http://dx.doi.org/10.24016/2022.v8.289
ORIGINAL ARTICLE
Academic self-efficacy as a protective factor for the
mental health of university students during the COVID-19 pandemic
La autoeficacia académica como factor
protector de la salud mental en estudiantes universitarios durante la pandemia
de COVID-19
Nayeli Lucía Ampuero-Tello 1, Angel Christopher Zegarra-López 1,2 *, Dharma
Ariana Padilla-López 1, Dafne Silvana Venturo-Pimentel 1
1 Círculo de
Investigación en Psicología, Facultad de Psicología, Universidad de Lima, Lima,
Peru.
2 Grupo de
Investigación en Psicología, Bienestar y Sociedad, Instituto de Investigación
Científica, Universidad de Lima, Lima, Peru.
* Correspondence: Facultad de Psicología, Universidad de Lima. 4600
Avenue Javier Prado Este, Santiago de Surco, Lima, 15023, Peru.
E-mail: azegarra@ulima.edu.pe.
Received: September 05,
2022. | Revised: November 01,
2022. | Accepted: December 08,
2022. | Published Online: December 28,
2022.
Ampuero-Tello, N., Zegarra-López, A., Padilla-López,
D., & Venturo-Pimentel, D. (2022). Academic
self-efficacy as a protective factor for the mental health of university
students during the COVID-19 pandemic. Interacciones, 8,
e289. http://dx.doi.org/10.24016/2022.v8.289
ABSTRACT
Background: University students are vulnerable to developing mental health problems
due to constant exposure to academic demands. A situation that has been
exacerbated by the COVID-19 pandemic and observed in several recent studies.
Therefore, current practices require further research and identification of
potentially protective factors for mental health. Objective: This study aimed
to analyze academic self-efficacy as a protective factor against depression,
anxiety, and stress in university students. Methods: A cross-sectional
design was used with 3525 university students from Lima, Peru. The prevalence
of depression, anxiety, and stress was measured using the DASS-21. Academic
self-efficacy was measured with the EPAESA and defined as a predictor of the
three mental health conditions. Structural equation modeling was used to test
the model, together with a multigroup analysis for gender and working status. Results: One-third of the
sample had severe to extremely severe symptoms of depression, anxiety, and
stress. Academic self-efficacy was a moderately statistically significant
predictor of the three mental health conditions. Relationships were invariant
to gender and working status.
Conclusions: Self-efficacy can be
considered a protective factor for mental health. Interventions to promote
academic self-efficacy may be effective in reducing depression, anxiety, and
stress in university students. The findings are discussed together with current
studies on the topic.
Keywords: Self Efficacy, Mental health, Depression, Anxiety, Stress, Higher
Education, University Students, COVID-19.
RESUMEN
Antecedentes: los
estudiantes universitarios son propensos a desarrollar problemas de salud
mental debido a la exposición constante a las exigencias académicas. Una
situación que se ha agravado con la pandemia de COVID-19 y se ha observado en
varios estudios contemporáneos. Por esta razón, las prácticas actuales
requieren más investigación e identificación de posibles factores protectores
de la salud mental. Objetivo: El
objetivo de este estudio fue analizar la autoeficacia académica como factor
protector frente a la depresión, la ansiedad y el estrés en estudiantes
universitarios. Método: Se realizó
un diseño transversal en 3525 estudiantes universitarios de Lima, Perú. La
prevalencia de depresión, ansiedad y estrés se midió con el DASS-21. La
autoeficacia académica se midió con la escala EAPESA y se definió como
predictor de las tres condiciones de salud mental. Se llevó a cabo un enfoque
de modelado de ecuaciones estructurales para probar el modelo junto con un
análisis multigrupo con respecto al sexo y la situación laboral. Resultados: Un tercio de la muestra
presentó síntomas severos a extremadamente severos de depresión, ansiedad y
estrés. La autoeficacia académica fue un predictor estadísticamente
significativo moderado de las tres condiciones de salud mental. Las relaciones
fueron invariantes en cuanto al sexo y la situación laboral. Conclusiones: La autoeficacia puede
considerarse como un factor protector de la salud mental. Las intervenciones
para fomentar la autoeficacia académica podrían ser efectivas para reducir la
depresión, la ansiedad y el estrés en estudiantes universitarios. Los hallazgos
se discuten junto con los estudios contemporáneos sobre el tema.
Palabras clave: Autoeficacia, Salud mental, Depresión, Ansiedad,
Estrés, Educación Superior, Estudiantes Universitarios, COVID-19.
BACKGROUND
The COVID-19 pandemic posed an unprecedented challenge
to governments around the world due to its alarming contagiousness and severity
of symptoms (Krishnan et al., 2021). Since the World Health Organization (WHO)
declared it a pandemic on March 11, 2020, most countries have opted to
implement lockdown and social distancing measures to contain its spread. As a
result, organizations that are not essential to governments, such as
educational institutions, have been forced to adapt from a face-to-face to a
remote methodology. Preparing for distance learning requires addressing several
immediate challenges related to access to digital connectivity and adapting
pedagogical teaching strategies to a virtual context to ensure appropriate
learning (United Nations Educational, Scientific and Cultural Organization
[UNESCO], 2020). Nevertheless, various economic, social, and health factors
have affected the academic performance of university students during the
pandemic (Aucejo et al., 2020; Reyes-Portillo et al.,
2022). Among these, students' mental health was one of the most affected
factors, consistently reported in several studies (e.g., Chen & Lucock, 2022; Elharake et al.,
2022).
According to the World Health Organization (WHO,
2022), mental health is essential to the overall well-being of a person. In
this sense, mental health problems are considered the leading cause of
disability and a fundamental public health problem worldwide. During the
COVID-19 pandemic, a greater emphasis was placed on the mental health of
vulnerable socio-demographic groups, such as university students (Son et al.,
2020). For most universities, social restrictions imposed strict social
learning measures, which became a constant stressor for students as it required
greater effort to adapt to a new learning approach and to cope with
pandemic-related stressors (Ghazawy et al., 2021).
Indeed, previous research has already shown that university students tend to
experience stress, anxiety, and depression due to the stressful nature of
academic demands (Limone & Toto, 2022).
Indeed, adolescents and young adults are vulnerable to
mental health problems (Nobre et al., 2021), such as
depression, anxiety, and stress are common in this socio-demographic group (Das
et al., 2016; García-Carrión et al., 2019; Silva et
al., 2020). Also, mental disorders affect motivation, concentration, and social
interactions, which are relevant aspects of the academic performance of
university students (Son et al., 2020). Furthermore, mental disorders rank high
among the factors that hinder academic success (Agnafors
et al., 2021). Globally, between 12 and 50% of university students meet at
least one diagnostic criterion for one or more mental disorders (Bruffaerts et al., 2018). However, recent studies have
shown an increase in mental health conditions due to the COVID-19 pandemic and
social distancing measures (e.g., Xiong et al., 2020;
Tsamakis et al., 2021; Jones et al., 2021; Chadi et
al., 2022).
In Peru, university students usually belong to
adolescence and early adulthood, being between 15 and 29 years old. The
Peruvian Ministry of Health (MINSA, 2020) estimates that 20% of the adult
population has mental health problems, highlighting stress, depression, and
anxiety. Ruiz-Frutos et al. (2021) found that
approximately 59% of Peruvian adults suffered from high levels of psychological
distress during the first year of the COVID-19 pandemic. In addition, Antiporta et al. (2021) showed that the pandemic had a
drastic effect on the general mental health of the Peruvian population, with
three out of ten participants reporting moderate to severe symptoms of
depression. Notably, the prevalence of these symptoms was five times higher
than the national level reached in 2018. In addition, Figueroa-Quiñones et al (2022) conducted a study on university
students during the pandemic and showed that 75% of students had mild to severe
symptoms of depression, as well as multiple difficulties in performing daily
activities, pain, and general discomfort, which significantly affected their
quality of life.
In the context of the increasing prevalence of mental
health problems, studies are needed to identify potential protective factors
against these problems in university students. This study aimed to assess
academic self-efficacy as a potential protective factor. Self-efficacy, a
concept proposed by Albert Bandura, refers to an individual's assessment of
their abilities and capabilities to perform tasks of varying difficulty levels.
Self-efficacy emphasizes an individual's past performance (Bong & Clark,
1999). Along with goal setting, self-efficacy is one of the most relevant
motivational predictors of how well people will perform in almost any activity.
This means that self-efficacy is a powerful determinant of people's effort,
persistence, strategy, training, and job performance (Heslin
et al., 2017). In academic contexts, self-efficacy is defined as an
individual's belief that they will be able to perform assigned academic tasks
at a given level. Several studies on academic self-efficacy have found that it
is directly related to perceived academic performance, stress, general
satisfaction, school attendance, school adjustment, and problem-coping behavior
(Karakose et al., 20-23).
In the academic context, it is necessary to consider
self-efficacy, as students with high self-efficacy set more complex goals and
show high commitment to achieving them. In addition, positive self-efficacy is
a predictor of good academic performance (Yokoyama, 2019). Furthermore,
self-efficacy has a strong correlation with mental health, which has been
demonstrated in the results of different studies (e.g., Grøtan
et al., 2019; García-Álvarez et al., 2021). For example, Tak
et al. (2017) shows that there is a negative relationship between academic
self-efficacy and depressive symptoms in early to middle adolescence. This
finding is echoed by Tahmassian and Jalali Moghadam (2011), who also found a negative
relationship between academic self-efficacy and anxiety. Furthermore, Sabouripour et al. (2021) state that self-efficacy is
crucial for stress management as it influences the evaluation of stressors and
allows the correct implementation of methods to deal with them. In this sense,
effective coping strategies to deal with stressors are associated with higher
student self-efficacy (Freire et al., 2020).
As mentioned above, symptoms of
depression, anxiety, and stress are considered important indicators of mental
health that can negatively affect well-being (Wainberg
et al., 2017). This study focused on one protective factor within the academic
context, academic self-efficacy, as a potentially protective factor against the
three aforementioned mental health conditions during the first year of the
COVID-19 pandemic. As shown in the literature, the pandemic itself brought
several stressors, and for university students, most of them are related to
changes in their academic efforts and well-being (e.g., Oliveira Carvalho et
al., 2021; Sauer et al., 2022; Werner et al., 2021). For this reason, we
hypothesize that higher academic self-efficacy in university students will be
associated with less severe symptoms of depression, anxiety, and stress.
Therefore, this study aimed to determine the predictive role of academic
self-efficacy on depression, anxiety, and stress in university students
residing in Lima Metropolitana, Peru, during the
first year of the COVID-19 pandemic.
METHOD
Participants
A sample of 3525 undergraduate university students
from Lima, Peru was recruited. Inclusion criteria included participants who
were at least 18 years old and enrolled in correspondence courses during the
2020 academic year. Data were collected through an online survey that indicated
the voluntary nature of participation and informed consent, which had to be
accepted before answering further questions. The sample consists of 32.40%
males and 67.60% females, aged between 18 and 28 years (M=20.52, SD=2.00). In
addition, 20.79% of the sample reported that they were working or in pre-professional
work placements alongside their respective studies, and the remaining 79.21%
were studying full-time.
Instruments
Academic Self-Efficacy
Academic self-efficacy is defined as students' own
beliefs about their ability to organize and perform actions related to the
achievement of academic goals (Bandura, 2001). In the present study, this
variable is operationalized by the Specific Perceived Self-Efficacy Scale for
Academic Situations (EAPESA; Palenzuela, 1983). The
original version consists of 10 items. However, it was decided to use a 9-item
version resulting from the adaptation study of the scale in Peruvian university
students. The format corresponds to Likert-type items with four response
alternatives, from never to always. In terms of its psychometric properties, a
high internal consistency indicates a high reliability (ω=.933) and an excellent fit to a unidimensional model
that reports validity based on its internal structure.
Mental Health
Mental health is measured as symptoms of depression,
anxiety, and stress experienced by university students and is operationalized
in the Spanish versions of the Depression, Anxiety, and Stress Scales (DASS). Lovinbond and Lovinbond (1995)
proposed the original 42-item scale; however, Antony et al. (1998) showed that
a shortened 21-item version retained fair to excellent psychometric properties
and the ability to discriminate features of depression, stress, and anxiety as
well as the full version. Both versions have been renamed DASS-42 and DASS-21
respectively. In the present study, the Spanish version of the DASS-21 is used,
where the items are presented with a four-level response scale from “Did not apply to me at all” to “Applied to me very much or most of the time”.
The total scores of the DASS-21 can be used to categorize people into symptom
severity levels: None, Mild, Moderate, Severe, and Extremely severe. In terms of its
psychometric properties, high internal consistency was found for the three
subscales (ω=.848-.932), indicating strong evidence of
reliability. In addition, an excellent fit to a multidimensional correlated
3-factor model provided evidence of validity based on its internal structure.
Data Analysis
Procedures
The data analysis is based on a structural equation
modeling (SEM) approach, an analytical technique that integrates the modeling
of latent variables through the fitting of measurement models and the analysis
of their relationships through structural models (Wang & Wang, 2020). In
this way, SEM uses the matrix of covariances or correlations of the observed
data for the joint estimation of the parameters of a model and the evaluation
of its respective fit, without having to rely on the estimation of overall
scores that ignore the theoretical models proposed for the latent variables (McNeish & Wolf, 2020), although this may be useful in
certain circumstances (Widaman & Revelle, 2022).
First, an exploratory analysis is presented together
with the distribution of severity of depression, anxiety, and stress as an
approximation of the prevalence of these mental health conditions in the
observed sample. Subsequently, the measurement models for the EAPESA and
DASS-21 are tested using confirmatory factor analysis (CFA; Brown, 2015),
together with the estimation of reliability measures with the omega coefficient
when assuming a congeneric model (Cho, 2016).
The structural models are then evaluated against the
main conceptual hypothesis of the study. The evaluation of the models is
developed considering the Comparative Fit Index (CFI), Root Mean Squared Error
of Approximation (RMSEA), and Standardized Root Mean Square Residual (SRMR)
indicators. Values of CFI≥.95, RMSEA≤.05, and SRMR≤.06 are established as
indicators of excellent fit, while CFI≥.90, RMSEA≤.08, and SRMR≤.08 suggest an
adequate value (Keith, 2019). The analyses are developed taking into account
polychoric correlation matrices, consistent with the ordinal nature of the
variables. The WLSMV estimator will be used in congruence with the use of
polychoric matrices and is robust to deviations from normality (Li, 2016).
To end with, a multigroup analysis is carried out to
assess the invariance of the proposed relationships regarding sex and work
status. We follow the modern approach shown by Svetina
et al. (2020) which is an applied demonstration of Wu and Estabrook (2016)
approach to assess measurement invariance for ordered categorical outcomes in
which a baseline model is established, followed by subsequent models where the
thresholds and loadings are constrained. Then, we analyzed the structural
invariance by constraining the latent variable variances, covariances, and
regressions. Incremental indexes ΔCFI, ΔRMSEA, and ΔSRMR were used to determine
invariance following common suggestions by Chen (2007), Rutkowski and Svetina
(2014;2017), and Svetina and Rutkowski (2017).
Ethical
considerations
The participants completed an online questionnaire
after expressing their informed consent. The research project was accepted by
the Comité de Investigación
y Ética (CIE) of the Faculty of Psychology of the
Universidad de Lima.
RESULTS
Prevalence of
Depression, Anxiety and Stress and Exploratory Analysis
An approximation of the prevalence of the severity of
depression, anxiety, and stress in the sample of university students is
presented in Figure 1. As can be seen, the distribution of severity in the
three mental health conditions explored denotes that approximately one-third of
the sample experienced severe to extremely severe symptoms of all three
conditions. In the same way, most participants presented a degree of severity
that is mild at best. The similarities in the observed distributions represent
empirical evidence about the relationship between the mental health conditions
studied, which means that correct modeling of these variables must recognize
their respective relationship.
Figure 1. Prevalence of Depression, Anxiety, and Stress in University
Students.
A set of descriptive statistics on the total scores is
presented in Table 1, as an exploratory analysis of the distribution of the
observed measures. Additionally, no atypical response patterns were identified
in the data set; however, floor effects were identified for the three mental
health measures and a ceiling effect was identified for the academic
self-efficacy measure. The presence of both indicators supposes limitations
that were addressed by using robust estimation methods towards non-normality.
Table 1. Descriptive
Statistics of Depression, Anxiety, and Stress Total Scores
|
Variable |
M |
SD |
Med |
γ₁ |
γ₂ |
|
Depression |
16.178 |
11.315 |
14 |
0.465 |
-0.724 |
|
Anxiety |
11.956 |
9.741 |
10 |
0.902 |
0.203 |
|
Stress |
18.615 |
9.956 |
18 |
0.199 |
-0.624 |
|
Academic
Self-Efficacy |
24.069 |
5.923 |
24 |
0.037 |
-0.500 |
Note. M = Mean, SD = Standard Deviation, Med = Median, γ₁ = Skewness, γ₂ = Kurtosis.
Measurement
Models
The one-dimensional measurement model proposed for the
EAPESA scale showed an excellent fit to the empirical data X2(27)=743.010, CFI=.990, RMSEA=.087 (90% CI .081-.092),
SRMR=.026. High factor loadings were found for all 9 items ranging from λ=0.732
to λ=0.883. These measures denoted a high observed internal consistency ω=.933 and average explained variance AVE=0.683. In the
same way, the multidimensional 3-factor model proposed for the DASS-21 scale
presents an appropriate fit to the empirical data X2(186)=6042.479,
CFI=.936, RMSEA=.095 (90% CI .092-.097), SRMR=.054, with high factor loadings,
internal consistency, and average explained variance for depression λ=.650-.882,
ω=.921, AVE=.672 ; anxiety λ=.474-.871, ω=.848, AVE=.524; and stress
λ=.681-.847, ω=.932, AVE=.561.
Structural
Model
The identified relationships supported the suitability
of the proposed model. Figure 2 presents the theoretical model proposed in this
study, with the respective estimated parameters. In summary, the estimated
model presents an excellent fit to the data X2(399)=5700.779,
CFI=.959, RMSEA=.061 (90% CI .060-.063), SRMR=.046. A moderate effect size was
found in the negative statistically significant relationship between perceived
academic self-efficacy and depression β=-.451, p<.001; anxiety β=-.357, p<.001; and stress β=-.337, p<. 001. Since the initial proposed model
showed an excellent fit to the empirical data, no ex post facto modifications
were made.
Figure 2. Proposed Structural Model for the Relationship Between
Academic Self-Efficacy on Depression, Anxiety and Stress.
Multigroup
Models
To further test the proposed model, a multigroup
analysis was carried out and its results are shown in Table 2. We found
supporting evidence for thresholds and loadings invariances regarding sex and
work status which denotes evidence for measurement invariance. Additionally,
structural invariance was supported for both sex and work status groups,
denoting invariant latent variable variances and covariances, as well as the
proposed regression paths on the structural model. As a reference, the
parameters estimated in the configural models are shown in Figure 3 to show no
practical differences regarding both sex and work status.
Table 2. Multigroup Analysis Regarding Sex and Work
Status.
|
Model |
χ² (df) |
CFI |
∆CFI |
RMSEA (CI 90%) |
∆RMSEA |
SRMR |
∆SRMR |
|
|
Sex |
Baseline |
5902.396 (798) |
.959 |
- |
.060 (.059, .062) |
- |
.048 |
- |
|
Thresholds invariance |
6179.408 (854) |
.957 |
-.002 |
.059 (.058, .061) |
-.001 |
.048 |
.000 |
|
|
Thresholds and loadings invariance |
6110.116 (880) |
.958 |
.001 |
.058 (.057, .059) |
-.001 |
.048 |
.000 |
|
|
Structural invariance |
4196.830 (890) |
.974 |
.024 |
.046 (.045, .047) |
-.012 |
.048 |
.000 |
|
|
Work status |
Baseline |
5785.346 (798) |
.960 |
- |
.060 (,058, 061) |
- |
0.047 |
- |
|
Thresholds invariance |
5933.104 (854) |
.959 |
-.001 |
.058 (.057, .060) |
-.002 |
0.047 |
.000 |
|
|
Thresholds and loadings invariance |
5892.764 (880) |
.959 |
.000 |
.057 (.055, .058) |
-.001 |
0.047 |
.000 |
|
|
Structural invariance |
3977.289 (890) |
.975 |
.024 |
.044 (.043, .046) |
-.013 |
0.048 |
.001 |
Note:
χ² = Chi-squared
value, df = degrees of freedom, CFI = Comparative Fit
Index, RMSEA = Root Mean Square Error of Approximation, CI = Confidence
intervals. SRMR = Standardized Root Mean Square Residual. ∆CFI = Change in CFI.
∆RMSEA = Change in RMSEA. ∆SRMR = Change in SRMR.
Figure 3. Estimated Parameters on the Configural Models
Regarding Sex and Work Status.
DISCUSSION
Most university students face multiple challenges in
the transition towards accessing higher education such as the need to adapt to
academic demands in a highly competitive environment while still learning to
make independent decisions about their lives and careers (Bruffaerts
et al., 2018; Hernández-Torrano et al., 2020). These
challenges impose psychological distress in a way that the probability of
suffering from mental health problems such as anxiety and depression can be six
times higher for graduate students than for the general population (Evans et
al., 2018). For this reason, there is a growing need to strengthen policies to
address mental health problems on university students, as well as increasing
the studies to further understand the burden of mental health challenges and
potential coping mechanisms (Grando Gaiotto et al., 2021; Nair & Otaki, 2021). In addition,
the COVID-19 pandemic brought a stronger need to address mental health problems
in university students, since several studies show an increase in prevalence of
psychological distress and multiple negative repercussions for this
sociodemographic group (e.g., Antiporta et al., 2021;
Chen & Lucock, 2022). In response to this need,
it is necessary and important to identify protective factors to mental health
problems in university students. Since academic demands are among the most
related factors to psychological distress on university students, the aim of
this study is to propose academic self-efficacy as a potential protective
factor against mental health problems. Self-efficacy is defined as the judgment
that a person has about their own skills and abilities in order to achieve
success in different tasks with different levels of complexity (Bandura, 2001).
In the academic field, self-efficacy allows university students to propose
complex tasks and commit themselves, to a greater extent, to carrying them out.
Academic self-efficacy is significantly related to psychological well-being and
mental health, since several authors have found that a higher confidence to
address academic tasks has a negative relationship with mental health
disorders, such as depression, anxiety, and stress (e.g., Tak
et al., 2017; Tahmassian & Jalali
Moghadam, 2011; Sabouripour et al., 2021; Freire et
al., 2020).
In correspondence to several studies on the prevalence
of mental health problems on university students during the COVID-19 pandemic
(e.g., Chen & Lucock, 2022; Li et al., 2021; Wang
et al., 2021; Chang et al., 2021), we found that approximately one third of the
sample experienced severe to extremely severe symptoms of depression, anxiety,
and stress. In most cases, students faced a disruption on their lives during
the pandemic such as the feelings of loneliness due to the social isolation
practices, lack of financial resources which increased stress and implied poor
nutrition and housing, as well as the need to keep adapting to academic demands
(Sauer et al., 2022). As such evidence persists, researchers conclude that
there is a strong need for providing mental health care resources to university
students, not only by their educational institution (Copeland et al., 2021),
but also as a government policy (Chen et al., 2020).
Regarding academic self-efficacy as a potential
protective factor, we observed a statistically significant negative
relationship with depression, with a moderate effect size. As noted, our
results are consistent with previous findings on the literature (e.g., Tak et al., 2017). García-Méndez and Rivera (2020) argued
that a severe experience of depressive symptoms implies a constant negative
perspective on current and future events as well as a lack of confidence in
one’s own abilities. On the contrary, a higher academic self-efficacy allows
university students to be aware and have confidence in their own abilities and
skills in different academic tasks. In this way, a positive self-perspective
towards reaching academic goals may prevent a pessimistic thinking about future
academic endeavors and even allowing students to see academic challenges as
opportunities to develop instead of potential stressors (Chen et al., 2020; Krifa et al., 2022).
With respect to anxiety, our results denote a moderate
statistically significant relationship with academic self-efficacy. Previous
studies have consistently found that a strong believe in one’s capability to
achieve academic goals is related to a lesser experience of anxiety-related
symptoms on undergraduate students (Tahmassian & Jalali, 2011; Faramarzi & Khafri, 2017; Hood et al., 2020). To further understand
this relationship, it is important to note that anxiety is characterized by the
persistent presence of worried thoughts and concerns either internal or
external that often provoke the avoidance of certain situations as well as the
experience of physical symptoms such as dizziness, trembling, increased heart
rate, among others (Craske et al., 2017). In this
sense, having a strong sense of credibility on one’s abilities reduces
uncertainty and concerns regarding academic chores while also reducing potential
avoidance behaviors such as absences or dropout. As Bandura (2007) stated,
persons believing in one’s ability to control potential treats are not
perturbed by them; in contrast, a low self-efficacy will experience high levels
of anxiety.
With reference to stress, a statistically significant
negative relationship was identified with academic self-efficacy, with a
moderate effect size. This finding is consistent with several investigations
that address the strong relationship between self-efficacy and positive
adaptation to stressful situations (Cattelino et al.,
2021; Freire et al., 2020). In fact, if a student has better strategies for
coping with stress, they will be able to feel more confident about their own
capabilities, thus they will achieve their academic goals; however, if a
student does not have efficient coping strategies towards stress, their
academic self-efficacy would be affected in such a way that the student would
not be able to successfully complete their assignments because they will not
feel capable of doing them and will experience chores as potential stressors
(Mete, 2021). In addition, Sabouripour et al. (2021)
denote that self-efficacy is important to effectively manage stress since one’s
beliefs on their own capabilities influence the way in which they assess
potential stressors and, in an academic environment, such assessment would lead
to a more efficient assignment of coping strategies do deal with academic
stressors (Freire et al., 2020). Furthermore, Meyer et al. (2022) explains that
self-efficacy can act as a mediator between a person’s beliefs regarding
COVID-19 and the potential stressful effects of the pandemic, suggesting that
fostering self-efficacy can lead to reducing the impact of stressing factors.
Further multigroup analyses revealed that the proposed
relationships were invariant among two main demographic groups. The invariance
of regression coefficients between men and women suggests that the strength of
the relationship is the same for both groups. This is particularly revealing
since it has been shown in previous studies that women tend to experience more
severe mental health problems during the pandemic (Dal Santo et al., 2022). The
same result has been found for work status, even though working and studying impose
higher demands on higher education students which is related to more mental
health problems and considerations (Pedrelli et al.,
2015).
In conclusion, academic self-efficacy can act as a
protective factor towards mental health problems related to depression,
anxiety, and stress. The observed relationship between academic self-efficacy
and all three mental health conditions was statistically significant, moderate,
and negative, with a slightly higher effect size for depression. Regarding
depression, a higher academic self-efficacy allows university students to be
more confident in their own skills, thus allowing them to successfully address
academic tasks and avoid negative feelings about their present and future
academic endeavors. With reference to anxiety, higher academic self-efficacy
prevents worried thoughts and concerns regarding academic chores; as a
consequence, academic demands are not seen as potential threats and students
are not perturbed by them. Lastly, having a strong confidence in one’s own
abilities can act as a coping mechanism towards stressful academic situations.
Lastly, multigroup analyses revealed that the measurement and structural model
are invariant across sex and work status. Thus, we recommend improving efforts
to foster academic self-efficacy on university students in order to reduce the
mental health impact that the academic environment and the COVID-19 pandemic
brought.
It is important to note that this study presents some
limitations. To begin with, we did not use a randomized sampling procedure
which limits the generalizability of results to wider populations. This is
because the non-probabilistic sampling doesn't give each individual the
possibility of being part of the sample, which is why it may not be
representative of the population. Furthermore, we employed a cross-sectional
approach and longitudinal designs may bring further insights into the dynamics
of the proposed relationships.
ORCID
Nayeli Lucía Ampuero Tello https://orcid.org/0000-0001-5672-5682
Angel Christopher Zegarra López https://orcid.org/0000-0001-5873-745X
Dharma Ariana Padilla López
https://orcid.org/0000-0003-3410-2761
Dafne Silvana Venturo
Pimentel https://orcid.org/0000-0002-8106-4182
CONTRIBUTION
OF THE AUTHORS
Nayeli Lucía Ampuero Tello: Design of the study, literature search,
drafting of the manuscript, and final revision of the manuscript.
Angel Christopher Zegarra
López: Design of the study, statistical procedures and analysis, drafting of
the manuscript, translation to English, and final revision of the manuscript.
Dharma Ariana Padilla
López: Design of the study, literature search, drafting of the manuscript, and
final revision of the manuscript.
Dafne Silvana Venturo Pimentel: Design of the study, literature search,
drafting of the manuscript, and final revision of the manuscript.
FUNDING
Our study was
self-financed.
CONFLICTS OF INTEREST
The authors of
this study report no conflict of interest.
ACKNOWLEDGMENTS
Not applicable.
REVIEW
PROCESS
This study has
been reviewed by external peers in a double-blind mode. The editor in charge Anthony Copez-Lonzoy. The review process can be
found as supplementary material 1.
DATA
AVAILABILITY STATEMENT
The datasets that support the present study are
available upon reasonable request and with permission of the Faculty of
Psychology and the Research and Ethics Committee of the Universidad de Lima.
DISCLAIMER
The authors are responsible for all
statements made in this article.
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