ORIGINAL RESEARCH article
Sec. Educational Psychology
Volume 13 - 2022 | https://doi.org/10.3389/fpsyg.2022.809230
Psychological Distress, Anxiety, and Academic Self-Efficacy as Predictors of Study Satisfaction Among Peruvian University Students During the COVID-19 Pandemic
- 1Facultad de Humanidades, Grupo de Investigación Avances en Investigación Psicológica, Universidad San Ignacio de Loyola, Lima, Peru
- 2Escuela de Psicología, Facultad de Derecho y Humanidades, Universidad Señor de Sipán, Chiclayo, Peru
- 3Facultad de Ciencias de la Salud, Universidad Privada del Norte, Lima, Peru
- 4Facultad de Ciencias de la Salud, Universidad Privada San Juan Bautista, Lima, Peru
The objective of this research study was to determine if psychological distress, anxiety, and academic self-efficacy predict satisfaction with studies in Peruvian university students during the COVID-19 pandemic. A cross-sectional and predictive design was used, in which 582 Peruvian university students participated, 243 men and 339 women, between the ages of 16 and 41. Student’s t-statistics were used to analyze the differences in scores of psychological distress, anxiety, academic self-efficacy, and satisfaction with studies based on the sex of the participants, Pearson’s R was used for the analysis of correlations between variables, and multiple linear regressions were used to evaluate the predictive model. In the analyses, the significance level was set at 0.05. The results show that men have higher levels of psychological distress, anxiety, and academic self-efficacy than women do (p < 0.01); high levels of psychological distress correlate with high levels of anxiety (r = 0.580, p < 0.01) and low levels of satisfaction with studies (r = –0.178, p < 0.01) and academic self-efficacy (r = −0.348, p < 0.01); high levels of anxiety correlate with low levels of satisfaction with studies (r = −0.122, p < 0.01) and academic self-efficacy (r = –0.192, p < 0.01); and high levels of academic self-efficacy correlate with high levels of satisfaction with studies (r = 0.429, p < 0.01). Academic self-efficacy was also found to predict satisfaction with studies (β = 0.429, p < 0.01). This concludes that, although there are significant correlations between psychological distress, anxiety, academic self-efficacy, and satisfaction with studies, academic self-efficacy is the variable that most predicts satisfaction with studies in Peruvian university students.
Today’s society demands that students graduate from universities with high professional skills (Rodrigo, 2016). This poses certain challenges in scenarios where virtual learning is applied (Durán et al., 2015), as was the case during the COVID-19 pandemic (Britez, 2020).
Because of the imposition of social restriction measures and lockdown to reduce the rate of infections (Peña-Otero et al., 2020) and to prevent overloading health systems (Rodríguez et al., 2020), sectors such as education have had to adapt and propose new strategies to continue the teaching–learning process without lowering educational standards (Bayham and Fenichel, 2020; Van and Parolin, 2020). In the case of Latin America, given the rapid growth in the infection rate (Barboza-Palomino et al., 2020; Gallegos et al., 2020), universities had had to establish virtual platforms based on the use of educational technologies to continue with the academic school year (Hernandez et al., 2020). These changes forced university students to face challenges, such as having to adapt to online education (Chau and Saravia, 2014) and self-regulate their learning (Alegre, 2015).
Even before the pandemic, several studies had reported that university populations are one of the development groups most prone to conflict, which is common during middle and late stage adolescence (Balanza et al., 2009). Primarily, manifestations of stress (Phinder-Puente et al., 2014), anxiety (Reyes et al., 2017), depression, suicidal behavior (Micin and Bagladi, 2011), and other psychological disorders (De Jesus et al., 2019) have been recurrently reported in this population. The impact of the pandemic on higher education study experience has been serious (Costa and Carvalho-Filho, 2020), since traditional education is not the same as learning via conference calls and online exercises (Connor et al., 2020), especially for those who need training in specialized laboratories (Warhadpande et al., 2020), where case virtual classes can hardly replace hands-on learning (Aquino-Canchari and Medina-Quispe, 2020).
Based on what has been described, it is urgent to reflect on satisfaction with studies in university students during the health emergency. Study satisfaction is defined as a positive assessment that an individual makes when comparing their ambitions with what they had actually achieved, a fact that in the academic field is understood as the enjoyment and sense of well-being in the experiences lived (Dominguez-Lara and Campos-Uscanga, 2017), which are precisely the driving force of the learning experience at higher educational levels.
A theoretical model that has proven useful when studying the processes that lead students to feel satisfied with their learning experience is self-determination theory (SDT, Tomás and Gutiérrez, 2019). This is interpreted as a motivational approach that describes the educational circumstances in which students experience enjoyment and well-being (Tarek and Hubbard, 2015). Studies carried out in this field show that there are three psychological conditions necessary toward feeling satisfied with the educational environment (Wang et al., 2019): autonomy (the experience of freedom of choice in learning), competence (perception of self-efficacy and the ability to master the learning environment), and relationship (feeling connected with peers, teacher, and administrators). If these conditions are not met, the student usually experiences academic stress or thinks about dropping out (Yu and Levesquel-Bristol, 2020).
To understand the predictor variables of study satisfaction in the context of the COVID-19 pandemic, the literature highlights the importance of psychological distress, anxiety, and academic self-efficacy because of their impact or the role they play.
Herrera and Rivera (2011) defined psychological distress as a reactive state that involves perceiving discomfort owing to psychological alterations related to perceived stress, depression, anxiety, or demoralization (Liébana-Presa et al., 2014). In this regard, research conducted 10 years ago revealed that a low level of students’ life satisfaction could be predicted as a function of experiencing symptoms related to anxiety, depression, and satisfaction with their department and socioeconomic level (Bulut Serin et al., 2010). Such facts were corroborated during the COVID-19 pandemic by Babar et al. (2021), who found that 41% of students face severe psychological distress and 65% face dissatisfaction with online classes. Under a linear regression model, these data show that psychological distress is a predictor of satisfaction with virtual education.
Flores et al. (2016) were the first to define anxiety as an adaptive response to a stressor. In this regard, studies such as that carried out by Arjanggi and Shanti (2016) concluded that social anxiety generates a negative effect on academic adjustments within the context of the educational experience in first-year university students. Likewise, Abdous (2019) reports that gender, prior online experience, and the feeling of readiness are variables related to feelings of anxiety. Regarding academic self-efficacy, it is understood as the belief the students have in their own capacity and efficiency to carry out tasks in the academic setting (Hechenleitner-Carvallo et al., 2019). In this regard, research such as that conducted by Shen et al. (2013) found that the self-efficacy of online learning accounts for learning satisfaction, a result that is gaining momentum with the finding of Kostagiolas et al. (2019), who conclude that, in effect, there are functional relations between study satisfaction, self-efficacy, and academic performance among undergraduate students.
With that in mind, throughout the years, there has always been an interest in understanding the cognitive and behavioral factors that favor or limit students’ performance in terms of academic requirements in the university context (Contreras et al., 2005; Cabanach et al., 2012; Gutiérrez-García and Landeros-Velázquez, 2018). Therefore, considering the uncovered evidence and the literature gap regarding the study of factors that has predictive power on satisfaction with studies in times of health crisis, determining which variables play an important role in the enjoyment of higher education experiences in the context of the COVID-19 pandemic is required.
In view of the foregoing, this research aims to determine if psychological distress, anxiety, and academic self-efficacy predict study satisfaction among Peruvian university students during the COVID-19 pandemic.
Materials and Methods
This is a cross-sectional predictive study (Ato et al., 2013) which uses psychological distress, anxiety, and academic self-efficacy as predictor variables, while the criterion variable is study satisfaction of Peruvian university students.
Non-probability sampling was used. The prior power analysis performed in the G*Power program (Faul et al., 2009), with a small effect size (f2 = 0.15), α = 0.05, and power = 0.95 and with three predictors, indicated that 74 participants were enough to identify the effects. However, the actual sample exceeded that number as 582 university students (58.2% female) participated. Participants attended different Peruvian universities, and their age ranged from 16 to 41 years (M = 21.79; SD = 5.05). From all, 90% were studying at a private university, 39.2% attended the School of Engineering and Architecture, and 36.4% were students from the School of Health Sciences.
The university students evaluated carried out their studies during the COVID-19 pandemic. Therefore, the transition from face-to-face to virtual education led to changes and challenges (Vilela et al., 2021). This led to a lot of worry and pressure because the students had to use a methodology that they were not trained to work with, and, for which, they were unprepared (Suárez et al., 2021). However, since the majority of the cohort studied in private universities, they had more opportunities to access virtual education. Nevertheless, while before the pandemic, the school dropout rate ranged from 15.8 to 17.6%, this rate increased to 18.1–42.6% during the pandemic (Benites, 2021).
Brief Scale of Study Satisfaction (EBSE; Merino-Soto et al., 2017). This is a brief measurement consisting of three items. It assesses the students’ satisfaction with their way of studying, their academic performance satisfaction, and their global study satisfaction. The items are in Likert-type format, with five response options stating agreement or disagreement with the statements, from “In strong disagreement” to “In strong agreement.” In this study, the EBSE showed good internal consistency (α = 0.87 [CI 95%:0.84–0.88]).
Generalized Anxiety Disorder Scale-2 (GAD-2; Kroenke et al., 2007). This is a brief measurement consisting of two items that assess the frequency of occurrence of behaviors linked to the generalized emotional and cognitive expression of anxiety in the last 2 weeks. The items are scaled in Likert-type format, with four response options, from 0 (none) to 3 (almost every day). The version used was adapted to Peruvian Spanish.1 For the study, the GAD-2 reported adequate reliability (α = 0.84 [CI 95%:0.81–0.86]).
Academic Self-Efficacy Scale [EAPESA (for its Spanish acronym); Palenzuela, 1983]. This scale assesses self-efficacy specifically perceived in academic situations. The version used was adapted for university students (Dominguez et al., 2012). It consists of nine items, with four response options, from “Never” to “Always.” The reliability of the EAPESA in this study was α = 0.93 (CI 95%:0.91–0.94).
Kessler Psychological Distress Scale (K6; Kessler et al., 2003). This scale consists of six items that assess psychological distress based on two factors, anxiety and depression, through the frequency with which the students experienced non-specific symptoms during the last 30 days. The items are based on the criteria diagnosed for major depression and generalized anxiety disorder from the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV; APA, 2004). The items are scaled in Likert-type format, with five response options, the values of which go from 0 (Never) to 4 (All the time). The version applied was that used in Peru by Dominguez-Lara and Alarcón-Parco (2020). In this study, the Psychological Distress Scale K6 showed adequate internal consistency (α = 0.84 [CI 95%:0.81–0.86]).
The study was approved by the ethics committee of the Universidad Peruana Unión (2020-CEUPeU-00023). Participants were contacted via social media (Facebook and WhatsApp), and the instruments were answered through Google forms. Before completing the instruments, they were required to sign an informed consent that communicated the purpose of the study and the anonymous and voluntary nature of their participation.
The analysis of data started with a descriptive analysis of the variables: study satisfaction, psychological distress, anxiety, and academic self-efficacy. The students’ t-test was used to assess the differences among the variables by gender. Additionally, Cohen’s d was used as an effect size (ES) measure to compare two independent groups (Caycho-Rodríguez, 2017a), where values of 0.20, 0.50, and 0.80 express a small, medium, and large ES, respectively (Cohen, 1998; Ferguson, 2009). The analysis of the relation between the study variables was carried out with Pearson’s correlation coefficient, calculating the correlations’ effect size based on the correlation coefficient value (≥0.20: minimum recommended; ≥0.50: moderate; ≥0.80: strong) and their respective confidence intervals (Caycho-Rodríguez, 2017b). Lastly, a regression model was estimated by calculating the ES based on the determination coefficient (R2) and its confidence intervals, where the values ≥ 0.02, ≥ 0.13, and ≥ 0.26 indicate a small, average, and large ME, respectively (Caycho-Rodríguez, 2017c,d). The statistical software SPSS, version 24.0, was used to conduct the statistical studies.
Table 1 shows that the skewness and kurtosis coefficients are below 1.5, this being an adequate range (Pérez and Medrano, 2010).
Table 1. Descriptive analyses of study satisfaction, psychological distress, anxiety, and academic self-efficacy.
Differences Between Study Satisfaction, Psychological Distress, Anxiety, and Academic Self-Efficacy by Gender
As can be observed in Table 2, the students’ t-test for independent samples indicates that there are no significant differences in study satisfaction between men and women. On the contrary, significant differences were found with respect to psychological distress (t = 1,110, p = 0.267), anxiety (t = −3,097, p = 0.002), and academic self-efficacy (t = −3,865, p = 0.000) between men and women. The analysis of mean values shows that women present higher levels of psychological distress and anxiety, whereas men show greater scores in academic self-efficacy. With respect to the effect size calculated by means of Cohen’s d, it is observed that the ES for the psychological distress variable is within the limit (d = 0.20), by no means negligible for the anxiety variable (d = 0.32), and good for academic self-efficacy (d = 0.57).
Table 2. Study satisfaction, psychological distress, anxiety, and academic self-efficacy between men and women.
Correlation Between Study Satisfaction, Psychological Distress, Anxiety, and Academic Self-Efficacy
Table 3 shows Pearson’s correlations between study satisfaction, psychological distress, anxiety, and academic self-efficacy. A statistically significant correlation between the study variables (p < 0.01) can be observed.
Table 3. Correlation between study satisfaction, psychological distress, anxiety, and academic self-efficacy.
Study Satisfaction Prediction
To determine the variables that better predict study satisfaction, a multiple regression study was carried out. The psychological distress, anxiety, and academic self-efficacy variables were introduced into this study. From these, academic self-efficacy turned out to be the predictor variable. Table 4 shows the adjusted R, R2, R2 multiple correlation coefficients, the standard error of estimate (EE), and the ANOVA F-value.
As shown in Table 4, the coefficient of determination R2 = 0.184 indicates that the academic self-efficacy variable accounts for 18.4% of the total criterion variable, study satisfaction. A greater value of the multiple determination coefficient indicates a greater explanatory power of the regression equation and, therefore, greater power of prediction of the dependent variable. The adjusted R2 accounts for the percentage of 18.3%. The ANOVA F-value (F = 131.005, p = 0.000) indicates that there is a significant linear relationship between the academic self-efficacy variable (predictor) and the study satisfaction variable (criterion).
Table 5 shows the unstandardized regression coefficients (B), the standardized regression coefficients (β), and the statistical coefficients related to the predictor variable. Coefficient β indicates that academic self-efficacy (predictor variable) significantly predicts study satisfaction (criterion variable). The T-value of beta regression coefficients of the predictor variable has been found to be highly significant (p < 0.01).
The COVID-19 outbreak has become a global problem with its impact exceeding the organic clinical manifestations related to this disease, with consequences in the mental health of the population being one of the emerging concerns requiring prompt and effective response from the field of psychology. In this situation, this article aimed at assessing the predictive role of psychological distress, anxiety, and academic self-efficacy with regard to study satisfaction among Peruvian university students during the COVID-19 pandemic. To do so, linear regression models were tested, and different comparative and correlational analyses were conducted.
As for the gender-based comparative analyses, the results of the study have shown that women presented higher scores for psychological distress than men, with said differences being significant. Similarly, other studies found that psychological distress is greater for women, as they have reported recent adverse events and difficulties in adapting to the academic environment more often than men (Verger et al., 2009). In other words, even with evidence of women surpassing men in some spheres, they are more prone to suffering from psychological distress (Adlaf et al., 2001; Pomerantz et al., 2002; Eisenbeck et al., 2019).
Regarding anxiety, significant differences were found in terms of gender, as women showed signs of anxiety more frequently than men. Other studies have reported similar results in different countries, both in the pre-pandemic context (Rahafar et al., 2016; Tran et al., 2018) and in the pandemic scenario (Bigalke et al., 2020; Debowska et al., 2020; Wang and Zhao, 2020; Burkova et al., 2021; Rodriguez-Besteiro et al., 2021). Additionally, there is evidence that the influence and intensity of academic anxiety are higher in women compared to men (Bhansali and Trivedi, 2008). Consequently, the fact that women present more indicators of psychological distress and anxiety than men possibly precedes the pandemic, but the pandemic context may increase these divergences (Debowska et al., 2020).
As for academic self-efficacy, this study shows significant gender-related differences. Women have lower academic self-efficacy levels than men, and these results are in line with those reported in other studies (Bondy et al., 2017; Yilmaz, 2017; Ryan and Poole, 2019). In other research reported that even when said differences are significant, the effect size is quite small (Huang, 2013). However, in this study, the effect size was large. Mohammadyari (2012) states that these differences may be the result of men’s ability and the confidence they have on their ability in contrast with women. Another explanation is that the women’s self-efficacy decreases as they progress through middle and secondary school (Assouline et al., 2020), which makes them change their focus toward non-academic objectives (Brown et al., 2019). Also, receiving feedback is considered to increase self-efficacy levels among women, which is in line with the idea that said differences are the result of men feeling more confident about their own skills than women (Bong, 1999). Conversely, given the evidence that anxiety is negatively correlated with self-efficacy (Chan, 2002), the high scores on the anxiety scale found in the female sample in the pandemic context may have had a negative impact on their beliefs about their abilities and academic performance; that is, it may have affected their self-efficacy.
With regard to study satisfaction, results show that the differences found between the answers provided by men and women are not significant. With that in mind, inconsistent results were found in the literature. This way, on the one hand, research indicates that the understanding of the variables associated with academic satisfaction may vary based on gender (Parahoo et al., 2013), while, on the other hand, studies found no evidence to corroborate the assumption that the women’s study satisfaction is different from their classmates (Thege, 2014). In any case, it is therefore necessary to address this subject from the perspective of other methodological aspects.
At the correlational level, this study also shows a significant correlation between academic self-efficacy and study satisfaction. In this sense, other research has demonstrated that both the variables are significantly related. Sivandani et al. (2013) even assert the existence of a positive influence of study satisfaction on self-efficacy (Zhen et al., 2017). However, it has also been reported that said variables do not relate to each other in the context of an environment open to remote learning (Coetzee and Oosthuizen, 2012). Conversely, it could be observed that the highest anxiety levels are significantly related to low levels of study satisfaction. Although said links are weak, evidence has shown that self-efficacy is an important predictor of the main effects of anxiety issues (Chan, 2002).
The results also show that psychological distress and anxiety are negatively related to study satisfaction. Despite their weakness, these have been considered significant at a statistical level. Although some studies show that students with lower anxiety levels are more satisfied than those showing higher levels of anxiety (Bolliger and Halupa, 2012), this is not the case of the relationship between psychological distress and study satisfaction. Thus far, we know that students’ psychological distress may influence other variables such as professional development, and it seems to negatively affect academic performance and contribute to academic dishonesty and substance abuse (Lepp et al., 2014). Several studies show that psychological distress is significantly associated with an increased risk of developing anxiety (Verger et al., 2009), and, in turn, anxiety, in the context of exams, is a significant predictor of psychological distress (Rajiah et al., 2014). Further, conversely, there is evidence of the fact that anxiety contributes to low well-being and academic performance levels (Leung et al., 2000; Antaramian, 2017; McIntyre et al., 2018).
In response to the main objective of the study, after including all the variables within a predictive model of study satisfaction, it could be observed that academic self-efficacy has a higher predictive value than psychological distress and anxiety. Thus, some studies highlight the predictive role of self-efficacy in study satisfaction and, in turn, indicate that the combination of self-efficacy and study satisfaction may be an essential mechanism to improve the academic performance of students (Chemers et al., 2001; Kostagiolas et al., 2019). These results are consistent with those of studies that point to self-efficacy as a predictor variable of academic performance in university students in the context of the pandemic (Talsma et al., 2021). A potential interpretation is that self-efficacy plays a relevant role in terms of satisfaction with studies and other variables related to academic performance of university students in a context characterized by uncertainty; therefore, it constitutes a protective variable against the risks of academic maladaptation caused by the COVID-19 pandemic. All this leads to the need to conduct further studies that provide further evidence on how said variables predict study satisfaction, as well as consider other variables, such as social support and academic performance, so they may help understand not only the predictable role but also the predictive function of study satisfaction.
The limitations of this research include, on the one hand, the exclusive use of self-reporting for the assessment of the study variables that may lead to biases related to the perception of the behavior itself. Additionally, the cross-sectional design limits the evaluation of causality between the predictor variables and the dependent variable. Future studies should address this problem using other causal or longitudinal designs (Ato et al., 2013). However, the absence of differentiated samples based on the level of responses of the educational institutions in implementing virtual teaching scenarios and the use of non-probabilistic sampling procedures limit the possibility of generalizing the results to the population. Despite the difficulties noted, the findings presented here are relevant as an approach to the study phenomenon in the broader context of higher education and seek to stimulate the development of research that delves into the problems arising from the new educational context, the impact of self-efficacy in other spheres of academic life, and the mental health of university students. Another limitation may be the presence of common method variance bias because both the predictor and outcome variables were self-reported in a cross-sectional survey. However, it is important to mention that recent studies based on statistical simulations indicated that the phenomenon must be very high (approximately more than 70%) to unduly inflate the correlations (Fuller et al., 2016). Similarly, other authors have examined the presence of common method variance in their data and found only low levels of variance bias (Schaller et al., 2015).
Thus, the significance of this research is that it highlights the importance of understanding the mechanisms that predict study satisfaction among university students to enable the implementation of effective and timely mental health policies and interventions aimed at improving academic self-efficacy and optimizing the learning experience of university students. Additionally, based on the results of this study, an increase in academic self-efficacy would translate into a decrease in psychological distress and anxiety. This, and the adoption of a comprehensive approach to mental healthcare and the welfare of the university community in a context that is particularly challenging, is essential to address the adverse effects of the pandemic.
Data Availability Statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
The studies involving human participants were reviewed and approved by Universidad Peruana Unión. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.
RCE, OM-B, and PRM conceived and designed the experiments, performed the experiments, analyzed and interpreted the data, and wrote the manuscript. TC-R and SL-H contributed reagents, materials, analysis tools, or data and wrote the manuscript. All authors contributed to the article and approved the submitted version.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Abdous, M. (2019). Influence of satisfaction and preparedness on online students’ feelings of anxiety. Inter. High. Educ. 41, 34–44. doi: 10.1016/j.iheduc.2019.01.001
Adlaf, E. M., Gliksman, L., Demers, A., and Newton-Taylor, B. (2001). The prevalence of elevated psychological distress among Canadian undergraduates: findings from the 1998 Canadian campus survey. J. Am. Coll. Health Assoc. 50, 67–72. doi: 10.1080/07448480109596009
Alegre, A. (2015). Autoeficacia académica, autorregulación del aprendizaje y rendimiento académico en estudiantes universitarios iniciales [Academic self-efficacy, self-regulation of learning and academic performance in early college students]. Propósitos Representaciones 2, 79–100. doi: 10.1017/CBO9781107415324.004
Antaramian, S. (2017). The importance of very high life satisfaction for students’ academic success. Cogent Educ. 4:1. doi: 10.1080/2331186X.2017.1307622
Aquino-Canchari, C. R., and Medina-Quispe, C. I. (2020). COVID-19 y la educación en estudiantes de medicina [COVID-19 and the education of medical students]. Revista Cubana Investigaciones Biomédicas 39:e758.
Arjanggi, R., and Shanti, L. (2016). The correlation between social anxiety and academic adjustment among freshmen. Proc. Soc. Behav. Sci 219, 104–107. doi: 10.1016/j.sbspro.2016.04.049
Assouline, S. G., Mahatmya, D., Ihrig, L., and Lane, E. (2020). High-achieving rural middle-school students’ academic self-efficacy and attributions in relationship to gender. High Abil. Stud., 32, 143–169. doi: 10.1080/13598139.2020.1740582
Ato, M., López-García, J. J., and Benavente, A. (2013). Un sistema de clasificación de los diseños de investigación en psicología [A classification system for research designs in psychology]. Anal. Psicol. 29, 1038–1059. doi: 10.6018/analesps.29.3.178511
Babar, M., Hassan, M., Hussain, S., Riaz, M., Rafiq, M., Mehmood, R., et al. (2021). Psychological impacts of COVID-19 and satisfaction from online classes: disturbance in daily routine and prevalence of depression, stress, and anxiety among students of Pakistan. Heliyon 7:e07030. doi: 10.1016/j.heliyon.2021.e07030
Balanza, S., Morales, I., and Guerrero, J. (2009). Prevalencia de Ansiedad y Depresión en una Población de Estudiantes Universitarios: factores Académicos y Sociofamiliares Asociados [Prevalence of Anxiety and Depression in a Population of University Students: associated Academic and Sociofamilial Factors]. Clin. Salud 20, 177–187.
Barboza-Palomino, M., Ventura-León, J., Caycho, T., Sandoval-Díaz, J., López-López, W., and Salas, G. (2020). Nuevo coronavirus (COVID-19): un análisis bibliométrico. Rev. Chil. Anest. 49, 408–415. doi: 10.25237/revchilanestv49n03.020
Bayham, J., and Fenichel, E. P. (2020). Impact of school closures for COVID-19 on the US health-care workforce and net mortality: A modelling study. Lancet Public Health 5, e271–e278. doi: 10.1016/S2468-2667(20)30082-7
Benites, R. (2021). Pontificia Universidad Católica del Perú. La Educación Superior Universitaria en el Perú Post-Pandemia [University Higher Education in post-pandemic Peru]. San Miguel: Pontificia Universidad Católica del Perú.
Bhansali, R., and Trivedi, K. (2008). Is academic anxiety gender specific: A comparative study. J. Soc. Sci. 17, 1–3. doi: 10.1080/09718923.2008.11892627
Bigalke, J. A., Greenlund, I. M., and Carter, J. R. (2020). Sex differences in self-report anxiety and sleep quality during COVID-19 stay-at-home orders. Biol. Sex Differ. 11:56. doi: 10.1186/s13293-020-00333-4
Bolliger, D. U., and Halupa, C. (2012). Student perceptions of satisfaction and anxiety in an online doctoral program. Dist. Educ. 33, 81–98. doi: 10.1080/01587919.2012.667961
Bondy, J. M., Peguero, A. A., and Johnson, B. E. (2017). The children of immigrants’ academic self-efficacy: the significance of gender, race, ethnicity, and segmented assimilation. Educ. Urban Soc. 49, 486–517. doi: 10.1177/0013124516644049
Bong, M. (1999). Personal factors affecting the generality of academic self-efficacy judgments: gender, ethnicity, and relative expertise. J. Exp. Educ. 67, 315–331. doi: 10.1080/00220979909598486
Britez, M. (2020). La educación ante el avance del COVID-19 en Paraguay. Comparativo con países de la Triple Frontera [Education in the face of COVID-19’s progression in Paraguay. Comparison with countries along the Triple Border]. SciELO [preprint]. doi: 10.1590/SCIELOPREPRINTS.22
Brown, T. M., Galindo, C., Quarles, B., and Cook, A. L. J. (2019). Self-efficacy, dropout status, and the role of in-school experiences among urban, young adult school-leavers and non-leavers. Urban Rev. 51, 816–844. doi: 10.1007/s11256-019-00508-3
Bulut Serin, N., Serin, O., and Özbaú, L. F. (2010). Predicting university students’ life satisfaction by their anxiety and depression level. Procedia Soc. Behav. Sci. 9, 579–582. doi: 10.1016/j.sbspro.2010.12.200
Burkova, V. N., Butovskaya, M. L., Randall, A. K., Fedenok, J. N., Ahmadi, K., Alghraibeh, A. M., et al. (2021). Predictors of anxiety in the COVID-19 pandemic from a global perspective: data from 23 countries. Sustainability 13:4017. doi: 10.3390/su13074017
Cabanach, R. G., Arias, A. V., Rodríguez, C. F., and Canedo, M. F. (2012). Relaciones entre la autoeficacia percibida y el bienestar psicológico en estudiantes universitarios. Rev. Mex. Psicol. 29, 40–48.
Caycho-Rodríguez, T. (2017a). Tamaño del efecto para diferencias de medias: aportes complementarios [Effect size for mean differences: complementary contributions]. Enfermería Intensiva 29, 48–49. doi: 10.1016/j.enfi.2017.05.001
Caycho-Rodríguez, T. (2017b). Tamaño del efecto e intervalos de confianza para correlaciones: aportes a Montes Hidalgo y Tomás-Sábado [Effect size and confidence intervals for correlations: contributions to Montes Hidalgo and Tomás-Sábado]. Enfermería Clínica 27, 331–332. doi: 10.1016/j.enfcli.2017.07.001
Caycho-Rodríguez, T. (2017c). Importancia práctica de los resultados derivados de modelos de regresión: contribuciones a Madera-Anaya et al. [Practical significance of results derived from regression models: contributions to Madera-Anaya et al.]. Enfermería Clínica 28, 277–278. doi: 10.1016/j.enfcli.2017.07.002
Caycho-Rodríguez, T. (2017d). Tamaño del efecto en análisis de regresión en investigación geriátrica: comentarios a Rubio et al. [Effect size in regression analysis in geriatric research: comments on Rubio et al.]. Rev. Esp. Geriatr. Gerontol. 53:61. doi: 10.1016/j.regg.2017.04.009
Chan, D. W. (2002). Stress, self-efficacy, social support, and psychological distress among prospective Chinese teachers in Hong Kong. Educ. Psychol. 22, 557–569. doi: 10.1080/0144341022000023635
Chau, C., and Saravia, J. C. (2014). Adaptación universitaria y su relación con la salud percibida en una muestra de jóvenes de Perú [University adaptation and its relationship with perceived health in a sample of young people in Peru]. Revista Colombiana Psicol. 23, 269–284. doi: 10.15446/rcp.v23n2.41106
Chemers, M. M., Hu, L. T., and Garcia, B. F. (2001). Academic self-efficacy and first-year college student performance and adjustment. J. Educ. Psychol. 93, 55–64. doi: 10.1037/0022-0618.104.22.168
Coetzee, M., and Oosthuizen, R. M. (2012). Students’ sense of coherence, study engagement and self-efficacy in relation to their study and employability satisfaction. J. Psychol. Africa 22, 315–322. doi: 10.1080/14330237.2012.10820536
Cohen, J. (1998). Statistical Power Analysis for the Behavioral Sciences. Hillsdale: Erlbaum.
Connor, R., Travis, G., Peace, K., Propper, B., Hale, D., Alseidi, A., et al. (2020). Using technology to maintain the education of residents during the COVID-19 pandemic. J. Surg. Educ. 77, 729–732. doi: 10.1016/j.jsurg.2020.03.018
Contreras, F., Espinosa, J. C., Esguerra, G., Haikal, A., Polanía, A., and Rodriguez, A. (2005). Autoeficacia, ansiedad y rendimiento académico en adolescentes [Self-efficacy, anxiety and academic performance in adolescents]. Perspect. Psicol. 1, 183–194. doi: 10.15332/s1794-9998.2005.0002.06
Costa, J., and Carvalho-Filho, M. (2020). Una nueva época para la educación médica después de la COVID-19 [A new era for medical education after COVID-19]. Revista Fundación Educ. Méd. 23, 55–57. doi: 10.33588/fem.232.1052
De Jesus, H., Macedo, B., and Branco, N. (2019). Transtornos mentais comuns em estudantes de medicina. Revista Bioética 27, 465–470. doi: 10.1590/1983-80422019273330
Debowska, A., Horeczy, B., Boduszek, D., and Dolinski, D. (2020). A repeated cross-sectional survey assessing university students’ stress, depression, anxiety, and suicidality in the early stages of the COVID-19 pandemic in Poland. Psychol. Med. 1–4. [Epub online ahead of print]. doi: 10.1017/S003329172000392X
Dominguez, S., Villegas, G., Yauri, C., Mattos, E., and Ramírez, F. (2012). Propiedades psicométricas de una escala de autoeficacia para situaciones académicas en estudiantes universitarios peruanos [Psychometric properties of a self-efficacy scale for academic situations in Peruvian university students]. Revista Psicol. UCSP 2, 27–39.
Dominguez-Lara, S., and Alarcón-Parco, D. (2020). Análisis estructural de la escala de malestar psicológico de Kessler (K6) en universitarios peruanos [Structural analysis of Kessler’s psychological distress scale (K6) in Peruvian university students]. Educ. Méd. 21, 155–156. doi: 10.1016/j.edumed.2019.10.008
Dominguez-Lara, S. A., and Campos-Uscanga, Y. (2017). Influence of study satisfaction on academic procrastination in psychology students: a preliminary study. Liberabit Revista Peruana Psicol. 23, 123–135. doi: 10.24265/liberabit.2017.v23n1.09
Durán, R., Estay-Niculcar, C., and Álvarez, H. (2015). Adoption of good virtual education practices in higher education. Aula Abierta 43, 77–86. doi: 10.1016/j.aula.2015.01.001
Eisenbeck, N., Carreno, D. F., and Uclés-Juárez, R. (2019). From psychological distress to academic procrastination: exploring the role of psychological inflexibility. J. Context. Behav. Sci. 13, 103–108. doi: 10.1016/j.jcbs.2019.07.007
Faul, F., Erdfelder, E., Buchner, A., and Lang, A. G. (2009). Statistical power analyses using G* Power 3.1: tests for correlation and regression analyses. Behav. Res. Meth. 41, 1149–1160. doi: 10.3758/BRM.41.4.1149
Ferguson, C. (2009). An effect size primer: A guide for clinicians and researchers. Prof. Psychol. Res. Pract. 40, 532–538. doi: 10.1037/a0015808
Flores, M., de los, Á, Chávez, M., and Aragón, L. E. (2016). Situaciones que generan ansiedad en estudiantes de Odontología. J. Behav. Health Soc. Issues 8, 35–41. doi: 10.1016/j.jbhsi.2016.11.004
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., and Babin, B. J. (2016). Common methods variance detection in business research. J. Bus. Res. 69, 3192–3198. doi: 10.1016/j.jbusres.2015.12.008
Gallegos, M., Zalaquett, C., Luna, S. E., Mazo-Zea, R., Ortiz-Torres, B., Penagoso-Corzo, J., et al. (2020). Cómo afrontar la pandemia del coronavirus (Covid-19) en las américas: recomendaciones y líneas de acción sobre salud mental [Coping with the coronavirus pandemic (Covid-19) in the Americas: mental health recommendations and courses of action]. Revista Interamericana Psicol. 54, 1–28.
Gutiérrez-García, A. G., and Landeros-Velázquez, M. G. (2018). Autoeficacia académica y ansiedad, como incidente crítico, en mujeres y hombres universitarios [Academic self-efficacy and anxiety, as a critical incident, in college women and men]. Revista Costarricense de Psicol. 37:1. doi: 10.22544/rcps.v37i01.01
Hechenleitner-Carvallo, M. I., Jerez-Salinas, A. A., and Pérez-Villalobos, C. E. (2019). Autoeficacia académica en estudiantes de carreras de la salud de una universidad tradicional chilena [Academic self-efficacy in students of health careers at a traditional Chilean university]. Revista Méd. Chile 147, 914–921. doi: 10.4067/s0034-98872019000700914
Hernandez, R., Flores-Cueto, J. J., Garay-Argandoña, R., Carranza, R. F., Mamani-Benito, O., Turpo, J., et al. (2020). Latin American scientific production on educational technology in scopus, 2010-2019. Psychol. Educ. 57, 239–244.
Herrera, L. M., and Rivera, M. S. (2011). Prevalencia De Malestar Psicológico En Estudiantes De Enfermería Relacionada Con Factores Sociodemográficos, Académicos Y Familiares [Prevalence of Psychological Distress in Nursing Students Related to Sociodemographic, Academic and Family Factors]. Ciencia Enfermería 17, 55–64. doi: 10.4067/s0717-95532011000200007
Huang, C. (2013). Gender differences in academic self-efficacy: A meta-analysis. Eur. J. Psychol. Educ. 28, 1–35. doi: 10.1007/s10212-011-0097-y
Kessler, R. C., Barker, P. R., Colpe, L. J., Epstein, J. F., Gfroerer, J. C., Hiripi, E., et al. (2003). Screening for serious mental illness in the general population. Arch. Gen. Psychiatry 60, 184–189.
Kostagiolas, P., Lavranos, C., and Korfiatis, N. (2019). Learning analytics: survey data for measuring the impact of study satisfaction on students’ academic self-efficacy and performance. Data Brief 25:104051. doi: 10.1016/j.dib.2019.104051
Kroenke, K., Spitzer, R., Williams, J., Monahan, P., and Lowe, B. (2007). Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Ann. Intern. Med. 146, 317–325. doi: 10.7326/003-4819-146-5-200703060-00004
Lepp, A., Barkley, J. E., and Karpinski, A. C. (2014). The relationship between cell phone use, academic performance, anxiety, and satisfaction with life in college students. Comput. Hum. Behav. 31, 343–350. doi: 10.1016/j.chb.2013.10.049
Leung, T. W., Siu, O. L., and Spector, P. E. (2000). Faculty stressors, job satisfaction, and psychological distress among university teachers in Hong Kong: the role of locus of control. Int. J. Stress Manag. 7, 121–138. doi: 10.1023/A:1009584202196
Liébana-Presa, C., Fernández-Martínez, M. E., Gándara, ÁR., Muñoz-Villanueva, M. C., Vázquez-Casares, A. M., and Rodríguez-Borrego, A. (2014). Psychological distress in health sciences college students and its relationship with academic engagement. Revista Escola Enfermagem 48, 715–722. doi: 10.1590/S0080-623420140000400020
McIntyre, J. C., Worsley, J., Corcoran, R., Harrison Woods, P., and Bentall, R. P. (2018). Academic and non-academic predictors of student psychological distress: the role of social identity and loneliness. J. Mental Health 27, 230–239. doi: 10.1080/09638237.2018.1437608
Merino-Soto, C., Dominguez-Lara, S., and Fernández-Arata, M. (2017). Validación inicial de una Escala Breve de Satisfacción con los Estudios en estudiantes universitarios de Lima [Initial validation of a Brief Satisfaction with Studies Scale in university students in Lima]. Educ. Méd. 18, 74–77. doi: 10.1016/j.edumed.2016.06.016
Micin, S., and Bagladi, V. (2011). Salud Mental en Estudiantes Universitarios: incidencia de Psicopatología y Antecedentes de Conducta Suicida en Población que Acude a un Servicio de Salud Estudiantil [Mental Health in University Students: incidence of Psychopathology and History of Suicidal Behavior in the Population Attending a Student Health Service]. Terapia Psicol. 29, 53–64. doi: 10.4067/s0718-48082011000100006
Mohammadyari, G. (2012). Comparative study of relationship between general perceived self-efficacy and test anxiety with academic achievement of male and female students. Proc. Soc. Behav. Sci. 69, 2119–2123. doi: 10.1016/j.sbspro.2012.12.175
Palenzuela, D. (1983). Construcción y validación de una escala de autoeficacia percibida específica de situaciones académicas [Construction and validation of a scale of perceived self-efficacy specific to academic situations]. Análisis Modificación Conducta 9, 185–219.
Parahoo, S. K., Harvey, H. L., and Tamim, R. M. (2013). Factors influencing student satisfaction in universities in the Gulf region: does gender of students matter? J. Market. High. Educ. 23, 135–154. doi: 10.1080/08841241.2013.860940
Peña-Otero, D., Díaz-Pérez, D., De-la-Rosa-Carrillo, D., and Bello-Dronda, S. (2020). Are We Ready for the New Coronavirus? Arch. Bronconeumol. 56, 195–196. doi: 10.1016/j.arbres.2020.02.009
Pérez, E. R., and Medrano, L. A. (2010). Análisis factorial exploratorio: bases conceptuales y metodológicas. Rev. Argent. Cienc. Comport. 2, 58–66.
Phinder-Puente, M., Sánchez-Cardel, A., Romero-Castellanos, F., Vizcarra-Garcia, J., and Enrique, S.-V. (2014). Percepción sobre factores estresantes en estudiantes de Medicina de primer semestre, sus padres y sus maestros [Perception of stressors in first-semester medical students, their parents and teachers]. Invest. Educ. Méd. 3, 139–146. doi: 10.1016/s2007-5057(14)72740-1
Pomerantz, E. M., Altermatt, E. R., and Saxon, J. L. (2002). Making the grade but feeling distressed: gender differences in academic performance and internal distress. J. Educ. Psychol. 94, 396–404. doi: 10.1037/0022-0622.214.171.1246
Rahafar, A., Maghsudloo, M., Farhangnia, S., Vollmer, C., and Randler, C. (2016). The role of chronotype, gender, test anxiety, and conscientiousness in academic achievement of high school students. Chronobiol. Int. 33, 1–9. doi: 10.3109/07420528.2015.1107084
Rajiah, K., Coumaravelou, S., and Ying, O. W. (2014). Relationship of test anxiety, psychological distress and academic motivation among first year undergraduate pharmacy students. Int. J. Appl. Psychol. 2014, 68–72. doi: 10.5923/j.ijap.20140402.04
Reyes, C., Monterrosas, A., Navarrete, A., Acosta, E., and Torruco, U. (2017). Ansiedad de los estudiantes de una facultad de medicina mexicana, antes de iniciar el internado [Anxiety in Mexican medical school students prior to starting their internships]. Stud. Educ. Méd. 6, 42–46. doi: 10.1016/j.riem.2016.05.004
Rodrigo, L. (2016). Educación universitaria, formando profesionales y personas [University education, training professionals and people]. Revista Fundación Educ. Méd. 19:281. doi: 10.33588/fem.196.861
Rodríguez, M. Á, Crespo, I., and Olmedillas, H. (2020). Exercising in times of COVID-19: what do experts recommend doing within four walls? Revista Española Cardiol. (in press), 18–20. doi: 10.1016/j.rec.2020.04.001
Rodriguez-Besteiro, S., Tornero-Aguilera, J. F., Fernández-Lucas, J., and Clemente-Suárez, V. J. (2021). Gender differences in the COVID-19 pandemic risk perception, psychology and behaviors of spanish university students. Int. J. Environ. Res. Public Health 18:3908. doi: 10.3390/ijerph18083908
Ryan, E., and Poole, C. (2019). Impact of virtual learning environment on students’ satisfaction, engagement, recall, and retention. J. Med. Imag. Rad. Sci. 50, 408–415. doi: 10.1016/j.jmir.2019.04.005
Schaller, T. K., Patil, A., and Malhotra, N. K. (2015). Alternative techniques for assessing common method variance: an analysis of the theory of planned behavior research. Organ. Res. Meth. 18, 177–206. doi: 10.1177/1094428114554398
Shen, D., Cho, M., Tsai, C., and Marra, R. (2013). Unpacking online learning experiences: online learning self-efficacy and learning satisfaction. Inter. High. Educ. 19, 10–17. doi: 10.1016/j.iheduc.2013.04.001
Sivandani, A., Koohbanani, S. E., and Vahidi, T. (2013). The Relation Between Social Support and Self-efficacy with Academic Achievement and School Satisfaction among Female Junior High School Students in Birjand. Proc. Soc. Behav. Sci. 84, 668–673. doi: 10.1016/j.sbspro.2013.06.623
Suárez, J., Bedoya, L., Posada, M., Arboleda, E., Urbina, A., Ramírez, S., et al. (2021). Percepción de los estudiantes sobre adaptaciones virtuales en cursos de anatomía humana por la contingencia SARS-CoV-2 [Student perceptions of virtual adaptations in human anatomy courses due to the SARS-CoV-2 contingency]. Acad. Virtual. 14, 151–168. doi: 10.18359/ravi.5275
Talsma, K., Robertson, K., Thomas, C., and Norris, K. (2021). COVID-19 beliefs, self-efficacy and academic performance in first-year university students: cohort comparison and mediation analysis. Front. Psychol. 12:2289. doi: 10.3389/fpsyg.2021.643408
Tarek, A., and Hubbard, N. (2015). Self-Determination Theory: opportunities and Challenges for Blended e-Learning in Motivating Egyptian Learners. Proc. Soc. Behav. Sci. 182, 513–521. doi: 10.1016/j.sbspro.2015.04.836
Thege, B. (2014). “Women in Male-Dominated Technology Study Programmes – Findings of a Survey Conducted at the Kiel University of Applied Sciences,” in Paths to Career and Success for Women in Science, eds B. Thege, S. Popescu-Willigmann, R. Pioch, and S. Badri-Höher (Wiesbaden: Springer VS), doi: 10.1007/978-3-658-04061-1_7
Tomás, J., and Gutiérrez, M. (2019). Aportaciones de la teoría de la autodeterminación a la predicción de la satisfacción académica en estudiantes universitarios [Contributions of self-determination theory to the prediction of academic satisfaction in college students]. Revista Invest. Educ. 37, 471–485. doi: 10.6018/rie.37.2.328191
Tran, A. G. T. T., Lam, C. K., and Legg, E. (2018). Financial Stress, Social Supports, Gender, and Anxiety During College: A Stress-Buffering Perspective. Counseling Psychol. 46, 846–869. doi: 10.1177/0011000018806687
Van, W., and Parolin, Z. (2020). COVID-19, school closures, and child poverty: a social crisis in the making. Lancet Public Health 5, e243–e244. doi: 10.1016/S2468-2667(20)30084-0
Verger, P., Combes, J. B., Kovess-Masfety, V., Choquet, M., Guagliardo, V., Rouillon, F., et al. (2009). Psychological distress in first year university students: socioeconomic and academic stressors, mastery and social support in young men and women. Soc. Psychiatry Psychiatr. Epidemiol. 44, 643–650. doi: 10.1007/s00127-008-0486-y
Vilela, P., Sánchez, J., and Chau, C. (2021). Desafíos de la educación superior en el Perú durante la pandemia por la covid-19 [Challenges for higher education in Peru during the COVID-19 pandemic]. Desde Sur 13:e0016. doi: 10.21142/des-1302-2021-0016
Wang, C., and Zhao, H. (2020). The impact of COVID-19 on anxiety in Chinese university students. Front. Psychol. 11:1168. doi: 10.3389/fpsyg.2020.01168
Wang, J., Chia, W., Hwa, Y., and KhoOn, L. (2019). Competence, autonomy, and relatedness in the classroom: understanding students’ motivational processes using the self-determination theory. Heliyon 5:e01983. doi: 10.1016/j.heliyon.2019.e01983
Warhadpande, S., Minhaj, M., Khaja, S., Saher, S., and Sabri, S. (2020). The Impact of COVID-19 on Interventional Radiology Training Programs: what You Need to Know. Acad. Radiol. 27, 868–871. doi: 10.1016/j.acra.2020.04.024
Yilmaz, R. (2017). Exploring the role of e-learning readiness on student satisfaction and motivation in flipped classroom. Comput. Hum. Behav. 70, 251–260. doi: 10.1016/j.chb.2016.12.085
Yu, S., and Levesquel-Bristol, C. (2020). A cross-classified path analysis of the self-determination theory model on the situational, individual and classroom levels in college education. Contemp. Educ. Psychol. 61:101857. doi: 10.1016/j.cedpsych.2020.101857
Zhen, R., Liu, R., De Ding, Y., Wang, J., Liu, Y., and Xu, L. (2017). The mediating roles of academic self-efficacy and academic emotions in the relation between basic psychological needs satisfaction and learning engagement among Chinese adolescent students. Learn. Individ. Differ. 54, 210–216. doi: 10.1016/j.lindif.2017.01.017
Keywords: psychological distress, anxiety, academic self-efficacy and study satisfaction, predictive analysis, university students, Peru
Citation: Carranza Esteban RF, Mamani-Benito O, Caycho-Rodriguez T, Lingán-Huamán SK and Ruiz Mamani PG (2022) Psychological Distress, Anxiety, and Academic Self-Efficacy as Predictors of Study Satisfaction Among Peruvian University Students During the COVID-19 Pandemic. Front. Psychol. 13:809230. doi: 10.3389/fpsyg.2022.809230
Received: 04 November 2021; Accepted: 31 March 2022;
Published: 25 April 2022.
Edited by:Meryem Yilmaz Soylu, Georgia Institute of Technology, United States
Reviewed by:Lorena Valdivieso-León, University of Valladolid, Spain
Asghar Afshar Jahanshahi, University of the Americas Puebla, Mexico
Copyright © 2022 Carranza Esteban, Mamani-Benito, Caycho-Rodriguez, Lingán-Huamán and Ruiz Mamani. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Renzo Felipe Carranza Esteban, firstname.lastname@example.org