Emotional Cognitive Regulation in University Students during Lockdown: A Comparative Analysis of Students from Spanish Universities

Abstract

Studies focusing on strategies for the cognitive regulation of emotions are gaining importance due to the development and perpetuation of psychopathologies. The obligatory home confinement imposed in response to the COVID-19 pandemic has led to new virtual learning methodologies. Objective: Our objective aimed to analyze and compare the cognitive emotional regulation of students from universities on the Spanish mainland with that of students attending the Universidad de Las Palmas de Gran Canaria. Methods: An online Emotional Regulation Questionnaire was applied, together with a survey covering the students’ beliefs about the pandemic, including information about their housing conditions and beliefs about online learning. The study included a sample of 1030 university students. Results: On the mainland and at Las Palmas de Gran Canaria, the students most frequently used adaptive strategies. Three of the strategies were used in both groups but to different extents (Acceptance, Positive reappraisal, Putting into perspective), while the other strategies were used in both groups to the same extent (Refocusing on planning, Positive refocusing, Rumination, Blaming others, Catastrophizing, Self-blame). Meanwhile, the results were quite similar regarding the students’ housing conditions and beliefs about the pandemic and online learning.

1. Introduction

The management of emotions is among the most important activities in everyday life. Emotional regulation influences a series of processes that systematize emotions, and it manifests itself as a conglomerate of different mechanisms that can modify, model, or suppress an affective state [1,2], attending to precedents or elements of responses [3]. When people do not properly regulate their emotions, the resulting uneasiness can be lasting and lead to different symptoms [4,5]. Accordingly, the regulation of emotions can either be positive or negative, depending on the context and a person’s interests [6]. A variety of psychological problems can interfere with emotional regulation, such as anxiety, depression, and post-traumatic stress disorder [7,8]. Emotional regulation models include some that are based on strategies. Such strategies may be adaptive, for example, those associated with psychological processes, like acceptance, or maladaptive, for example, those related to rumination. Flexibility is a key factor when putting those strategies into practice [9]. Effective emotional regulation is related to such positive effects as well-being and proper work performance, whereas ineffective emotional regulation can be associated with such problems as anxiety and depression [10,11]. The current consensus regards emotional regulation as a process in which an individual can contribute to the type of emotion, the moment it occurs, and the way it is expressed [8,12]. For Gross [13], emotional regulation can affect a subject’s well-being by means of two processes. The first process is based on the formulation of the emotion and on regulating the precedents of the emotional process, locating the cognitive restructuring processes in reevaluating a situation—referred to as essential strategies [14]. The second process is based on the involvement in the emotional response, leading to an alteration in said response, for example, by being able to reduce negative emotions and increasing positive ones [13,14]. Here it is worth highlighting resilience from among other psychological factors that can affect emotional regulation [15]. Resilience is regarded as a group of positive personal qualities that can improve the individual subject’s adaptation to adverse situations and contexts [15,16]. Starting with Gross’ process model [13], which relevantly explains emotional regulation strategies, we can highlight the main stages in the emotional generation process laid out by Pérez et al. [13] (p. 116): (a) presentation of situations or stimuli, (b) identification and meaning of the same, (c) choice of techniques for handling those evaluations and, lastly, (d) implementation of responses for facilitating the desired change. Gross’ process model [13] (p. 116) includes different categories of emotional regulation strategies in the various stages of the process: (a) choice of the situation and modification of that situation, (b) attention deployment, (c) cognitive reevaluation, and (d) modification of the response.

Stress is currently one of the most frequently studied psychosocial factors arising from the new measures and adaptations related to COVID-19 [17,18]. Stress is regarded as a behavioral, psychological, or physiological response to a situation or stimulus that can be considered a risk [19,20]. Such response can cause difficulties associated with adaptation and the performance of activities. This focus factors in a number of variables related to the description above, such as “academic-related stress”, “subjective stress experiences”, “academic stress moderators”, and “academic stress effects” [21]. Academic activities carried out in the university environment can lead to anxiety and stress that, in turn, can affect students’ psychological and physical well-being [22]. In the university context, studies such as those in [21,23,24] and [25] show that anxiety and stress can affect a student’s academic performance. In [26], it is shown that students earning low grades may be influenced by high academic demands to feel stress.

A study by Husky [27] has shown that students who remained in their student residence halls, instead of the family home, during the lockdown had higher levels of anxiety and stress. In [28], the psychological impact of the pandemic on university students in Ethiopia is analyzed, highlighting a constant increase in the levels of stress, anxiety, and depression. Similar data can be seen in [29], a study on North American students showing an increase in stress, especially among female students. In the Spanish context, it has been shown, in [30], that university students with the greatest emotional cognitive regulation difficulties are the most susceptible to suffering possible effects on their studies and a possible increase in stress. As for the general population, González-Sanguino [31] provided evidence that women with symptoms associated with COVID-19 or a close family member affected by the virus have a higher level of depression and anxiety.

Academic persistence is a specific virtue that can be altered by anxiety and depression. Such persistence can also be affected by a student’s academic and social integration, which, in turn, affects one’s sense of belonging, academic commitment, and self-efficacy, all of which are involved in one’s academic performance [32]. Depression and anxiety are associated with academic performance [33], and they regularly inhibit that performance [34]. We should also note that university changes can be stressful for students, leading to a reduced academic persistence [35]. Some factors associated with academic persistence include students’ ability to build up and maintain the kind of personal resources, like support relationships, that can arise at university [35,36,37]. Thus, with the current provisional virtual learning model, a student’s attitude and motivation could be directly or indirectly affected, especially in online learning environments that were not implemented at the beginning of the school year. Nevertheless, studies, such as [38] (p. 1) show that students’ “attitude to online learning was not found to mediate their intrinsic motivation to make accomplishments and develop relationships. A negative mediation effect was partially supported by amotivation and engagement”.

Given all the aforementioned information, it is clear that there is a wide range of references in the literature showing that psychological well-being is a factor that can affect persistence and early university dropout possibilities, and that the lockdown situation can cause stress [23,30,39]. We believe that this is a good time to analyze and compare the emotional cognitive regulation of students from mainland Spanish universities with that of students from the Universidad de Las Palmas de Gran Canaria. It is worth noting that between the 2001–2002 and 2017–2018 school years, the Universidad de Las Palmas de Gran Canaria expanded considerably, with a 33.2% increase in new student enrollments [40]. University mobility within the Canary Island community is particularly expensive, given the impossibility of land-based transportation. Any movement between islands or provinces must be done by air or sea, increasing the expense of transport fees, thereby making daily transportation difficult. Thus, displacements must be permanent and not temporary, bringing with them the added cost of residing outside the family home. 95.5% of the students newly entering the ULPGC (Las Palmas de Gran Canaria University) in the 2012–13 period were born in Spain, with over half of the rest from Latin America. [41] (p254.): Of all new students (degree and post-degree) born in Latin America, 97.1% have their place of residence in the Autonomous Community of the Canary Islands.

2. Materials and Methods

A total of 1030 students from Spanish and Latin American universities participated in this research. The sample was divided into two sub-groups: students from Spanish mainland universities and students from Spanish universities at Las Palmas de Gran Canaria. In the case of the mainland universities, the sample comprised 266 women (20.05%), 1055 men (75.50%), and six missing values (0.45%). The age of the students ranged from 18 to 37 (M = 25.18, DS = 9.15). In the case of the Universidad de las Palmas de Gran Canaria, the sample comprised 168 women (29%), 409 men (70%), and six missing values (1%). The age of the students ranged from 18 to 35 (M = 23.58, DT = 7.67).

2.1. Procedure

An invitation was sent to university professors, explaining the general objective of the research and requesting their voluntary collaboration. Interested professors helped to send the instrument to the students online during class hours. It was explained to those students that their participation was strictly voluntary and that all their information would remain confidential. The questionnaire was applied at the end of March 2020 in the Spanish universities.

2.2. Measurement Instruments

The CC/COVID-19 adaptation of Cruz [30] is an instrument that was designed specifically for this study. It focuses on discovering the beliefs of university students about the pandemic and the housing conditions of the place where they spent their home confinement. The primary objective of the instrument is to evaluate the possibility of implementing online learning. Some of the questions were answered by means of a Likert scale, while others were answered by a dichotomous reply.

This questionnaire was administered at the same time as the Cognitive Emotion Regulation Questionnaire [42,43,44], adapted from [45], the adjustment of which was developed according to the guidelines of the International Test Commission [46], using a retro-translation method based on the original English version. It consists of nine scales, each with four items and conceptually different: Self-blame, Acceptance, Rumination, Positive refocusing, Refocus on planning, Positive reappraisal, Putting into perspective, Catastrophizing, and Blaming others. The instrument contains nine dimensions, with one per strategy: five are adaptive, i.e., they help adapt to the situation, and four are maladaptive, i.e., they make managing the experience more difficult. This instrument is made up of five dimensions: Beliefs about the Covid-19 pandemic, Beliefs about the effectiveness of virtual learning, Social conditions of the lockdown and description of the cohabitation situation, Description of the lockdown housing, and the Perception of the suitability of the lockdown housing. Some of the questions required answers according to a Likert scale, while others were of dichotomous reply type. This information was collected through 36 items, which were answered by means of a five-point Likert scale (from 1 = almost never to 5 = almost always), making it possible to know how often each individual uses each of the strategies.

3. Results

3.1. Descriptive Analysis, CC/COVID-19

Table 1. Beliefs about the COVID-19 pandemic.

Belief	Canary Islands			General
	N	$\bar{X}$	DS	N	$\bar{X}$	DS
Young people are agents spreading the disease to older people	560	4.14	0.966	1256	3.87	1.042
Young people are immune to the virus	560	1.43	0.709	1256	1.46	0.681
Older people can infect me with the virus	560	4.29	0.878	1256	4.06	0.938
Governments have known how to take proper measures	560	2.81	1.134	1256	2.71	1.108
The national health system is prepared for a pandemic	560	1.96	0.935	1256	1.97	0.934

shows the beliefs of Canary Island students concerning the pandemic in comparison with the overall sample. While the results point to the same conclusions, the Canary Island sample shows slightly higher scores for most items. When asked whether they believe themselves to be capable of spreading the virus to older people, the Canary Island students seemed to be more aware of this (4.14) than the general sample (3.87). Similarly, when asked about their immunity to the virus, the Canary Island students showed an average score of 1.43, compared with the 1.46 figure for the general sample. This would seem to indicate that the Canary Island students have a higher level of awareness when it comes to this factor. Similar results were obtained when asking them if they believed that older people can transmit the virus (4.29 in the Canary Island sample and 4.06 in general). As for government actions, we can see that the Canary Island sample shows a higher score (2.81) than the general sample (2.71), with students denying, in both cases, that the authorities knew how to act properly, although it is also clear that there was less agreement regarding this. Finally, on the question related to the health system’s preparation for confronting the pandemic, the scores were practically the same (1.96 in the Canary Islands and 1.97 in the general sample), showing a lack of preparation.

In addition to their beliefs concerning the pandemic, the students’ evaluation of virtual learning—to which they were suddenly subjected—is worthy of note. These items took different agents into consideration, including the university itself, the professors, and the students themselves. Regarding the university, it is interesting to see that the Canary Island population thought their university is not as well prepared (2.81 compared to 3.01 in the general sample), while believing, at the same time, that the professors had more resources for virtual teaching. Indeed, that item obtaining a score of 3.03, compared to the general sample figure of 3.02. Apart from the resources, when asked about the preparation of teachers for giving online classes, the Canary Island students showed a score of 2.19, while the general sample showed a score of 2.58. As for their personal skills in dealing with online classes, the Canary Island students regarded themselves as more competent (4.06), digitally speaking, than the general sample (3.64). In regard to the planning of study time, the Canary Island sample showed a 2.87 score, which is very close to the general average of 2.96. All of this information can be seen in

Table 2. Beliefs concerning the effectiveness of virtual teaching.

Belief	Canary Islands			General
	N	$\bar{X}$	DS	N	$\bar{X}$	DS
My university has adequate services and resources for virtual teaching	560	2.81	1.229	1256	3.01	1.118
The professors are properly trained for engaging in online education	560	2.19	1.123	1256	2.58	1.103
The professors have the necessary resources for engaging in online education	560	3.03	1.182	1256	3.02	1.098
I am digitally capable of engaging in online learning	560	4.06	0.973	1256	3.64	1.081
I have improved the planning of my study time during the lockdown	560	2.87	1.342	1256	2.96	1.243

.

Table 3. Social conditions of the lockdown and a description of the cohabitation situations.

	Canary Islands			General
	Yes %	No %	N	Yes %	No %	N
Family residence	84.0	14.1	572	83.0	14.3	1292
Home of another family member	8.6	91.3	582	6.9	92.8	1324
Temporary student residence	31.2	67.6	576	21.6	77.8	1320
Cohabitation with children	19.2	80.1	579	24.0	75.4	1319
Cohabitation with people older than 70	12.3	87.3	581	14.3	85.4	1323
Cohabitation with a pet that needs to be walked	32.9	65.5	574	34.5	64.1	1309

brings together information on the social conditions of the lockdown and a description of the cohabitation situation.

The average number of people in any given home confinement situation varied between 3 and 4 (3.49 for the Canary Island group and a bit higher (3.62) for the general group). The minimum was 1 (student confined at home and alone), with a maximum of 10 for the Canary Island students and 13 for the rest.

The vast majority of students were confined, in both cases, to the family residence (84% and 83% for Canary Island and general students, respectively) and did not cohabitate with people older than 70 (regarded as a population at risk) nor with pets that need to be walked, which would justify a daily and momentary break from confinement.

As for the housing conditions in the residence where the students spent the lockdown (compiled in

Table 4. Description of the lockdown dwellings.

	Canary Islands			General
	Yes %	No %	N	Yes %	No %	N
Dwelling in an urban area	72.2	25.9	572	74.9	22.9	1298
Dwelling in a rural area	24.5	74.4	577	22.2	76.9	1314
House with a large yard	14.1	85.9	581	17.6	81.8	1318
House with a small yard	8.6	91.4	581	15.8	84.1	1326
Dwelling with a large terrace	29.7	69.5	578	27.4	72.0	1319
Dwelling with a small terrace	24.5	74.6	578	35.6	63.1	1309
Dwelling with a large interior patio	10.3	89.2	580	18.5	81.0	1321
Dwelling with a small interior patio	19.2	80.3	580	26.4	73.5	1325
Dwelling with no exterior space	30.2	69.1	579	20.1	79.4	1320
Dwelling with outside views	88.3	9.1	568	83.7	13.6	1291

), it is worth highlighting that the vast majority, both in the Canary Island sample (72.2) and in the general sample (74.9), spent the lockdown in a dwelling located in an urban area, generally with the possibility of enjoying the outside without leaving the home. In the case of the Canary Island group, 30.2% of the students had no outside space beyond the home, whereas the figure for the general sample was 20.1%. On another front, 13.6% of the students in the general sample did not have any outside views, whereas 9.1% of the surveyed Canary Island students suffered from this situation.

Table 5. Perception of the suitability of the lockdown dwellings.

	Canary Islands			General
	Yes %	No %	N	Yes %	No %	N
Large home	57.1	41.0	572	62.5	36.0	1307
Comfortable home	87.7	10.3	571	89.0	8.5	1294
Small dwelling	34.1	65.0	578	28.8	70.1	1312
Oppressive dwelling	15.4	83.5	577	11.4	88.2	1321
WiFi available in the home	94.0	3.3	567	92.0	5.2	1290
Dwelling well equipped for studying	77.2	20.9	572	77.8	20.0	1298
Dwelling well equipped for physical exercise	49.4	49.7	578	44.9	53.9	1311
Dwelling well equipped for entertainment	63.6	34.0	569	64.6	33.4	1300

brings together the perceptions on the suitability of the dwelling where the students spent the lockdown. The scores are quite similar for the Canary Island and general samples, although with slight differences. The great majority of the students (87.7% of the Canary Island sample and 89% of the general sample) spent the lockdown in a dwelling they considered to be comfortable. Only 15.4% of the Canary Island group and 11.4% of the general group thought that their dwelling was oppressive. Almost all of the surveyed students had the ability to use WiFi in their home, with 94% of the Canary Island students and 92% of the general sample. As for their studies, 20.9% of the Canary Island sample and 20% of the general sample opined that their dwelling was not properly equipped for this purpose. Regarding the possibility of carrying out physical exercise and having the required equipment available, almost half of the Canary Island sample (49.4%) had what was needed, while this figure was 44.9% for the general group. Finally, as for entertainment, most students in the Canary Island group (63.6%) and the general group (64.6%) said that they had the equipment needed for entertainment in the dwelling where they spent the lockdown.

3.2. Descriptive Analysis of the Cognitive Emotion Regulation Questionnaire (CERQ)

After applying the Cognitive Emotion Regulation Questionnaire, in

Table 6. Group statistics.

Strategies	Canary Islands			General
	N	$\bar{X}$	DS	N	$\bar{X}$	DS
Self-blame	583	1.31	0.41	1327	1.44	0.52
Acceptance	583	3.38	0.88	1327	3.40	0.81
Rumination	583	2.90	1.06	1327	2.96	1.02
Positive refocusing	583	3.00	1.12	1327	3.11	1.07
Refocusing on planning	583	3.05	0.92	1327	3.14	0.86
Positive reappraisal	583	3.29	1.10	1327	3.39	1.04
Putting into perspective	583	3.52	0.89	1327	3.39	0.88
Catastrophizing	583	1.86	0.78	1327	2.05	0.81
Blaming others	583	2.51	1.28	1327	2.57	1.16

, we present the main descriptive characteristics, broken down into nine groups for each of the cognitive strategies analyzed.

Below, we present the nine strategies used in the general and Canary Island samples, which are ordered according to the scores obtained, with a maximum of four points. One can see that the order in the two samples is quite similar, with changes in the three most commonly used strategies, while the others appear in the same order, albeit with different scores. This may be due, in the case of the Canary Island sample, to the feeling caused by the students’ insularity, which allows them to put their experience into perspective more easily, while in the general sample it would seem easier to accept the situation.

Regarding the Canary Island sample,

Table 7. The order of the strategies most commonly used by the Canary Island students.

Strategy	$\bar{X}$
Putting into perspective	3.52
Acceptance	3.38
Positive Reappraisal	3.29
Refocusing on planning	3.05
Positive refocusing	3
Rumination	2.9
Blaming others	2.51
Catastrophizing	1.86
Self-blame	1.31

shows the three most commonly used strategies to be Putting into Perspective (3.52), a strategy by which one compares one’s situation with another’s which is worse, making their own situation seem milder; Acceptance (3.38), which consists in accepting the situation and thus avoiding judgments about having the same and associated feelings; and finally, Positive Reappraisal (3.29), which is the attempt to focus on the possible positive effects that might arise from the experience. The following strategies—which are still above the average score—are Refocusing on Planning, which consists in confronting the situation by thinking of ways to solve the problem (3.05); Positive Refocusing, which involves diverting one’s attention toward more agreeable thoughts when feeling stress from an experience (3 points); Rumination, by which one’s thoughts focus excessively on the lockdown situation (2.9); and Blaming Others, which involves making others responsible for the situation (2.51). Catastrophizing (1.86), which involves focusing one’s attention on the most negative aspects, and Self-blame (1.31), that is, feeling that one is responsible for everything being experienced, showed below-average scores.

Table 8. Order of the strategies most commonly used by students in the general sample.

	$\bar{X}$
Acceptance	3.4
Positive reappraisal	3.39
Putting into perspective	3.39
Refocusing on planning	3.14
Positive refocusing	3.11
Rumination	2.96
Blaming others	2.57
Catastrophizing	2.05
Self-blame	1.44

, meanwhile, brings together data from the general sample. Here, we can see that the first three strategies are the same, yet they are ordered differently. First, we have Acceptance, with a score of 3.4. Second and third are Positive Reappraisal and Putting into Perspective, both with 3.39 points. In terms of their scores, the other strategies line up in the same order as that observed in the case of the Canary Island sample: Refocusing on Planning (3.14), Positive Refocusing (3.11), Rumination (2.96), Blaming Others (2.57), Catastrophizing (2.05), and Self-blame (1.44). As in the Canary Islands sample, the last strategies obtained below-average scores.

After finding which of the strategies were the most commonly used in each group, we decided to apply the t-Student test to check which of the differences were significant.

The results shown in

Table 9. t test for the equality of means.

	Mean Difference	t	Significance
Self-blame	−0.12902	−5.314	0.000 *
Acceptance	−0.01660	−0.402	0.688
Rumination	−0.06029	−1.175	0.240
Positive Refocusing	−0.11722	−2.175	0.030 *
Refocusing on planning	−0.08339	−1.908	0.057
Positive reappraisal	−0.09849	−1.877	0.061
Putting into perspective	0.13076	2.973	0.003 *
Catastrophizing	−0.18759	−4.721	0.000 *
Blaming others	−0.06836	−1.151	0.250

Note: *: The difference is significant at a level of 0.05.

allow us to ascertain that there are significant differences (p > 0.05) in four of the strategies used by both groups: the differences in Self-blame, Positive Refocusing, and Catastrophizing are in favor of the general group; and the differences in Putting into Perspective are in favor of the Canary Island students.

3.3. Cognitive Strategies and Lockdown Conditions

Table 10. Correlations between lockdown conditions and cognitive strategies.

Strategies	Canary Islands				General
	A	B	C	D	A	B	C	D
Self-blame	−0.004	−0.019	−0.050	−0.009	−0.043	0.122 **	0.037	0.030
Acceptance	−0.003	−0.013	0.047	0.027	0.036	−0.031	−0.036	−0.011
Rumination	−0.052	0.094 *	0.029	0.124 **	−0.001	0.025	−0.036	0.048
Positive refocusing	0.015	−0.083 *	−0.159 **	−0.170 **	0.036	−0.060 *	−0.085 **	−0.147 **
Refocusing on planning	−0.023	−0.041	−0.124 **	−0.113 **	0.045	−0.054	−0.096 **	−0.117 **
Positive reappraisal	0.011	−0.084 *	−0.193 **	−0.134 **	0.008	−0.036	−0.119 **	−0.156 **
Putting into perspective	0.018	−0.096 *	−0.149 **	−0.170 **	0.033	−0.044	−0.061 *	−0.116 **
Catastrophizing	0.006	0.093 *	0.115 **	0.217 **	−0.030	0.138 **	0.030	0.126 **
Blaming others	−0.007	0.062	0.047	0.087 *	−0.069 *	0.076 **	−0.015	0.038

Note: A: Living with a pet that needs to be walked; B: Availability of a WiFi network in the home; C: Dwelling with good equipment for physical exercise; D: Dwelling with good equipment for entertainment; **. The correlation is significant at the 0.01 level; *. The correlation is significant at the 0.05 level.

shows the results of both questionnaires related to the cognitive strategies used by the students and certain situations that make home confinement more tolerable. These situations include living with a pet that needs to be walked (this being among those circumstances that justified leaving one’s home), having WiFi available at one’s home (which reduces the feeling of isolation through the sense of being connected to the outside world), having good physical exercise equipment available (making it possible to maintain a healthy lifestyle), and having good entertainment equipment (as a basic part of an individual’s mental health).

Of the nine strategies used by the students, those that were to a greater or lesser extent affected were the following: Blaming oneself in the case of the availability or lack thereof of WiFi in the home in the general group (p < 0.01); the Rumination strategy correlated with the availability of WiFi (p < 0.05), or good entertainment equipment (p < 0.01) in the Canary Island student group; Positive refocusing was related to having a pet (p < 0.05) in both groups, along with having good physical exercise and entertainment equipment available (p < 0.01); Refocusing on planning was also correlated with good exercise and entertainment equipment in both groups at this level (p < 0.01); Positive reappraisal showed a statistically significant relation (p < 0.05) to the availability of WiFi for Canary Island students and to good exercise and the availability of entertainment equipment for both groups (p < 0.01); Putting into perspective was related to the availability of WiFi (p < 0.05) among the Canary Island students and to the availability of physical exercise and entertainment equipment for both groups (p < 0.05 y p < 0.01); Catastrophizing correlated in both groups with WiFi availability (p < 0.05 for the Canary Island students and p < 0.01 for the general group), while a relation with good physical exercise equipment was only seen in the Canary Island group, and good entertainment equipment was related to this strategy in both groups (p < 0.01); finally, the strategy of Blaming others seemed to be related to good entertainment equipment in the Canary Island group (p < 0.05) and, in the general group, to living with a pet (p < 0.05) and having WiFi available (p < 0.01).

Next, we investigated whether these special lockdown conditions caused some sort of differential response when employing the different cognitive strategies.

First, we checked if the greater lockdown flexibility, which is associated with having to go out several times a day to walk the pet, results in a significant difference between those who have a pet and those who do not. In order to determine the independence of the results for both groups, and after checking for compliance with the requirements of normalcy and equality of variances, the t-Student test was applied. The main values are shown in

Table 11. Comparison of the independence of groups who spent the lockdown with a pet that needed to be walked and those who did not in the Canary Island sample.

	M1–M2	t	gl	Sig.
Self-blame	0.00361	0.00361	572	0.921
Acceptance	0.00583	0.00583	572	0.941
Rumination	0.11597	0.11597	572	0.215
Positive refocusing	−0.03651	−0.03651	572	0.713
Refocusing on planning	0.04535	0.04535	572	0.578
Positive reappraisal	−0.02632	−0.02632	572	0.787
Putting into perspective	−0.03469	−0.03469	572	0.659
Catastrophizing	−0.01036	−0.01036	572	0.88
Blaming others	0.02019	0.02019	572	0.858

and

Table 12. Comparison of the independence of the groups who spent the lockdown with a pet that needed to be walked and those who did not in the general sample.

	M1–M2	t	gl	Sig.
Self-blame	0.04658	1.543	1306	0.123
Acceptance	−0.05987	−1.288	1306	0.198
Rumination	0.00138	0.023	1306	0.981
Positive refocusing	−0.0805	−1.299	1306	0.194
Refocusing on planning	−0.0804	−1.611	1306	0.107
Positive reappraisal	−0.01845	−0.307	1306	0.759
Putting into perspective	−0.06104	−1.187	1306	0.235
Catastrophizing	0.04658	1.543	1306	0.123
Blaming others	−0.05987	−1.288	1306	0.198

.

Given the above results, we can conclude that being able to walk a pet did not affect the cognitive strategies used, as none of the differences seen are at a level of significance below 5%.

Similarly, the next step was to analyze whether the availability of a WiFi network led to the use of different cognitive strategies by those students who had such networks and those who did not and if these differences were significant. The main results after applying the t test are shown in

Table 13. Comparison of the independence of the groups in home lockdown with a home WiFi network and those without such a network in the Canary Island sample.

	M1–M2	t	gl	Sig.
Self-blame	0.09657	0.459	565	0.646
Acceptance	0.20807	0.3	565	0.764
Rumination	0.24625	−2.254	565	0.025 *
Positive refocusing	0.26247	1.976	565	0.049 *
Refocusing on planning	0.21549	0.977	565	0.329
Positive reappraisal	0.25633	1.994	565	0.047 *
Putting into perspective	0.20721	2.289	565	0.022 *
Catastrophizing	0.18098	−2.213	565	0.027 *
Blaming others	0.29751	−1.477	565	0.14

Note: *. The difference is significant at a level of 0.05.

and

Table 14. Comparison of the independence of the groups in lockdown with a home WiFi network and those without such a network in the general sample.

	M1–M2	t	gl	Sig.
Self-blame	−0.28036	−4.403	1287	0 **
Acceptance	0.11028	1.112	1287	0.266
Rumination	−0.11501	−0.912	1287	0.362
Positive refocusing	0.28435	2.149	1287	0.032 *
Refocusing on planning	0.204	1.923	1287	0.055 *
Positive reappraisal	0.16771	1.305	1287	0.192
Putting into perspective	0.17475	1.596	1287	0.111
Catastrophizing	−0.49421	−4.987	1287	0 **
Blaming others	−0.39066	−2.736	1287	0.006 **

Note: **. The difference is significant at a level of 0.01; *. The difference is significant at a level of 0.05.

.

Table 13 allows us to see if, in the case of students from the Canary Islands, the use of such strategies as Rumination, Positive refocusing, Refocusing on planning, Positive reappraisal, Putting into perspective, and Catastrophizing was affected by the availability or unavailability of a WiFi network. The differences found (p < 0.05) provide evidence of a correlation. As for the students in the general sample (Table 14), significant differences were found in relation to the use of such strategies as Positive refocusing, Refocusing on planning (at 0.05), Self-blame, Catastrophizing, and Blaming others, at a level of 0.01.

In the case of students who were confined in a home with good physical exercise equipment, significant differences could be seen in the use of some of the cognitive strategies being analyzed.

Table 15. Comparison of the independence of the groups who spent the lockdown with good physical exercise equipment and those who did not in the Canary Island sample.

	M1–M2	t	gl	Sig.
Self-blame	0.04105	1.197	576	0.232
Acceptance	−0.08299	−1.125	576	0.261
Rumination	−0.0604	−0.685	576	0.493
Positive refocusing	0.35553	3.855	576	0 **
Refocusing on planning	0.22876	3.005	576	0.003 **
Positive reappraisal	0.42417	4.724	576	0 **
Putting into perspective	0.26483	3.628	576	0 **
Catastrophizing	−0.17829	−2.775	576	0.006 **
Blaming others	−0.17829	−2.776	571,891	0.006 **

Note: **. The difference is significant at a level of 0.01; *. The difference is significant at a level of 0.05.

shows the results obtained for the Canary Island student sample.

Table 16. Comparison of the independence of the groups who spent the lockdown in a home with good physical exercise equipment and those who did not in the general sample.

	M1–M2	t	gl	Sig.
Self-blame	−0.03872	−1.34	1308	0.181
Acceptance	0.05761	1.295	1308	0.196
Rumination	0.0743	1.316	1308	0.188
Positive refocusing	0.18333	3.101	1308	0.002 **
Refocusing on planning	0.16628	3.505	1308	0 **
Positive reappraisal	0.24779	4.343	1308	0 **
Putting into perspective	0.10827	2.21	1308	0.027 *
Catastrophizing	−0.0492	−1.094	1308	0.274
Blaming others	0.03417	0.532	1308	0.595

Note: **. The difference is significant at a level of 0.01; *. The difference is significant at a level of 0.05.

allows us to see if, in the case of students in the general sample, significant differences appear when using strategies including Positive refocusing, Refocusing on planning, Positive reappraisal (p < 0.01), and Putting into perspective (p < 0.05).

Finally, we looked at whether having had good entertainment equipment at home during the lockdown affected the way different cognitive strategies were employed. With the Canary Island students,

Table 17. Comparison of the independence of the groups who spent the lockdown in homes with good entertainment equipment and those who did not in the Canary Island sample.

	M1–M2	t	gl	Sig.
Self-blame	0.00821	0.225	567	0.822
Acceptance	−0.04983	−0.636	567	0.525
Rumination	−0.27463	−2.97	567	0.003 **
Positive refocusing	0.40338	4.119	567	0 **
Refocusing on planning	0.21987	2.719	567	0.007 **
Positive reappraisal	0.30945	3.217	567	0.001 **
Putting into perspective	0.31836	4.111	567	0 **
Catastrophizing	−0.35472	−5.286	567	0 **
Blaming others	−0.23246	−2.072	567	0.039 *

Note: **. The difference is significant at a level of 0.01; *. The difference is significant at a level of 0.05.

shows that the differences found were significant at a level of 0.01 in the use of Rumination, Positive refocusing, Refocusing on planning, Positive reappraisal, Putting into perspective, and Catastrophizing, while the strategy of blaming others was only significant to a level of 0.05.

In the group of students included in the general sample (

Table 18. Comparison of the independence of the groups who spent the lockdown in a home with good entertainment equipment and those who did not in the general sample.

	M1–M2	t	gl	Sig.
Self-blame	−0.0331	−1.091	1297	0.275
Acceptance	0.0187	0.397	1297	0.692
Rumination	−0.10323	−1.73	1297	0.084
Positive refocusing	0.33252	5.36	1297	0 **
Refocusing on planning	0.21239	4.248	1297	0 **
Positive reappraisal	0.34235	5.691	1297	0 **
Putting into perspective	0.21755	4.22	1297	0 **
Catastrophizing	−0.21539	−4.578	1297	0 **
Blaming others	−0.09158	−1.352	1297	0.177

Note: **. The difference is significant at a level of 0.01.

), spending the lockdown in a home with good entertainment equipment displayed significant differences (p < 0.01) in terms of the use of the following strategies: Positive refocusing, Refocusing on planning, Positive reappraisal, Putting into Perspective, and Catastrophizing.

4. Discussion

The home confinement measures imposed due to COVID-19 have had ongoing and damaging effects on university students, leading to more intense and long-lasting emotions [47]. In this situation, the proper regulation of emotions is associated with a number of positive effects, such as a better performance at work, well-being, and prosperity in personal and professional relations [11]. Nevertheless, these same strategies can have negative effects if used in a maladaptive manner, such as an increase in anxiety, depression, and other symptoms [10,48]. In this context, we decided to analyze and compare the general emotional regulation strategies among Spanish university students on the mainland and at the Universidad de Las Palmas de Gran Canaria, along with the students’ beliefs about the pandemic and the living conditions in the dwellings where they spent the lockdown.

Using the “Emotional Regulation Questionnaire”, nine cognitive strategies were analyzed, showing significant differences between the two groups of students in some of these strategies. Significant differences were seen in such strategies as “Self-blame”, “Positive refocusing”, “Putting into perspective”, and “Catastrophizing” in terms of the averages for the students in general. The least frequently used strategies for both groups were “Self-blame”, “Catastrophizing”, “Blaming others”, and “Rumination”, which are all associated with negative effects and emotional interference [9]. The most commonly used strategies for both groups were “Acceptance”, “Positive reappraisal”, and “Putting into perspective”—strategies that are not associated with negative effects [49]. We believe, as in [49], that the abovementioned strategies call for a more rational information process, which would allow for a more solid application. Moreover, the coping strategies (in our case, “Acceptance”, “Positive reappraisal”, and “Putting into perspective”) can activate the coping mechanism through cognitive strategies and behaviors in order to resist anxiety in interactions with environmental factors [30,50].

With the results obtained, we can show that a higher degree of emotional regulation is related to a lower experience of stress factors, in accordance with the research of [51]. We believe that the ability to manage less adaptive emotions significantly favors interpersonal relations, while decreasing the number of controversies as the result of one’s preparedness for academic and social contexts [51,52].

Every student has their own way of confronting the social isolation resulting from the lockdown, as they must deal with uncertainty, anxiety, and worries caused by the situation [53]. Family support becomes an important element that can help to lessen some of the less adaptive emotions. Throughout the home confinement required by the COVID-19 pandemic, not all young people had the same life conditions or adequate access to technology, nor did they have similar behaviors and skills for confronting those situations [54,55]. Ref. [56] shows that families who are resistant to painful situations—such as the lockdown resulting from the COVID-19 pandemic—are capable of making continual adaptations and changes [56]. In our research, confinement in a home with WiFi availability and good entertainment equipment led to changes in emotional regulation, highlighting adaptive strategies. Accordingly, we can show that such changes may well be due to family influence and support, among other causes, such that resilient families could demonstrate a higher level of adaptation to the changes and greater life satisfaction, leading to a better ability to adapt to new academic situations on the part of the student [57,58].

Based on the claims of [6] that emotions may be positive or negative depending on the context and interest required, we coincide with [59] in obtaining evidence that positive emotions foster relations with others, and that participating in productive tasks and leisure activities increases well-being, along with the ability to adapt.

Our results are similar to the ones obtained in the research carried out by [60], showing that a student’s effort to adapt to a new learning model demands more commitment. This situation calls for more management of emotions, considering such variables as social isolation, internet access, the economic context, and the general uneasiness associated with the pandemic [61]. Based on our research, we coincide with [62] in thinking that academic adaptation is not only a question of means, but also of teaching models that can best minimize the problems associated with the lack of classroom attendance. Accordingly, the university must adapt itself to a new teaching model that allows for students’ academic development. Regarding the students, the Psycho-pedagogical Department/Academic Orientation Unit must offer programs that help students to better adapt to the new model, preventing possible early dropouts caused by poor academic and social adaptation [23,39].

It is worth keeping in mind such research as that reported in [63], in which it is shown that many young people from the Canary Islands eventually develop a feeling of isolation in comparison with those on the mainland. In the case of the Canary Islands, the students’ higher levels of regulation through acceptance—as the most commonly used strategy—could be attributable to the fact that they are more accustomed to isolation and to having feelings of solitude than the students on the mainland.