Early and Dynamic Socio-Academic Variables Related to Dropout Intention: A Predictive Model Made During Pandemic

Abstract

Social and academic integration variables have shown to be relevant for the understanding of university dropout. However, there is less evidence regarding the influence of these variables on dropout intention, as well as predictive models that explain their relationships. Improvements in this topic become relevant considering that dropout intention stands as a useful measure to anticipate and intervene on this phenomenon. The objective of the present study was to evaluate a predictive model for the university dropout intention that considers the relationships between social and academic variables, during the first university semester of 2020. The research was carried out using a cross-sectional associative-predictive design, with a convenience sampling (n=711) due the restrictions of pandemic period. The results showed a good fit of the proposed hypothetical model that explains 38.7% of dropout intention. Both social support and perceived social isolation predicted the sense of belonging, and through it, engagement. Previous academic performance predicted early academic performance, and through it, engagement. The set of variables predicted the intention to quit, through engagement. These results are a contribution both to the understanding of the phenomenon and to guide potential interventions in the early stages of the university experience.

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Citation: Maluenda-Albornoz, J.;
Infante-Villagrán, V.; Galve-González,
C.; Flores-Oyarzo, G.; Berríos-
Riquelme, J. Early and Dynamic
Socio-Academic Variables Related to
Dropout Intention: A Predictive
Model Made during the Pandemic.
Sustainability 2022,14, 831. https://
doi.org/10.3390/su14020831
Academic Editors: Roy Rillera Marzo,
Siyan Yi, Mostafa Dianatinasab,
Edlaine Faria de Moura Villela,
Praval Khanal and Yulan Lin
Received: 2 December 2021
Accepted: 3 January 2022
Published: 12 January 2022
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sustainability
Article
Early and Dynamic Socio-Academic Variables Related to
Dropout Intention: A Predictive Model Made during
the Pandemic
Jorge Maluenda-Albornoz 1, *, Valeria Infante-Villagrán2, Celia Galve-González 3, Gabriela Flores-Oyarzo 4
and JoséBerríos-Riquelme 5
1Facultad de Psicología, Universidad San Sebastián, Sede Concepción, Concepción 4080871, Chile
2Programa de Doctorado en Psicología, Departamento de Psicología, Universidad de Concepción,
Concepción 4070386, Chile; valeria.a.infante.v@gmail.com
3Departamento de Psicología, Universidad de Oviedo, 33003 Oviedo, Spain; celiagalvegon@gmail.com
4Investigadora Independiente, Concepción 4080871, Chile; gabflores@udec.cl
5Departamento de Ciencias Sociales, Universidad de Tarapacá, Iquique 1113749, Chile; jberrios@uta.cl
*Correspondence: Jorge.maluenda@uss.cl
Abstract:
Social and academic integration variables have been shown to be relevant for the under-
standing of university dropout. However, there is less evidence regarding the influence of these
variables on dropout intention, as well as the predictive models that explain their relationships.
Improvements in this topic become relevant considering that dropout intention stands as a use-
ful measure to anticipate and intervene this phenomenon. The objective of the present study was
to evaluate a predictive model for university dropout intention that considers the relationships
between social and academic variables during the first university semester of 2020. The research
was conducted using a cross-sectional associative-predictive design, with a convenience sampling
(n= 711
) due to the restrictions of the pandemic period. The results showed a good fit of the proposed
hypothetical model that explained 38.7% of dropout intention. Both social support and perceived
social isolation predicted the sense of belonging and, through it, engagement. Previous academic
performance predicted early academic performance and, through it, engagement. The set of variables
predicted the intention to quit through engagement. These results are a contribution both to the
understanding of the phenomenon and to guide potential interventions in the early stages of the
university experience.
Keywords:
dropout intention; perceived social isolation; perceived social support; engagement; sense
of belonging; higher education
1. Introduction
1.1. University Dropout and Dropout Intention
University dropout in Latin America and the Caribbean is a critical problem, with
rates that can reach 54%. In addition, approximately 22% of the population between 25 and
29 years old has abandoned their studies [
1
]. In this context, the first year of university is
the greatest concern as it produces a higher dropout rate in higher education, making the
educational process difficult at an early stage [
2
]. Chile is no exception, reaching dropout
rates of 26.4% at the higher education level and 23.1% at the university level during the first
year of studies [
3
]. The effects of dropout include an impact at the individual and family
level, with repercussions on the life project and the family economy [
4
,
5
] at the institutional
level with respect to quality and efficiency indicators. At the social level, dropout affects
social and economic development due to the decline in human capital [6].
In recent years, there has been an important interest in studying the dropout intention
of university students as it is a variable that can be measured early to anticipate complete
Sustainability 2022,14, 831. https://doi.org/10.3390/su14020831 https://www.mdpi.com/journal/sustainability

Sustainability 2022,14, 831 2 of 18
dropout. Its measurement in early stages, for example, during the first year, would influ-
ence the decision of the students through strategies to support them. For example, these
strategies would help promote better social and academic integration in university. In
addition, some research has shown the importance of studying the perceptions of university
students with respect to their dropout intention, as dropout intention can negatively impact
well-being and academic performance [7].
It has been observed that the variables that influence the social and academic inte-
gration of students are linked to dropout [
8
–
11
], and may also influence dropout inten-
tion [
12
–
15
]. However, the research is still incipient, and there is room for improvement in
the refinement of the differential importance of these variables, as well as the elaboration of
a theoretically coherent model that allows the prediction of their occurrence.
It is important to indicate that the COVID-19 pandemic has brought a series of impor-
tant consequences for the development of university education. The COVID-19 pandemic
gave rise to a remote or hybrid educational process, without the teachers and university
systems having been sufficiently prepared to face this rearrangement [
16
–
18
]. This has
implied an accelerated adjustment of teachers in the necessary tools for remote education,
a change in teaching strategies, and the updating of technological supports [19,20].
Mooney and Becker [
21
] conducted a study where they proposed that the events
surrounding COVID-19 were a challenge for the sense of belonging of many students,
mainly for those entering the first year. In total, 50% of the students who participated in
the study reported that levels of stress and anxiety related to COVID-19 were extremely
challenging or very challenging. This study showed that, to a greater extent, COVID-19
affects the sense of belonging in men and women who do not feel they belong, with the
results being statistically significant in men. This could be explained by the fact that
virtual environments are not able to replicate the key facets of presence [
22
]. An additional
explanation is that the sense of belonging and the physical space of the campus are closely
related [23], and that belonging increases with social interaction [24].
The characteristics of remote education in times of pandemic could introduce differ-
ences in the influence that predictive variables have on dropout intention in the context of a
regular study. For example, students have had to adjust to the new educational conditions
with difficulties related to access and technological literacy, the adjustment of the home to
office space, and study and work conditions in very diverse socioeconomic backgrounds
(or contexts) among families [25].
In addition to the abovementioned factors, today’s educational process takes place in
a different context than the usual process. Today, the educational process is marked by a
lack of direct interpersonal contact, a lower possibility of teacher control over the student’s
activity, and, therefore, the need for skills among students to be able to face their learning
more autonomously.
1.2. Support and Perceived Social Isolation
There are different sources of support that can be provided by the community, social
networks, and trusted people. However, social support tends to come more frequently
from trusted people with whom one shares a greater degree of intimacy [26].
Research has shown that peer and teacher support influence the decision to drop out
of university studies [
15
,
27
]. This relationship arises as the most immediate support that
students have during their studies is that of their significant teachers and peers.
Perceived social support is defined as the evaluation made by the student regarding
the quantity and quality of social support available, if its use is necessary [
28
]. In this
way, it constitutes a subjective perception of the availability of the social network and the
satisfaction of personal needs through support [29].
Supports can fulfill both an expressive function with an end in itself (e.g., sharing
a problem or a moment of pleasure) and an instrumental function aimed at achieving a
specific objective or good (e.g., receiving education or information) [
30
]. This distinction
is relevant if we consider the results observed in university dropout studies, where social

Sustainability 2022,14, 831 3 of 18
interaction specifically linked to support in academic work showed a more important
effect [31].
In the current educational context, social variables can play a very important role
due to the confinement and forced social isolation of university studies. It is possible that
isolation has effects in different dimensions, such as socio-emotional balance, which will be
increased in students with pre-existing problems [32].
Perceived social isolation is defined as the subjective evaluation regarding the avail-
ability of contacts or social ties [33] to the extent necessary for each person.
The attributional discrepancy theory is important both for understanding perceived
social support and social isolation. The subjective evaluation that the students make of
their social relationships varies according to their own standards [
34
]. In this way, the
perception of support and social isolation considers the level of social contact that people
require. The perception of support and social isolation can each be heterogeneous. In other
words, students may perceive more or less support, isolation, or social belonging with
respect to the available objective levels [28,33].
Both support and social isolation have shown their importance in university studies
due to their impact on social integration of students and the consequences of this on mental
health and the networks available to advance in academic activities [
35
,
36
], in addition
to being directly related to lower dropout rates [
37
]. Therefore, the greater the social
integration, the lower the probability of drop out, where social integration is being affected
by both social support and social isolation.
College students who do not make effective connections with their peers and pro-
fessors are likely to feel alienated and/or marginalized. When this situation is sustained
over time, it can become an incentive for dropout [
35
]. In addition, it has been observed
that social isolation can severely deteriorate the educational experience, being linked to
anxiety, depression, and stress [
35
] and disengagement with studies [
38
]. However, having
social support can act as a buffer for student stress and discomfort in difficult situations,
favoring conditions that allow a better approach and decision making [
39
], which can act
as a protective factor against dropout intention.
It has been observed that the perceived social support and the interpersonal relation-
ships that students establish with their peers, teachers, and members of the university
campus are fundamental aspects to develop a sense of belonging [
40
–
44
], an aspect in-
versely related to the dropout intention. This is as social support and positive interactions
are essential for the development of a sense of belonging in university students [
40
,
45
].
The support of peers and parents has also shown to influence the sense of belonging to the
institution and has been linked to a greater institutional engagement [46].
Student’s social integration with peers and teachers has shown to be a direct and
strong predictor of academic engagement and an indirect predictor of the intention to stay
or drop out [
47
]. The perception of support from teachers has been negatively related to
the dropout intention [
48
]. Therefore, the greater the social integration, the greater the
academic engagement and the lower the dropout intention.
A few studies have directly measured social isolation in college students during the
pandemic [
49
]. Regarding this specific scenario, it has been observed that social isolation
influences the mental health of students [50–57].
Some studies during the current pandemic have observed similar results to those in
the regular educational context: social isolation in university students is related to mental
health effects such as stress, anxiety, and insomnia [58,59].
Social integration variables have been one of the most studied in recent years, among
which, recently, social adaptation and the sense of belonging have become relevant [
27
,
60
].
1.3. Sense of Belonging
The sense of belonging is defined as the perception of membership or feeling part of
the educational organization (study program) in which a person studies [
61
]. Feelings of
belonging to the career implies that the student feels valuable and respected in their own

Sustainability 2022,14, 831 4 of 18
educational program [
40
,
43
–
45
,
62
–
66
]. It implies a perceived bond between the student
and others, which unites them to a group or community, even in difficult moments or in
the face of challenges [
67
], and the impulse that mobilizes them to create and maintain
meaningful and lasting interpersonal relationships [68].
The model proposed in this study focuses on the sense of belonging to the study
program in which the students study, so the kind of sense of belonging that is referred to in
this study is the sense of career belonging.
The sense of belonging arises due to the process of integration of a person in their
organization and, consequently, due to the levels of support or isolation perceived by the
students. When students connect with the formal academic, social, and cultural learning
environment of the academic community, they develop a sense of belonging that translates
into a desire to stay and complete their educational goals [69].
Belonging students share cultural aspects of the organization and voluntarily par-
ticipate in the life and activities of the organization [
70
]. When there is a deep sense of
belonging, the student’s self-definition can be connected to what defines the organization,
affecting their identity and behavior [71].
The social integration of students fosters a sense of belonging to the community, a
variable that has been shown to be a predictor of permanence in university studies in a
regular educational context [
46
]. Therefore, when the student is socially integrated, it favors
the development of a sense of belonging.
On the other hand, when students do not feel valued and respected by others, or do
not feel that they belong to a social environment, they are more likely to drop out of their
studies [
72
], the sense of belonging to the career being a significant predictor of the dropout
intention in university students [73].
The link between the sense of belonging and the dropout intention is due in part to the
fact that it strengthens the engagement of students. It has been observed that the similarity
and connection that students perceive with respect to their immediate academic community
has been a predictor of engagement [
74
]. It has also been shown to be a predictor of the
exertion of committed behaviors such as respecting the rules or assuming more functions
than the mandatory ones [75].
The pandemic of COVID-19, poses various challenges for university students, includ-
ing adjusting to an online educational system while keeping their academic and work
duties and responsibilities up to date, adjusting to changes in terms and schedules, and the
lack of a space or physical context for interaction where they can share their concerns and
experiences with peers [
76
]. In a study carried out by Markel and Guo [
22
] during the first
months of the COVID-19 pandemic, they showed that, in virtual learning environments,
although remote technologies can contribute to inclusion, they also pose additional barriers
for students.
It has been observed that high levels in the sense of belonging in university students
contribute to increasing their levels of participation, being able to seek help in the face of dif-
ficulties, feeling less alone, anxious, or depressed, increasing the use of self-regulation strate-
gies, and raising levels of academic self-confidence and motivation [
64
,
66
,
77
]. In addition,
various investigations have observed that the sense of belonging turns out to be a direct pre-
dictor of study engagement, dropout, and permanence in studie
s [40,41,45,65,66,73,77–80].
1.4. Academic Variables and University Dropout Intention
The relationship between academic performance and dropout has been reported
many times, showing, in general, that performance is a significant predictor of college
dropout [2,9].
Academic performance is understood as the level of knowledge demonstrated in an
area or subject compared to the age norm and academic level [
81
]. However, in practical
terms, performance is usually measured from classroom assessments that do not necessarily
entail associated standardizations. Performance is commonly considered as the level of
achievement that a student obtains in their training process, expressed through a numerical

Sustainability 2022,14, 831 5 of 18
assessment [
82
]. Their relationship has been investigated and described as an academic
precedent for dropping out of studies where the score in the University Selection Test (PSU)
has been the most used in the Chilean context [83,84].
The theoretical relationship between previous performance and dropout lies in the
fact that previous performance reflects the academic abilities that students develop before
entering higher education, which influence the academic integration process [
85
]. In this
way, the level of prior academic preparation of students would influence the mastery of
basic knowledge and skills necessary for current studies.
The relationship between academic performance during studies and dropout has been
less explored and could be important in the student’s decision making regarding whether
to remain or abandon ongoing studies.
For Bernardo et al. [
86
] academic performance during studies operates as an indicator
for the student about their degree of academic integration, which becomes a key element in
the decision to remain or abandon studies. In addition, there is research that has shown its
influence on student decision making about permanence and the effect it has on university
dropout [87].
Early academic performance would operate as feedback on the effectiveness of the
efforts made to study and the ability to face a university career. In addition, it becomes
vital information to decide in terms of cost–benefit on the continuation of the studies [88].
1.5. Engagement and Dropout Intention
Different studies with university students have shown that the level of engagement
exhibited by students proves to be a strong significant predictor of dropout in university
students [13,73,89].
Engagement is understood as the set of manifestations of motivation with studies [
90
]
which have developed, over the last decades, theories that group this phenomenon into
three main dimensions [
91
]: the behavioral dimension, which would refer to all those
behaviors carried out by the student who is interested in learning; the cognitive dimension,
which would refer to all those thoughts, beliefs, and perceptions about the importance of
academic work and the effort that it entails; and the emotional dimension, which includes
the feelings and attitudes that the student experiences around the institution.
In this sense, the engagement proposal is based on the Self-determination Theory
(SDT) [
92
]. This is understood as the set of manifestations of motivation for studies [
90
] that
arises from the satisfaction of the needs of competence, autonomy, and relationship in the
context of studies [
90
]. In the educational context, the need for autonomy is satisfied when
the student feels that he or she makes choices and is motivated by intrinsic rather than
external factors. The need for competence is favored when the structure of the class allows
the desired results to be achieved. The need to be related is satisfied when the student
establishes relationships with their teachers and peers based on support and concern [90].
As for the relationship between engagement and dropout intention, there is a much
smaller volume of research. Despite this, it has been observed that engagement is also a
strong significant predictor of dropout intention [93,94].
During 2020 and 2021, most of the published studies have shown that the current
educational context has generated damage in the motivation and participation of stu-
dents [
20
,
95
] and a decrease in their levels of engagement [
96
,
97
]. Some studies have
attributed this deficit to factors associated with mental health such as stress, anxiety, and
insomnia during confinement, which affect the energy and vigor levels associated with
student engagement associated with the situation of social isolation and remote educa-
tion [58,59].
A predictive associative study during the pandemic with university students from nine
countries found that engagement was a positive predictor of performance and a negative
predictor of dropout intention [
98
]. Another study carried out during the pandemic with
Chilean university students observed that the expectations about their level of engagement

Sustainability 2022,14, 831 6 of 18
and about their performance during the semester were shown to be predictors of their early
dropout intention [19].
All the variables previously described are considered dynamic variables, as they
can change through intervention and constitute a set of key factors to understand the
phenomenon of university dropout, as the evidence presented preliminarily has shown.
The variables included in this research represent two specific virtues: (a) are variables
that can be influenced during university studies favoring potential interventions; (b) are
variables that can be measured in very early stages of the educational process, therefore
favoring a rapid response by universities in the face of risk situations.
The main objective of the present research was to evaluate a predictive model for the
university dropout intention that considers the relationships between previous and early
academic performance, sense of belonging to the career, support, and perceived social
isolation in the career, and academic engagement during the first university semester of
2020. This study, therefore, has been developed during the start of the COVID-19 pandemic
in Chile. The hypothetical model of relationships based on the theoretical and empirical
aspects previously raised is observed in Figure 1.
Sustainability 2022, 14, x FOR PEER REVIEW 6 of 19
[20,95] and a decrease in their levels of engagement [96,97]. Some studies have attributed
this deficit to factors associated with mental health such as stress, anxiety, and insomnia
during confinement, which affect the energy and vigor levels associated with student en-
gagement associated with the situation of social isolation and remote education [58,59].
A predictive associative study during the pandemic with university students from
nine countries found that engagement was a positive predictor of performance and a neg-
ative predictor of dropout intention [98]. Another study carried out during the pandemic
with Chilean university students observed that the expectations about their level of en-
gagement and about their performance during the semester were shown to be predictors
of their early dropout intention [19].
All the variables previously described are considered dynamic variables, as they can
change through intervention and constitute a set of key factors to understand the phe-
nomenon of university dropout, as the evidence presented preliminarily has shown. The
variables included in this research represent two specific virtues: (a) are variables that can
be influenced during university studies favoring potential interventions; (b) are variables
that can be measured in very early stages of the educational process, therefore favoring a
rapid response by universities in the face of risk situations.
The main objective of the present research was to evaluate a predictive model for the
university dropout intention that considers the relationships between previous and early
academic performance, sense of belonging to the career, support, and perceived social
isolation in the career, and academic engagement during the first university semester of
2020. This study, therefore, has been developed during the start of the COVID-19 pan-
demic in Chile. The hypothetical model of relationships based on the theoretical and em-
pirical aspects previously raised is observed in Figure 1.
Figure 1. Hypothetical model for Dropout Intention.
2. Materials and Methods
2.1. Participants
The sample was made up of 711 first-semester students enrolled in 2020 from a Chil-
ean university, equivalent to 16.78% of the total population. It was distributed among 285
men (40.09%), 422 women (59.35%), and 4 students who identified with another prefer-
ence (0.56%). The average age of the students was 18.8 years, with a standard deviation of
1.7 years, a minimum of 17 years and a maximum of 33.
The students were recruited through the authorities of their respective careers; their
participation was voluntary and did not imply compensation of any kind.
Figure 1. Hypothetical model for Dropout Intention.
2. Materials and Methods
2.1. Participants
The sample was made up of 711 first-semester students enrolled in 2020 from a Chilean
university, equivalent to 16.78% of the total population. It was distributed among 285 men
(40.09%), 422 women (59.35%), and 4 students who identified with another preference
(0.56%). The average age of the students was 18.8 years, with a standard deviation of
1.7 years, a minimum of 17 years and a maximum of 33.
The students were recruited through the authorities of their respective careers; their
participation was voluntary and did not imply compensation of any kind.
The distribution of students according to the disciplinary area of their career and the
dropout percentage reported by the degree in which the student enrolled during 2020 is
shown in Table 1.
2.2. Design
The current research was carried out using a cross-sectional associative-predictive de-
sign. The selection of the participants was carried out using a non-probability convenience
sampling due to the restrictions imposed by the COVID-19 pandemic for access to the
participants. All first-semester students enrolled in 2020, belonging to a Chilean university,
were invited to participate openly and voluntarily. The voluntary invitation was made by

Sustainability 2022,14, 831 7 of 18
email. The students read and accepted an informed consent approved by the university’s
research ethics committee, which led them to the instrument in electronic format. The data
collection was carried out during May and June of the year 2020 to have students who have
had initial experience at the university and have their first qualifications.
Table 1. Distribution of participants by career area and dropout rate.
Career Area
High Dropout
Rate
(N)
Medium
Dropout Rate
(N)
Low Dropout
Rate
(N)
Total
(N)
Legal, economic, and
administrative 20 28 5 53
Agriculture and forestry
technology and sciences 21 17 48 86
Social sciences and
humanities 64 57 46 167
Exact and natural sciences
70 11 39 120
Technology and health
sciences 22 42 91 155
Engineering science and
technology 48 72 10 130
Total 245 227 239
2.3. Instruments
An electronic questionnaire was made from different instruments that have been
adapted to the Chilean context with recent evidence of validity and reliability for the
variables of this research. In those studies, all the psychometric properties were tested
using Confirmatory Factor Analysis (CFA), the Cronbach’s alpha index, and the McDonald’s
omega index.
The instrument consisted of 33 items whose response format was through a Likert-
type scale of 1 to 7 points (1 indicates maximum disagreement and 7 indicates maximum
agreement). It included:
-
University Student Engagement Scale (15 items) created by Maroco et al. [
89
] and
adapted to Chilean university students [
13
]. This instrument measures engagement as
the result of high motivation for studies in the career context. The validation study
showed a bifactorial structure with one general factor and three subfactors: Interest
(5 items), Effort (5 items), and Participation (5 items). In the adapted version the fit
indices showed good performance of the bifactorial model (
χ2
= 210.276,
p< 0.001
;
RMSEA = 0.047 (95% IC: 0.040–0.055; CFI = 0.967; TLI = 0.954) as well as reliability
(α= 0.841; ω= 0.843) and criterion validity.
-
Membership factor of the Organizational Identification Questionnaire with Study
Centers created by Yáñez et al. [
99
] and adapted to Chilean university students [
100
].
It measures, through 4 items, the degree of belonging perceived by the students within
the career they are studying. The adapted version showed good fit indices for a one
factor structure (
χ2
= 3.126, p= 0.20; RMSEA = 0.028 (95% IC: 0.000–0.085; CFI = 0.999;
TLI = 0.999; RSMR = 0.005) as well as reliability (α= 0.815; ω= 0.834).
-
Perceived social support items inspired by the measurement carried out in Chilean
university students in the FONDECYT project N
◦
1161502, adapted to refer specifically
to the career level [
101
]. These 4 items measure the perception of having a reliable net-
work in the university context (by peers and professors) when it is needed. It showed
good fit indices for a one factor structure (
χ2
= 11.616, p= 0.003;
RMSEA = 0.072
(95% IC: 0.041–0.131; CFI = 0.997; TLI = 0.992; RSMR = 0.011) as well as reliability
(α= 0.798 ω= 0.823).
-
Perceived social isolation items based on the UCLA Loneliness Scale—revised ver-
sion [
102
] adapted to refer specifically to the career level. It measures through 4 items

Sustainability 2022,14, 831 8 of 18
the perception of lack of social relationships and meaningful ties in the university con-
text (with peers and professors). It showed good fit indices for a one factor structure
(
χ2
= 5.741, p= 0.056; RMSEA = 0.051 (95% IC: 0.000–0.103; CFI = 0.999; TLI = 0.997;
RSMR = 0.008) as well as reliability (α= 0.800 ω= 0.817).
-
The dropout intentions were measured from 4 items taken from FONDECYT project
N
◦
1161502 that have been previously used in the same population and that refer to
the student’s dropout intention of university [
101
]. It showed good fit indices for
a one factor structure (
χ2
= 9.732, p= 0.007; RMSEA = 0.074 (95% IC:
0.032–0.123
;
CFI = 0.999; TLI = 0.996; RSMR = 0.004) as well as reliability (α= 0.834 ω= 0.834).
-
One item was considered to collect the prior academic performance, which is mea-
sured through the simple average of grades obtained by the students in the national
university selection test called “Prueba de Selección Universitaria” (PSU).
-
Finally, one item was considered to collect early academic performance. It corresponds
to the simple average of grades obtained by the student in the middle of the first
academic semester (May–June 2020).
2.4. Analysis
The evaluation of the proposed model and the associated research hypotheses followed
the 3 phases proposed by Kline [103] for the evaluation of structural models:
-
Specification of the evaluated model. The included variables and its relationships
were specified based on the literature review. The result was the hypothetical model
presented in Figure 1which consisted of 5 latent and 2 observed variables as principal
components of this research.
-
Estimation by “Weighted Least Square Mean and Variance” (WLSMV). It allows work
with continuous and categorical variables at the same time [
104
]. In addition, it is an
estimator that works well with samples of moderate size and complex models [105].
-
Evaluation of the model. Goodness of fit was calculated to evaluate the hypothetical
model. Based on these results and theoretical background decisions about re-specified
model were made. The reference values used to evaluate goodness of fit were: sig-
nificant
χ2
, decrease in the NCP value in the re-specified model, CFI and TLI
≥
0.90,
RMSEA
≤
0.08 [
106
], and
ω
> 0. 70,
α
> 0.70 [
106
,
107
]. All analyses were performed
using the statistical software MPLUS version 8.
Mediation analysis to study sense of belonging and study engagement as possible
intervention variables were made using MPLUS version 8.
3. Results
3.1. Preliminary Analyses
Table 2shows the means, standard deviations, skewness, kurtosis, minimum, and
maximum value. All asymmetry and kurtosis values were less than 3, which show that the
structure of the data tends to approximate a univariate normal distribution except for the
dropout intention, which presents a kurtosis value slightly higher than this criterion. The
results of the Kolmogorov–Smirnov normality test did not show statistically significant
differences in any of the variables evaluated. This result corroborates what was previously
found in the descriptive analysis presented. Thus, the data are assumed to have a univariate
normal distribution.
3.2. Research Results
The evaluation of the proposed model showed an appropriate fit in all the fit indices
tested except for the
χ2
index, which turned out to be significant. However, it has been
observed that this indicator tends to be misaligned with large sizes [
105
]. Its correction
through the NCP ratio reaches a small value, an indicator of a good fit [
106
]. All these values
are shown in Table 3. It is important to add that the two criteria to obtain the minimum
required/desirable sample size proposed by Hair et al. [
106
] were considered: the 10x rule

Sustainability 2022,14, 831 9 of 18
and the minimum r2. According to the above, it was observed that the recommended, as
well as the desirable, minimum sample size was 308.
Table 2. Descriptive statistics.
Variable n Min Max Mean SD Skewness Kurtosis
Previous academic performance 711 200 809 623.56 71.12 −0.42 2.25
Early academic performance 711 30 70 57.43 6.85 −0.70 0.26
Sense of belonging 711 4 28 19.99 5.04 −0.60 −0.19
Perceived social support 711 4 28 17.29 5.59 −0.32 −0.50
Isolation 711 4 28 11.73 5.39 −0.54 −0.46
Study engagement 711 18 105 82.48 11.93 −0.94 1.99
Dropout intentions 711 4 28 7.19 4.40 1.77 3.30
Table 3. Initial model Fit Indices.
Model χ2gl NCP CFI TLI RMSEA SRMR
Initial model 2102.512; p<
0.001 485 2.27 0.931 0.924 0.068 IC 95%
(0.065–0.072) 0.071
The standardized beta values of the model show significant values in most of the
relationships proposed between the variables, except for the routes that include the direct
influence of perceived social support on study engagement (
β
= 0.024, p> 0.05) and
on dropout intention (
β
=
−
0.030, p> 0.05). For the other relationships, the observed
standardized beta values were significant and fluctuated between moderate and strong
values (β= 0.217 β=−0.796, p< 0.01). The initial model is shown in Figure 2.
Sustainability 2022, 14, x FOR PEER REVIEW 9 of 19
Table 2. Descriptive statistics.
Variable n Min Max Mean SD Skewness Kurtosis
Previous academic performance 711 200 809 623.56 71.12 −0.42 2.25
Early academic performance 711 30 70 57.43 6.85 −0.70 0.26
Sense of belonging 711 4 28 19.99 5.04 −0.60 −0.19
Perceived social support 711 4 28 17.29 5.59 −0.32 −0.50
Isolation 711 4 28 11.73 5.39 −0.54 −0.46
Study engagement 711 18 105 82.48 11.93 −0.94 1.99
Dropout intentions 711 4 28 7.19 4.40 1.77 3.30
3.2. Research Results
The evaluation of the proposed model showed an appropriate fit in all the fit indices
tested except for the χ2 index, which turned out to be significant. However, it has been
observed that this indicator tends to be misaligned with large sizes [105]. Its correction
through the NCP ratio reaches a small value, an indicator of a good fit [106]. All these
values are shown in Table 3. It is important to add that the two criteria to obtain the min-
imum required/desirable sample size proposed by Hair et al. [106] were considered: the
10x rule and the minimum r2. According to the above, it was observed that the recom-
mended, as well as the desirable, minimum sample size was 308.
Table 3. Initial model Fit Indices.
Model χ2 gl NCP CFI TLI RMSEA SRMR
Initial model 2102.512; p < 0.001 485 2.27 0.931 0.924 0.068 IC 95% (0.065 – 0.072) 0.071
The standardized beta values of the model show significant values in most of the
relationships proposed between the variables, except for the routes that include the direct
influence of perceived social support on study engagement (β = 0.024, p > 0.05) and on
dropout intention (β = −0.030, p > 0.05). For the other relationships, the observed stand-
ardized beta values were significant and fluctuated between moderate and strong values
(β = 0.217 β = −0.796, p < 0.01). The initial model is shown in Figure 2.
Figure 2. Tested model for Dropout Intention. p values were all p < 0.001.
Figure 2. Tested model for Dropout Intention. pvalues were all p< 0.001.
A re-specified model was evaluated only with significant relations, considering as
a hypothesis that the effect of social support on the dropout intention occurs through a
double mediation given by the sense of belonging and academic engagement. The new
model improved all the fit indices (Table 4) except for
χ2
, which turned out to be significant.
However, the contrast in the NCP values showed a better fit in the second model. The

Sustainability 2022,14, 831 10 of 18
re-specified model and its values are shown in Figure 3and Table 4, respectively. In this
sense, the new model showed a better fit in all the indicators and reflected 38.7% of the
explanation for dropout intention.
Table 4. Re-specified model Fit Indices.
Model χ2gl NCP CFI TLI RMSEA SRMR
Re-specified
model
1995.754; p<
0.001 486 2.12 0.955 0.950 0.066 IC 95%
(0.063–0.069) 0.071
Sustainability 2022, 14, x FOR PEER REVIEW 10 of 19
A re-specified model was evaluated only with significant relations, considering as a
hypothesis that the effect of social support on the dropout intention occurs through a dou-
ble mediation given by the sense of belonging and academic engagement. The new model
improved all the fit indices (Table 4) except for χ2, which turned out to be significant.
However, the contrast in the NCP values showed a better fit in the second model. The re-
specified model and its values are shown in Figure 3 and Table 4, respectively. In this
sense, the new model showed a better fit in all the indicators and reflected 38.7% of the
explanation for dropout intention.
Figure 3. Re-specified model for Dropout Intention. p value were all p < 0.001.
Table 4. Re-specified model Fit Indices.
Model χ2 gl NCP CFI TLI RMSEA SRMR
Re-specified model 1995.754; p < 0.001 486 2.12 0.955 0.950 0.066 IC 95% (0.063–0.069) 0.071
3.3. Mediation Analysis
The evaluation of mediation analysis considering study engagement as a dependent
variable showed an indirect effect of perceived social isolation on study engagement
through the sense of belonging (Table 5). A direct effect of perceived social support on
study engagement was found, but not a direct effect of perceived social isolation on study
engagement. Additionally, an indirect effect of both variables mediated by sense of be-
longing on study engagement was found.
Table 5. Standardized estimates of indirect, direct, and total effects of perceived social isolation and
perceived social support on study engagement with sense of belonging as a mediator.
Effect [95% IC] Estimate p Value
Direct effects −0.009 0.905
Perceived social isolation → Study Engagement
Perceived social support → Study Engagement 0.259 <0.001
Indirect effects
Perceived social isolation → Sense of belonging → Study Engagement −0.197 <0.001
Perceived social support → Sense of belonging → Study Engagement 0.161 <0.001
Total
Perceived social isolation → Study Engagement −0.206 0.007
Perceived social support → Study Engagement 0.420 <0.001
Figure 3. Re-specified model for Dropout Intention. pvalue were all p< 0.001.
3.3. Mediation Analysis
The evaluation of mediation analysis considering study engagement as a dependent
variable showed an indirect effect of perceived social isolation on study engagement
through the sense of belonging (Table 5). A direct effect of perceived social support
on study engagement was found, but not a direct effect of perceived social isolation on
study engagement. Additionally, an indirect effect of both variables mediated by sense of
belonging on study engagement was found.
Table 5. Standardized estimates of indirect, direct, and total effects of perceived social isolation and
perceived social support on study engagement with sense of belonging as a mediator.
Effect [95% IC] Estimate pValue
Direct effects −0.009 0.905
Perceived social isolation →Study Engagement
Perceived social support →Study Engagement 0.259 <0.001
Indirect effects
Perceived social isolation →Sense of belonging →Study
Engagement −0.197 <0.001
Perceived social support →Sense of belonging →Study
Engagement 0.161 <0.001
Total
Perceived social isolation →Study Engagement −0.206 0.007
Perceived social support →Study Engagement 0.420 <0.001

Sustainability 2022,14, 831 11 of 18
The evaluation of mediation analysis considering dropout intention as a dependent
variable showed an indirect effect of sense of belonging on dropout intention through the
study engagement but not a direct effect on it (Table 6).
Table 6.
Standardized estimates of indirect, direct, and total effects of sense of belonging on dropout
intention with study engagement as a mediator.
Effect [95% IC] Estimate pValue
Direct effects −0.006 0.756
Sense of belonging →Dropout intention
Indirect effects
Sense of belonging →Study engagement →Dropout intention −0.256 <0.001
Total
Sense of belonging →Dropout intention −0.306 <0.001
4. Discussion
4.1. General Model: University Dropout Intention
The present research proposed a model based on social and academic integration
variables to explain university dropout intention in first-year students. The research is
based on two essential assumptions that are at the base of the hypothetical model proposed.
Firstly, it was argued that the integration of a student in the social life of a career is related
to the sense of belonging, a variable with a strong influence on the degree of engagement
that he or she manifests with their academic activities and with the human group that
makes up the career, which influences the decision to stay or drop out of their current
university. Secondly, it has been proposed that academic performance can act through
the capacities developed to face academic life and as a source of information that affects
decision making regarding staying or leaving studies.
To these assumptions, three key specifications are added, which this research aims to
provide evidence for. Firstly, the importance of specifying the measurement of variables
at the career level, as it is the immediate context in which students operate and the one
that may have the greatest impact on their decisions during the educational process. The
only exception to this condition was previous performance due to its past nature. Secondly,
the importance of considering variables that can be measured early in the educational
process was raised. This is due to the need to have relevant information regarding the
decision to dropout or remain in the studies which is possible to know quickly and which
allows decisions to be made before the dropout has been done. Thirdly, the need to work
mainly with predictive variables that were potentially modifiable (dynamic variables)
was proposed to contribute to the knowledge that can be applied in the improvement of
institutional processes.
From these results, it is possible to indicate the fulfillment of the objective of this
study. The results showed an adequate general model fit, with most of the hypothetical
relationships raised being significant with moderate to strong values. However, the routes
that include the direct influence of perceived social support on study engagement and on
dropout intention were not statistically significant, the reason it was decided to re-specify
the model. The new model showed a better fit in all the indicators and reflected 38.7% of
the explanation for dropout intention.
From the re-specified model, it is possible to conclude that both the social [
48
] and aca-
demic variables considered have a relevant influence on the dropout intention, reaffirming
what has already been described in the preliminary research [73,98].
In the present model, the influence of the social and academic integration variables
predicts engagement, which acts as the main mediating variable of the model. The influence
of social support and perceived social isolation, in turn, is mediated by the sense of
belonging to the career, a variable that exerts a strong influence on engagement. The
influence of previous academic performance on engagement is in turn predicted by early
academic performance.

Sustainability 2022,14, 831 12 of 18
The original model was proposed with an independent influence between social and
academic variables due to its measurement in the same time cut-off. It is not reasonable to
argue that current perceived social support, isolation, and sense of belonging influenced
early performance that had already been achieved. The relationship of the variables taken
into account in the model will be presented, classifying them according to whether they are
of a social or academic nature.
4.2. Social Variables and the Dropout Intention
The observed results suggest that the perceived social integration, given by the per-
ception of support and lack of isolation, affects the sense of belonging they perceive to
the human group that makes up their career. The sense of belonging, in turn, affects the
engagement experienced by students, mobilizing specific motivational components such
as interest, participation and effort linked to studies. Experienced engagement is strongly
linked to early dropout intention. This chain of relationships shows the relevance of social
variables on the motivation of students and, through it, on their decisions associated with
the continuity of their studies, especially if the emotional dimension is considered, as
previously stated.
It is important to indicate that the measures carried out contemplate perceptions about
social integration, which highlight the importance of its evaluation in the measure of indi-
vidual needs, according to the approaches of the theory of attributional discrepancy [34].
It is relevant to remember that, in this study, social variables have been measured
considering focus on relationships with peers and teachers, showing the relationship
between these and dropout intention, according to previous research with Chilean stu-
dents [
13
,
19
,
29
]. The results suggest the importance of these relationships within the study
program community, highlighting their important influence on dropout intention. This
could help clarify the types of support and isolation relevant to dropout intention.
Social support did not show to be a predictor of engagement, in the final model, as
suggested in the initial model. As mentioned, the results show that the influence of social
variables is explained by the presence of a sense of belonging. In this way, it is possible to
observe that the social support of peers and teachers can affect the engagement of students
by affecting how much they feel they belong to their career. Although mediation analysis
showed a direct influence of perceived social support on study engagement, this influence
is explained for the mediator role of sense of belonging. This may be indicating that
strengthening sense of belonging is key to improve study engagement. At the same time,
it is important to highlight that the sense of belonging has a negative relationship with
dropout intention, explained by study engagement. Thus, it is important to work with
students’ social support and relationships in order to improve sense of belonging and study
engagement. This can be a way to reduce university dropouts.
However, it seems important to understand that engagement is understood as the
set of manifestations of motivation by studies [
90
] that include behavioral, cognitive and
emotional dimensions [
91
]. This means that taking these dimensions into account is
essential to understand the correlation between academic variables and the intention to
remain in higher education.
At this point the theory of attributional discrepancy becomes relevant again, as how
much support and how much belonging the students perceive and need is an idiosyn-
cratic aspect of their experience. This finding is an important contribution given that
most of the previous research establishes direct relationships between support and engage-
ment [74,108,109].
Social support was also not shown to be a direct predictor of dropout intention. As in
the previous case, the observed mediations show that social variables influence belonging
and, through this, engagement. This last variable once again plays a key role as the set of
social variables only affects dropout intention by affecting the motivation of students. This
finding also contributes to a deeper understanding considering that preliminary research
focused on the direct relationship of social support and the dropout intention.

Sustainability 2022,14, 831 13 of 18
In the same way, the perceived social integration could have been modified taking
into account the COVID-19 pandemic. This perceived social integration, as well as the
sense of belonging to the institution, may have been diminished to the detriment of face-
to-face classes, a fact that will need to be taken into consideration for future research. In
addition, social isolation and the sense of loneliness have also been variables that have
suffered for variations due to this situation, as has been observed in studies such as that of
Zurlo et al. [110].
4.3. Academic Variables and Dropout Intention
The results reaffirm what has already been observed in previous research. On the one
hand, previous academic performance is a predictor of early academic performance [
111
].
However, the form of influence of previous academic performance on early one is something
that should be deepened in later research, as it is possible that it is indicative of the influence
of previous learning and/or the previously developed sense of self-efficacy on current
learning.
Early academic performance is a predictor of engagement, as observed in previous
research [
112
,
113
]. At this point, it is possible that early academic performance acts as an
informative factor [86] that fuels student motivation for studies.
Neither of the two variables was shown to be a direct predictor of the dropout intention,
according to the original approach, with engagement being an important mediator of its
influence on the dropout intention. Thus, both types of performance only affect the dropout
intention by affecting this cognitive-motivational variable.
It is also important to note that academic performance may not have shown to be a
predictor of dropout intention due to the time the data was collected, as student grades
tend to change as they adapt to the new educational context, not ruling out that this may
influence later.
However, it is also important to understand that the current contingency due to the
COVID-19 pandemic has been able to influence the results of the research, considering that
early academic performance of students may have been modified considering the online
modality. In addition, this may have influenced the engagement of students to a degree.
Therefore, the interpretation of the results obtained must take into account the current
contingency in order to be able to replicate the data in detail in the future and in different
contexts.
4.4. Applications of the Results
On the one hand, the results contribute, in a certain way, to a better understanding
of the relationships between the variables that have been analyzed throughout the in-
vestigation, deepening and distinguishing the relative influence of the variables. In this
way, as has been discussed, new lines of research emerge and contribute to furthering the
understanding of the phenomenon.
On the other hand, they contribute to the identification of relevant variables for
the dropout intention and their relationships. As indicated, the variables included are
susceptible to early detection (except for previous performance). This knowledge can
contribute to the development of preventive actions that contribute to the social and
academic integration of the student body, to maintain and increase their engagement and
to reduce university dropout intention and therefore the consummate abandonment.
In order to prevent or alleviate the phenomenon of university dropout, some recom-
mendations can be outlined, such as the implementation of actions that promote adaptation
in the university environment with programs such as reception days [
114
] or programs to
help the retention through the implementation of tutoring programs, first-year seminars, or
the improvement of the use of technology to make teaching more flexible and motivating
for students, among others [
115
]. These and other measures could improve social and
academic adaptation of the student, which in turn will lead to greater support mechanisms
for not dropping out during the first year (one of the academic years in which the risk

Sustainability 2022,14, 831 14 of 18
of dropping out increases). In addition, the improvement of the use of new technologies
since the beginning of higher education will allow accessibility and better understanding
of the use of Information and Communication Technologies to all those who are studying
in online or hybrid mode as a consequence of the COVID-19 pandemic.
4.5. Limitations
This research has some limitations. On the one hand, this sample, although it repre-
sents a significant amount of the population, is limited to a single educational institution,
which limits the possibilities of extrapolating the results to different contexts. For this
reason, the results contribute to suggest the indicated relationships and the proposed ex-
planations so that they are deepened in later research. However, in future research, we will
consider deepening the analysis, incorporating a complete mediation model to analyze the
mediations produced between the academic and social variables of the model, engagement,
and the intention to drop out.
On the other hand, this model does not consider other variables that could be impor-
tant, such as self-efficacy perceived by the students. This variable could properly explain
the relationship between performance and engagement. According to De Besa et al. [
116
],
the more perceived self-efficacy increases, that is, the more aware the individual is that
they have their own abilities to carry out any action, the more their expectations of results
increase. Therefore, future research should take these limitations into account to be able to
propose a more adjusted model according to the results obtained in the present research.
We also consider it relevant to retest the model in normal contexts, without COVID-19.
Considering that the instruments used are self-report, this can generate simulation
biases such as social desirability in the responses or scalar errors. In addition, there are
limitations inherent to the research design as, as it is transversal, a sample is taken from a
specific moment, not allowing causal relationships to be established.
Author Contributions:
Conceptualization, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; methodology,
J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; software, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.;
validation, J.M.-A.; formal analysis, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; investigation, J.M.-A.,
V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; resources, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; data curation,
J.M.-A.; writing—original draft preparation, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; writing—
review and editing, J.M.-A., V.I.-V., C.G.-G., G.F.-O. and J.B.-R.; visualization, J.M.-A., V.I.-V., C.G.-G.,
G.F.-O. and J.B.-R.; supervision, J.M.-A.; project administration, J.M.-A.; and funding acquisition,
J.M.-A. All authors have read and agreed to the published version of the manuscript.
Funding: This research was funded by the Agencia Nacional de Investigación y Desarrollo (ANID),
Chile; through the scholarship for doctoral studies, grant number 21180225.
Institutional Review Board Statement:
The study was conducted in accordance with the Declaration
of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Universidad de
Concepción, Chile (protocol code CEBB 645-2020 approved in April 2020). for studies involving humans.
Informed Consent Statement:
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data base is available in: https://bit.ly/3qILkrw.
Conflicts of Interest: The authors declare no conflict of interest.
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