that I encounter in life), presented on a five-point Likert scale (1–does not describe me at all; 5–describes me well). In the original version, the scale presented a reliability value of 0.70. In the Portuguese version, Cronbach’s alpha values were below the threshold of 0.70. The authors [37] argued that this construct is context-dependent. Additionally, reliability coefficients tend to penalize measures with a reduced number of items (four items). In our study, Cronbach’s alpha values achieved adequate results (0.80).

Emotions and affective states (EASs). To measure emotions and affective states indicating what people felt in relation to the pandemic context, we presented 25 items to participants, in order to cover a wide range of possibilities across the following categories: basic emotions; social emotions; and self-conscious emotions. We also extended the items to assess affective states, since they can be important in influencing behaviors [38]. The items are as follows: (1) interested; (2) nervousness; (3) enthusiastic; (4) frightened; (5) inspired; (6) active; (7) scared; (8) guilt; (9) determined; (10) tormented; (11) fear; (12) sadness; (13) disgust; (14) attentive/alert; (15) joyful; (16) anger; (17) shame; (18) contempt; (19) surprise; (20) proud; (21) frustration; (22) insecurity; (23) preoccupation; (24) apprehension; (25) despair. The 25 items were obtained from three sources: the positive and negative affect schedule, PANAS, adapted to the Portuguese language [39]; Izard’s differential emotion scale (DES), adapted by Vinagre [40]; and affective states studied in uncertain and vulnerable contexts [34,41]. We asked participants “To what extent did you feel the following emotions and affective states regarding the pandemic context”? The response possibilities were presented on a 5-point Likert scale (1–not at all; 5–extremely). The psychometric values of this scale of emotions and affective states will be analyzed in the results section.

2.4. Statistical Analysis

Data analysis was carried out using SPSS^® software, version 26. In the statistical treatment of the data, initially, a descriptive and exploratory analysis of the sample data was carried out, in which absolute (n) and relative frequencies (%) were used as qualitative variables. Measures of central tendency, such as mean (M) and standard deviation (SD) were used for continuous quantitative variables.

After data collection, a data analysis procedure was conducted in order to perform an exploratory factor analysis of emotional and affective state measurements, through principal component analysis (PCA), with a Varimax rotation. An internal consistency analysis (Cronbach’s alpha) was also carried out on the factors extracted.

Pearson’s correlation coefficients were calculated between resilient coping and the factors related to emotional and affective states. Finally, a linear regression analysis was performed to investigate the emotional and affective states as predictors of coping.

The results in this study were considered statistically significant at a significance level of less than 5%.

3. Results

3.1. Exploratory Factorial Analysis

Considering the multidimensional nature of emotions, our intention was to identify an emotional structure for the measurements selected through principal component analysis (PCA). Using Kaiser’s criterion (Eigenvalue > 0.1), we extracted four components that explained 63.87 per cent of the total variance. By analyzing the saturation matrix after Varimax rotation, we eliminated item 19 (surprise) due to high cross-loading and insufficient factor saturation.

The Kaiser–Meyer–Olkin (KMO) test was used to assess sample adequacy for an exploratory factor analysis. This coefficient achieved a value of 0.926, and Bartlett’s sphericity test was statistically significant (p < 0.05). These results demonstrate that the sample collected was adequate for conducting an exploratory factor analysis.

Four factors were extracted (

Table 1. Factor structure: factorial rotation matrix (Varimax) of the EFA items and internal consistency assessed with Cronbach’s alpha.

Items	Component 1
	Factor 1 Negative	Factor 2 Moral	Factor 3 Positive	Factor 4 Active
2. Nervous	0.73
4. Frightened	0.87
7. Scared	0.89
10. Tormented	0.80
11. Fear	0.85
12. Sadness	0.62
21. Frustration	0.58
22. Insecurity	0.75
23. Preoccupation	0.63
24. Apprehension	0.70
25. Despair	0.67
8. Guilt		0.55
13. Disgust		0.70
16. Anger		0.75
17. Shame		0.76
18. Contempt		0.86
3. Enthusiastic			0.81
5. Inspired			0.82
6. Active			0.56
15. Joyful			0.68
20. Proud			0.63
1. Interested				0.67
9. Determined				0.55
14. Attentive/alert				0.71
% Explained variance (with rotation)	27.95	14.16	13.63	8.13
Total % explained variance (with rotation)	63.87
Reliability values (Cronbach’s alpha)	0.94	0.83	0.79	0.61

¹ Extraction method: principal component analysis. Rotation method: Varimax with Kaiser normalization.

): the first factor, with 11 items and saturation between 0.89 and 0.58, is referred to as the negative dimension; the second factor, with 5 items, is referred to as the moral dimension, presenting loadings between 0.86 and 0.55; the third factor is referred to as the positive dimension, with loadings ranging from 0.82 to 0.56; and the fourth factor is referred to as the active dimension, with factor loadings ranging from 0.67 to 0.55.

The reliability analysis showed an adequate reliability. Cronbach’s alpha values were 0.94 for the negative dimension subscale, 0.83 for the moral dimension, and 0.79 for the positive dimension. The value for the active dimension was 0.61.

3.2. Mean, Standard Deviations, and Pearson’s Coefficient Correlation

Mean and standard deviations for coping, negative dimension, active dimension, moral dimension, and positive dimension are presented in

Table 2. Mean, standard deviations, and Pearson’s correlation coefficient between coping and negative, active, moral and ositive dimensions.

Descriptive Statistics			Correlations
	Mean	Std. Deviation	Coping	Active Dimension	Moral Dimension	Negative	Positive
Coping	3.30	0.81
Active Dimension	3.64	0.59	0.33 **
Moral Dimension	1.56	0.64	−0.25 **	−0.08
Negative Dimension	2.70	0.80	−0.26 **	0.03	0.54 **
Positive Dimension	2.66	0.68	0.30 **	0.45 *	−0.06	−0.32 **

* p < 0.05; ** p < 0.001.

. According to Pearson’s correlation coefficient, coping was statistically significant and negatively correlated with the negative dimension (R = −0.26, p = 0.000) and with the moral dimension (R = −0.25, p = 0.000); and coping was statistically significant and positively correlated with the positive dimension (R = −0.30, p = 0.000) and with the active dimension (R = −0.33, p = 0.000).

3.3. Linear Regression Analysis for Coping with Emotional Dimensions as Predictors

A linear regression analysis was performed to assess the emotional and affective dimensions as predictors of coping (see

Table 3. Linear regression model with emotional dimensions as predictors and coping as the criterion variable.

Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	2.256	0.224		10.072	0.000
	Active Dimension	0.364	0.059	0.267	6.224	0.000	0.735	1.361
	Moral Dimension	−0.182	0.057	−0.144	−3.205	0.001	0.664	1.507
	Negative Dimension	−0.148	0.049	−0.146	−3.015	0.003	0.578	1.729
	Positive Dimension	0.150	0.054	0.126	2.790	0.005	0.657	1.521

). The dependent variable was coping, and the independent variables entered in the regression model were the emotional and affective dimensions obtained in the exploratory factor analysis: negative, active, moral and positive dimension. A significant model was obtained, with all variables entered in the model explaining 20% of the variance in coping: R = 0.447, R² = 0.200 (F (4, 593) = 37.094, p = 0.000).

The analysis of the β coefficients and respective p-values shows that emotional dimensions are predictors of coping: the active dimension (β = 0.267, t = 6.224, p = 0.000), the moral dimension (β = −0.144, t = −3.205; 0.001), the negative dimension (β = 0.146, t = −3.015, p = 0.003), and the positive dimension (β = 0.126; t = 2.790; p = 0.005).

The assumption of collinearity was tested. In collinearity statistics tests, VIF values close to 10 indicate the presence of multicollinearity, while values close to 1 indicate the absence of multicollinearity. Acceptable Tolerance values must be greater than 0.20. The results indicated that multicollinearity was not a significant problem in the model tested (tolerance values ranged from 0.578 to 0.735 and the VIF values ranged from 1.36 to 1.73).

4. Discussion

Our study aimed to identify an emotion and affect structure in our sample and to analyze the relation of these dimensions to resilient coping in the context of COVID-19 pandemic. According to the concept of the multidimensional nature of our measurement of emotions and affective states (EASs), our results reveal a factor structure constituted by four factors: the negative dimension; the moral dimension; the positive dimension and the active dimension. The reliability analysis shows good internal consistency.

4.1. The Multidimensional Structure

The negative dimension includes 11 items: scared; frightened; fear; tormented; insecurity; nervousness; apprehension; despair; preoccupation; sadness and frustration. The moral dimension includes five items: contempt; shame; anger; disgust; guilt. The positive dimension includes five items: inspired; enthusiastic; joyful; proud; active. Finally, the active dimension includes three items: attentive/alert; interested; determined.

This structure reveals that the negative dimension explains more variance in the results and includes emotions and affective states such as scared, frightened; fear; and tormented, as adaptive responses to a threat. These types of emotions and feelings have been identified in other studies [4,5] and are related to distress and depression responses to COVID-19 [42]. Emotional and affective states, such as insecurity, nervousness, apprehension, despair, and preoccupation, probably related to the categorization of this threat as uncertain, unknown, and uncontrollable, also appear, in accordance with findings from other studies [8,9,34]. Sadness and frustration as negative emotions have also been related to distress and depression during COVID-19 [42]. Perceived vulnerability to a health threat, intolerance to uncertainty, and the experience of negative emotions can be accentuated by individual differences [4]. For instance, personality traits, such as neuroticism, were positively and significantly related to high anxiety during the COVID-19 pandemic [12,43]. Some authors have also demonstrated that low levels of neuroticism can help individuals to maintain a sense of security in stressful situations and develop curiosity about the external and internal world [44].

The moral dimension includes two self-conscious emotions: shame and guilt [29]. These emotions have also been considered moral emotions with impacts on moral behavior [45]. According to Lewis [29], shame is a consequence of a set of ideas about the self: accepting responsibility for a failure and evaluating one’s actions. This self-evaluation is global, and the person who experiences it wishes to hide or disappear. This may result in confusion and inability to speak. Guilt also occurs in response to accepting responsibility for a failure, but it is less intense than shame, since guilt is focalized on the person’s specific actions that led to a failure and does not involve the whole self. Through an act of reparation, people can overcome this feeling. Lewis [29] also emphasizes that these moral emotions are related to a coping style included in the compass of shame scale (COSS-4), developed by Elison et al. [46]. This coping style is characterized by the tendency to attack oneself and the tendency to hide or withdraw when experiencing shame (e.g., avoid others).

According to the CAD (community, autonomy, divinity) theory of violations [47], contempt, anger, and disgust can be linked to a different domain in behavior. Behaviors that neglect the social hierarchy, violate one’s duties, or display disloyalty to the community are related to contempt, since contempt appears in the context of relations between individuals and groups. During the pandemic, social order depended a lot on the sense of community, and people may not have been in agreement with the community.

Violations of autonomy include oppression, rights violations, and anger, as moral emotion is related to these appraisals. The pandemic context was characterized by multiple discussions about rights violations (e.g., vaccination) that could explain this moral emotion.

Divinity violations lead to disgust, since behaviors that degrade oneself to a less human status can cause a sense of impurity and degradation. Due to the excessive number of COVID-19 cases, we saw many images of hospitals that were unable to assist their patients, and incidents like these may have led to the feeling of disgust many times, but more research is needed to explain the type of events associated with this type of emotion. According to the suggestions of some authors [29], it is important to understand these feelings to foster adaptive moral processes and, consequently, moral behavior in order to benefit the persons involved.

The positive dimension includes emotional and affective states related to a positive, inspired, enthusiastic, and active affect, accompanied by social emotions, such as pride, also considered as a self-conscious emotion that signifies a successful evaluation of the self [29]. Positive emotions are congruent with positive psychology strategies that emphasize the boost of these types of emotions when people care for themselves, their loved ones, and their community. According to Waters et al. [48], the pandemic context represented an experience in which we were able to develop our capacity to cope, cultivate develop positive emotions, and build strengths.

The active dimension represents an affective state characterized by an active disposition (interested, determined) with some cognitive aspects (attentive/alert). In a pandemic context characterized by uncertainty, it was important to be determined and pay attention to the information about COVID-19 given by the World Health Organization (WHO) and national health systems in order to deal with this threat. In accordance with this active dimension, Polizzi et al. [28], in a recent review, analyzed the knowledge that we acquired from the pandemic, emphasizing that behavioral activation is a strategy for dealing with COVID-19 that promotes resilience.

4.2. Relations between Emotional Dimensions and Resilient Coping

The correlation analysis reveals that negative and moral dimensions are positively correlated, and that both are also negatively correlated with resilient coping, with the negative dimension presenting a major correlation. The regression analysis reveals that the moral and the negative dimensions are predictors of resilient coping with a negative effect.

Negative and moral feelings contribute to diminishing resilient coping. As other studies [20] have emphasized, a maladaptive emotional regulation is a risk factor for developing depression and anxiety. Hence, emotions-focused coping is not effective, and the individual maintains negative feelings that could lead to ruminations, catastrophizing, and self-blame (e.g., feeling scared; frightened; fearful; apprehensive; in despair; preoccupied; sad; frustrated; ashamed; contemptuous). These feeling states can be related to neural mechanisms that cause an over-reaction of the amygdala, increasing fear, anxiety, and hyperexcitability. Mood disorders can be characterized by an alteration in the amygdala–hippocampal–prefrontal network, and high-level cognitive structures, such as the pre-frontal cortex, may be compromised. Behavioral outcomes (e.g., ruminations, preoccupation) lead to maladaptive emotional regulation [15].

Therefore, our study emphasizes that these emotions do not benefit our resilient coping in vulnerable situations and underlines the importance of knowing them and teaching people how to deal with such situations.

The correlation analysis also reveals that the active and positive dimensions are positively related, and both are also correlated with resilient coping, with the active dimension presenting a major correlation. The regression analysis reveals that the active and positive dimensions are predictors of resilient coping with a positive effect. The active dimension has more value in explaining the predictions.

The active and positive dimensions contribute to promoting resilient coping. As other studies have underlined [20], an adaptive emotional regulation is a resilience factor that contributes to decreasing the negative impact of COVID-19. Adaptive emotional regulation can be divided in two categories: emotion-focused and problem-focused. Emotion-focused strategies involve acceptance, optimism, reappraisal of the negative emotions [20,27,28], and developing positive emotions [48]

Other studies [25] examined the role of positive versus negative emotions in individual differences in resilience in the context of the COVID-19 pandemic. The author found that positive emotions are strongly linked to resilience in times of prolonged stress. Additionally, it seems that this effect is more evident among individuals who experience more negative emotions alongside their positive emotions. Therefore, the author argues that suffering (experiencing negative feelings) is a part of human existence that cannot be avoided, but can also be the key to flourishing. Negative feelings can make a unique contribution to resilience when transformed. The author suggests that the challenge to human beings is the pursuit of balancing negative feelings with positive ones. According to Waters et al.’s [48] positive psychology guidelines, the COVID-19 pandemic provided ample and just causes for negative emotions, but it also offered an experience that can boost our positive emotions by fostering care for others, for the community, and by developing our capacity to cope with vulnerable situations. For example, social support and connectivity can contribute to the overall well-being and resilience of older adults during periods of lockdown, as well as in their everyday lives [7]. Social connectedness can also help people to reduce worries unrelated to COVID-19, such as distress and fatigue [49], revealing the importance of social networks in coping strategies.

As an adaptive emotional regulation, problem-focused strategies involve planning, searching for information, and taking decisions according to this information, being linked to lower risks of depression and anxiety symptoms [20]. As explained before, the active dimension is characterized by interest, determination, attention/alertness, and an affective state that is important for collecting information, making informed decisions, developing planning strategies, and engaging in resilient coping. Among these characteristics, the active dimension is the dimension that predicts more resilient coping. Therefore, the most resilient people are those who take an interest in their vulnerable situations and are receptive and attentive to information about how to deal with these situations. This adaptive emotional regulation is characterized by cognitive aspects (attention/alertness), with active behavioral outcomes (interest, determination) that could be linked to neural processes and may indicate an influence of higher-level cognitive structures (e.g., the prefrontal cortex), acting as cognitive regulation [15,16].

4.3. Limitations and Future Directions

This study has several limitations. First, a cross-sectional design was used, not allowing stable and causal evidence to be presented. Next, this study was based on self-reported questionnaires to assess emotions and resilient coping. Self-report data have limitations as they are susceptible to social desirability. Third, despite having calculated the sample, it was not obtained randomly.

Our study is observational, based on a cross-sectional design. In future directions, there is a need for further longitudinal studies to establish causality between emotional dimensions and coping strategies. Furthermore, future studies involving comparative analyses across different demographics or cultures could add depth to the conclusions drawn from our study in the several emotional dimensions. For example, regarding the negative dimension, some authors have already presented some evidence on the influence of cultural differences on negative emotional experiences and emotional regulation strategies (e.g., rumination and suppression) [50].

4.4. Practical Implications

In vulnerable situations, it is important to recognize and deal with emotions. People who present positive emotions have higher levels of resilient coping. On the other hand, when people seek information (because they are in a state of attention/alertness; interest; and determination), they are more prepared to deal with situations of great vulnerability, such as a pandemic, catastrophe, or chronic illness. In this sense, the most resilient people are those who are interested in their vulnerable situations and are receptive to information on how to deal with these situations. Some authors found that problem-focused strategies seem to be very effective in groups of chronically-ill patients during the COVID-19 pandemic [51].

These findings reinforce the need to prepare health professionals to help people in vulnerable situations to be more active and positive when facing situations that cause suffering, shame, and guilt. They should provide information, encourage the person to search for this information, help them recognize emotions and reframe events, particularly in cases of oncological disease [52] and in the COVID-19 pandemic context [48].

5. Conclusions

Resilience coping is an essential attribute for dealing with a person’s vulnerability to the challenges and vicissitudes of life, especially in a pandemic context. It can be useful to understand the emotional factors that reinforce or diminish the resilient coping of people before pandemic vulnerabilities in order to prevent psychological breakdowns during stressful health events. In our study, emotional dimensions are predictors of coping, with moral and negative dimensions having a negative effect, while active and positive dimensions have a positive effect. When designing interventions for coping strategies, we must consider multiple dimensions in emotional and affective states of people who are in vulnerable situations. Therefore, our study reinforces the necessity to know moral emotions associated with vulnerable health situations and inform people on how to deal with them. Developing an active dimension with interest, determination, and attention in people gives us some direction in improving resilient coping.