Depression, anxiety, and stress in the Chilean Educational System: children and adolescents post-pandemic prevalence and variables

Abstract

The mental health of children and adolescents in the Chilean Educational System (ChES) has become a severe post-pandemic public health problem. This cross-sectional study, which included 1,174 children and adolescents from five Chilean regions, used the DASS-21 scale, focusing on determining the prevalence of depression, anxiety, and stress, as well as identifying associated risk factors. The results exposed a high prevalence of depression, anxiety, and stress (60.2%, 63.6%, and 50.2%, respectively). Risk factors for depression involve being female, having separated parents, being in high school, having a cell phone, difficulty sleeping, ruminative thoughts, and low self-esteem. For anxiety, factors included being female, being 12 years old, owning a cell phone, having sleep problems, having ruminations, having low self-esteem, and being an atheist. For stress, factors were identified as being female, owning a cell phone, sleep problems, ruminations, low self-esteem, being atheist, as well as extensive use of social networks. The research underscores the urgent need for intervention by educational authorities, given the marked deterioration in the mental health of children and adolescent students in the ChES, to prevent long-term consequences.

Full text

feduc-09-1407021 October 15, 2024 Time: 18:16 # 1
TYPE Original Research
PUBLISHED 18 October 2024
DOI 10.3389/feduc.2024.1407021
OPEN ACCESS
EDITED BY
Carlos Laranjeira,
Polytechnic Institute of Leiria, Portugal
REVIEWED BY
Carlos Alberto Pereira de Oliveira,
Rio de Janeiro State University, Brazil
Mia Mikaela Maurer,
Lund University, Sweden
*CORRESPONDENCE
María-Mercedes Yeomans-Cabrera
mmyeomans@outlook.com
RECEIVED 26 March 2024
ACCEPTED 04 October 2024
PUBLISHED 18 October 2024
CITATION
Martínez-Líbano J and
Yeomans-Cabrera M-M (2024) Depression,
anxiety, and stress in the Chilean Educational
System: children and adolescents
post-pandemic prevalence and variables.
Front. Educ. 9:1407021.
doi: 10.3389/feduc.2024.1407021
COPYRIGHT
© 2024 Martínez-Líbano and
Yeomans-Cabrera. This is an open-access
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Creative Commons Attribution License
(CC BY). The use, distribution or reproduction
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in this journal is cited, in accordance with
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which does not comply with these terms.
Depression, anxiety, and stress in
the Chilean Educational System:
children and adolescents
post-pandemic prevalence and
variables
Jonathan Martínez-Líbano1and
María-Mercedes Yeomans-Cabrera2*
1Facultad de Educación y Ciencias Sociales, Universidad Andrés Bello, Santiago, Chile, 2Facultad
de Salud y Ciencias Sociales, Universidad de Las Américas, Santiago, Chile
The mental health of children and adolescents in the Chilean Educational
System (ChES) has become a severe post-pandemic public health problem.
This cross-sectional study, which included 1,174 children and adolescents from
five Chilean regions, used the DASS-21 scale, focusing on determining the
prevalence of depression, anxiety, and stress, as well as identifying associated
risk factors. The results exposed a high prevalence of depression, anxiety,
and stress (60.2%, 63.6%, and 50.2%, respectively). Risk factors for depression
involve being female, having separated parents, being in high school, having a
cell phone, difficulty sleeping, ruminative thoughts, and low self-esteem. For
anxiety, factors included being female, being 12 years old, owning a cell phone,
having sleep problems, having ruminations, having low self-esteem, and being
an atheist. For stress, factors were identified as being female, owning a cell
phone, sleep problems, ruminations, low self-esteem, being atheist, as well as
extensive use of social networks. The research underscores the urgent need
for intervention by educational authorities, given the marked deterioration in
the mental health of children and adolescent students in the ChES, to prevent
long-term consequences.
KEYWORDS
mental health, children, adolescents, post-pandemic, scholar system
1 Introduction
Currently, child and adolescent mental health has become a critical public health
challenge worldwide. The COVID-19 pandemic broke out and affected the quality of
life of people worldwide in unexpected ways, leaving a profound and lasting impact
on global society (Kumar et al., 2021;Martínez-Líbano et al., 2023b;Yeomans and
Silva, 2020;Martínez-Líbano and Yeomans, 2021;Martínez-Líbano and Yeomans, 2023;
Yeomans et al., 2021;Martínez-Líbano et al., 2021;Martínez-Líbano et al., 2022b;
Martínez-Líbano and Yeomans-Cabrera, 2023). In this context, children and adolescents
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have witnessed unprecedented environmental transformation
and faced significant emotional and psychological challenges
(Martínez-Líbano et al., 2023b;Yeomans and Silva, 2020;Martínez-
Líbano and Yeomans, 2021;Martínez-Líbano and Yeomans, 2023;
Yeomans et al., 2021;Martínez-Líbano et al., 2021;Martínez-
Líbano et al., 2022b;Martínez-Líbano and Yeomans-Cabrera, 2023;
Singh et al., 2020). One of the central issues that deserves attention
and study in this new post-pandemic reality is their mental
health and the consequences that the pandemic has brought at
the emotional and social levels (Martínez-Líbano and Yeomans-
Cabrera, 2023;Wang J. et al., 2021;Łaskawiec et al., 2022).
This research aimed to explore the complexities of this problem,
recognizing that mental health disorders in this population not
only represent a serious public health problem but also pose unique
challenges in the context of long-term development and well-being.
The importance of mental health in young people transcends
the individual level, affecting the social and economic fabric of
societies (Meherali et al., 2021). Optimal mental well-being during
these crucial life stages is not only critical for cognitive and
emotional development (Wang, 2023) but also essential for forming
healthy relationships, academic performance, and adapting to life’s
changes and challenges (Kwon et al., 2018). In addition, early
and effective interventions can prevent the progression of mental
disorders and reduce the risk of chronic problems in adulthood
(Colizzi et al., 2020).
Society and, specifically, the scientific community are
increasingly concerned about the prevalence of depression,
anxiety, and stress in children and adolescents, as these conditions
pose significant public health challenges (Martínez-Líbano et al.,
2023b;Yeomans et al., 2021;Martínez-Líbano et al., 2021;
Martínez-Líbano and Yeomans-Cabrera, 2023;Schlack et al.,
2021;Hellström and Beckman, 2021;World Health Organization,
2020;Huerta-Ojeda et al., 2021;Martínez-Líbano et al., 2022c).
Preceding the onset of the COVID-19 pandemic, mental disorders
were already manifesting as a prominent health concern among
the global youth demographic (Polanczyk et al., 2015). According
to studies conducted in the pre-pandemic period, the prevalence
of depression and anxiety was around 5.4% and 9% in children
and adolescents (Vicente et al., 2012). During the pandemic,
some measurements placed prevalences at 36% for depression
(Moya-Vergara et al., 2023); likewise, an increase in anxiety levels
was observed between 2018 and 2021 (Caqueo-Urízar et al., 2023).
Depression, like anxiety and stress, not only affects the quality of life
of children and adolescents but can also have lasting effects on their
cognitive, emotional, and social development (Martínez-Líbano
et al., 2023b;Martínez-Líbano and Yeomans, 2023;Yeomans et al.,
2021;Martínez-Líbano and Yeomans-Cabrera, 2023;Alkhathami,
2014;Yeomans-Cabrera and Martínez-Líbano, 2023).
Depression in children and adolescents may manifest
differently compared to adults (Rice et al., 2019), and its symptoms
are often a mixture of emotional and physical behaviors (Melton
et al., 2016). Young people with depression may experience
persistent sadness, irritability, or anger, even over minor issues
(Stringaris et al., 2018). Individuals frequently exhibit a diminished
inclination towards previously pleasurable pursuits (Aprilia and
Aminatun, 2022) and a marked decline in academic performance
(Pascoe et al., 2020). Alterations in sleep and eating patterns—such
as sleeping too much or too little or eating too much or too little—
are also indicators (Begdache et al., 2019). In addition, they may
present with symptoms of fatigue and pain without apparent cause
(Pinquart and Shen, 2011), concentration difficulties (Humensky
et al., 2010), feelings of worthlessness or guilt (Tilghman-Osborne
et al., 2008;Gambin and Sharp, 2018), and, in severe cases,
thoughts of self-harm or suicide (Martínez-Líbano and Yeomans,
2021;Hawton et al., 2012). Attention to these signs is crucial,
as young people may have difficulty expressing their emotions
directly (Silk et al., 2003;Bariola et al., 2011).
Anxiety among children and adolescents can also manifest
itself through various symptoms. On an emotional level, these
young people may show excessive worry about aspects of daily
life, such as academic performance, social relationships, or the
safety of loved ones (Freidl et al., 2017;Lebowitz and Omer,
2013;Rapee et al., 2023). They commonly experience intense fears
or irrational phobias about specific situations or objects (Essau
et al., 2013;Rockhill et al., 2010;Gerhert et al., 2022). Physically,
they may present symptoms such as stomach aches, headaches,
fatigue, and increased heart rate (Tarbell et al., 2014;Falla et al.,
2022). Behaviorally, it is possible to observe nervousness, agitation,
avoidance of activities or situations that generate anxiety, difficulty
concentrating, and, in some cases, panic attacks (Rockhill et al.,
2010;Chiu et al., 2016;Klein et al., 2023).
In children and adolescents, stress, signs of irritability, anxiety,
sadness, or frustration may appear (Brotman et al., 2017), in
addition to behavioral problems at school or home (Barnes et al.,
2003) and changes in sleeping and eating patterns, such as insomnia
or overeating (Hong and Kim, 2014). Children and adolescents
under stress may exhibit physical symptoms, including headaches,
stomachaches, exhaustion, and muscle tightness (Friedrichsdorf
et al., 2016). They may also have difficulty concentrating or
remembering information (Aprilia and Aminatun, 2022;Lopez-
Serrano et al., 2021).
The manifestations of melancholy, anxiety, and stress in
children and adolescents can have a substantial impact on
their everyday functioning, hence influencing their academic
achievements, interpersonal connections, and overall state of being
(Martínez-Líbano et al., 2023b;Martínez-Líbano and Yeomans-
Cabrera, 2023;Huerta-Ojeda et al., 2021;Yeomans-Cabrera and
Martínez-Líbano, 2023;Seemi et al., 2023;Pop-Jordanova, 2019).
1.1 Before the pandemic
Before the onset of the COVID-19 epidemic, the mental
well-being of children and adolescents was already a subject
of increasing global apprehension (Benton et al., 2021). The
prevalence of mental diseases within this demographic exhibited
an upward trend, indicating a multitude of obstacles and stressors
that impacted their emotional and psychological welfare (Gruber
et al., 2021;Viner et al., 2022). These challenges manifested
diversely, from specific mental disorders to broader social and
emotional adjustment problems (Compas et al., 2017). Childhood
and adolescence are critical phases for developing cognitive,
emotional, and social skills, significantly impacting a person’s life
(Yurgelun-Todd, 2007;Rueda et al., 2016).
Nevertheless, despite the significance of this developmental
phase, a considerable number of children and adolescents are
already susceptible to mental health issues. Some pre-pandemic
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FIGURE 1
Procedure for data collection.
studies reported that the overall prevalence of mental disorders in
this population was 13.4% (Polanczyk et al., 2015). Factors such
as academic pressure (Steare et al., 2023), bullying (deLara, 2019),
stressful family dynamics (Santesteban-Echarri et al., 2018), and
early exposure to technology (Ospina-Pinillos et al., 2018) and
social networks (Martínez-Líbano et al., 2022a) contributed to a
complex and challenging picture. The emergence of the pandemic
has exacerbated these pre-existing tensions by implementing
mitigating measures, such as social separation and school closures
(Nenna et al., 2022). These circumstances have heightened mental
health concerns in this vulnerable population, highlighting the need
to address these issues with greater urgency and understanding.
The pandemic has not only brought new challenges. Still, it has also
exacerbated existing problems (Murphy et al., 2021;Panchal et al.,
2021), creating a scenario in which child and adolescent mental
health alertness has become more critical than ever.
1.2 Throughout the pandemic
The lives of children and adolescents were significantly
impacted by the COVID-19 pandemic, resulting in substantial
transformations such as the cessation of in-person education
for children and adolescents, as well as limitations on social
connections (Meherali et al., 2021), plunging them into a state
of constant uncertainty and fear of illness (Sandín et al., 2021;
Korte et al., 2021). This new reality, intertwined with economic and
health concerns at the family level, created an environment prone
to mental health problems (Ravens-Sieberer et al., 2022) and has
been a critical factor in the increase of anxiety disorders, depression,
and stress among young people (Martínez-Líbano et al., 2023b).
These challenges, exacerbated by uncertainty and environmental
stress, generated a significant psychological impact, manifesting
in symptoms such as anxiety (Orgilés Amorós et al., 2021),
isolation (Loades et al., 2020), loss of interest in previous activities
(Montreuil et al., 2023), and changes in mood and behavior
(Francisco et al., 2020;Sadeghi et al., 2022). The pandemic not
only disrupted their daily routines but also affected their emotional
and social development, marking a critical period in their mental
health that requires specialized attention and care (Gruber et al.,
2021). In the case of young people, according to a systemic
review with meta-analysis, it was established that the worldwide
prevalence of depression and anxiety symptoms doubled during the
COVID-19 pandemic, with rates of 25.2% and 20.5%, respectively
(Racine et al., 2021).
1.3 Predictors
Several predictors have been evidenced as an influence on the
mental health of children and adolescents; most of them are related
to social well-being, family situation, cognitive functioning, and
religious beliefs.
Regarding disorders related to social networks, previous
research has linked cell phone use to mental health disorders in
children and adolescents, such as anxiety and depressive symptoms
(Moshe et al., 2021;Augner et al., 2023), sleep problems (Lund
et al., 2021;Correa et al., 2022), and addictive behaviors (Jeong
et al., 2023). Considering that nowadays, most cell phones are
smartphones, excessive mobile phone use can be associated with
mental health problems, such as anxiety and depression, due to
constant exposure to social networks and lack of face-to-face
interaction (Wacks and Weinstein, 2021;Primack et al., 2017). The
compulsion to use a mobile phone can interfere with daily activities
and sleep, contributing to higher levels of stress and mental health
problems such as anxiety and depression (Daraj et al., 2023). The
excessive concern about the opinion of others—connected to social
networks— can lead to low self-esteem and social anxiety, which
negatively affects young people’s mental health and self-image
(Hamdani et al., 2023;Papapanou et al., 2023); besides, low self-
esteem is an important risk factor for the development of mental
health problems such as depression and anxiety, which impact
on adolescents’ general well-being and social development (Thuy,
2023;Solera et al., 2024). Regarding sleep disorders, they are closely
linked to mental health problems, such as anxiety, depression,
and cognitive difficulties, which can affect academic and social
performance (Ramos et al., 2021;Gold and Gold, 2021). Finally,
addiction to social networks can lead to decreased emotional
well-being, increased anxiety and depression, and reduced
quality of offline interpersonal relationships (Zhang et al., 2023;
Vally et al., 2023).
Regarding family variables, several studies have shown that
family support plays a fundamental role in the psychological and
mental well-being of minors (Bersia et al., 2022;Renwick et al.,
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2022); a high level of family support is associated with better
mental health, as it provides a safe and emotionally supportive
environment that helps to manage stress and emotional difficulties
(Yang et al., 2022;Acoba, 2024). Likewise, it has been observed
that separation from parents may represent a risk factor for the
mental health of children and adolescents (Saurabh and Ranjan,
2020;Tullius et al., 2022); it might generate emotional instability
and stress in children and adolescents, negatively affecting their
mental health and psychological development (Wang F. et al., 2021;
Karhina et al., 2023).
Regarding cognitive aspects, recent studies indicate that
rumination can lead young people to focus negatively on their
circumstances, which affects their self-esteem and is associated
with major problems such as depression and suicidal ideation
(Martinez et al., 2021;Lin et al., 2022). Also related to sleep
disorders, rumination, or the tendency to dwell on adverse
events repeatedly, is linked to depression and anxiety and
prevents children and adolescents from effectively managing
their emotions and solving problems (Kraft et al., 2023;
Kovac et al., 2023).
Regarding religious beliefs, believing in God has been
considered a protective factor in young people’s mental health
(Pastwa-Wojciechowska et al., 2021;Sarizadeh et al., 2020); this
can provide a sense of purpose and emotional support, which can
benefit mental health and resilience in the face of stress (Bouwhuis-
Van Keulen et al., 2024;Bridi et al., 2023;Zubair et al., 2023).
This set of interconnected variables can provide a
comprehensive analysis of factors influencing child and adolescent
mental health, thus allowing for the identification of possible
interventions and needed supports.
Regarding sociodemographics, it is crucial to know the context
of children, which may explain mental health issues. For example,
it is important to recognize the significant impact of gender
differences and social factors on the mental health of children and
adolescents. Research indicates that girls tend to exhibit higher
levels of anxiety and depression, while boys are more likely to
exhibit aggressive behaviors and oppositional defiant disorder
(Babicka-Wirkus et al., 2023;Ettekal et al., 2023). These trends
are further influenced by individuals’ developmental stages, with
older adolescents tending to be more prone to depression than
their younger peers (Mangione et al., 2022;Davis et al., 2024).
Also, environmental factors play a crucial role, particularly the
disparity in access to mental health resources and socioeconomic
conditions between urban and rural settings (Crouch et al., 2023;
Hardy et al., 2024). These disparities can result in different
experiences and exposures significantly affecting mental health
outcomes. In addition, the type of educational setting —public,
private, rural, or urban— can influence children’s mental health.
Public schools, for example, may find it more challenging to provide
sufficient psychological support than private schools (Reupert et al.,
2022;Babkina and Kochetova, 2022). In addition, immigrant and
ethnic minority children often face challenges related to cultural
adaptation and discrimination, which can further complicate
their mental health situation (Coelho et al., 2022;Berrios-
Riquelme et al., 2022). Finally, the academic level and intensity
of studies are critical factors. Higher graders may experience
more significant academic pressures and stress, adversely affecting
their mental health and future decisions and career paths
(Gedda-Muñoz et al., 2023).
1.4 Present study
The COVID-19 pandemic was announced over by the World
Health Organization (WHO) on May 5, 2023 (United Nations,
2023). Regarding the fluctuation in mental disorders compared
to before and after the pandemic (OECD, 2019;OECD, 2021;
OECD, 2023), it is imperative to ascertain the present state of
mental health among children and adolescents in the ChES after
the pandemic. Therefore, this research aimed to determine the
prevalence of depression, anxiety, and stress after the pandemic
among children and adolescents in the Chilean Educational System
as well as identify associated risk factors.
Our hypotheses were:
The prevalence of mental health disorders has risen among
children and adolescents in the ChES region after the COVID-
19 pandemic.
The prevalence of depression, anxiety, and stress exhibits
notable disparities across all age and gender cohorts within the
ChES population, indicating the unequal impact of the pandemic
on different segments.
2 Materials and methods
2.1 Research methodology and sample
This study utilized a cross-sectional descriptive quantitative
design, employing a self-report survey with a Likert-scale
questionnaire. The sample was purposive, as we aimed to
conduct a survey targeting children and adolescents between the
ages of 10 and 18.
The inclusion criteria encompassed individuals aged 10 to
18, currently attending a school in the ChES, residing in Chile,
possessing a consent form signed by the minors’ legal guardians
and/or parents, and providing informed assent by the students
themselves before completing the survey. Questionnaires that were
not fully completed were included.
2.2 Instruments
DASS-21 —The Depression Anxiety Stress Scale (Lovibond
and Lovibond, 1995)— is a psychological instrument
employed to evaluate the extent of depression, anxiety,
and stress experienced by individuals. The DASS-21
scale comprises three self-report subscales that have been
specifically developed to assess the severity and occurrence
of Anxiety (7 items), Depression (7 items), and Stress (7
items). The grading system spans from 0 to 3, indicating the
evaluation of the previous week (ranging from "relatively
irrelevant to me" to "largely relevant to me"). The depression
scale assesses emotions such as melancholy, emptiness,
self-criticism, loss of interest, and inability to get pleasure.
The Anxiety scale evaluates the psychological and physical
manifestations of fear, autonomic nervous system activation,
anxiety in certain circumstances, and the individual’s
subjective perception of feeling anxious (Huerta-Ojeda et al.,
2021). The scale score is determined by summing the scores
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of the related items, which range from 0 to 21. The ranges of
scores for classifying levels of depression, anxiety, and stress
are: (i) Normal (depression ≤4; anxiety ≤3; stress ≤7), which
indicates normal levels or absence of significant symptoms;
(ii) Mild (depression = 5 to 6; anxiety = 4 to 5; stress, 8 to 9),
which reflects mild symptoms; (iii) Moderate (depression = 7
to 10; anxiety = 6 to 7; stress = 10 to 12), which indicates a
moderate level of symptoms; (iv) Severe (depression = 11
to 13; anxiety = 8 to 9; stress = 13 to16), which suggests
severe symptoms; (v) Extremely severe (depression ≥14;
anxiety ≥10; stress ≥17), which indicates highly severe
symptoms. In this case, Cronbach’s alpha coefficient was
calculated to be α= 0.949, while the omega coefficient was
determined to be ω= 0.950.
2.2.1 Sociodemographic variables
Sociodemographic variables included age, gender, region,
nationality, and grade. Gender differences can significantly
influence the prevalence and presentation of mental health
problems in children and adolescents. Girls tend to have higher
levels of anxiety and depression, while boys may show more
externalizing behaviors, such as aggression (Babicka-Wirkus et al.,
2023;Ettekal et al., 2023). Age is a crucial factor, as rates of
certain mental disorders, such as depression and anxiety, can
vary significantly between developmental stages. Older adolescents
may be more prone to depression than younger children
(Mangione et al., 2022;Davis et al., 2024). Regarding the
chosen instruments, measuring age when applying the DASS-21
is crucial for several reasons related to interpreting the results
and understanding the context of the person being assessed.
First, psychological development and maturity vary significantly
with age; children and adolescents may manifest symptoms of
depression, anxiety, and stress differently, and different ages
are associated with various life events and stressors, such as
the academic stress experienced by adolescents at the end of
school. Comparing the results with age-specific norms allows for
a more contextualized and relevant assessment, facilitating better
interpretation of individual results by having similar reference
groups (Simon and Bernardo, 2022). The region of residence
can also influence access to mental health resources and the
level of stress due to socioeconomic and environmental factors.
Children in urban areas may have different experiences and
stressors than those in rural areas (Crouch et al., 2023;Hardy
et al., 2024). The type of school (public, private, rural, urban)
can influence the student’s educational and social environment,
affecting their mental health. Private schools may offer more
resources for psychological support, while public schools may face
more difficulties in this regard (Reupert et al., 2022;Babkina and
Kochetova, 2022). Nationality may reflect cultural differences in
the perception and management of mental health. In addition,
immigrant or ethnic minority children may experience additional
stress related to cultural adaptation and discrimination (Coelho
et al., 2022;Berrios-Riquelme et al., 2022). The level of study
may indicate the level of academic and social stress the student
faces. Higher-graders may experience more academic pressure and
anxiety concerning their performance and future career decisions
(Gedda-Muñoz et al., 2023).
2.2.2 Variables of interest
In developing a questionnaire to assess factors influencing the
mental health of children and adolescents, we carefully selected
variables based on solid empirical evidence. Cell phone ownership:
research consistently links cell phone use to mental health problems
in young people, such as anxiety and depressive symptoms (Moshe
et al., 2021;Augner et al., 2023), sleep disorders (Lund et al., 2021;
Correa et al., 2022), and addictive behaviors (Menendez-García
et al., 2022;Serra et al., 2021); Family variables: Family support
is crucial for the psychological and mental well-being of minors
(Bersia et al., 2022;Renwick et al., 2022), while parental separation
is identified as a potential risk factor for their mental health
(Saurabh and Ranjan, 2020;Tullius et al., 2022); Cognitive aspect:
Ruminative behaviors have been shown to negatively influence self-
esteem and correlate with serious problems such as depression and
suicidal ideation (Martinez et al., 2021;Lin et al., 2022); Belief
in God: Several studies suggest that spiritual beliefs may serve as
a protective factor against mental health problems among young
individuals (Pastwa-Wojciechowska et al., 2021;Sarizadeh et al.,
2020). These variables were selected to ensure a comprehensive
assessment of the various influences on child and adolescent mental
health to guide the development of specific interventions and
support mechanisms. The variables of interest were conducted
through closed questions with dichotomous answers of YES/NO.
Among the questions asked were: Are my parents separated? Do I
have the support of my family? Do I have trouble falling asleep? Are
there things I can’t stop thinking about? Do I believe I have a social
media addiction? Do I worry about other people’s opinions of me?
Do I have low self-esteem? Do I believe in God? Do I keep my eyes
on my mobile? Do I spend too much time on social media.
2.3 Procedure for data collection
The data collection occurred during November and December
of 2023 (See Figure 1). The sample was intentional. To recruit
schools for this study, a call was made to all candidates from
a master’s degree program in Emotional Education from a
Chilean university (n = 169) who are professionals working
in the Chilean educational system (ChES). Regarding this call,
23 schools answered: 11 declined the invitation via email, and
12 accepted the invitation to participate in an informative
meeting via Zoom. Finally, due to time constraints and
administrative procedures, five schools agreed to participate in
the study with their students. As inclusion criteria, the schools
had to belong to the Chilean educational system and have
students between 10 and 18 years of age. For data collection,
participating students were taken to computer labs in their
respective schools to complete the questionnaire directly in
Google Forms. Before starting, the principals of schools gave
their formal approval to conduct the study, and informed
consent was obtained from the student’s parents and tutors,
as well as informed assent from the participating students.
The pupils completed the questionnaire directly using Google
Forms. This facilitated efficient and secure data collection
and analysis. At the end of the study, a descriptive report
was provided to each participating school, containing only
the overall results of the educational community, maintaining
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the confidentiality of individual responses and ensuring that
individual participants could not be identified.
Subsequently, a couple of teachers per school were trained to
help in the field application of the questionnaires. The survey was
inputted into Google Forms, creating distinct hyperlinks for each
educational institution. The confidentiality of the surveys rendered
it unfeasible to ascertain the identity of the primary respondent.
Beforehand, signed informed consent was obtained from the legal
guardians and/or parents of the children and adolescents, and, in
addition, the minors themselves had to give their assent before
answering the surveys. Out of the 1,216 surveys gathered, 42
did not match the inclusion requirements due to the lack of
agreement from the children and adolescents, although having
parental informed consent. The purpose of these questionnaires
was to collect data for analysis.
2.4 Statistical analysis
The data in this study was analyzed using several statistical
approaches. The study commenced with a descriptive analysis,
wherein the means and standard deviations were computed for
all variables of interest, facilitating a fundamental comprehension
of the data distribution. Following that, the statistical methods
of Students’ t-tests and ANOVA were employed to examine
noteworthy disparities among the various groups. The conducted
analysis facilitated the identification of potential statistically
significant differences in the important measures among the
participants. The researchers conducted a logistic regression
analysis utilizing the forward approach, explicitly employing the
likelihood ratio (LR) to delve deeper into the associations among
the variables. This approach allowed us to identify variables that
contributed significantly to predicting the outcome of interest,
iteratively selecting them for inclusion in the model. Logistic
regression was conducted using the inclusion approach after
identifying the significant variables. The concluding stage of the
logistic regression study facilitated the assessment of the collective
influence and associations among the chosen factors pertaining
to the dependent variable. The Hosmer-Lemeshow test was used
to assess the adequacy of the final logistic regression model. The
test yielded a quantitative assessment of the model’s goodness-of-
fit, thereby verifying the extent to which the model’s predictions
aligned with the observed data.
Finally, a review of specific statistics reveals significant increases
in depression, anxiety, and stress among the Chilean child and
adolescent population compared to the prevalence reported in
pre-pandemic studies.
2.5 Ethics statement
The Central Bioethics Committee of the Universidad Andrés
Bello granted approval for this project on August 11, 2023. The
Bioethics Committee of the Faculty of Education and Social
Sciences of Universidad Andrés Bello was established under
decision 88024/2016. It is essential to acknowledge that no sensitive
information was solicited that may reveal the identities of the
students who participated in the study. Ultimately, the informed
consent was granted by the parents and/or tutors of all participants
at the outset of the questionnaire, and all participants provided their
signature as their agreement. No individuals were reimbursed for
their involvement.
3 Results
3.1 Participants
Table 1 displays the sociodemographic and educational
attributes of the participants involved in the study. The study
sample consisted of males and females in a similar proportion; the
average age of the participants was 13.71 years, with the largest
proportion of individuals falling within the 13-year-old age group
(19.8%). Regarding the school’s administration, public, half-private,
and private schools participated in varied proportions. Students
were mostly Chilean; however, some students in the ChES were
originally from abroad. Students lived in 5 different regions of
the country, and 2/5 belonged to the capital city. Most subjects
had access to cell phones, and more than 1/3 lived with separated
parents. Most of the sample perceived family support; half of them
had sleeping disturbances, rumination was present in almost 4/5 of
the sample, addiction to social networks was perceived in 2/5 of the
sample, and 3/5 affirmed concern for other’s opinions. 2/5 of the
sample referred to low self-esteem, 1/5 were atheists, 1/2 referred to
compulsion to use cell phones, and 3/5 spent a lot of time on social
networks. Detailed data can be found in Table 1.
3.2 Descriptive statistics of depression,
anxiety, and stress
Table 2 displays the descriptive statistics pertaining to the
research variables. The average score for depression, anxiety, and
stress were 7.42, 6.78, and 7.97, respectively.
3.3 Levels of depression, anxiety, and
stress
The study examined the prevalence of various levels
of depression, anxiety, and stress among the sample under
investigation, as presented in Table 3.
3.4 Binary logistic regression for
depression
Table 4 shows results from the logistic regression analysis
on depression. The model’s coefficient was −0.559 (standard
error = 0.395, Wald = 2.000, p= 0.157). The Hosmer and Lemeshow
tests were employed to evaluate the sufficiency of the logistic
regression model. The study’s findings revealed a strong alignment
between the model and the data, as evidenced by a Chi-square
value of 2(8) = 8.164, p= 0.418. According to this test results,
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TABLE 1 Participant characteristics, differences of depression, anxiety, and stress by characteristics.
Characteristics Categories n(%) Depression Anxiety Stress
M±SD M ±SD t/F M ±SD t/F M ±SD t/F
Gender Male 629 (53.6) 5.76 ±5.36 59.39** 4.97 ±4.56 87.96** 6.25 ±5.071 77.38**
Female 540 (46) 9.29 ±6.07 8.84 ±5.56 9.91 ±5.31
Others 5 (0.4) 14.60 ±7.16 12.20 ±5.35 15.40 ±4.03
Age (yrs.) 13.71 ±1.75
10 33 (2.8) 7.33 ±6.76 1.58 6.70 ±4.32 1.201 7.88 ±5.22 1.034
11 115 (9.8) 6.31 ±5.99 6.51 ±5.51 7.46 ±5.68
12 156 (13.3) 7.94 ±6.20 7.85 ±5.82 8.66 ±5.73
13 232 (19.8) 6.98 ±5.75 6.31 ±5.00 7.58 ±5.10
14 213 (18.1) 8.22 ±6.42 7.05 ±6.06 8.43 ±5.88
15 230 (19.6) 7.14 ±5.66 6.45 ±5.28 7.53 ±5.38
16 142 (12.1) 7.42 ±5.56 6.69 ±4.99 8.15 ±5.35
17 49 (4.2) 8.57 ±6.24 7.04 ±4.89 8.55 ±5.69
18 4 (0.3) 6.00 ±5.35 6.50 ±6.40 7.50 ±6.45
Region Santiago 472 (40.2) 8.67 ±6.12 9.02** 7.77 ±5.626 9.81** 9.15 ±5.50 11.89**
Coquimbo 84 (7.2) 5.42 ±5.88 4.92 ±5.27 5.93 ±5.64
Viña del Mar 144 (12.3) 6.47 ±5.52 5.06 ±4.61 6.19 ±5.12
Maule 117 (10) 7.09 ±6.21 6.59 ±5.04 7.67 ±5.60
Talcahuano 357 (30.4) 6.74 ±5.63 6.68 ±5.29 7.73 ±5.24
Type of school Public 84 (7.2) 5.42 ±5.88 10.41** 4.92 ±5.27 5,98* 5.93 ±5.64 7.74**
Half-Private 733 (62.4) 7.98 ±6.09 7.05 ±5.45 8.33 ±5.57
Private 357 (30.4) 6.74 ±5.63 6.68 ±5.29 7.73 ±5.24
Nationality Chilean 1047 (89.2) 7.36 ±5.94 −0.97 6.75 ±5.38 −0.65 7.98 ±5.52 0.16
Foreign 127 (10.8) 7.91 ±6.30 7.08 ±5.6 7.90 ±5.45
Level Middle school
(5th–8th)
699 (59.5) 7.31 ±6.03 −0.80 6.84 ±5.44 0.44 7.98 ±5.48 0.52
High school (9th to
12th)
475 (40.5) 7.59 ±5.92 6.70 ±5.36 7.96 ±5.55
Grade Fifth 127 (10.8) 6.94 ±6.43 0.97 6.66 ±5.27 0.77 7.82 ±5.59 0.51
Sixth 79 (6.7) 6.05 ±5.50 6.25 ±4.99 7.25 ±5.52
Seventh 285 (24.3) 7.59 ±6.09 7.32 ±5.71 8.21 ±5.59
Eighth 208 (17.7) 7.62 ±5.84 6.52 ±5.34 8.04 ±5.26
Nineth 225 (19.2) 7.67 ±5.97 6.72 ±5.67 7.75 ±5.62
Tenth 180 (15.3) 7.33 ±5.82 6.70 ±5.08 8.17 ±5.42
Eleventh 65 (5.5) 7.94 ±6.18 6.43 ±5.15 7.94 ±5.80
Twelveth 5 (0.4) 9.40 ±5.12 9.20 ±4.60 10.40 ±4.39
Having a cellphone YES 1127 (96) 7.41 ±5.987 6.77 ±5.44 7.96 ±5.51
NO 47 (4.0) 7.72 ±6.07 −0.35 7.19 ±4.71 −0.52 8.38 ±5.56 −0.51
Separated parents YES 424 (36.1) 7.96 ±6.01 2.30* 6.99 ±5.42 0.97 8.38 ±5.63 1.91
NO 750 (63.9) 7.12 ±5.95 6.67 ±5.41 7.74 ±5.42
Perception of family
support
YES 1083 (92.2) 7.05 ±5.74 6.35** 6.50 ±5.21 −5.25** 7.72 ±5.34 −4.79**
NO 91 (7.8) 11.84 ±6.98 10.20 ±6.41 11.05 ±6.46
Sleep disorders YES 600 (51.1) 9.46 ±6.11 12.76** 8.55 ±5.46 12.16** 9.62 ±5.34 10.96**
NO 574 (48.9) 5.29 ±5.03 4.94 ±4.696 6.26 ±5.150
(Continued)
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TABLE 1 (Continued)
Characteristics Categories n(%) Depression Anxiety Stress
M±SD M ±SD t/F M ±SD t/F M ±SD t/F
Rumination YES 931 (79.3) 8.32 ±5.97 12.17** 7.61 ±5.38 12.24** 8.91 ±5.33 13.11**
NO 243 (20.7) 3.98 ±4.65 3.63 ±4.24 4.38 ±4.645
Social networking
addiction
YES 487 (41.5) 8.66 ±5.96 6.06** 7.61 ±5.31 4.41** 9.07 ±5.33 5.79**
NO 687 (58.5) 6.54 ±5.85 6.20 ±5.41 7.20 ±5.50
Concern for the opinion
of others
YES 714 (60.8) 8.61 ±6.02 8.88** 7.80 ±5.405 8.33** 9.09 ±5.30 8.92**
NO 460 (39.2) 5.59 ±5.44 5.21 ±5.04 6.24 ±5.38
Low self-esteem YES 493 (42) 11.15 ±5.79 20.56** 9.52 ±5.316 15.91** 10.82 ±5.09 16.60**
NO 681 (58) 4.72 ±4.49 4.80 ±4.556 5.92 ±4.849
Belief in god YES 767 (65.3) 6.65 ±5.73 −6.06** 6.03 ±5.10 −6.46** 7.34 ±5.34 −5.45**
NO 407 (34.7) 8.89 ±6.185 8.21 ±5.685 9.16 ±5.62
Cell phone compulsion YES 573 (48.8) 8.47 ±6.07 5.90** 7.46 ±5.48 4.23** 8.86 ±5.61 5.45**
NO 601 (51.2) 6.43 ±5.73 6.13 ±5.37 7.13 ±5.27
Too much time on social
networks
YES 731 (62.3) 8.08 ±5.99 4.86** 7.30 ±5.39 4.25** 8.61 ±5.41 5.14**
NO 443 (37.7) 6.34 ±5.82 5.93 ±5.33 6.92 ±5.51
M, mean; SD, standard deviation; t= values of t-test; F= values of ANOVA; * p<0.05; ** p<0.00; yrs = years.
TABLE 2 Descriptive statistics of research variables.
Variables Range M ±SD Skewness Kurtosis
Depression 0–21 7.42 ±5.988 0.628 −0.665
Anxiety 0–21 6.78 ±5.414 0.646 −0.516
Stress 0–21 7.97 ±5.511 0.360 −0.799
M, mean; SD, standard deviation.
TABLE 3 Levels of depression, anxiety, and Stress among children and adolescents in the ChES.
LEVEL Depression Anxiety Stress
n%n%n%
Absent 469 39.9 427 36.4 585 49.8
Mild 150 12.8 77 6.6 134 11.4
Moderate 219 18.7 208 17.7 193 16.4
Severe 118 10.1 109 9.3 165 14.1
Extremely Severe 218 18.6 353 30.1 97 8.3
no statistically significant disparities were identified between the
frequencies observed and those predicted by the model.
3.5 Binary logistic regression for anxiety
Table 5 represents the logistic regression analysis results.
The model’s constant was determined to be −0.056 (standard
error = 0.399, Wald = 0.020, p= 0.888). The Hosmer and
Lemeshow test was used to assess the logistic regression model
adequacy for anxiety. The study’s findings revealed no statistically
significant disparity between the observed frequencies and the
models’ projected frequencies (γ2(8) = 13.279, p= 0.103).
3.6 Binary logistic regression for stress
Table 6 displays the logistic regression analysis for stress.
The model constant was determined to be −1.062 (standard
error = 0.374, Wald = 8.068, p= 0.005). The Hosmer and Lemeshow
test evaluated the logistic regression model’s goodness of fit. The
results indicated no statistically significant difference between the
observed values and those predicted by the model (γ2(8) = 3.105,
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TABLE 4 Binary logistic regression results for depression.
Variables B Standard
error
Wald df Sig. Exp(B) 95% C.I. for EXP(B)
Inferior Superior
Girl 0.715 0.152 22.017 1 0.000 2.045 1.517 2.757
Coquimbo −1.765 0.312 32.060 1 0.000 0.171 0.093 0.315
Middle school −0.493 0.153 10.422 1 0.001 0.611 0.453 0.824
Having cell phone −0.975 0.368 7.002 1 0.008 0.377 0.183 0.777
Separated parents 0.486 0.153 10.017 1 0.002 1.625 1.203 2.195
Trouble sleeping 0.868 0.147 35.062 1 0.000 2.382 1.787 3.174
Rumination 1.009 0.180 31.415 1 0.000 2.742 1.927 3.902
Low self-esteem 1.799 0.165 118.338 1 0.000 6.043 4.370 8.356
Constant −0.559 0.395 2.000 1 0.157 0.572
TABLE 5 Binary logistic regression for anxiety.
Variables B Standard
error
Wald df Sig. Exp(B) 95% C.I. for EXP(B)
Inferior Superior
Girl 0.851 0.153 31.151 1 0.000 2.343 1.738 3.160
12 years old 0.697 0.228 9.338 1 0,002 2.008 1.284 3.140
Coquimbo −0.976 0.284 11.846 1 0.001 0.377 0.216 0.657
Having cell phone −1.238 0.380 10.602 1 0.001 0.290 0.138 0.611
Trouble sleeping 0.771 0.147 27.412 1 0.000 2.162 1.620 2.885
Ruminations 1.231 0.177 48.350 1 0.000 3.426 2.421 4.848
Low self-esteem 1.422 0.165 74.730 1 0.000 4.146 3.003 5.724
Belief in God −0.547 0.157 12.138 1 0.000 0.579 0.425 0.787
Constant −0.056 0.399 0.020 1 0.888 0.945
TABLE 6 Binary logistic regression for stress.
Variables B Standard
error
Wald df Sig. Exp(B) 95% C.I. for EXP(B)
Inferior Superior
Girl 0.650 0.146 19.814 1 0.000 1.916 1.439 2.551
Coquimbo −0.839 0.281 8.890 1 0.003 0.432 0.249 0.750
Viña del Mar −0.567 0.221 6.606 1 0.010 0.567 0.368 0.874
Having cell phone −0.818 0.345 5.619 1 0.018 0.441 0.224 0.868
Trouble sleeping 0.548 0.138 15.750 1 0.000 1.730 1.320 2.268
Ruminations 1.176 0.188 39.063 1 0.000 3.242 2.242 4.689
Low self-esteem 1.186 0.143 68.842 1 0.000 3.275 2.475 4.334
Belief in god −0.441 0.144 9.446 1 0.002 0.643 0.485 0.852
Too much time on
social networks
0.396 0.144 7.571 1 0.006 1.486 1.121 1.969
Constant −1.062 0.374 8.068 1 0.005 0.346
p= 0.928). The obtained outcome indicates a strong alignment with
the logistic regression model.
3.7 Prevalence comparison
Our comprehensive review of statistical data reveals a marked
increase in mental health problems among the Chilean child and
adolescent population after the pandemic. Before the pandemic,
the prevalence of depression and anxiety was recorded at 5.4%
and 9%, respectively (Vicente et al., 2012). Recent measurements
during the pandemic period show a substantial increase, with
depression rates skyrocketing to 36% (Moya-Vergara et al., 2023)
and anxiety levels escalating significantly between 2018 and 2021
(Caqueo-Urízar et al., 2023). Our research further underscores
this trend, documenting a dramatic increase in symptomatology,
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TABLE 7 Transversal risk factors of depression, anxiety, and stress among children and adolescents in the ChES.
Risk factors Depression Anxiety Stress
Gender Higher risk in girls Higher risk in girls Higher risk in girls
Age Not mentioned Increased at 12 years Not mentioned
Cell phone Increased likelyhood Increased likelyhood Increased likelyhood
Family structure Higher risk with separated parents Not mentioned Not mentioned
Sleep disturbances Strongly related Related Related
Intrusive or obsessive ideas Related Related Related
Low self-esteem Related Related Related
Religious beliefs Not mentioned Protective factor Protective factor
with 60.2% for depression, 63.6% for anxiety, and 50.2% for
stress.
To quantify these changes, we meticulously compared
prevalence percentages from our study with historical data. We
ensure the statistical robustness of our results by maintaining
95% confidence intervals. This rigorous approach allows us to
state with statistical significance that there has been a substantial
escalation of depression, anxiety, and stress among post-pandemic
children compared to pre-pandemic levels. Our results highlight
the urgent need to address these mental health issues in the
affected population.
4 Discussion
The objective of this research was to determine the prevalence
of depression, anxiety, and stress after the pandemic among
children and adolescents in the Chilean Educational System as well
as identify associated risk factors.
As already mentioned, several variables have been evidenced
as an influence on the mental health of children and adolescents:
(1) Mobile phone ownership, (2) Family variables, (3) Cognitive
aspects, and (4) the belief in God. This set of variables was
chosen to comprehensively analyze factors influencing child and
adolescent mental health.
4.1 Prevalence of depression, anxiety,
and stress in ChES children and
adolescents
Our research findings indicate a high incidence of mental
health issues among the sample of children and adolescents in the
ChES after the pandemic was declared over. Specifically, depression
was observed in 60.2% of the participants, followed by anxiety in
63.6% and stress in 50.2%.
The occurrence of depression in children and adolescents
from ChES can be elucidated from many viewpoints that consider
the three-year impact of the pandemic on the physical and
mental growth of these groups. Regarding the high prevalence of
depression in a Post-Pandemic Era, social isolation and decreased
interaction played a critical role (Beattie et al., 2015), along with
social isolation and decreased interactions, digital technologies as
a double-edged sword (Orben et al., 2020), disruption of daily
routines (Mesa, 2021), bereavement and pathological grief (Murata
et al., 2021;Chen and Tang, 2021;Rancour and Zeno, 2021), and
uncertainty and the future outlook (Cohrdes et al., 2021).
Regarding the high prevalence of anxiety in a post-pandemic
era, fear of contagion and health concerns were critical (Rania
and Coppola, 2022), besides information overload and media
consumption (Sandín et al., 2020), and the disruption of the
educational process and uncertainty.
Regarding the high prevalence of stress in a post-pandemic era,
disruptions to the educational process and accelerated changes in
digital technology were crucial (Yeomans and Silva, 2020;Ahmed
and Opoku, 2022), along with family dynamics and economic
hardship (Ayuso et al., 2020;Rees et al., 2023), reduction in physical
and recreational activities (de Araújo et al., 2021;O’sullivan
et al., 2021;McNamara, 2021), and academic pressure and future
uncertainty (Shahbaz et al., 2021;Williams et al., 2024).
4.2 Risk factors with depression, anxiety,
and stress among children and
adolescents in the ChES
4.2.1 Risk factors associated with depression
among children and adolescents in the ChES
This research endeavors to delineate the constellation of
risk factors contributing to depression among children and
adolescents within the Chilean Educational System (ChES),
offering insights crucial for the development of nuanced prevention
and treatment methodologies tailored to this demographic.
Our findings underscore the multifaceted nature of these
risk factors, spanning biological, psychological, environmental,
and social domains.
4.2.1.1 Gender differences and vulnerability
A salient finding of our study is the pronounced gender
disparity in depression risk, with females exhibiting a notably
higher susceptibility than males. Considering that in Chile, most
females (gender) are women (biological sex), specifically 99,99%
(Claramunt Carrasco, 2023;Datosmacro.com, 2024), this increased
risk among them can be connected to biological changes in
this population, such as hormonal fluctuations during puberty
(Rosenblum and Lewis, 2006;Goddings et al., 2012). Besides,
sociocultural pressures include heightened expectations around
self-image and behavior (Olenik-Shemesh et al., 2018). Early
development of cognitive and emotional competencies in females
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may amplify their sensitivity to emotional and interpersonal
stressors, potentially predisposing them to depression (Hyde and
Mezulis, 2020;Rapee et al., 2019).
4.2.1.2 Geographical variability in depression prevalence
Our analysis also reveals geographical variability in depression
prevalence, with specific locales such as Coquimbo demonstrating a
lower incidence. This phenomenon suggests that regional cultural,
environmental, and socioeconomic differences may significantly
influence mental health outcomes, positing a more favorable
mental health milieu in certain areas (Sameroff and Seifer, 2021).
4.2.1.3 Educational level as a risk factor
The transition through educational levels emerges as a critical
period for mental health, with students in higher educational tiers
reporting increased depression risk. This pattern likely reflects
the cumulative academic stress and evolving social pressures,
underscoring the need for targeted mental health support within
educational settings (Barker et al., 2018;Pitt et al., 2018).
4.2.1.4 Technological influences on mental health
Technological engagement, particularly cell phone usage, is
identified as a risk factor associated with an increased likelihood
of depression. The mechanisms underlying this relationship may
include information overload, reduced face-to-face interaction, and
the psychosocial impacts of social media use (Matthes et al., 2020),
which can foster isolation and unfavorable social comparison,
especially among adolescents (Clark et al., 2018;Reer et al., 2019).
4.2.1.5 Family structure and emotional well-being
Family dynamics, specifically the experience of parental
separation, significantly affect the mental health of children
and adolescents, with those from separated families showing
a heightened depression risk. This association highlights the
profound impact of familial stability and changes in family
structure on children’s emotional well-being (Garriga and Pennoni,
2022;Xerxa et al., 2020).
4.2.1.6 Sleep disturbances and cognitive patterns
Sleep disturbances and problematic cognitive patterns, such as
obsessive or intrusive thoughts, are closely linked with depression.
Insufficient sleep can adversely affect cognitive function, academic
performance, and mood (Hershner, 2020), while maladaptive
thought patterns, characterized by worry, fear, or negative
rumination (Lawrence et al., 2021), perpetuate a cycle of sadness
and hopelessness (Park and Kim, 2020;Wrosch and Scheier, 2020).
Furthermore, low self-esteem and self-critical views may exacerbate
vulnerability to depression (Rimes et al., 2023;Shokrpour et al.,
2021), underscoring the interrelation between self-perception and
mental health.
In synthesizing these findings, it becomes evident that
addressing depression in children and adolescents within the ChES
demands an integrated approach that considers the broad spectrum
of individual, familial, educational, and socio-environmental risk
factors. Enhancing our understanding of these determinants
is fundamental to crafting effective interventions and support
mechanisms that can mitigate the incidence and severity of
depression in this population, fostering a more supportive and
resilient developmental milieu.
4.2.2 Risk factors associated with anxiety among
children and adolescents in the ChES
In the context of identifying risk factors for anxiety among
children and adolescents within the Chilean Educational
System (ChES), this paper delineates a comprehensive analysis,
underscoring the multifactorial nature of anxiety disorders in
this demographic. Several key determinants have been identified,
spanning biological, developmental, environmental, technological,
and psychological domains, alongside the protective role of
religious beliefs.
4.2.2.1 Gender and biological factors
A pivotal finding of our research is the pronounced
gender disparity in anxiety prevalence, with females exhibiting
a significantly higher likelihood (134% more) of encountering
anxiety disorders compared to males. This discrepancy is attributed
to physiological differences, including elevated levels of anxiety-
associated hormones such as cortisol and adrenaline among females
(Lundberg, 2005;Lovallo et al., 2006). Additionally, hormonal
fluctuations during puberty and adolescence are posited to
influence emotional regulation and mood, potentially heightening
females’ susceptibility to anxiety (Holder and Blaustein, 2014).
4.2.2.2 Developmental and age-related factors
Age emerges as a critical risk factor, particularly at the onset
of adolescence, around 12 years old, a phase characterized by
profound physical, emotional, and social transformations. The
confluence of these developmental changes, coupled with escalating
academic and social pressures, can precipitate or exacerbate anxiety
symptoms in this transitional period (Worthman and Trang, 2018;
Simmons, 2017).
4.2.2.3 Environmental and regional influences
Our analysis reveals regional disparities in anxiety prevalence,
with individuals residing in Coquimbo displaying a lower incidence
of anxiety compared to other areas. This variation may be
attributable to environmental and lifestyle factors inherent to
Coquimbo, such as its relatively tranquil setting and potentially
more supportive community structures (Generaal et al., 2019).
4.2.2.4 Technological factors and lifestyle
The possession and use of cell phones have been linked
to increased anxiety, underscoring the role of technology in
contributing to mental health challenges. Excessive engagement
with mobile devices and social media can lead to information
overload, unfavorable social comparisons, and sleep disturbances,
all of which are known to exacerbate anxiety (Matthes et al., 2020).
4.2.2.5 Sleep disturbances
Sleep quality is intimately connected to anxiety, with sleep
difficulties amplifying the risk of developing anxiety disorders.
Insufficient or disrupted sleep can impair stress management
capabilities, mood regulation, and academic performance, further
intensifying anxiety levels (Maajida Aafreen et al., 2018).
4.2.2.6 Psychological factors
Intrusive or obsessive thought patterns and low self-esteem
are identified as significant psychological risk factors for anxiety.
These elements reflect a propensity towards negative thinking
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and excessive worry, hallmark features of anxiety disorders. Low
self-esteem may render individuals more susceptible to feelings
of inadequacy and an inability to navigate challenges effectively,
thereby elevating anxiety risk (Murad, 2020).
4.2.2.7 Protective role of religious beliefs
Contrastingly, our study indicates that religious beliefs may
confer a protective effect against anxiety. Faith and religious
engagement can give individuals hope, purpose, and belonging,
offering solace during stressful times. Spiritual practices are
also associated with structured support networks and coping
mechanisms that can mitigate anxiety (Butler et al., 2019).
In conclusion, our comprehensive analysis elucidates the
intricate interplay of multiple factors that contribute to anxiety
among children and adolescents in the ChES, underscoring the
necessity for intervention strategies that exhibit a wide range of
approaches. The findings of this study provide evidence in favor
of adopting targeted approaches that consider various elements,
including biological, developmental, environmental, technological,
and psychological influences. Moreover, it is critical to recognize
the potential advantageous influence of religious and community
engagement in mitigating anxiety.
4.2.3 Risk factors associated with stress among
children and adolescents in the ChES
The analysis of stress variables among children and adolescents
in the Chilean Educational System (ChES) reveals various
risk factors, underscoring the intricate interplay of biological,
psychological, environmental, and social influences.
4.2.3.1 Biological and gender-specific factors
A noteworthy finding is the increased vulnerability of females
to stress, with a 91.6% higher likelihood when compared to
males. The observed disparity can be ascribed to gender-specific
pressures and cultural expectations, which place a significant
burden on females, often requiring them to balance multiple
roles as caregivers, homemakers, and professionals (Nielson et al.,
2020), alongside hormonal fluctuations during puberty, which may
intensify emotional and psychological responses to stress (Hodes
and Epperson, 2019).
4.2.3.2 Environmental influences
Geographical location within Chile also plays a pivotal role,
with Coquimbo and Viña del Mar residents exhibiting a lower stress
incidence. These regions’ reduced population density and more
serene settings suggest an environmental buffer against stressors,
highlighting the importance of physical and social environments in
stress mitigation (Akpınar, 2021).
4.2.3.3 Technological and lifestyle factors
Ownership and cell phone usage contribute to increased
stress levels. The pressures of constant connectivity, exposure
to disturbing content, and sleep disruption are underscored as
primary concerns (Beyens et al., 2016;Soriano Sánchez, 2022;
Martínez-Líbano et al., 2023a), alongside the negative impact of
social media on relaxation and sleep quality (Beyens et al., 2016;
Soriano Sánchez, 2022;Martínez-Líbano et al., 2023a;Woods and
Scott, 2016).
4.2.3.4 Sleep and psychological well-being
Sleep’s critical role is evident, with sleep difficulties directly
linked to heightened stress levels. Sufficient sleep is indispensable
for effective stress management, mood regulation, and academic
performance, indicating a bidirectional relationship between stress
and sleep (Martínez-Líbano and Yeomans-Cabrera, 2023).
4.2.3.5 Psychological vulnerabilities
Obsessive or intrusive thoughts and low self-esteem are
highlighted as significant psychological risk factors. These elements
foster a cycle of worry and self-doubt, exacerbating stress sensitivity
and impeding effective coping mechanisms (Nielson et al., 2020).
4.2.3.6 Protective role of religious beliefs
Conversely, religious beliefs and practices emerge as protective
factors, offering emotional support, community, and coping
strategies that bolster resilience against stress (King, 2019).
4.2.3.7 Implications for Intervention
This analysis underlines the necessity for a collaborative
approach among schools, health professionals, and families in
identifying and supporting students at risk of stress. Proposed
strategies encompass emotional and psychological support
programs, educational initiatives to enhance mental health literacy,
responsible technology use, and bolstering family support systems.
Moreover, the accessibility of mental health services, irrespective
of geographical or socioeconomic status, is paramount.
The confluence of biological, psychological, environmental,
and social factors delineates a complex landscape of risk
factors for stress among children and adolescents in the
ChES. Understanding these factors is decisive for developing
comprehensive preventive and therapeutic interventions. By
fostering a supportive educational environment, promoting mental
health education, and ensuring a collaborative effort among key
stakeholders, it is feasible to mitigate the adverse effects of stress,
thereby enhancing students’ well-being and academic success
within the ChES.
Table 7 represents the comprehensive analysis of the various
risk factors and their correlation with depression, anxiety, and
stress in children and adolescents within the ChES. The table
categorizes risk factors such as Gender, Age, Cell Phone Use,
Family Structure, and Sleep Disturbances. Each factor is then
associated with its impact on depression, anxiety, and stress: (i).
Gender, identified as an increased risk for depression and stress
in females and anxiety in males; (ii). Age, specifically, anxiety
increases at age 12, but no specific age-related risk is mentioned
for depression or stress; (iii) Mobile phone use, associated with an
increased likelihood of all three conditions: depression, anxiety, and
stress; (iv) Family structure, risk of depression increases in cases
of separated parents, but no significant correlation is mentioned
for anxiety and stress; (v) Sleep disturbances, strongly related to
depression and also to anxiety and stress.
The risk factors identified suggest a multifactorial nature of
mental health problems in children and adolescents. Gender-
specific trends highlight possible biological and sociocultural
influences. The impact of technology (cell phone use) and family
dynamics (family structure) highlight environmental and social
factors. Sleep disorders, as a common risk factor, underscore the
function of physical health in mental well-being.
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These findings are consistent with global research highlighting
gender differences in mental health vulnerability, the impact of
technology on youth mental health, and the critical role of the
family environment (Centers for Disease Control and Prevention,
2023;Selph and McDonagh, 2019). For example, studies often
report higher rates of depression and anxiety in females during
adolescence (Racine et al., 2021). The association between cell
phone use and sleep disturbances has been a growing concern in
contemporary research (Kowalchuk et al., 2022).
A comprehensive understanding of these risk variables is
essential for formulating precise preventative and intervention
measures within the school system. This underscores the necessity
of implementing gender-sensitive strategies, closely monitoring the
utilization of technology, providing assistance to youngsters from
diverse familial backgrounds, and advocating for the cultivation of
appropriate sleep patterns.
This study provides a thorough examination of the mental
health difficulties experienced by children and adolescents in the
Chilean Educational System (ChES), highlighting the need for a
comprehensive and multifaceted strategy to tackle the complex
nature of depression, anxiety, and stress within this specific
population. Comprehending the diverse individual, familial,
educational, and socio-environmental factors is essential in
formulating and executing efficacious interventions and support
structures. The implementation of these treatments is crucial for
mitigating the frequency and severity of various mental health
issues, hence fostering a supportive and flexible environment.
4.3 Limitations of the present study
When analyzing the findings of this study, it is crucial to
consider certain constraints. Establishing a causal association
between the detected risk factors and mental health issues is
not possible due to the cross-sectional character of the study.
Conducting longitudinal research would be advantageous in
gaining a deeper understanding of the interplay between these
characteristics among children and adolescents in the ChES.
Furthermore, it should be noted that the purposive sample’s
constraint restricts the generalizability of the findings to the
broader community. Even though the students originated from
five distinct regions within the country, it is possible that their
representation may not fully encompass the nation’s geographic,
cultural, and socioeconomic diversity. Subsequent investigations
may derive advantages from a more heterogeneous sample.
Another significant disadvantage is the dependence on self-reports
for data collection. While the scales employed in this study have
been validated, it is essential to acknowledge that self-perception
can be influenced by subjective factors and biases, potentially
compromising the accuracy of the obtained data. These findings
could be enhanced by doing clinical exams and making behavioral
observations. Furthermore, despite identifying multiple significant
risk variables, other factors, such as the influence of social networks,
the quality of family connections, and the availability of mental
health treatments, were not thoroughly examined. To obtain a
more comprehensive understanding of the factors that influence
mental health in this group, future investigations could delve into
these and additional potential determinants. As a final limitation,
it is necessary to state that the participation of schools in this type
of study is voluntary and depends on the willingness and agenda of
each school, which may affect the sample’s representativeness.
4.4 Projections and practical implications
of the study
This study opens several future research and practical
applications. First, it would be helpful to investigate specific
interventions to address the identified risk factors. These include
emotional and psychological support programs in schools, training
for parents and teachers, and methods to encourage healthy use of
social networks and technology. To evaluate their effectiveness in
decreasing the prevalence of mental disorders among children and
adolescents in the ChES, long-term studies could be conducted.
In addition, future research could focus on developing more
accurate and less invasive assessment and diagnostic tools that
could be used frequently in the school setting to identify at-risk
students early. This would facilitate more timely and targeted
interventions. Another area of interest is the study of resilience
and protective factors in this population. Understanding how some
students manage stress and anxiety could provide vital information
for creating prevention and support programs. Research could
include a more comprehensive assessment of how Chile’s cultural,
socioeconomic, and regional variations influence student mental
health. This would facilitate the development of more culturally
specific intervention strategies. Finally, it would be advantageous
to combine this area of research with government policies
and educational practices. This study could be used to inform
policymakers and educators around the mental health needs of
students, which could lead to changes in school curriculum,
staff training, and resource allocation for support services. Future
research should focus on quantitatively assessing these risk factors,
examining their interaction, and exploring additional factors such
as socioeconomic status or educational environment. Longitudinal
studies could provide information on the evolution of these risk
factors over time.
5 Conclusion
The objective of this study was to determine the prevalence
of depression, anxiety, and stress in the population of Chile
after the pandemic, as well as identify associated risk factors.
The findings of the study revealed a significant occurrence of
sadness (60.2%), anxiety (63.6%), and stress (50.2%). Depression
risk factors encompass female gender, parental separation, high
school age, cell phone ownership, sleep disturbances, rumination,
and diminished self-worth. The factors contributing to anxiety were
female gender, age of 12, cell phone ownership, sleep disturbances,
rumination, low self-esteem, and being an atheist. Finally, several
characteristics were discovered as contributing to stress, including
being female, possessing a cell phone, experiencing sleep problems,
engaging in rumination, having low self-esteem, identifying as an
atheist, and extensively using social networks.
Concerning our hypothesis, there has been a notable rise in
the occurrence of disorders such as depression, anxiety, and stress
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Martínez-Líbano and Yeomans-Cabrera 10.3389/feduc.2024.1407021
among children and adolescents in the ChES after the COVID-19
pandemic, as compared to levels observed before the pandemic. In
addition, the prevalence of depression, anxiety, and stress exhibited
notable disparities across all age and gender cohorts within the
ChES population, indicating the unequal impact of the pandemic
on different segments.
Data availability statement
The datasets presented in this study can be found in
online repositories. The names of the repository/repositories
and accession number(s) can be found in the article/
supplementary material.
Ethics statement
The studies involving humans were approved by the Bioethics
Committee of the Faculty of Education and Social Sciences
of Universidad Andrés Bello. The studies were conducted
in accordance with the local legislation and institutional
requirements. The researchers did not request any compromising
information that may potentially identify the students who took
part in the study. Ultimately, informed consent was granted
by all participants’ parents and/or tutors at the outset of the
questionnaire, and all participants provided their signature as their
agreement. No compensation was provided for participation.
Author contributions
JM-L: Conceptualization, Data curation, Formal analysis,
Investigation, Methodology, Project administration, Resources,
Software, Visualization, Writing – original draft. M-MY-
C: Conceptualization, Funding acquisition, Investigation,
Methodology, Resources, Supervision, Visualization, Writing –
original draft, Writing – review and editing.
Funding
The author(s) declare financial support was received for the
research, authorship, and/or publication of the article. This research
was funded by the ADIPA – Academia Digital de Psicología y
Aprendizaje, grant number A20240303.
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.
Publisher’s note
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.
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