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International Educational Research; Vol. 8, No. 2; 2025
ISSN 2576-3059 E-ISSN 2576-3067
https://doi.org/10.30560/ier.v8n2p67
67 Published by IDEAS SPREAD
Validation Syndrome: The Root of Deception and Developmental
Predictors of Dark Triad Traits in Adolescents for Forensic and
Developmental Psychology
Francis C. Ohu.1 & Laura A. Jones1
1 Department of Forensic Cyberpsychology, Capitol Technology University, United States
Correspondence: Francis C. Ohu., Department of Forensic Cyberpsychology, Capitol Technology University,
Laurel, MD, United States. E-mail: fohu captechu.edu
Received: March 8, 2025; Accepted: March 18, 2025; Published: March 20, 2025
Abstract
This study examines the early developmental predictors of Dark Triad traits, narcissism, machiavellianism, and
psychopathy in adolescents using a mixed-methods approach grounded in the Validation Syndrome Diagnostic
Triangle (VSDT) framework. The VSDT posits that self-doubt, desire, and self-gratification interact with
environmental and familial influences to shape personality traits. Data from the Add Health Longitudinal Study
(N = 15,000 adolescents, aged 12–18) were analyzed using Pearson correlations, multiple regression, and thematic
analysis. Findings indicate that familial conflict and socioeconomic stress strongly predict Dark Triad tendencies,
particularly self-doubt (r = .953, p < .05), self-gratification (r = .898, p < .05), and desire (r = .812, p < .05).
Conversely, parental monitoring demonstrated a protective effect, negatively correlating with self-doubt (β = -
0.008, p < .05) and self-gratification (β = 0.269, p < .05). Regression analysis identified familial conflict as the
strongest predictor of maladaptive traits (β = 0.158, p < .001), accounting for 92.68% of the variance in self-doubt
(R² = .927). Thematic analysis corroborated these findings, linking Dark Triad traits to validation-seeking
behaviors in adverse familial environments. Adolescents with high Dark Triad tendencies engaged in
cyberbullying and manipulative online behaviors, while supportive environments and parental monitoring fostered
resilience. These findings validate the VSDT framework, emphasizing the role of familial and environmental
factors in adolescent personality development. The findings have implications for forensic cyberpsychology,
examining how online interactions shape developmental patterns and influence digital deception. The study
provides actionable insights for early interventions to mitigate antisocial behavior. Future research should explore
cross-cultural interventions to support healthier adolescent development.
Keywords: Antisocial Personality Behavior, Validation Syndrome, Forensic Cyberpsychology, Dark Triad,
Socioeconomic Stress, Parenting, Familial factors, Light Triad
1. Introduction
1.1 Background and Context
Adolescence is a pivotal stage of personality development, where environmental, familial, and psychological
factors converge to shape enduring behavioral patterns [1]-[3]. Among these patterns, the Dark Triad
traits,narcissism, machiavellianism, and psychopathy, have garnered significant attention due to their association
with manipulative behaviors, lack of empathy, and antisocial tendencies. These traits, while potentially adaptive
in resource-scarce or high-stress environments, often lead to detrimental outcomes such as deception, criminality,
and social deviance when left unchecked [4],[5]. Research highlights that adolescents exposed to familial conflict,
socioeconomic pressures, and inadequate parental involvement are particularly vulnerable to developing
maladaptive traits [6]. These individuals often adopt deceitful behaviors as coping mechanisms, seeking validation
through manipulation and external approval [7]. Understanding the origins and developmental predictors of the
Dark Triad is crucial to informing early interventions that mitigate these tendencies, promoting prosocial outcomes
and reducing societal instability.
2. Problem Statement
Antisocial personality development among adolescents has emerged as a significant societal concern, with
measurable increases in maladaptive behaviors. Recent statistics reveal that 20-30% of adolescents worldwide
exhibit antisocial tendencies, including manipulative and delinquent behaviors, contributing to rising rates of youth
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violence and criminal activity [8],[9]. In the United States, juvenile crime accounts for nearly 15% of all arrests,
with a notable rise in cyberbullying and peer exploitation behaviors over the past five years [10],[11].
The general problem is that antisocial personality development during adolescence exacerbates societal instability
through escalating delinquency, violence, and mental health challenges [12]. The specific problem is the lack of
comprehensive early detection tools and intervention strategies that address the interplay between psychological
and environmental factors influencing antisocial personality traits [13]. Building on forensic cyberpsychology, this
research addresses the gap in understanding how dark personality traits manifest in both physical and virtual
environments. Forensic cyberpsychology provides a theoretical basis for identifying traits that increase the risk of
cybercrime among adolescents, particularly those predisposed to antisocial behaviors [14]. This gap leaves
educators, clinicians, and policymakers under-equipped to mitigate these behaviors effectively [15],[9].
3. Purpose of the Study
The purpose of this mixed-methods study is to investigate the early developmental predictors of Dark Triad traits
among adolescents. Specifically, it examines the interplay between psychological drivers (self-doubt, desire, and
self-gratification) and environmental factors (familial conflict, socioeconomic stress, and parental monitoring). By
identifying both risk and protective factors, this research aims to provide actionable insights for professionals,
including educators, clinicians, and policymakers. These insights will inform evidence-based prevention strategies
designed to reduce risk factors, foster prosocial behaviors, and promote healthier developmental trajectories in
adolescents.
4. Originality, Rationale and Significance
Forensic cyberpsychology, an emerging interdisciplinary field, integrates principles of psychology and digital
forensics to understand and mitigate cyber-related behaviors [16]. This study builds on forensic cyberpsychology
by exploring how dark personality traits in adolescents are influenced by familial and environmental factors. This
approach aligns with the Validation Syndrome Diagnostic Triangle (VSDT) framework, offering a psychological
lens to understand how these traits translate to both offline and digital contexts. Reference [17] emphasize that
forensic cyberpsychology can enhance the understanding of behavioral patterns that lead to cybercrimes, providing
insights into how adolescents with Dark Triad traits may develop manipulative behaviors in online environments.
The originality of this study lies in its integration of psychological constructs with environmental stressors through
the Validation Syndrome Diagnostic Triangle (VSDT) model. This novel framework highlights how psychological
drivers, self-doubt, craving for validation, and self-gratification interact with adverse familial and socioeconomic
conditions to amplify maladaptive behaviors [18]. The rationale for this study is grounded in the increasing
prevalence of antisocial behaviors among adolescents and the societal burden of juvenile delinquency. Without
effective interventions, 60% of adolescents with early antisocial tendencies persist into adulthood, leading to
chronic criminality, emotional detachment, and reduced community cohesion [10],[9]. Existing tools such as the
Early Assessment Risk List Version 3 (EARL-V3) have limited accessibility and fail to capture the complex
interplay of risk and protective factors within broader developmental contexts [19]. The significance of this study
transcends academic inquiry by contributing to theoretical frameworks that elucidate the complex interplay
between psychological and environmental factors in shaping adolescent personality development. The findings
have practical implications, offering educators, clinicians, and policymakers’ evidence-based tools and strategies
for early detection and intervention. By addressing the roots of maladaptive traits, this research seeks to reduce the
societal burden of antisocial behaviors and promote the development of prosocial, resilient adolescents.
This study aims to elucidate the psychological and environmental factors that contribute to the development of
Dark Triad traits in adolescents. Specifically, it seeks to identify the psychological drivers, including self-doubt,
desire, and self-gratification, as well as environmental factors, such as familial conflict, socioeconomic stress, and
parental monitoring, that shape the emergence of these maladaptive traits. Furthermore, the study aims to validate
the utility of the Validation Syndrome Diagnostic Triangle (VSDT) framework in understanding the development
of Dark Triad traits. By doing so, it will provide a comprehensive framework for identifying and addressing the
underlying factors that contribute to the emergence of these traits. In addition, the study will explore the protective
role of Light Triad traits, including self-confidence, self-contentment, and selflessness, in promoting prosocial
behaviors. This will provide valuable insights into the mechanisms by which these traits can mitigate the negative
effects of Dark Triad traits. Ultimately, the study aims to provide actionable recommendations for early
intervention strategies targeting at-risk adolescents. By adopting a structured approach, this research aims to
advance theoretical understanding and practical applications, ultimately contributing to societal stability and
individual well-being.
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5. Literature Review
This literature review adopts a systematic approach to explore the primary drivers of antisocial personality
development in adolescents and the influence of familial and environmental factors on this development. The
overarching research question guiding this review is: What are the primary drivers of antisocial personality
development in adolescents, and how do familial and environmental factors influence this development? The
review focuses on peer-reviewed articles published within the last 2-3 years, prioritizing recent 2024 references to
ensure relevance and timeliness. Articles not in English or lacking peer-review credentials were excluded. Over
one hundred and fifty peer-reviewed papers published between 2022 and 2024 were screened, and only the most
relevant studies were included in this paper. Only one non-peer reviewed article and a government sponsored
research report was cited. The search strategy included specific terms such as "adolescent personality
development," "Dark Triad traits," "environmental influences on antisocial behaviors," and "parenting styles and
personality traits." Databases such as PsycINFO, MDPI, PubMed, and Google Scholar were utilized to ensure a
comprehensive collection of studies that meet the inclusion criteria. This method ensures the integration of current,
high-quality evidence into the analysis, providing a robust foundation for understanding the interplay between
psychological drivers and environmental stressors in shaping adolescent personality traits.
A. Key Drivers of Dark Triad Traits
The development of personality traits in adolescence is significantly shaped by environmental and familial contexts
[1]. Research has consistently shown that high-conflict family settings, socio-economic challenges, and inadequate
parental supervision can influence the emergence of maladaptive traits [20],[21],[6]. Adolescents in such contexts
often experience self-doubt and a heightened desire for validation, leading to a craving for social recognition and
self-gratification [22]. Studies have also shown that individuals raised in high-stress environments are more likely
to internalize feelings of self-doubt and frustration, which, when coupled with unmet desires and a need for self-
gratification, foster a dependency on external validation [22],[23]. This interdependence encapsulates how self-
doubt, desire, and self-gratification intertwine to fuel Dark Triad traits and behaviors.
B. Development of Dark Triad Traits from Familial Environmental Factors
The development of Dark Triad traits is often a response to early familial dynamics and environmental pressures,
for instance, adolescents experiencing neglect or overly permissive parenting may exhibit heightened self-doubt
and insecurity, leading to a craving for social validation and the use of manipulative strategies to fulfill self-
gratifying needs [24]. In the absence of supportive relationships, these adolescents may resort to antisocial
behaviors to assert themselves, especially if self-doubt, desire, and self-gratification remain reinforced by
continuous exposure to negative familial or environmental influences [25]. This persistence of maladaptive traits
highlights the resilience of these drivers, often outweighing positive influences and creating a reinforced loop of
Dark Triad characteristics that persist into adulthood [23].
C. Commonalities in Dark Triad Traits
Research by [18] stated that the Dark Triad traits are anchored by common psychological drivers: self-doubt, desire,
and self-gratification; and suggests that these elements not only initiate but also sustain the development of Dark
Triad traits from adolescence into adulthood [26]. Self-doubt, when combined with unmet desire and a need for
self-gratification, encourages behaviors focused on control, manipulation, and validation [23]. Adolescents
exhibiting these traits often prioritize self-interested behaviors that override pro-social impulses, as the need for
validation and self-affirmation eclipses alternative positive cues from their environment, highlighting the
entrenched nature of these core drivers and their role in shaping long-term personality outcomes [27],[28].
D. Interplay of Protective and Risk Factors
In contrast, adolescents who cultivate traits like selflessness, self-confidence, and self-contentment, often due to
positive familial and environmental reinforcement, tend to rely less on external validation and are more resilient
against social pressures to engage in manipulative or antisocial behaviors [29]. Supportive relationships and stable
environments provide a buffer, helping mitigate the allure of Dark Triad traits even in the face of adversity, while
adolescents who lack such environments may increasingly turn to maladaptive behaviors as coping mechanisms
[23].
E. Impact of Socioeconomic Stressors and Parental Influence
Socioeconomic challenges add another layer of complexity to the development of Dark Triad traits, as adolescents
in economically disadvantaged settings often experience heightened levels of stress and instability, which can
exacerbate self-doubt and foster desires that may be unmet in typical social structures [30]. Parental monitoring,
or lack thereof, also plays a crucial role in shaping adolescent personality development [24]. For example,
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permissive parenting, characterized by a lack of boundaries, allows for the unchecked development of self-doubt
and a heightened need for validation, leading adolescents to adopt narcissistic traits as a means of compensating
for their insecurities [31]. In contrast, authoritative parenting, characterized by consistent boundaries and warmth,
has been shown to reduce the likelihood of Dark Triad trait development by reinforcing positive behaviors,
emotional regulation, and empathy [32]. Adolescents raised in such supportive environments are more likely to
develop self-contentment, self-confidence and selflessness, which counteract the core drivers of the Dark Triad
[23]. Therefore, socioeconomic stressors and parenting style are integral to understanding both the risks of
developing maladaptive traits and the potential for cultivating resilience and prosocial behaviors in adolescents
[6].
F. Forensic Cyberpsychology Context and Implications
Forensic cyberpsychology bridges the gap between psychological analysis and digital behavioral profiling.
Reference [17] highlights that integrating psychological frameworks with digital forensics can reveal how
personality traits like narcissism and machiavellianism predispose individuals to cyber-related offenses. This study
complements findings from [14], which outline a comprehensive framework for cyber behavioral analysis, by
focusing on how familial dynamics influence these traits. For example, adolescents in high-conflict families are
more likely to develop validation-seeking behaviors that translate into digital manipulations, such as cyberbullying
or hacking. As noted by [17], forensic cyberpsychology bridges the gap between behavioral psychology and digital
forensics, enhancing predictive capabilities for addressing cybercrime driven by Dark Triad traits.
G. Broader Environmental Influences on Dark Triad Traits in Adolescents
Cultural norms and societal expectations significantly shape adolescent behavior, including the development of
Dark Triad traits [33]. In cultures that prioritize individualism, adolescents often learn to value self-promotion and
competition, which can cultivate narcissistic and machiavellian traits as they seek to establish their social standing
[34]. In contrast, collectivist cultures, though emphasizing social cohesion, may still foster machiavellian traits in
adolescents who learn to navigate complex social hierarchies to secure social acceptance, for example, a study
comparing Western and East Asian adolescents found that Western participants displayed higher levels of
narcissism, while East Asian participants exhibited covert manipulative behaviors to navigate group dynamics [35].
Environmental stressors such as familial conflict have also been shown to foster manipulative tendencies
associated with the Dark Triad traits [36].
H. The role of Parenting Styles: Authoritative, Permissive and Neglectful Approaches
Parenting style is a central determinant in adolescent personality development, and extensive research shows that
each style, authoritative, permissive, neglectful, and authoritarian has distinct impacts on Dark Triad traits [37].
Authoritative parenting, which combines warmth and structure, promotes emotional stability and self-confidence
in adolescents, countering the development of traits such as narcissism and machiavellianism, for example,
adolescents raised in authoritative households often display high levels of self-regulation and empathy, as they are
consistently guided by supportive boundaries [32]. In contrast, permissive parenting, characterized by a lack of
boundaries, allows for the unchecked development of self-doubt and a heightened need for validation; and
adolescents in these environments may adopt narcissistic traits as a means of compensating for their insecurities
[31]. Neglectful parenting, however, has been linked with more severe outcomes, such as psychopathy and a
tendency toward emotional detachment [38]. A study by [39] on familial impact on psychopathy found that
adolescents with neglectful parents displayed high levels of self-gratification and low empathy, which are
foundational to psychopathic tendencies. These adolescents, lacking emotional connection and supervision, often
develop manipulative behaviors to satisfy their own needs without regard for others [24]. Authoritarian parenting,
though often associated with discipline, may also contribute to the development of Dark Triad traits by instilling
resentment and a need for control, especially in environments with high levels of conflict [40].
I. The influence of Cultural Norms, Social Media and Societal Expectations
Societal expectations, particularly around success, appearance, and social media presence, exacerbate these
tendencies. In many cultures, adolescents are under constant pressure to project an idealized self-image, often
leading them to adopt deceptive behaviors to maintain a façade [41]. This pressure is amplified by social media,
where instant feedback mechanisms encourage validation-seeking and self-gratification [42]. Such platforms
provide immediate reinforcement for narcissistic behaviors, further embedding Dark Triad traits as adolescents
prioritize online status over genuine connections [43]. Forensic cyberpsychology highlights the role of cultural
norms in shaping the expression of Dark and Light Triad traits, particularly in digital contexts [33]. As [36]
highlights, human psychological factors play a critical role in risk behaviors, which align with the manipulative
tendencies observed in individuals with Dark Triad traits, particularly in digital environments.
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J. Peer Influence and Social Validation in the Development of Dark Triad Traits
Peer influence is a critical factor in the development of Dark Triad traits, as adolescents often prioritize social
acceptance over ethical behavior [34]. Research indicates that adolescents whose peer groups value status or
control are more likely to engage in narcissistic and machiavellian behaviors [34]. For instance, adolescents who
seek popularity may adopt narcissistic traits, projecting confidence and charisma to dominate social interactions
[44]. Moreover, social media adds a layer of complexity, offering adolescents a platform to curate their image and
receive immediate validation, reinforcing these tendencies [41]. Peers can also influence psychopathic traits,
particularly in high-risk settings, as adolescents in peer groups that endorse risk-taking or disregard for social
norms often adopt psychopathic tendencies to fit in, demonstrating low empathy and high impulsivity [45]. This
is particularly pronounced in online spaces, where anonymity enables aggressive behaviors with minimal
consequences, reinforcing deviant traits [46].
K. Biological and Genetic Factors: The Heritability of Dark Triad Traits
Genetic factors also contribute to Dark Triad traits [47], with studies indicating that narcissism, psychopathy, and
machiavellianism have moderate to high heritability; studies reveal that psychopathic traits, in particular, are
significantly influenced by genetic predispositions, suggesting that some individuals may be biologically inclined
toward emotional detachment and impulsivity [48], [47]. Similarly, narcissism appears to have a genetic
component, with research indicating that traits such as grandiosity and entitlement are heritable [49]. However,
genetic predispositions interact with environmental factors, meaning that a supportive or structured environment
can mitigate the expression of Dark Triad traits even in genetically predisposed individuals [37]. For example,
adolescents with a genetic tendency toward narcissism may develop self-confidence rather than arrogance if raised
in an authoritative, nurturing environment. Thus, while genetic factors play a role in personality development,
environmental influences remain a crucial factor, for understanding the complex interplay between biology and
external influences [47].
6. Research Methods
A. Participants
The study utilized data from the Add Health Longitudinal Study, which surveyed 15,000 adolescents aged 12–18
years from diverse socioeconomic backgrounds, family structures, and environmental settings. Participants
completed questionnaires over five waves of data collection (1995–2018), ranging from adolescence in Wave I:
12–18 years, to adulthood in Wave V: 32–42 years [50], [51]. Responses were scored using a Likert scale (1–5),
with weighted scores calculated to represent population distributions accurately. No additional participants were
recruited or excluded during the analysis, as raw data were preserved
B. Materials
The data were drawn from the Add Health dataset, a comprehensive resource that captures variables relevant to
family conflict, socioeconomic status, parental monitoring, and personality traits. Variables were thematically
coded to align with constructs central to the research, including self-doubt ("I often question my abilities," H1FS9)
and family conflict ("My family argues almost daily," PB20). Other key variables analyzed were associated with
themes such as desire (H3SP27), self-gratification (H3TO102), selflessness (H3CC1), and parental monitoring
(H2PF11). The thematic codes were refined to match phrases directly from adolescent responses, enabling a more
nuanced thematic analysis. The refined codes are presented in Tables 1,5,6,7,8 and 9; and fig. 6.
Table 1. Mapping of Addhealth Survey Data Variables in Thematic Codes
Theme:
Self-Doubt (SD)
Thematic code
(Phrase):
"I often question my
abilities.
AddHealth Data
Variable: H1FS9
Theme:
Desire or Craving
(DC)
Thematic code
(Phrase):
"I need constant
validation and
reassurance."
AddHealth Data
Theme:
Self-Gratification (SG)
Thematic code (Phrase):
"I see no harm in taking
advantage of others to
benefit myself”
AddHealth Data
Variable: H3TO102
Theme:
Self-Confidence (SC)
Thematic code (Phrase):
"I don’t compare myself
to others because I value
and trust my uniqueness"
AddHealth Data
Variable: H3TO97
Theme:
Self-Contentment (SCT)
Thematic code (Phrase):
"I am grateful for what I have
and at peace with my
circumstances"
AddHealth Data Variable:
H3SP3
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Variable: H3SP27
Theme:
Self-Lessness (SL)
Thematic code
(Phrase):
"I am most fulfilled
when I can help
someone in need."
AddHealth Data
Variable: H3CC1
Theme:
Family Conflict:
(FC)
Thematic code
(Phrase):
"My family argues
almost daily, and it
affects me a lot."
AddHealth Data
Variable: PB20
Theme:
Socio-economic Status
(SES)
Thematic code (Phrase):
"Sometimes we don’t
have enough food or the
things we need at home"
AddHealth Data
Variable: PA56
Theme:
Parental Monitoring
(PM)
Thematic code (Phrase):
"My Parents know who
my friends are and what
we do together."
AddHealth Data
Variable: H2PF11
Theme:
Lack of Parental Monitoring
(LPM)
Thematic code (Phrase):
"I feel like I have made mistakes
that could have been avoided if
my parents paid more attention"
AddHealth Data Variable:
H1PR3
C. Procedure
Data were extracted from publicly available adolescent and parent questionnaire responses following Add Health
guidelines [52]. Variables were mapped to thematic codes for subsequent analysis. Quantitative data were analyzed
for correlations and regression, while qualitative data underwent thematic analysis based on [53],[54] six-phase
framework [55].
D. Analysis
A mixed-methods approach was adopted, integrating quantitative and qualitative methodologies:
Quantitative Analysis: Statistical analysis was conducted using Python libraries, and a range of statistical
techniques were employed to examine the relationships between variables. Pearson correlation was used to assess
the relationships between constructs, including self-doubt, desire, and self-gratification, and familial factors such
as parental monitoring and family conflict. Correlation coefficients and p-values were calculated to determine the
strength and significance of these relationships. Additionally, multiple regression analysis was used to evaluate
the predictors of personality traits, with familial and environmental factors serving as independent variables. The
variance explained by these factors was tested using regression models, providing insight into the relative
importance of each factor in predicting personality traits. To verify the accuracy of the results, manual correlation
and regression calculations were conducted.
Qualitative Analysis: A six-phase thematic analysis, as outlined by [53], was employed to extract adolescent
narratives related to personality traits. Open coding revealed recurring themes linked to familial and environmental
influences, which are presented in Tables 5, 6, 7, 8 and 9; and fig. 6. Thematic heat maps were used to visualize
the interconnections between these themes, facilitating a deeper understanding of validation-seeking and self-
acceptance behaviors, as depicted in Fig. 1, 3 and 5.
Data was visualized using tables, heatmaps and line graphs to triangulate findings.
7. Results
As we examine the results, we can see that the coefficient values reveal the magnitude of the relationship between
the variables, the p-values indicate the likelihood of the relationship occurring by chance, and the regression values
show the direction and strength of the relationship, providing valuable insights into the significance and
implications of our findings.
This section presents the findings from both quantitative and qualitative analyses, focusing on the relationships
between familial factors, personality traits, and adolescent behaviors. Tables and figures are included to visually
enhance understanding of the data.
The statistical analysis revealed significant correlations between familial factors and personality traits, as depicted
in Tables 2, 3, and 4, as well as Fig. 1, 2, 3, 4 and 5
A. Example Manual Correlation Calculations: Risk Predictors
To validate the results derived from statistical software, manual Pearson correlation and regression calculations
were performed. The following examples illustrate the manual calculations.
Example 1: Pearson Correlation Coefficient
The correlation between self-doubt and lack of parental monitoring was calculated using raw values:
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Σ (xi − x) (yi − ȳ)
(∑ (xi − x) ²⋅∑ (yi − ȳ) ²) (1)
The Pearson correlation coefficient formula is widely used to measure the strength and direction of relationships
between variables [56].
Using the formula, a correlation coefficient of r = 0.95279 was obtained, indicating a very strong positive
correlation between self-doubt and lack of parental monitoring.
Example 2: Regression Calculations
The linear regression equation for self-doubt was calculated as:
y = β0 + β1x1 + β2x2 + … + βkxk + ε (2)
The regression methodology used in this analysis aligns with the guidelines provided by [56] emphasizing its
suitability for multivariate relationships. The formula was applied to manually calculate the coefficient for parental
monitoring. The calculated coefficient, β = 0.61126, indicates that parental monitoring has a significant impact on
self-doubt. Specifically, for every unit increase in parental monitoring, self-doubt increases by an average of 0.611
units.
The findings suggest that excessive parental monitoring may inadvertently foster higher levels of self-doubt in
adolescents, potentially exacerbating the development of dark triad traits. However, the correlation between self-
contentment and parental monitoring was strong and positive (r = 0.86696), suggesting that parental monitoring
may have a protective effect on self-contentment in adolescents. The manual Pearson correlation and regression
calculations support these findings.
B. Quantitative Results: Risk Behavior Predictors
Self-Doubt: Family conflict (r = 0.786) and socioeconomic stress (r = 0.850) demonstrated strong positive
correlations, while lack of parental monitoring exhibited the strongest correlation (r = 0.953).
Desire (Craving): Parental monitoring showed a strong negative correlation (r = -0.689), while family conflict (r
= 0.812) and socioeconomic stress (r = 0.860) were positively correlated.
Self-Gratification: The strongest predictor was family conflict (r = 0.898), followed by socioeconomic stress (r =
0.792) while Parental monitoring correlated negatively.
Figure 1. Heatmap of Correlations for Risk Predictors
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Figure 2. Line graph of correlations for risk factors
Table 2. Pearson Correlation Coefficient between Familial Factors and Risk Predictors
Dependent
Independent
Correlation
P-Value
Desire (Craving)
Parental Monitoring
0.6891427395919163
0.0
Desire (Craving)
Family Conflict
0.8121846132306475
0.0
Desire (Craving)
Socio-Economic Stress
0.8600062266498096
0.0
Desire (Craving)
Lack or Parental Monitoring
0.8483231860361031
0.0
Self-Gratification
Parental Monitoring
0.7316128635360266
0.0
Self-Gratification
Family Conflict
0.898030274286622
0.0
Self-Gratification
Socio-Economic Stress
0.7917912244627876
0.0
Self-Gratification
Lack of Parental Monitoring
0.75717996331397
0.0
Table 2 summarizes the Pearson correlation coefficients between familial factors and various risk behavior
predictors, illustrating the strength and direction of these associations. This provides a quantitative foundation for
understanding how familial dynamics contribute to self-doubt, desire, and self-gratification.
C. Quantitative Results: Protective Behavior Predictors
Self-Contentment: Strongly associated with parental monitoring (r = 0.867) and moderately linked to
socioeconomic stress (r = 0.659), while family conflict demonstrated resilience-building potential (r = 0.743).
Self-Confidence: Strong positive correlations were found with parental monitoring (r = .848) and family conflict
(r = 0.675), suggesting resilience-building aspects.
Selflessness: Correlations with parental monitoring (r = 0.703) and socioeconomic stress (r = 0.419) suggested
that adversity could foster prosocial behaviors.
Figure 3. Heatmap of Correlations for Protective Predictors
Note: Parental monitoring is strongly associated with self-confidence and self-contentment.
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Figure 4. Line graph of Protective Traits and Familial Factors
Note: Highlights how constructive conflict resolution in family settings fosters selflessness.
Table 3. Pearson Correlation Coefficients between the Protective Behavior Predictors (SC, SCT, SL) and Familial
Factors (PM, FC, SES, LPM)
Predictor Variable
Familial and Environmental
Variable
Correlation Value
P-Value
Self-Content
Parental Monitoring
0.8669643584082596
0.0
Self-Content
Family Conflict
0.7429940482450558
0.0
Self-Content
Socio-Economic Stress
0.6593420630436255
0.0
Self-Content
Lack of Parental Monitoring
0.5556258908665815
0.0
Selflessness
Parental Monitoring
0.7028444145153122
0.0
Selflessness
Family Conflict
0.6402497870780437
0.0
Selflessness
Socio-Economic Stress
0.4186546621447843
0.0
Selflessness
Lack of Parental Monitoring
0.35279922616472414
0.0
Self-Confidence
Parental Monitoring
0.8480352411073511
0.0
Self-Confidence
Family Conflict
0.6750147638373033
0.0
Multiple regression models explained 92.68% of the variance in self-doubt (R² = .9268). Family conflict and
socioeconomic stress were significant predictors of maladaptive traits, while active parental monitoring played a
protective role, lack of parental monitoring had limited direct significance.
Table 4. Multiple Linear Regression Analysis Results for the Risk Predictors (SD, DC, SG)
Dependent
Variable
R-Squared
Coefficients
P-Value
Self-Doubt
0.9268420380265109
{'const': -0.34872721498436476,
'Parental Monitoring': -
0.008453382245699581, 'Family
Conflict': 0.15796239380726296,
'Socio-Economic Stress':
0.1261070505389621, 'L
{'const': 1.826233102302997e-
157, 'Parental Monitoring':
0.039165688117789706, 'Family
Conflict': 1.9457404966527473e-
294, 'Socio-Economic Stress':
1.756736559819308e-64, 'Lack
of Parental Monitoring': 0.0}
Desire
(Craving)
0.8551686222661512
{'const': 0.0, 'Parental
Monitoring': 0.0, 'Family
Conflict': 4.8581678707330875e-
86, 'Socio-Economic Stress': 0.0,
'Lack of Parental Monitoring':
0.0}
{'const': 0.0, 'Parental
Monitoring': 0.0, 'Family
Conflict': 4.8581678707330875e-
86, 'Socio-Economic Stress': 0.0,
'Lack of Parental Monitoring':
0.0}
Self-
Gratification
0.8516636548324787
{'const': -1.2575213725400496,
'Parental Monitoring':
{'const': 0.0, 'Parental
Monitoring':
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76 Published by IDEAS SPREAD
0.26878265147198244, 'Family
Conflict': 0.6958260432189234,
'Socio-Economic Stress':
0.36915869051531747, 'Lack of
Parental Monitoring':
0.1678513817761756}
2.1899981396055704e-229,
'Family Conflict': 0.0, 'Socio-
Economic Stress':
5.5079334334529444e-136,
'Lack of Parental Monitoring':
1.238752443619641e-79}
Figure 5. Heatmap of Coefficients for Risk and Protective Predictors
The heatmaps presented in Figures 1, 3, and 5 visually illustrate the strength of correlations between the variables,
revealing family conflict as the most influential predictor across both risk and protective factors. The regression
coefficients in Table 4, illustrating the statistical influence of familial factors, reveal that family conflict (β = 0.158,
p < .001) is the most significant predictor. Table 4 presents the results of multiple linear regression analyses,
showcasing the extent to which familial factors explain variations in adolescent risk behaviors. The coefficients
and p-values highlight the statistical significance and practical implications of these predictors.
D. Qualitative Results
Table 5 presents the Coding Categories and Definitions used in the qualitative analysis, which guided the
systematic coding and analysis of the adolescent narratives to identify themes and patterns related to personality
traits and familial dynamics.
Table 5. Coding Categories and Definitions
Category
Code
Definition
Environmental and
Familial Factors
Family Conflict (FC)
Tensions, disagreements, and disputes within the
family.
Socio-Economic Stress
(SES)
Financial and social pressures impacting the family
environment.
Parental Monitoring
(PM)
Active supervision and involvement in adolescents'
lives by parents.
Lack of Parental
Monitoring (LPM)
Insufficient parental oversight or involvement.
Risky Behavioral Trait
Self-Doubt (SD)
Persistent feelings of inadequacy or questioning
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Predictors
one's abilities.
Self-Gratification (SG)
The tendency to prioritize personal pleasure or gain
over ethical considerations.
Desire or Craving (DC)
The need for constant reassurance or validation
Protective Behavioral Trait
Predictors
Self-confidence (SC)
Belief in one’s own abilities and trust in one’s
uniqueness.
Self-Contentment (STC)
A sense of gratitude and peace with one’s
circumstances.
Selflessness (SL)
Fulfillment derived from helping or supporting
others.
Outcome Traits
Dark Triad Traits (DTT)
Maladaptive traits, including Machiavellianism,
Narcissism, and Psychopathy.
Light Triad Traits (LTT)
Ethical behavior and Positive traits, such as
empathy, altruism, and compassion
To complement the quantitative findings, qualitative thematic analysis was conducted to capture the nuanced
experiences of adolescents. These narratives provide deeper insights into how familial factors influence personality
traits and behaviors
Thematic analysis revealed two dominant behavioral patterns:
Validation-Seeking Behaviors (Dark Triad Traits): Adolescents reported external validation needs (e.g., “I need
constant reassurance”), linking to traits like machiavellianism and narcissism. Narratives linked self-doubt, desire,
and self-gratification to neglectful parenting, family conflict, and economic stress.
Self-Acceptance Behaviors (Light Triad Traits): Traits like self-confidence and selflessness were connected to
supportive parental involvement and constructive conflict resolution. Adolescent narratives reflected traits such as
self-confidence and selflessness (e.g., "I value my uniqueness"), suggesting resilience and prosocial orientation,
Table 6. Thematic Analysis Matrix Table – Dark Triad Traits
Theme
Theme
Descriptio
n
Code(s)
Causal
Familial
Factors
Linked
Personality
Trait
Illustrative
Quotes
Data
Interpretation
Triad
Affiliati
on
Self-doubt
(SD)
Pervasive
feelings of
uncertaint
y and
inadequac
y in
adolescent
s.
"I often
question
my
abilities."
Lack of
Parental
Monitori
ng
(LPM),
Family
Conflict
(FC)
Psychopathy
"I feel
uncertain
about my
decisions."
Ineffective
monitoring and
high family
conflict foster
self-doubt and
disengagement
, linked to
psychopathy.
Dark
Triad
Desire
(Craving)
(DC)
Adolescen
t's intense
longing
for
attention
and
validation
from
others.
"I need
constant
validation
and
reassuranc
e"
Family
Conflict
(FC),
Lack of
Parental
Monitori
ng
(LPM),
Socio-
economi
c Stress
(SES),
Machiavellian
ism
"I crave
social
media
attention
and likes."
High family
conflict and
neglectful
parenting
reinforce
manipulative
tendencies,
linked to
Machiavelliani
sm.
Dark
Triad
Self-
Gratificati
on (SG)
An
overarchi
ng focus
on
“I see no
harm in
taking
advantage
Socio-
economi
c Stress
(SES),
Narcissism
"I think
self-
advancem
ent should
Economic
hardship and
insufficient
guidance foster
Dark
Triad
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personal
entitlemen
t, self-gain
and
immediate
rewards
of others
to benefit
myself."
Lack of
Parental
Monitori
ng
(LPM),
Family
Conflict
(FC),
always
come
first."
selfish and
entitlement-
driven
behavior,
linked to
narcissism
Table 7. Thematic Analysis Matrix Table – Light Triad Traits
Theme
Theme
Description
Code (s)
Causal
Familial
Factors
Linked
Personalit
y Trait
Illustrati
ve
Quotes
Data
Interpretatio
n
Triad
Affiliati
on
Self-
Confidenc
e (SC)
Positive self-
regard and
unwavering
trust in one’s
abilities and
judgement.
“I don’t
compare
myself to
others
because I
value and
trust my
uniqueness."
Parental
Monitori
ng (PM),
Conflict
Resolutio
n Skills
(FC)
Empathy
"I
believe
in myself
and my
potential
."
"Effective
parental
involvement
through open
and honest
communicati
on builds
trust and
empathy in
adolescents".
Light
Triad
Self-
Contentme
nt (SCT)
Feeling
satisfied with
one's life and
accomplishme
nts despite
challenges
"I'm grateful
for what I
have and at
peace with
my
circumstance
s."
Parental
Monitori
ng (PM),
Socio-
economic
Stress
(SES),
Compassi
on
"I feel
content
while
still
working
toward
my
goals."
Resilience
developed
through
hardship and
parental
involvement
fosters a
positive
sense of
identity and
self-
acceptance,
leading to
increased
self-
contentment
Light
Triad
Selflessne
ss (SL)
Prioritizing
others' needs
and well-being
above one's
own desires
and interests.
"I am most
fulfilled
when I can
help
someone in
need."
Parental
Monitori
ng (PM),
Family
Conflict
(FC)
Altruism
"I enjoy
working
with
others to
achieve a
common
goal."
Effective
parental
monitoring
and open
communicati
on fosters
selflessness
and altruism
in
adolescents
Light
Triad
The sampled quotes revealed how adolescents perceived familial dynamics, underscoring the significance of
validation-seeking behaviors in promoting maladaptive traits and self-acceptance behaviors in fostering prosocial
traits. The tables (7 and 8) and thematic process diagram (Fig. 6) provided additional support for these findings,
demonstrating the intricate relationships between familial factors and personality traits.
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Figure 6. illustrates the thematic analysis process, connecting key familial dynamics to adolescent personality traits.
This visual framework aids in understanding the pathways leading to either maladaptive or prosocial behaviors.
Figure 6. Thematic Analysis Process Diagram
Table 8. Qualitative Analysis Summary Table: Dark Triad Traits
Research
Question/
Objective
Key Themes
Identified
Code/Phrase
Linked Trait
Behavior
Predictor
Deduced
Implications
Sources
How does
parental
monitoring
(PM)
influence the
development
of Dark Triad
traits in
adolescents?
Self-doubt
(SD)
"I often
question my
abilities."
Psychopathy
Risk (SD):
Ineffective
parental
Monitoring
Lack of parental
encouragement
fosters
psychopathic
tendencies.
[11]
[15]
[26]
[60]
[61]
[62]
[63]
How does
lack of
parental
monitoring
(LPM)
influence the
development
of Dark Triad
traits in
adolescents?
Desire
(Craving)
(DC)
"I need
constant
validation
and
reassurance"
Machiavellianism
Risk (DC):
Neglectful
Parenting
Lack of Parental
structure and
overindulgence
promotes
manipulative
tendencies in
adolescents.
[14]
[26]
[27]
[52]
[60]
[63]
[64]
How do
socio-
economic
stressors
(SES)
influence the
development
of Dark Triad
traits in
adolescents?
Self-
Gratification
(SG)
“I see no
harm in
taking
advantage of
others to
benefit
myself."
Narcissism
Risk (SG):
Economic
Strain
Financial
hardship fosters
selfish
entitlement and
narcissistic
behavior.
[6] [15]
[20]
[21]
[22]
[59]
[82]
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Table 9. Qualitative Analysis Summary Table: Light Triad Traits
Research
Question/
Objective
Key Themes
Identified
Code/Phrase
Linked
Trait
Behavior
Predictor
Implications
Sources
How does
parental
monitoring
(PM)
influence the
development
of Dark Triad
traits in
adolescents?
Self-
Confidence
(SC)
“I don’t compare
myself to others
because I value
and trust my
uniqueness."
Empathy
Protective
(SC):
Effective
Parental
Monitoring
Active Parental
involvement
builds trust and
fosters Light
Triad traits like
altruism,
empathy and
compassion.
[6] [15]
[20]
[21]
[22]
[59]
[82]
How does lack
of parental
monitoring
(LPM)
influence the
development
of Light Triad
traits in
adolescents?
Self-
Confidence
(SC)
"I feel like I’ve
made mistakes
that could have
been avoided if
my parents paid
more attention."
Empathy
Protective
(SC)
Reduced
Parental
oversight might
foster
autonomy or
self-reliance in
some
adolescents.
[20]
[65]
[66]
[67]
[68]
[69]
[70]
How do socio-
economic
stressors
(SES)
influence the
development
of Light Triad
traits in
adolescents?
Self-
Contentment
(SCT)
"I'm grateful for
what I have and
at peace with my
circumstances."
Altruism
Protective
(SCT):
Resilience
through
Hardship
Economic
hardship builds
appreciation,
empathy, and
selflessness in
adolescents, as
they develop
coping
strategies
focused on
community and
kindness,
[24]
[71]
[72]
[73]
[74]
[75]
[76]
How does
family conflict
(FC) influence
the
development
of Light Triad
traits in
adolescents?
Selflessness
(SL)
"I am most
fulfilled when I
can help
someone in
need."
Compassion
Protective
(SL):
Conflict
Resolution
Skills
Constructive
conflict
resolution can
foster
compassion and
empathy,
promoting
prosocial traits.
[24]
[68]
[70]
[80]
[81]
[82]
[83]
The qualitative analysis summary Tables 8 and 9, provide a comprehensive overview of the narratives of
adolescents from recent studies, directly addressing the research question and aligning with the explanatory
sequential design described by [57]. This design was chosen to triangulate findings, further illustrate results, and
offset methodological limitations in this study.
8. Discussion
The research findings highlight that parental monitoring plays a critical role in adolescent behavior, with lower
parental involvement correlating with increased risk behaviors such as self-doubt, desire (craving), and self-
gratification [21]. The present study explored the impact of familial and environmental factors on adolescent
personality development, focusing on the interplay of risk predictors (self-doubt, desire/craving, self-gratification)
and protective traits (self-confidence, self-contentment, selflessness) [1]. Quantitative analyses revealed strong
correlations between familial conflict, socioeconomic stress, and risk predictors. For instance, self-doubt exhibited
the highest correlation with lack of parental monitoring (r = 0.953, p < 0.05), indicating the critical role of parental
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involvement in the life of adolescents. Conversely, protective traits were strongly associated with positive parental
monitoring, with self-confidence (r = 0.848, p < 0.05) and self-contentment (r = 0.867, p < 0.05) emerging as
significant outcomes of supportive parenting.
Regression analyses confirmed the findings, revealing that familial conflict and socioeconomic stress significantly
predicted maladaptive traits, with R² values up to 0.93 for self-doubt. The results indicated that Dark Triad traits
often emerge as responses to early familial dynamics and environmental pressures [24]. For instance, adolescents
experiencing neglect or overly permissive parenting frequently exhibit heightened self-doubt and insecurity, which
fosters a craving for social validation and the use of manipulative strategies to fulfill self-gratifying needs [24]. In
the absence of supportive relationships, these adolescents may resort to antisocial behaviors to assert themselves,
especially if self-doubt, desire, and self-gratification remain reinforced by continuous exposure to negative familial
or environmental influences [25]. The persistence of maladaptive traits highlights the resilience of these drivers,
often outweighing positive influences and creating a reinforced loop of Dark Triad characteristics that persist into
adulthood [23]. The thematic analysis complemented these results, underscoring the alignment of adolescent
narratives with the Validation Syndrome Diagnostic Triangle (VSDT) framework (fig. 7). These findings indicate
that parental monitoring and familial environments critically shape the trajectory of adolescent personality traits
[58],[3].
The results from the quantitative analysis empirically support the Validation Syndrome Diagnostic Triangle
(VSDT) theory. Specifically, that risk predictors increase with negative familial factors, fitting the theoretical
"validation-seeking" pathway. Protective predictors flourish under positive influences, aligning with the "self-
confidence" and "self-contentment" aspects of the framework, fitting the "self-acceptance" pathway. These
findings complement prior research [29] suggesting that empathy-building and resilience-focused interventions
can disrupt the validation-seeking cycle. Integrating this knowledge, the Validation Syndrome Diagnostic Triangle
(VSDT) framework shown on Fig. 7, offers a comprehensive lens for understanding how early familial and
environmental conditions shape an adolescent’s trajectory toward either Dark or Light Triad traits.
Figure 7. The Validation Syndrome Diagnostic Triangle (VDST) Framework
Note. The Validation Syndrome Diagnostic Triangle (VDST) Framework © 2024 by Francis C. Ohu and Laura A
Jones is licensed under CC By 4.0
The Validation Syndrome (VS) aligns with patterns found in antisocial personality traits, yet it emphasizes self-
doubt and the pursuit of validation as key drivers [18]. This nuance suggests that interventions aimed at
strengthening self-contentment, fostering autonomous self-confidence, and developing prosocial values could
prevent escalation into more entrenched antisocial or exploitative behaviors. The findings of this study underscore
the VSDT framework, which posits that self-doubt, desire, and self-gratification coalesce in negative familial
environments to perpetuate maladaptive behaviors [18]. Emerging evidence highlights how adolescent
engagement with digital platforms often mirrors offline behavioral tendencies, particularly in individuals
exhibiting Dark Triad traits [34]. These traits correlate strongly with cyberbullying, trolling, and other deceptive
behaviors in online environments, where anonymity and reduced accountability amplify manipulative tendencies.
Adolescents experiencing high family conflict and low parental monitoring often described behaviors driven by
external validation, including manipulation and self-serving tendencies [59]. This reflects the cyclical nature of
the VSDT, where self-doubt fosters desire, leading to self-gratification as a coping mechanism for unmet needs
[21]. Conversely, parental monitoring emerged as a critical protective factor, reinforcing traits like self-confidence
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and selflessness [20]. Narratives revealed that adolescents with strong parental involvement expressed gratitude,
resilience, and fulfillment in helping others, behaviors aligned with the Light Triad traits of empathy, altruism, and
compassion [84],[30]. Socioeconomic stress showed dual influences: while it exacerbated self-gratification, it also
fostered resilience and self-contentment in some adolescents, suggesting that adversity may yield adaptive traits
when paired with supportive parenting [59].
The findings of this study have significant implications for both theoretical and practical understanding.
Theoretically, the study validates the Validation Syndrome Diagnostic Triangle (VSDT) framework as a holistic
model for understanding how familial and environmental factors influence the emergence of Dark and Light Triad
traits in adolescents. The integration of psychological and environmental dimensions highlights the dual role of
familial conflict as both a risk factor and a potential resilience builder. Practically, the results emphasize the need
for family-based interventions that reduce conflict, enhance parental monitoring, and address socioeconomic
stressors. The Validation Syndrome Diagnostic Triangle (VSDT) framework can be leveraged as a valuable tool
for developing targeted interventions that interrupt the development of maladaptive traits and behaviors, as well
as a practical framework for modeling parenting styles that promote healthy family dynamics. Furthermore,
programs that foster self-confidence and selflessness in adolescents can mitigate maladaptive behaviors and
promote prosocial development [28].
A. Forensic Cyberpsychology Implications of the Findings
This study also situates its findings within a forensic cyberpsychology context, examining how online interactions
influence developmental patterns. Adolescents with Dark Triad tendencies often engage in cyberbullying,
catfishing, or other manipulative online behaviors, aligning with themes of self-gratification and desire.
Conversely, supportive digital environments and parental monitoring of online activity foster resilience and
protective traits [85]. The findings of this study have significant implications for forensic cyberpsychology.
Adolescents with high levels of self-doubt and a craving for validation, often influenced by negative familial
dynamics, are at a higher risk of engaging in cyber-related manipulations. The Validation Syndrome Diagnostic
Triangle (VSDT) provides a framework to assess these traits, offering tools to predict and prevent cyber offenses.
This supports the observations of [86], who underscores the importance of behavioral analytics in identifying risk
factors, which could be instrumental in detecting manipulative online behaviors linked to Dark Triad traits.
Additionally, this research highlights the dual role of socioeconomic stress. While economic hardship fosters self-
gratification and risky behaviors in some adolescents, it also promotes resilience in others when paired with
positive parenting. Forensic cyberpsychology can use these findings to design interventions that leverage parental
monitoring to reduce online risks, such as cyberbullying or unauthorized access to digital systems, as described by
[87].
The Validation Syndrome Diagnostic Triangle (VSDT) can be applied to understand the psychological drivers
behind cyber-related antisocial behaviors. By correlating these traits with online risk behaviors, the current study
enhances forensic cyberpsychology’s ability to inform targeted interventions, such as digital literacy programs and
psychological assessments in schools. Reference [88] proposes that ethical leadership, and behavioral interventions
can mitigate cyber risks, aligning with the need to foster resilience and protective traits among adolescents. Further
corroborating these findings, [89] identifies the role of machiavellian and psychopathic tendencies in exacerbating
insider threats, which are mirrored in the exploitative online behaviors of adolescents with Dark Triad traits. The
study's strengths include its comprehensive mixed-methods approach, combining robust quantitative analysis with
rich qualitative insights. However, it’s reliance on secondary data limits the exploration of nuanced individual
experiences, and self-reported measures may introduce bias. Additionally, the cross-sectional design precludes
causal inference. Future longitudinal studies are recommended to confirm these findings over time and across
diverse cultural contexts.
9. Conclusion
This study aimed to uncover the underlying mechanisms of deception and early warning signs of Dark Triad trait
development in adolescents. The findings reveal a complex interplay between familial dynamics, with negative
influences such as family conflict and socioeconomic stress exacerbating Dark Triad traits [1],[59] and protective
factors like parental monitoring and resilience-building interventions promoting the development of Light Triad
tendencies [29],[23]. These findings offer actionable insights for educators, clinicians, and policymakers seeking
to foster adaptive adolescent development. The study's contributions to the field include the validation of the
Validation Syndrome Diagnostic Triangle (VSDT) framework and the identification of key factors influencing
adolescent personality development [18].
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The findings indicate that familial conflict is the strongest predictor of Dark Triad traits, with adolescents in high-
conflict environments displaying heightened self-doubt, desire, and self-gratification [24]. Socioeconomic stress
compounds the development of antisocial behaviors, creating vulnerabilities for manipulation and narcissistic
tendencies [30]. On the other hand, parental monitoring acts as a significant protective factor, fostering traits like
self-confidence, self-contentment, and selflessness [27]. Adolescents exposed to positive familial environments
exhibit increased resilience, reducing their reliance on validation-seeking behaviors [29]. Additionally, the
Validation Syndrome Diagnostic Triangle (VSDT) framework effectively maps the interplay between
psychological drivers and environmental stressors, providing a diagnostic tool for early intervention [18].
The practical implications of this study are vast. First, integrating artificial intelligence (AI) tools using the VSDT
framework can enhance behavioral forensics and criminal profiling by detecting early signs of manipulative or
antisocial behaviors in high-risk adolescents [15],[14]. Community-based initiatives can train parents on
authoritative parenting techniques to mitigate maladaptive traits [27]. Targeted socioeconomic interventions, such
as family assistance programs, can alleviate the indirect impact of financial instability on adolescent personality
development [59]. Schools can use AI-driven behavioral analytics to identify at-risk students for early intervention
[46], while therapeutic applications of the VSDT framework can provide personalized interventions for
adolescents exhibiting early signs of antisocial traits [18]. By incorporating forensic cyberpsychology insights,
policymakers can create culturally sensitive programs that address both offline and digital manifestations of dark
personality traits [17]. Emerging evidence highlights how adolescent engagement with digital platforms often
mirrors offline behavioral tendencies, particularly in individuals exhibiting Dark Triad traits; these traits correlate
strongly with cyberbullying, trolling, and other deceptive behaviors in online environments, where anonymity and
reduced accountability amplify manipulative tendencies [90]. Public health campaigns can raise awareness about
the role of familial dynamics in shaping adolescent personality development, emphasizing preventive strategies
[12]. Additionally, cultural adaptations of interventions can account for norms influencing the expression of Dark
and Light Triad traits [91]. Strategies to moderate technology’s role in reinforcing narcissistic traits, such as
through social media, are also crucial [41]. The findings of this study underscore the value of forensic
cyberpsychology in designing targeted interventions to prevent cyber-related manipulations by adolescents
exhibiting Dark Triad traits [17]. Resilience-building activities like mindfulness and empathy training in schools
and community centers can promote prosocial development [29]. Finally, advocacy for early detection tools and
evidence-based interventions within public health and education systems can significantly reduce the societal
burden of antisocial behaviors [15].
10. Recommendations for Future Research
Future research should focus on conducting longitudinal studies to track the progression of Dark and Light Triad
traits across different developmental stages [12]. Validation of the VSDT framework across diverse cultural
settings is necessary to assess its universal applicability [18]. Investigating the neurobiological underpinnings of
validation-seeking behaviors can deepen understanding of their origins, and future research should explore the
integration of forensic cyberpsychology and neurobiological measures to deepen our understanding of the
mechanisms underpinning antisocial behaviors in digital environments [47]. AI and machine learning models
should be explored to refine predictive tools for identifying at-risk adolescents [46]. Tailored intervention
programs based on the VSDT framework should be tested in clinical and educational settings [27]. Qualitative and
mixed-method designs can capture the nuanced experiences of adolescents in various familial and environmental
contexts [59]. Finally, policy impact studies should assess the long-term societal impacts of these research-derived
policies, focusing on public health and education outcomes [15].
By addressing these areas, future research can build on the foundational insights of this study, advancing the
understanding and mitigation of antisocial personality traits in adolescents.
Acknowledgments
We give all appreciation and acknowledgment to God, our Almighty Father.
References
[1] Crone, E. A., & Van Drunen, L. (2024b). Development of self-concept in childhood and adolescence: How
neuroscience can inform theory and vice versa. Human Development, 255–271.
https://doi.org/10.1159/000539844
[2] Milenkova, V., & Nakova, A. (2023). Personality development and behavior in adolescence: Characteristics
and dimensions. Societies, 13(6), 148. https://doi.org/10.3390/SOC13060148
[3] Yinxin, Y. (2021). Adolescent personality development and its influencing factors. Journal of Sociology and
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
84 Published by IDEAS SPREAD
Ethnology, 3(7), 1–5. https://doi.org/10.23977/JSOCE.2021.030701
[4] Basto-Pereira, M., Farrington, D. P., & Maciel, L. (2024). Unraveling the Sequences of Risk Factors Underlying
the Development of Criminal Behavior. Journal of Developmental and Life-Course Criminology, 10(2), 242–
264. https://doi.org/10.1007/S40865-024-00254-5/TABLES/4
[5] Loggen, J., Moneva, A., & Leukfeldt, R. (2024). A systematic narrative review of pathways into, desistance
from, and risk factors of financial-economic cyber-enabled crime. Computer Law & Security Review, 52,
105858. https://doi.org/10.1016/J.CLSR.2023.105858
[6] Miller, A., & Johnston, C. A. (2024). Family structure and material hardship: Child and adolescent pathways
to health and well-being. Infant and Child Development. https://doi.org/10.1002/ICD.2510
[7] Wissing, B. G., & Reinhard, M. A. (2019). The dark triad and deception perceptions. Frontiers in Psychology,
10(AUG). https://doi.org/10.3389/fpsyg.2019.01811
[8] Thomsen, L., & Homel, R. (2024). Cumulative sociodemographic risk as a predictor of adolescent antisocial
behaviour. Child Indicators Research, 17(5), 2123–2148. https://doi.org/10.1007/s12187-024-10157-y
[9] Viding, E., McCrory, E., Baskin-Sommers, A., De Brito, S., & Frick, P. (2024). An ‘embedded brain’ approach
to understanding antisocial behaviour. Trends in Cognitive Sciences, 28(2), 159–171. Elsevier Ltd.
https://doi.org/10.1016/j.tics.2023.08.013
[10] Carroll, S. L. (2024). The Origins of Antisocial Behavior: Influences of Genes, Development, and Context
(Publication No. 3123917696) [Doctoral dissertation, Michigan State University]. ProQuest Dissertations &
Theses Global. Available at:
https://login.captechu.idm.oclc.org/login?url=https://www.proquest.com/dissertations-theses/origins-
antisocial-behavior-influences-genes/docview/3123917696/se-2
[11] Huang, Y., Gan, X., Jin, X., Rao, S., Guo, B., He, Z., & Wei, Z. (2023). The relationship between the Dark
Triad and bullying among Chinese adolescents: The role of social exclusion and sense of control. Frontiers
in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1173860
[12] Chow, R. T. S., Yu, R., Geddes, J. R., & Fazel, S. (2024). Personality disorders, violence and antisocial
behavior: Updated systematic review and meta-regression analysis. The British Journal of Psychiatry, 1–11.
https://doi.org/10.1192/bjp.2024.226
[13] Abhishek, R., & Balamurugan, J. (2024). Impact of social factors responsible for Juvenile delinquency – A
literature review. Journal of Education and Health Promotion, 13(1).
https://doi.org/10.4103/JEHP.JEHP_786_23
[14] Martineau, M., Spiridon, E., & Aiken, M. (2023). A comprehensive framework for cyber behavioral analysis
based on a systematic review of cyber profiling literature. Forensic Sciences, 3(3), 452–477.
https://doi.org/10.3390/FORENSICSCI3030032
[15] McGovern, R., Balogun-Katung, A., Artis, B., Bareham, B., Spencer, L., Alderson, H., Brown, E., Brown, J.,
Lingam, R., McArdle, P., Newham, J. J., Wojciechowska, A., Rankin, J., Redgate, S., Thomason, P., & Kaner,
E. (2024). The effectiveness of preventative interventions to reduce mental health problems in at-risk children
and young people: A systematic review of reviews. Journal of Prevention, 45(4), 651–684.
https://doi.org/10.1007/s10935-024-00785-z
[16] Ogonowska, A. (2023). Cyberpsychology and media studies: Contemporary research directions and sources
of mutual inspiration. Annals of Psychology, 26(4), 315–330. https://doi.org/10.18290/RPSYCH2023.0017
[17] Rich, M. S., & Aiken, M. P. (2024). An interdisciplinary approach to enhancing cyber threat prediction
utilizing forensic cyberpsychology and digital forensics. 1 Forensic Sciences, 4(1), 110–151.
https://doi.org/10.3390/forensicsci4010008
[18] Liang, T., Wang, X., Ng, S., Xu, X., & Ning, Z. (2024a). The dark side of mental toughness: A meta-analysis
of the relationship between the dark triad traits and mental toughness. Frontiers in Psychology, 15.
https://doi.org/10.3389/fpsyg.2024.1403530
[19] Smaragdi, A., Schwarz, L. J., Austevik, T. J., Walsh, M., Webster, C., & Augimeri, L. (2024). Inter-rater
reliability of the Early Assessment Risk List Version 3 (EARL-V3) for children displaying antisocial behavior.
Children and Youth Services Review, 164, 107824. https://doi.org/10.1016/j.childyouth.2024.107824
[20] Cheng, C. H., Tein, J. Y., Shaw, D. S., Wilson, M. N., & Lemery-Chalfant, K. (2025). Predictors of
stability/change in observed parenting patterns across early childhood: A latent transition approach. Early
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
85 Published by IDEAS SPREAD
Childhood Research Quarterly, 70, 91–101. https://doi.org/10.1016/j.ecresq.2024.09.002
[21] Cheng, W. Y., Cheung, R. Y. M., & Chung, K. K. H. (2024). The role of family conflict and cohesion in
adolescents’ social responsibility: Emotion regulation ability as a mediator. PLOS ONE, 19(9), e0311265.
https://doi.org/10.1371/journal.pone.0311265
[22] Barnhart, S., Garcia, A. R., & Karcher, N. R. (2022). Adolescent Mental Health and Family Economic
Hardships: The Roles of Adverse Childhood Experiences and Family Conflict. Journal of Youth and
Adolescence, 51(12), 2294–2311. https://doi.org/10.1007/S10964-022-01671-9
[23] Martínez-Casanova, E., Molero-Jurado, M. del M., & Pérez-Fuentes, M. del C. (2024). Self-esteem and risk
behaviours in adolescents: A systematic review. Behavioral Sciences, 14(6), 432.
https://doi.org/10.3390/BS14060432
[24] Petrica, E., & Panisoara, G. (2024). The influence of Dark Triad-specific personality traits (Machiavellianism,
narcissism, psychopathy) on parenting styles and parental competence in raising and educating children.
Global Journal of Social Sciences Studies, 10(2), 68–75. https://doi.org/10.55284/gjss.v10i2.1182
[25] Gubbels, J., Assink, M., & van der Put, C. E. (2024). Protective factors for antisocial behavior in youth: What
is the meta-analytic evidence? Journal of Youth and Adolescence, 53(2), 233–257.
https://doi.org/10.1007/s10964-023-01878-4
[26] Huynh, H. P., Thomas, J., Castellanos, I., Weatherford, D. R., & Lilley, M. K. (2024). Social comparison,
belongingness, self-doubt, and stress: The case of Hispanic students at Hispanic majority institutions.
Hispanic Journal of Behavioral Sciences, 46(2), 99–121. https://doi.org/10.1177/07399863241292243
[27] García-Sastre, M. M., González-Alegre, P., Luengo-González, R., Cuesta-Lozano, D., Rodríguez-Rojo, I. C.,
Lluch-Canut, T., & Peñacoba-Puente, C. (2024). Promoting mental health in adolescents: “Teens Mental+”,
a nursing intervention program based in the positive mental health model. Psychology International, 6(3),
710–721. https://doi.org/10.3390/PSYCHOLINT6030044
[28] Hastings, P. D., Miller, J. G., Weissman, D. G., Hodge, R. T., Robins, R. W., Carlo, G., & Guyer, A. E. (2024).
Parasympathetic regulation and support from family and friends predict prosocial development in U.S.
Mexican-origin adolescents. Developmental Psychology. https://doi.org/10.1037/DEV0001780
[29] Kaufman, S. B., Yaden, D. B., Hyde, E., & Tsukayama, E. (2019a). The light vs. dark triad of personality:
Contrasting two very different profiles of human nature. Frontiers in Psychology, 10(MAR).
https://doi.org/10.3389/fpsyg.2019.00467
[30] Lee, I., Chang, Y., Lei, Y., & Yoo, T. (2024b). Adolescent health and dark personalities: The role of
socioeconomic status, sports, and cyber experiences. International Journal of Environmental Research and
Public Health, 21(8), 987. https://doi.org/10.3390/IJERPH21080987
[31] Ashraf, A., Khan, M. L., & Atta, N. (2024). Permissive Parenting, Self Regulation and Risk-Taking Behavior
among Adolescents. Global Social Sciences Review, IX(I), 89–101. [https://doi.org/10.31703/GSSR.2024(IX-
I).09](https://doi.org/10.31703/GSSR.
[32] Yang, R. (2024). The influence of the parenting style on children’s social ability and developmental ability.
Lecture Notes in Education Psychology and Public Media, 33(1), 95–99. https://doi.org/10.54254/2753-
7048/33/20231508
[33] Gómez-Leal, R., Fernández-Berrocal, P., Gutiérrez-Cobo, M. J., Cabello, R., & Megías-Robles, A. (2024a).
The dark tetrad: Analysis of profiles and relationship with the Big Five personality factors. Scientific Reports,
14(1), 1–10. https://doi.org/10.1038/s41598-024-55074-w
[34] Szabó, Z. P., Orosz, N. Z., Gulyás, R., & Láng, A. (2024a). The associations of peer-rated popularity and
likeability with Dark Triad personality traits in adolescent groups. Europe’s Journal of Psychology, 20(3),
165–177. https://doi.org/10.5964/EJOP.11667
[35] Song, H., Chan, J. S., & Ryan, C. (2024). Differences and similarities in the use of nine emotion regulation
strategies in Western and East-Asian cultures: Systematic review and meta-analysis. Journal of Cross-
Cultural Psychology. https://doi.org/10.1177/00220221241285006
[36] Jones, L. (2024). Unveiling human factors: Aligning facets of cybersecurity leadership, insider threats, and
arsonist attributes to reduce cyber risk. SocioEconomic Challenges, 8(2), 44–63.
https://doi.org/10.61093/sec.8(2).44-63.2024
[37] Putri, A. A. T., Parwatha, N. W., Sutrisna, I. P. B., & Wiguna, I. G. R. P. (2024). Parenting models, spirituality
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
86 Published by IDEAS SPREAD
and personality disorders in adolescence. International Journal of Health & Medical Sciences, 7(2), 40–52.
https://doi.org/10.21744/ijhms.v7n2.2279
[38] Mutie Wambua, F., & S. K., F. (2024). Influence of neglectful parenting approaches on self-esteem of
teenagers aged 13–19 years in selected day secondary schools in Lari Sub County in Kiambu County, Kenya.
International Journal of Psychology, 9(3), 15–30. https://doi.org/10.47604/IJP.2648
[39] Brazil, K. J., Farrell, A. H., Boer, A., & Volk, A. A. (2024). Adolescent psychopathic traits and adverse
environments: Associations with socially adaptive outcomes. Development and Psychopathology, 1–13.
https://doi.org/10.1017/S0954579424000051
[40] Ceroni, D. B., & Yalch, M. M. (2024). Influence of childhood maltreatment on Machiavellianism. Journal of
Aggression, Maltreatment & Trauma, 33(9), 1045–1054. https://doi.org/10.1080/10926771.2024.2358870
[41] Pérez-Torres, V. (2024). Social media: A digital social mirror for identity development during adolescence.
Current Psychology, 43(26), 22170–22180. https://doi.org/10.1007/s12144-024-05980-z
[42] Charmaraman, L., Hojman, H., Auqui, J. Q., & Bilyalova, Z. (2024). Understanding adolescent self -esteem
and self-image through social media behaviors. Pediatric Clinics of North America, 0(0).
https://doi.org/10.1016/j.pcl.2024.07.034
[43] Tan, C. N.-L., & Fauzi, M. A. (2024). Unravelling late adolescents’ addiction to social media: A unified theory
perspective. Global Knowledge, Memory and Communication. https://doi.org/10.1108/GKMC-02-2024-0099
[44] di Giacomo, E., Andreini, E., Lorusso, O., & Clerici, M. (2023). The dark side of empathy in narcissistic
personality disorder. Frontiers in Psychiatry, 14. https://doi.org/10.3389/fpsyt.2023.1074558
[45] Xu, F. (2024). The relationship between family function and aggression in peer relationships among
adolescents. Journal of Education, Humanities and Social Sciences IMPES, 2023.
https://doi.org/10.54097/2ev1xt38
[46] Toro-Alvarez, M. M. (2024). Digital violence in schools: A unified theory and structural equation model to
counteract cyberbullying. Journal of Aggression, Conflict and Peace Research.
https://doi.org/10.1108/JACPR-03-2024-0886
[47] Myznikov, A., Korotkov, A., Zheltyakova, M., Kiselev, V., Masharipov, R., Bursov, K., Yagmurov, O., Votinov,
M., Cherednichenko, D., Didur, M., & Kireev, M. (2024a). Dark triad personality traits are associated with
decreased grey matter volumes in ‘social brain’ structures. Frontiers in Psychology, 14.
https://doi.org/10.3389/fpsyg.2023.1326946
[48] Moreira, D., Azeredo, A., Ramião, E., Figueiredo, P., Barroso, R., & Barbosa, F. (2024). Systematic
exploration of antisocial behavior. European Psychologist, 29(2), 108–122. https://doi.org/10.1027/1016-
9040/A000527
[49] Leota, J., Faulkner, P., Mazidi, S., Simpson, D., & Nash, K. (2024). Neural rhythms of narcissism: Facets of
narcissism are associated with different neural sources in resting-state EEG. The European Journal of
Neuroscience, 60(5), 4907–4921. https://doi.org/10.1111/EJN.16479
[50] Add Health. (2019). The National Longitudinal Study of Adolescent to Adult Health (Add Health).
https://addhealth.cpc.unc.edu/
[51] DSDR. (2022). National Longitudinal Study of Adolescent to Adult Health (Add Health) Data Guide 1994 -
2018. https://www.icpsr.umich.edu/web/pages/DSDR/add-health-data-guide.html
[52] Harris, K. M. (2020). Guidelines for analyzing Add Health data. https://doi.org/10.17615/C6BW8W
[53] Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport,
Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
[54] Braun, V., & Clarke, V. (2024). Supporting best practice in reflexive thematic analysis reporting in Palliative
Medicine: A review of published research and introduction to the Reflexive Thematic Analysis Reporting
Guidelines (RTARG). Palliative Medicine, 38(6), 608–616. https://doi.org/10.1177/02692163241234800
[55] Naeem, M., Ozuem, W., Howell, K., & Ranfagni, S. (2023). A step-by-step process of thematic analysis to
develop a conceptual model in qualitative research. International Journal of Qualitative Methods, 22.
https://doi.org/10.1177/16094069231205789
[56] Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied Multiple Regression/Correlation Analysis
for the Behavioral Sciences. 3rd edn. https://doi.org/10.4324/9780203774441
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
87 Published by IDEAS SPREAD
[57] Busetto, L., Wick, W., & Gumbinger, C. (2020). How to use and assess qualitative research methods.
Neurological Research and Practice, 2(1), 1–10. https://doi.org/10.1186/S42466-020-00059-Z/TABLES/1
[58] de Moor, E. L., Nelemans, S. A., Becht, A. I., Meeus, W., & Branje, S. (2023). Personality development across
adolescence and young adulthood: The role of life transitions and self-concept clarity. European Journal of
Personality, 37(5), 587–604. Available at: https://osf.io/nhs5t
[59] Miller, P., Blatt, L., Hunter-Rue, D., Barry, K. R., Jamal-Orozco, N., Hanson, J. L., & Votruba-Drzal, E.
(2024a). Economic hardship and adolescent behavioral outcomes: Within- and between-family associations.
Development and Psychopathology. https://doi.org/10.1017/S0954579423001451
[60] Hillman, J. G., Fowlie, D. I., & MacDonald, T. K. (2023). Social verification theory: A new way to
conceptualize validation, dissonance, and belonging. Personality and Social Psychology Review, 27(3), 309–
331. Available at: https://doi.org/10.1177/10888683221138384
[61] de Moor, E. L., Nelemans, S. A., Becht, A. I., Meeus, W., & Branje, S. (2023). Personality development across
adolescence and young adulthood: The role of life transitions and self-concept clarity. European Journal of
Personality, 37(5), 587–604. Available at: https://doi.org/10.1177/08902070221119782
[62] Grotevant, H. D., Lo, A. Y. H., Fiorenzo, L., & Dunbar, N. D. (2017). Adoptive identity and adjustment from
adolescence to emerging adulthood: A person-centered approach. Developmental Psychology, 53(11), 2195–
22
[63] Ferencz, T., Láng, A., Kocsor, F., Kozma, L., Babós, A., & Gyuris, P. (2023). Sibling relationship quality and
parental rearing style influence the development of Dark Triad traits. Current Psychology, 42(28), 24764–
24781. https://doi.org/10.1007/s12144-022-03506-z
[64] Abhishek, R., & Balamurugan, J. (2024). Impact of social factors responsible for juvenile delinquency – A
literature review. Journal of Education and Health Promotion, 13(1).
https://doi.org/10.4103/JEHP.JEHP_786_23
[65] Arbel, R. (2024). Daily profiles of parents’ supportive extrinsic emotion regulation of adolescents’ negative
emotion. Emotion. https://doi.org/10.1037/EMO0001377
[66] Wang, M. (2024). Social anxiety in adolescents: An analysis of the psychological influence mechanism of
social media use. International Journal of Education and Humanities, 16(3), 55–58.
https://doi.org/10.54097/ry4jbb84
[67] Xing, H., Zhang, Y., Yao, M., Zhu, W., & Liu, H. (2024). How perceived parenting qualities link to the
reciprocal relationship between adolescents’ self-concept and life satisfaction. Journal of Social and Personal
Relationships. https://doi.org/10.1177/02654075241268780
[68] Stern, J. A., Bailey, N. A., Costello, M. A., Hellwig, A. F., Mitchell, J., & Allen, J. P. (2024). Empathy across
three generations: From maternal and peer support in adolescence to adult parenting and child outcomes.
Child Development. https://doi.org/10.1111/CDEV.14109
[69] Jiang, X., Liu, C., Xiao, X., & Zhan, Y. (2024). Role of narcissism and empathy in the relationship between
parental attachment and moral response patterns. European Journal of Developmental Psychology, 21(3),
365–387. https://doi.org/10.1080/17405629.2024.2325173
[70] Li, F., Gou, C., Tang, X., Qiu, Y., Deng, M., & Ji, X. (2024). Parental warmth, friendship quality, empathy
and bystander defending behavior in cyberbullying among adolescents in China. The Journal of Genetic
Psychology, 1–12. https://doi.org/10.1080/00221325.2024.2374712
[71] Çelik, O. (2024). Academic motivation in adolescents: The role of parental autonomy support, psychological
needs satisfaction and self-control. Frontiers in Psychology, 15.
https://doi.org/10.3389/FPSYG.2024.1384695
[72] Hong, Y. K., & Choi, H.-J. (2024). Multiple mediating effects of autonomy, competence and relatedness on
the relation between parents’ autonomy support and adolescents’ career maturity. The Korea Parents
Education Association, 21(1), 5–28. https://doi.org/10.61400/JPE.2024.21.1.05
[73] Kozyreva, V. V., & Pham, V. A. T. (2024). Correlation between emotional acceptance of parents and
independence level of adolescents. Vestnik Universiteta, 5, 246–256. https://doi.org/10.26425/1816-4277-
2024-5-246-256
[74] Edler, K., & Valentino, K. (2024). Parental self-regulation and engagement in emotion socialization: A
systematic review. Psychological Bulletin, 150(2), 154–191. https://doi.org/10.1037/BUL0000423
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
88 Published by IDEAS SPREAD
[75] Lin, J., & Li, Y. (2024). A study of the effects of parental psychological control on adolescents’ self-control.
Journal of Psychology and Behavior Studies, 4(1), 88–93. https://doi.org/10.32996/JPBS.2024.1.10
[76] Nisskaya, A. K., & Tsyganova, E. M. (2024). Parental practices of controlling and supporting the autonomy
of elementary school children and early adolescents in Russia: A qualitative study. Psychology in Russia:
State of the Art, 17(2), 3–22. https://doi.org/10.11621/PIR.2024.0201
[77] Islami, J. P., Fani, I., Nur, S., Latifa, R., & Napitupulu, L. (2024). Gratitude as a determinant of psychological
well-being in adolescents: An Islamic psychology perspective. Psikis: Jurnal Psikologi Islami, 10(1), 167–
174. https://doi.org/10.19109/PSIKIS.V10I1.21706
[78] Wong, Y. J., Pandelios, A. L., Carlock, K., & Thielmeyer, A. M. B. (2024). Stronger together: Perspectives on
gratitude social processes in group interventions for adolescents. Frontiers in Psychology, 15.
https://doi.org/10.3389/FPSYG.2024.1476511
[79] Lombardi, A. R., Rifenbark, G. G., Shogren, K. A., Taconet, A., & Hicks, T. A. (2024). Exploring the
relationship between self-determination and economic hardship constructs among adolescents with and
without disabilities. Remedial and Special Education. https://doi.org/10.1177/07419325241247343
[80] Peng, Y., Xia, M., & Chi, X. (2024). Age-varying associations of parent-adolescent relationship and school
connectedness with adolescent self-compassion: Differences by gender. Journal of Adolescence.
https://doi.org/10.1002/JAD.12378
[81] Krok, D., & Tkaczyk, J. (2024). The Light vs. Dark Triad and compassion for others: The mediating role of
inner harmony among teachers. Archives of Psychiatry and Psychotherapy, 26(3), 17–26.
https://doi.org/10.12740/APP/183678
[82] Apriyeni, E., Patricia, H., & Rahayuningrum, D. C. (2024). Adolescents conflict resolution patterns: A
descriptive analysis. International Journal of Multidisciplinary Approach Research and Science, 2(2), 813–
821. https://doi.org/10.59653/IJMARS.V2I02.748
[83] Sitota, G., & Tefera, B. (2024). Family cohesion and disruptive behavior among school adolescents: The
mediating role of self-regulation. International Journal of Evaluation and Research in Education (IJERE),
13(1), 9–17. https://doi.org/10.11591/IJERE.V13I1.24969
[84] Lalita, R. (2024). Social competence and altruistic behaviour among adolescents: A review study.
International Journal for Multidisciplinary Research, 6(1).
https://doi.org/10.36948/IJFMR.2024.V06I01.12771
[85] Adinata, S. P., & Kesumaningsari, N. P. A. (2024). Adolescents cyberbullying: Examining the role of social
media use intensity and Dark Triad personality. Journal of Educational, Health and Community Psychology,
13(4). https://doi.org/10.12928/jehcp.v13i4.28751
[86] Burton, S. L., Burrell, D. N., Nobles, C., & Jones, L. A. (2023). Exploring the Nexus of Cybersecurity
Leadership, Human Factors, Emotional Intelligence, Innovative Work Behavior, and Critical Leadership
Traits. Scientific Bulletin, 28(2), 162–175. https://doi.org/10.2478/BSAFT-2023-0016
[87] Davidson, J., Aiken, M., Phillips, K., & Farr, R. (2022). European youth cybercrime, online harm and online
risk-taking: 2022 research report. CC-DRIVER 2021 European Youth Survey. Available at:
https://repository.uel.ac.uk/item/8v59y
[88] Jones, L. A. (2021). A content analysis review of literature to create a usable framework for reputation risk
management. In Advances in Cybersecurity Leadership: The Human Element, 91–133.
https://doi.org/10.4018/978-1-7998-3811-1.CH006
[89] Burrell, D. N., Nobles, C., Cusak, A., Jones, L. A., Wright, J. B., Mingo, H. C., Ferreras-Perez, J., Khanta, K.,
Shen, P., & Richardson, K. (2023). Cybersecurity and cyberbiosecurity insider threat risk management. In
Handbook of Research on Cybersecurity Risk in Contemporary Business Systems, 121–136.
https://doi.org/10.4018/978-1-6684-7207-1.CH006
[90] Lim, J., & Huh, Z. (2024). Relationship between parental monitoring and cyberbullying perpetration among
male and female adolescents: Dual sequential mediating effects of self-control and peer conformity of
antisocial behaviors. Korea University Institute of Educational Research, 91, 139–165.
https://doi.org/10.24299/kier.2024.372.139
[91] Castagna, P. J., & Hart, W. (2024). Light triad traits moderate the relationship between the dark tetrad and
immoral character. Personality and Individual Differences, 222, 112593.
ier.ideasspread.org International Educational Research Vol. 8, No. 2; 2025
89 Published by IDEAS SPREAD
https://doi.org/10.1016/J.PAID.2024.112593
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