Association Between Resilience and Self-Esteem in Adolescents from Peruvian Schools
MarioJ.Valladares-Garrido1✉Emailmario.valladares@upch.pe
MaríaJuliaCómina-Tamayo2
ÓscarTuestaGarcía3
LuzA.Aguilar-Manay4
JassminSantinVásquez4
AngieValladares-Garrido5
VíctorJ.Vera-Ponce6,7
CésarJ.Pereira-Victorio8
1Escuela de Medicina HumanaUniversidad Señor de SipánChiclayoPeru
2Facultad de Medicina HumanaUniversidad Peruana Cayetano HerediaSan Martín de PorresPeru
3Facultad de Medicina HumanaUniversidad Privada Antenor OrregoTrujilloPeru
4Facultad de Medicina HumanaUniversidad San Martín de PorresChiclayoPeru
5Universidad Nacional de PiuraPiuraPeru
6Instituto de Investigación de Enfermedades TropicalesUniversidad Nacional Toribio Rodríguez de Mendoza de AmazonasChachapoyas, AmazonasPeru
7Facultad de Medicina (FAMED)Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM)AmazonasPeru
8Facultad de MedicinaUniversidad ContinentalLimaPeru
Mario J. Valladares-Garrido1; María Julia Cómina-Tamayo2, Óscar Tuesta García3, Luz A. Aguilar-Manay4, Jassmin Santin Vásquez4, Angie Valladares-Garrido5, Víctor J. Vera-Ponce6,7, César J. Pereira-Victorio8
1 Escuela de Medicina Humana, Universidad Señor de Sipán, Chiclayo, Peru
2 Facultad de Medicina Humana, Universidad Peruana Cayetano Heredia, San Martín de Porres, Peru
3 Facultad de Medicina Humana, Universidad Privada Antenor Orrego, Trujillo, Peru
4 Facultad de Medicina Humana, Universidad San Martín de Porres, Chiclayo, Peru
5 Universidad Nacional de Piura, Piura, Peru
6 Instituto de Investigación de Enfermedades Tropicales, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas, Chachapoyas, Amazonas, Peru
7 Facultad de Medicina (FAMED), Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas (UNTRM), Amazonas, Peru
8 Facultad de Medicina, Universidad Continental, Lima, Peru
Correspondence:
Mario J. Valladares-Garrido
Email: mario.valladares@upch.pe
A
ABSTRACT
Background
Self-esteem is a key component in adolescents' psychological development and is associated with multiple factors related to well-being and success. Resilience, defined as the ability to cope with and overcome adversity, is a potential protective factor for self-esteem. However, in Peru, evidence on this relationship is limited and has focused on specific populations, with some methodological constraints. Understanding this relationship is essential for designing strategies to promote adolescent mental health. Thus, this study aimed to examine the association between resilience and self-esteem among adolescents from five educational institutions in the Lambayeque region, Peru.
Methods
An analytical cross-sectional study was conducted through secondary analysis of data collected between September and December 2022. A total of 1,307 secondary school adolescents were included. Self-esteem was assessed using the Rosenberg Self-Esteem Scale, and resilience was measured with the 10-item CD-RISC. Descriptive and bivariate analyses were performed using chi-square tests. The association between resilience and self-esteem was estimated using Poisson regression models with robust variance, adjusting for confounders.
Results
The prevalence of low self-esteem in the studied population was 44.6% (95% CI: 42.03–47.40). Adolescents with low resilience showed a higher prevalence of low self-esteem compared to those with high resilience (48.5% vs. 26.1%; p < 0.001). In the adjusted analysis, high resilience was associated with a lower prevalence of low self-esteem (PR: 0.68; 95% CI: 0.53–0.86; p = 0.002). Other factors associated with low self-esteem included severe family dysfunction (PR: 2.17; 95% CI: 1.65–2.84; p < 0.001), family history of mental illness (PR: 1.19; 95% CI: 1.01–1.40; p = 0.043), and excessive television use (PR: 1.18; 95% CI: 1.04–1.33; p = 0.009).
Conclusion
Resilience emerged as a significant protective factor against low self-esteem in adolescents, while family dysfunction and a family history of mental illness were identified as risk factors. These findings underscore the need for school- and community-based strategies to enhance resilience, improve family functioning, and address modifiable risk factors, with the ultimate goal of promoting psychological well-being and preventing self-esteem problems in this population.
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A. Trial registrationClinical trial number: not applicable.
Keywords:
Self-esteem
resilience
adolescents
mental health
psychosocial factors.
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INTRODUCTION
Self-esteem can be defined as the concept an individual develops about their worth (1, 2, 3). This concept is subjective and encompasses the way one thinks, loves, and behaves toward oneself (1, 3). Self-esteem has a significant impact on an individual’s life development; reports have shown a relationship between higher levels of self-esteem and greater personal, social, and professional success (4, 5). On the other hand, low levels of self-esteem have been shown to be associated with poor social performance, depression, and substance abuse (6, 7). Multiple external factors influence the development of self-esteem, especially during adolescence, a period characterized by rapid physical, mental, and social changes (6, 8). Studies have shown that up to one-third of adolescents worldwide experience difficulties associated with low self-esteem, particularly during the early years of adolescence (9, 10). In adolescents from countries such as China, Tunisia, Ethiopia, Vietnam, and Saudi Arabia, the estimated prevalence of low self-esteem is 57.5%, 29.5%, 19%, 19.4%, and 41%, respectively (2, 11, 12, 13, 14). In Latin America, studies have found that 18.51%, 47.9%, and 45% of adolescents from Ecuador, Colombia, and Mexico, respectively, presented low self-esteem (15, 16, 17). Peru is no exception to this statistic, as the literature reports that between 25% and 35% of Peruvian adolescents have low levels of self-esteem (18, 19, 20).
Resilience, defined as the ability to overcome and recover from adverse circumstances, and its relationship with self-esteem levels have been the subject of study (21–30). In adolescents from countries such as Australia, Iran, Singapore, and the United States of America (USA), high prevalences of moderate-to-high resilience levels have been reported, at 73%, 52.5%, 67.3%, and 66.3%, respectively (31, 32, 33, 34). Reports on the prevalence of moderate-to-high resilience in adolescents from Latin American countries show values of 45%, 65.8%, and even 100% in Mexico, Colombia, and Bolivia, respectively (35, 36, 37). In Peruvian adolescents, the literature reports prevalence of moderate-to-high resilience levels ranging from 72.5–97.2% (29, 38).
Studies have shown that resilience in adolescents and young people is positively associated with self-esteem and mental health (19, 21, 22, 23, 24, 26). This is because resilience is thought to strengthen adolescents’ confidence, their ability to face challenges, and to overcome adversity, which contributes to higher self-esteem in difficult situations (21, 22, 23). In Chinese adolescents, self-esteem levels were found to positively predict resilience (26). In Polish adolescents, resilience was identified as a positive predictor of self-esteem levels (24). Finally, in Nicaraguan adolescents, a positive relationship was also found between high resilience levels and good self-esteem (22). Similarly, results have been published showing that the inclusion of programs aimed at strengthening resilience is beneficial for the development of self-esteem and emotional regulation (24, 25, 26, 27).
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However, most of the published literature analyzing the relationship between resilience and self-esteem in adolescence has certain limitations. First, the results are difficult to extrapolate to the national context due to differences in cultural, social, and educational aspects, as most studies have focused on Asian (23, 26, 27, 32), European (24), and Central and North American adolescents (22, 23). Even the Peruvian studies have focused exclusively on adolescents and young people from the city of Lima (19, 28, 30). Second, previous national evidence has limited its study population exclusively to students from a single educational institution (18, 28, 29, 30). Third, prior Peruvian studies have focused on university student populations (28, 30), which do not exclusively include the adolescent group, resulting in the loss of the necessary focus on analyzing the impact of self-esteem and resilience during the vulnerable stage of adolescence, particularly in its early years. Fourth, Peruvian studies have not considered the influence of potentially relevant factors in the relationship between resilience and self-esteem, such as Body Mass Index (BMI) (18, 28, 29, 30), family history of mental illness (18, 28, 29, 30), alcohol and/or tobacco use (18, 28, 29, 30), acne (18, 28, 29, 30), level of physical activity (18, 28, 29, 30), religion (18, 28, 29, 30), and time spent on social media (18, 28, 29, 30). Some studies have limited their analysis to age, sex, and year of study (18, 28, 29), while others have included academic performance (29, 30). Fifth, previous evidence has limited statistical power due to small sample sizes (18, 28, 29). Sixth, prior studies have used instruments with inadequate and unreliable psychometric properties to measure resilience and self-esteem in adolescents. Seventh, studies lack rigorous statistical analyses, as they have examined the association only in a bivariate manner (19, 28, 29) and have not estimated association measures to determine the magnitude and strength of the relationship between resilience and self-esteem (39).This study aims to determine the association between resilience and self-esteem in adolescents from five different schools in the northern region of Peru.
METHODS
Study design
An analytical cross-sectional study was conducted based on the secondary analysis of data collected from adolescent students in five secondary-level educational institutions in the Lambayeque region, Peru. Data collection was carried out between September and December 2022, in the context of the fifth wave of the COVID-19 pandemic.
The objective of this analysis was to evaluate the association between resilience and self-esteem in adolescents. The analyzed data came from a primary database whose initial purpose was to examine the relationship between the presence of acne and various mental health outcomes in this population.
Clinical trial number: not applicable.
Population and sample
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The study population consisted of 1,972 adolescents enrolled in five secondary-level educational institutions in the Lambayeque region, Peru, during the 2022 academic year. In the primary study, inclusion criteria were students who attended classes regularly, completed the main questionnaires, and provided their informed assent. A
Those whose parents did not authorize their participation through informed consent were excluded.In the original database, the response rate reached 72.8% (n = 1,436). For the present secondary analysis, a new data cleaning process was performed, removing 129 records with incomplete information in the resilience and self-esteem questionnaires. Finally, the sample analyzed in this study consisted of 1,307 adolescents, representing an adjusted response rate of 66.3%.
A statistical power calculation was performed to assess the study’s ability to detect differences in the prevalence of low self-esteem according to resilience level in adolescents. For this calculation, the proportion of low self-esteem in the low-resilience group (p₁ = 0.48) and in the high-resilience group (p₂ = 0.26) was considered, along with their respective sample sizes (n₁ = 1,081 for adolescents with low resilience and n₂ = 226 for adolescents with high resilience). The results indicated a statistical power of 100%, suggesting that the study has optimal capacity to detect significant differences in the association between resilience and self-esteem in the analyzed population.
Sampling was non-probabilistic.
Procedures
Data collection was carried out between September and December 2022 in five secondary-level educational institutions in the Lambayeque region, Peru. The instruments were administered in person in classrooms previously assigned by the administration of each school, ensuring adequate conditions for participants’ concentration. Before the administration of the questionnaires, the adolescents were informed about the purpose of the study, and their voluntary participation and the confidentiality of the data were ensured.
Participants completed a structured electronic questionnaire using the Research Electronic Data Capture (REDCap) platform, which included sociodemographic-academic information and variables of interest such as resilience and self-esteem. The data digitization and cleaning process was carried out by a team of previously trained researchers. A rigorous review was conducted to identify and remove incomplete or inconsistent responses. In addition, quality control procedures were applied to the data, minimizing potential biases in variable coding.
For the analysis, the resilience and self-esteem variables were categorized into two groups: high/low resilience and high/low self-esteem, following cutoff points previously established in the scientific literature. Finally, the processed database was used in the corresponding statistical analyses to assess the association between resilience and self-esteem in the study population.
Variables
The dependent variable was low self-esteem, operationally defined as a score lower than 15 points on the Rosenberg Self-Esteem Scale. This score was obtained by summing the responses to the 10 items of the questionnaire, following the methodology previously validated in similar studies.
The exposure variable was a high level of resilience, defined as a score of 30 points or higher on the abbreviated 10-item version of the Connor–Davidson Resilience Scale (CD-RISC) questionnaire. This score was obtained by summing the participants’ individual responses, in accordance with the cutoff points established in the scientific literature for classifying resilience levels in adolescents.
Several secondary independent variables were considered to explore their influence on the relationship between resilience and self-esteem in adolescents. Among the sociodemographic characteristics, age was included, classifying participants according to their developmental stage into early adolescence (10–13 years), middle adolescence (14–16 years), and late adolescence (17–19 years). Sex (male, female) and type of educational institution (public, private) were also recorded, distinguishing between publicly and privately managed schools. In addition, place of residence (rural, urban, marginal urban) was taken into account.
Family and academic conditions were assessed through the number of household members (1–5, 6–10, 11–15) and the presence of a family history of mental illness (yes, no). Regarding aspects related to physical health, BMI was included and categorized as underweight, normal weight, overweight, and obesity.
Academic performance was evaluated by determining whether the participant had failed any course during their school years (yes, no). Social interaction was also explored through the frequency of contact with friends (infrequent, frequent, very frequent) and relationship status (in a relationship, not in a relationship).
Regarding digital habits, the frequency of television use (1–5 hours, 6–10 hours, more than 11 hours) and the frequency of social media use during the COVID-19 pandemic (never, little, moderate, quite a lot to extreme, extreme) were analyzed. In addition, the presence of facial acne (no acne, grade 1, grade 2, grade 3, grade 4) was considered as a potential factor influencing self-esteem perception.
Regarding consumption habits, cigarette use was assessed (never, fewer than 10 cigarettes/day, 11–20 cigarettes/day, 21–30 cigarettes/day, more than 31 cigarettes/day) as well as alcohol consumption (never, monthly or less, 2–4 times a month, 2–3 times a week, 4 or more times a week). Physical activity was categorized as inactive or active.
Family APGAR questionnaire (measures family function based on Adaptability, Partnership, Growth, Affection, and Resolve), establishing four levels: functional family, mild dysfunction, moderate dysfunction, and severe dysfunction. These variables were incorporated into the analysis to identify potential factors associated with self-esteem in adolescents and its relationship with resilience.
Instruments
Rosenberg Self-Esteem Scale
Instrument designed to assess self-esteem. It consists of 10 items on a 4-point Likert scale, where each item can score from 1 (Strongly agree) to 4 (Strongly disagree). It should be noted that items 2, 5, 6, 8, and 9 are reverse scored (i.e., “Strongly agree” scores 4 points and “Strongly disagree” scores 1 point). A higher score correlates with a higher level of self-esteem. Scores below 15 suggest low self-esteem. The scale has shown excellent psychometric properties, with an estimated reliability of 0.92 in adolescents (40) and correlation coefficients ranging from 0.82 to 0.88 in studies conducted in the United States, Norway, and Asian countries (40, 41, 42). It has also been applied to Latin American adolescents, with reliability values ranging from 0.70 to 0.78 in adolescent populations from Chile and Argentina (43, 44). This scale has been used to assess adolescents during the COVID-19 pandemic (45, 46).
Abbreviated CD-RISC
Instrument designed to measure individual resilience levels. This is an abbreviated model of the original scale (25 items) consisting of 10 items, each rated on a Likert scale ranging from 0 (never) to 4 (almost always) (47). These items assess the dimensions of “personal competence,” “trust and strength,” “acceptance,” “control,” and “spirituality.” The total score ranges from 0 to 40 points, with higher scores indicating higher levels of resilience (47). It has a Cronbach’s alpha of 0.85, demonstrating good internal validity (47). This scale has previously been applied in adolescent populations in Colombia (α = .838) (48) and Peru (α = .827) (49), showing good reliability and validity. Likewise, it has been used to assess adolescents during the COVID-19 pandemic (α = .92) (50).
Family APGAR
Instrument that reflects family members’ perception of the overall functioning of the family unit. It evaluates five basic family functions: adaptation, partnership, personal resource gradient, affection, and resources. It consists of 9 items on a Likert scale ranging from 0 (never) to 4 (always). Scores below 17 points are associated with family dysfunction. The instrument has a correlation index of 0.80, and in evaluations conducted in multiple studies involving adolescents, correlation indices ranged from 0.71 to 0.83 (51, 52, 53). The scale has shown good reproducibility coefficients in Latin American adolescent populations (54). Studies have employed this scale during the lockdown period caused by the COVID-19 pandemic, including adolescent populations (55, 56).
Spanish Acne Severity Scale (EGAE)
Instrument used to assess the severity of vulgar acne that requires iconographic material for its application. It consists of 2 items: a facial scale ranging from grade 1 (least severe) to grade 4 (most severe), and a trunk scale (chest and back) ranging from grade 1 to grade 3 (57). This instrument has been widely reproduced and demonstrates high intra- and inter-observer reliability (α ≥ 0.8) (58). The scale has also been applied to Latin American populations during the COVID-19 pandemic, although not limited to adolescent populations (59).
Physical Activity Questionnaire for Adolescents (PAQ-A)
Instrument designed to assess physical activity in adolescents. It consists of 9 items that evaluate various aspects of physical activity performed in the past 7 days. It uses a 5-point Likert scale. The final score is calculated based on the arithmetic mean of the first 8 questions, while question 9 excludes the presence of any condition that prevented the participant from performing physical activity (60). The scale demonstrates high reliability values and has been replicated with Cronbach’s alpha coefficients ranging from 0.74 to 0.82 in adolescents from Spain and the United States (USA), respectively (60, 61). This instrument has proven adaptable to the national context, achieving good levels of internal consistency in Peruvian adolescent populations, with a Cronbach’s alpha of 0.8 (62).
Statistical Analysis Plan
Data analysis was performed using Stata version 18.0 (StataCorp LP, College Station, TX, USA). Initially, a descriptive exploration of the study variables was conducted. For categorical variables, absolute and relative frequencies were calculated, while numerical variables were analyzed using measures of central tendency and dispersion, following verification of data normality.
In the bivariate analysis, the association between resilience and self-esteem was evaluated using the chi-square test of independence, considering a significance level of 5% (p < 0.05).
To evaluate the association between resilience and self-esteem, generalized linear models (GLM) with a Poisson distribution and robust variance were used, allowing for the estimation of prevalence ratios (PR) with 95% confidence intervals (CI), thereby quantifying the magnitude of the effect between the analyzed variables. The educational institution was included as a cluster in the regression models to account for potential intra-school correlation and obtain more precise estimates. In the multiple regression model, adjustments were made for confounding variables identified in the bivariate analysis and those of epidemiological relevance, aiming to control the relationship between resilience and self-esteem. Additionally, collinearity among variables included in the final model was assessed by calculating the variance inflation factor (VIF), ensuring the stability of the estimated coefficients.
Ethical Considerations
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This study was approved by the Research Ethics Committee of Universidad San Martín de Porres, Lima, Peru, ensuring compliance with ethical principles for research involving human subjects. To protect participants’ privacy and confidentiality, data were collected through anonymous questionnaires without including any identifying information. A
Informed assent was obtained from the adolescents, and informed consent was secured from their parents or legal guardians prior to participation. Furthermore, it was ensured that the information collected would be used exclusively for research purposes, without compromising the participants’ integrity or well-being. A
All stages of the study were conducted in accordance with the principles of respect, beneficence, and justice, consistent with the Declaration of Helsinki and the applicable national regulations.RESULTS
Sociodemographic and Academic Characteristics
A total of 1,307 adolescents were included, with an average age of 14.63 ± 1.40 years. Most were in the middle stage of adolescence (69.2%), female (54.3%), and attended public schools (65.1%). Urban residency predominated (83.2%), and the majority lived in households with 1 to 5 members (60.0%). Additionally, 85.2% of the adolescents reported no family history of mental illness. Regarding nutritional status, the largest proportion had a normal BMI (63.1%). Nearly half (45.7%) reported having failed at least one course. Regarding interpersonal relationships, 47.0% reported frequent contact with friends, and 62.4% stated they were in a romantic relationship. A large majority (92.4%) of adolescents reported watching television between 1 to 5 hours daily, while 32.8% indicated frequent or extreme use of social media. Most adolescents had never smoked (94.0%) nor consumed alcohol (78.2%). In terms of physical activity, 66.2% were classified as inactive. Regarding family functionality, 40.4% of adolescents had a functional family, while 29.8% presented severe dysfunction. Concerning mental health, 82.7% exhibited low resilience, and 44.6% had low self-esteem (95% CI: 42.03–47.40). See Table 1.
Characteristics | N (%) | |
|---|---|---|
Age (years)* | 14.63 ± 1.40 | |
Adolescent stage (years) | ||
Early | 296 (22.7) | |
Middle | 905 (69.2) | |
Late | 106 (8.1) | |
Sex | ||
Male | 598 (45.8) | |
Female | 709 (54.3) | |
Type of institution | ||
Public | 851 (65.1) | |
Private | 456 (34.9) | |
Place of residence | ||
Rural | 185 (14.2) | |
Urban | 1087 (83.2) | |
Peri-urban | 35 (2.7) | |
Number of family members (categorized) | ||
1 a 5 | 784 (60.0) | |
6 a 10 | 474 (36.3) | |
11 a 15 | 49 (3.8) | |
Religion | ||
None | 305 (23.3) | |
Catholic | 739 (56.5) | |
Other | 263 (20.1) | |
Family history of mental illness | ||
No | 1114 (85.2) | |
Yes | 193 (14.8) | |
BMI (categorized) | ||
Underweight | 276 (21.1) | |
Normal | 824 (63.1) | |
Overweight | 166 (12.7) | |
Obesity | 41 (3.1) | |
Failed a subject during school years | ||
No | 710 (54.3) | |
Yes | 597 (45.7) | |
Relationship with friends | ||
Infrequent | 314 (24.0) | |
Frequent | 614 (47.0) | |
Very frequent | 379 (29.0) | |
Romantic partner | ||
No | 492 (37.6) | |
Yes | 815 (62.4) | |
Daily television use frequency | ||
1 a 5 | 1207 (92.4) | |
6 a 10 | 71 (5.4) | |
11 a 15 | 29 (2.2) | |
Frequency of social media use during the COVID-19 pandemic | ||
Never | 114 (8.7) | |
Rarely | 286 (21.9) | |
Moderate | 362 (27.7) | |
High to extreme | 428 (32.8) | |
Extreme | 117 (9.0) | |
Facial acne | ||
No | 664 (50.8) | |
Grade 1 | 558 (42.7) | |
Grade 2 | 60 (4.6) | |
Grade 3 | 7 (0.5) | |
Grade 4 | 18 (1.4) | |
Cigarette smoking | ||
Never | 1228 (94.0) | |
Less than 10 cigarettes/day | 41 (3.1) | |
11–20 cigarettes/day | 23 (1.8) | |
21–30 cigarettes/day | 6 (0.5) | |
≥ 31 cigarettes/day | 9 (0.7) | |
Alcohol consumption | ||
Never | 1022 (78.2) | |
Monthly or less | 164 (12.6) | |
2–4 times a month | 82 (6.3) | |
2–3 times a week | 25 (1.9) | |
4 or more times a week | 14 (1.1) | |
Physical activity | ||
Inactive | 838 (66.2) | |
Active | 428 (33.8) | |
Family dysfunction | ||
No | 493 (40.4) | |
Mild | 241 (19.8) | |
Moderate | 122 (10.0) | |
Severe | 363 (29.8) | |
Resilience | ||
Low | 1081 (82.7) | |
High | 226 (17.3) | |
Self-esteem | ||
Low | 583 (44.6) | |
Moderate | 384 (29.4) | |
High | 340 (26.0) | |
* Mean ± standard deviation (SD) | ||
Self-Esteem in Adolescents
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Fifty percent of the surveyed adolescents agreed that they feel worthy of appreciation. Additionally, 49.3% agreed that they possess positive qualities, and 44% indicated feeling capable of doing things as well as most people. On the other hand, 39.5% stated they do not have much to be proud of, and 29.9% tended to think of themselves as a failure. Furthermore, 37.4% agreed with the idea that sometimes they believe they are not a good person, while 34.4% occasionally considered themselves useless. Regarding self-perception, 44.9% wished to feel more self-respect, with 36.3% strongly agreeing with this statement. Finally, 40.2% reported feeling satisfied with their life overall, whereas 23.5% disagreed with this affirmation. See Fig. 01.A
Fig. 1
Distribution of response in the Rosenberg self-esteem test.
Association Between Resilience and Self-Esteem, and Other Factors in Bivariate Analysis
Low self-esteem was more frequent in adolescents with low resilience compared to those with high resilience (48.5% vs. 26.1%; p < 0.001). Additionally, the prevalence of low self-esteem was 20.9%, 36.7%, and 37.5% higher in adolescents with mild, moderate, and severe family dysfunction, respectively, compared to those from functional families (p < 0.001). A higher prevalence of low self-esteem was also observed in adolescents with a family history of mental illness compared to those without such history (56.0% vs. 42.6%; p = 0.001). Regarding sociodemographic factors, low self-esteem was more frequent in males than in females (52.8% vs. 37.7%; p < 0.001), and in adolescents who had failed at least one course compared to those who had not (48.4% vs. 41.4%; p = 0.011). With respect to risk behaviors, adolescents with higher cigarette consumption showed a significantly greater prevalence of low self-esteem compared to non-smokers, with a dose–response relationship observed (69.6% among those who smoked 11–20 cigarettes/day vs. 43.0% among non-smokers; p < 0.001). Similarly, adolescents with higher alcohol consumption showed a greater prevalence of low self-esteem, with 71.4% among those who drank 4 or more times per week compared to 42.0% among non-drinkers (p = 0.003). Regarding technological habits, adolescents with higher television use (≥ 6 hours per day) had a significantly higher prevalence of low self-esteem (60.6–65.5% vs. 43.2%; p = 0.001). Likewise, extreme social media use was associated with a higher prevalence of low self-esteem compared to moderate use (54.7% vs. 35.6%; p = 0.001). Finally, adolescents with insufficient physical activity showed a higher prevalence of low self-esteem compared to those who were physically active (49.3% vs. 35.3%; p < 0.001). See Table 2.
Variables | Self-esteem | p* | ||
|---|---|---|---|---|
No (n = 724) | Yes (n = 583) | |||
n(%) | n(%) | |||
Adolescent stage (years) | < 0.001 | |||
Early | 135 (45.6) | 161 (54.4) | ||
Middle | 517 (57.1) | 388 (42.9) | ||
Late | 72 (67.9) | 34 (32.1) | ||
Sex | < 0.001 | |||
Male | 282 (47.2) | 316 (52.8) | ||
Female | 442 (62.3) | 267 (37.7) | ||
Type of institution | 0.591 | |||
Public | 476 (55.9) | 375 (44.1) | ||
Private | 248 (54.4) | 208 (45.6) | ||
Place of residence | 0.667 | |||
Rural | 102 (55.1) | 83 (44.9) | ||
Urban | 600 (55.2) | 487 (44.8) | ||
Peri-urban | 22 (62.9) | 13 (37.1) | ||
Number of family members (categorized) | 0.110 | |||
1 a 5 | 447 (57.0) | 337 (43.0) | ||
6 a 10 | 246 (51.9) | 228 (48.1) | ||
11 a 15 | 31 (63.3) | 18 (36.7) | ||
Religion | 0.570 | |||
None | 161 (52.8) | 144 (47.2) | ||
Catholic | 414 (56.0) | 325 (44.0) | ||
Other | 149 (56.7) | 114 (43.4) | ||
Family history of mental illness | 0.001 | |||
No | 639 (57.4) | 475 (42.6) | ||
Yes | 85 (44.0) | 108 (56.0) | ||
BMI (categorized) | 0.389 | |||
Underweight | 158 (57.3) | 118 (42.8) | ||
Normal | 460 (55.8) | 364 (44.2) | ||
Overweight | 88 (53.0) | 78 (47.0) | ||
Obesity | 18 (43.9) | 23 (56.1) | ||
Failed a subject during school years | 0.011 | |||
No | 416 (58.6) | 294 (41.4) | ||
Yes | 308 (51.6) | 289 (48.4) | ||
Relationship with friends | 0.222 | |||
Infrequent | 161 (51.3) | 153 (48.7) | ||
Frequent | 345 (56.2) | 269 (43.8) | ||
Very frequent | 218 (57.5) | 161 (42.5) | ||
Romantic partner | 0.045 | |||
No | 290 (58.9) | 202 (41.1) | ||
Yes | 434 (53.3) | 381 (46.8) | ||
Daily television use frequency | 0.001 | |||
1 a 5 | 686 (56.8) | 521 (43.2) | ||
6 a 10 | 28 (39.4) | 43 (60.6) | ||
11 a 15 | 10 (34.5) | 19 (65.5) | ||
Frequency of social media use during the COVID-19 pandemic | 0.001 | |||
Never | 55 (48.3) | 59 (51.8) | ||
Rarely | 151 (52.8) | 135 (47.2) | ||
Moderate | 233 (64.4) | 129 (35.6) | ||
High to extreme | 232 (54.2) | 196 (45.8) | ||
Extreme | 53 (45.3) | 64 (54.7) | ||
Facial acne | 0.028 | |||
No | 359 (54.1) | 305 (45.9) | ||
Grade 1 | 326 (58.4) | 232 (41.6) | ||
Grade 2 | 31 (51.7) | 29 (48.3) | ||
Grade 3 | 4 (57.1) | 3 (43.9) | ||
Grade 4 | 4 (22.2) | 14 (77.8) | ||
Cigarette smoking | < 0.001 | |||
Never | 700 (57.0) | 528 (43.0) | ||
Less than 10 cigarettes/day | 14 (34.2) | 27 (65.9) | ||
11–20 cigarettes/day | 7 (30.4) | 16 (69.6) | ||
21–30 cigarettes/day | 3 (50.0) | 3 (50.0) | ||
≥ 31 cigarettes/day | 0 (0.0) | 9 (100.0) | ||
Alcohol consumption | 0.003 | |||
Never | 593 (58.0) | 429 (42.0) | ||
Monthly or less | 81 (49.4) | 83 (50.6) | ||
2–4 times a month | 36 (43.9) | 46 (56.1) | ||
2–3 times a week | 10 (40.0) | 15 (60.0) | ||
4 or more times a week | 4 (28.6) | 10 (71.4) | ||
Physical activity | < 0.001 | |||
Inactive | 425 (50.7) | 413 (49.3) | ||
Active | 277 (64.7) | 151 (35.3) | ||
Family dysfunction | < 0.001 | |||
No | 367 (74.4) | 126 (25.6) | ||
Mild | 129 (53.5) | 112 (46.5) | ||
Moderate | 46 (37.7) | 76 (62.3) | ||
Severe | 134 (36.9) | 229 (63.1) | ||
Resilience | < 0.001 | |||
Low | 557 (51.5) | 524 (48.5) | ||
High | 167 (73.9) | 59 (26.1) | ||
* p-value calculated using the Chi-square test of independence. | ||||
Association Between Resilience and Self-Esteem, and Other Factors in Simple and Multiple Regression Analysis
In the simple regression analysis, adolescents with low resilience had a higher prevalence of low self-esteem (PR: 0.54; 95% CI: 0.41–0.70; p < 0.001), and this relationship remained in the adjusted model, where adolescents with high resilience showed a 32% lower prevalence of low self-esteem (PR: 0.68; 95% CI: 0.53–0.86; p = 0.002). See Table 3.
Characteristics | Self-esteem | ||||||
|---|---|---|---|---|---|---|---|
Simple regression | Multiple regression* | ||||||
PR | CI 95% | p** | PR | CI 95% | p** | ||
Adolescent stage (years) | Ref. | ||||||
Early | Ref. | 1.66 | 0.73–0.88 | < 0.001 | |||
Middle | 0.79 | 0.71–0.88 | < 0.001 | 2.11 | 0.45–0.81 | 0.001 | |
Late | 0.59 | 0.45–0.77 | < 0.001 | 2.17 | |||
Sex | |||||||
Male | Ref. | Ref. | |||||
Female | 0.71 | 0.57–0.90 | 0.004 | 0.71 | 0.67–0.75 | < 0.001 | |
Type of institution | |||||||
Public | Ref. | Ref. | |||||
Private | 1.03 | 0.73–1.45 | 0.863 | 1.09 | 0.96–1.24 | 0.172 | |
Place of residence | |||||||
Rural | Ref. | Ref. | |||||
Urban | 0.98 | 0.85–1.13 | 0.820 | 0.98 | 0.86–1.12 | 0.749 | |
Peri-urban | 0.85 | 0.60–1.21 | 0.374 | 0.78 | 0.65–0.94 | 0.008 | |
Number of family members (categorized) | |||||||
1 a 5 | Ref. | Ref. | |||||
6 a 10 | 1.12 | 1.01–1.23 | 0.030 | 1.13 | 1.09–1.17 | < 0.001 | |
11 a 15 | 0.83 | 0.60–1.17 | 0.290 | 0.61 | 0.63–0.85 | < 0.001 | |
Religion | |||||||
None | Ref. | Ref. | |||||
Catholic | 0.93 | 0.76–1.13 | 0.444 | 1.01 | 0.91–1.11 | 0.852 | |
Other | 0.93 | 0.82–1.04 | 0.208 | 0.91 | 0.80–1.02 | 0.115 | |
Family history of mental illness | |||||||
No | Ref. | Ref. | |||||
Yes | 1.29 | 1.17–1.43 | < 0.001 | 1.19 | 1.01–1.40 | 0.043 | |
BMI (categorized) | |||||||
Underweight | Ref. | Ref. | |||||
Normal | 1.02 | 0.92–1.12 | 0.737 | 1.05 | 0.86–1.28 | 0.613 | |
Overweight | 1.11 | 0.78–1.58 | 0.571 | 1.05 | 0.75-1-46 | 0.783 | |
Obesity | 1.30 | 1.02–1.65 | 0.035 | 1.07 | 0.81–1.40 | 0.651 | |
Failed a subject during school years | |||||||
No | Ref. | Ref. | |||||
Yes | 1.17 | 1.01–1.35 | 0.032 | 1.06 | 0.94–1.20 | 0.322 | |
Relationship with friends | |||||||
Infrequent | Ref. | Ref. | |||||
Frequent | 0.89 | 0.81–0.98 | 0.020 | 1.08 | 0.92–1.26 | 0.345 | |
Very frequent | 0.87 | 0.70–1.06 | 0.165 | 1.05 | 0.98–1.12 | 0.132 | |
Romantic partner | |||||||
No | Ref. | Ref. | |||||
Yes | 1.13 | 1.04–1.22 | 0.004 | 1.18 | 1.1–1.26 | < 0.001 | |
Daily television use frequency | |||||||
1 a 5 | Ref. | Ref. | |||||
6 a 10 | 1.41 | 1.19–1.67 | < 0.001 | 1.18 | 1.04–1.33 | 0.009 | |
11 a 15 | 1.46 | 1.19–1.79 | < 0.001 | 1.08 | 0.77–1.51 | 0.649 | |
Frequency of social media use during the COVID-19 pandemic | |||||||
Never | Ref. | Ref. | |||||
Rarely | 0.90 | 0.79–1.02 | 0.106 | 0.88 | 0.65–1.19 | 0.396 | |
Moderate | 0.68 | 0.52–0.90 | 0.007 | 0.79 | 0.57–1.10 | 0.164 | |
High to extreme | 0.87 | 0.66–1.16 | 0.344 | 0.93 | 0.63–1.36 | 0.695 | |
Extreme | 1.05 | 0.71–1.53 | 0.817 | 1.01 | 0.62–1.66 | 0.954 | |
Facial acne | |||||||
No | Ref. | Ref. | |||||
Grade 1 | 0.88 | 0.78-1.00 | 0.057 | 0.92 | 0.84–1.02 | 0.108 | |
Grade 2 | 1.04 | 0.80–1.34 | 0.774 | 1.31 | 0.84–2.05 | 0.236 | |
Grade 3 | 0.92 | 0.69–1.24 | 0.581 | 0.78 | 0.59–1.04 | 0.097 | |
Grade 4 | 1.58 | 1.43–1.76 | < 0.001 | 1.33 | 1.03–1.72 | 0.029 | |
Cigarette smoking | |||||||
Never | Ref. | Ref. | |||||
Less than 10 cigarettes/day | 1.55 | 1.32–1.81 | < 0.001 | 1.05 | 0.87–1.53 | 0.312 | |
11–20 cigarettes/day | 1.62 | 1.07–2.43 | 0.021 | 1.14 | 0.82–1.59 | 0.441 | |
21–30 cigarettes/day | 1.45 | 0.95–2.23 | 0.087 | 1.39 | 0.90–2.15 | 0.133 | |
≥ 31 cigarettes/day | 2.32 | 2.10–2.57 | < 0.001 | 1.07 | 0.48–2.34 | 0.874 | |
Alcohol consumption | |||||||
Never | Ref. | Ref. | |||||
Monthly or less | 1.19 | 0.85–1.66 | 0.321 | 1.16 | 0.87–1.53 | 0.312 | |
2–4 times a month | 1.34 | 1.13–1.60 | 0.001 | 1.14 | 0.82–1.59 | 0.441 | |
2–3 times a week | 1.42 | 1.04–1.95 | 0.029 | 1.39 | 0.90–2.15 | 0.133 | |
4 or more times a week | 1.74 | 1.12–2.69 | 0.013 | 1.07 | 0.48–2.34 | 0.874 | |
Physical activity | |||||||
Inactive | Ref. | Ref. | |||||
Active | 0.72 | 0.61–0.83 | < 0.001 | 0.91 | 0.79–1.04 | 0.158 | |
Family dysfunction | |||||||
No | Ref. | Ref. | |||||
Mild | 1.82 | 1.50–2.21 | < 0.001 | 1.66 | 1.42–1.95 | < 0.001 | |
Moderate | 2.44 | 1.74–3.41 | < 0.001 | 2.11 | 1.58–2.83 | < 0.001 | |
Severe | 2.47 | 1.83–3.33 | < 0.001 | 2.17 | 1.65–2.84 | < 0.001 | |
Resilience | |||||||
Low | Ref. | Ref. | |||||
High | 0.54 | 0.41–0.70 | < 0.001 | 0.68 | 0.53–0.86 | 0.002 | |
*Adjusted for relevant covariates | |||||||
**p-values obtained using Generalized Linear Models (GLM). Poisson family, log link function, robust variance, school as cluster | |||||||
Additionally, adolescents with mild, moderate, and severe family dysfunction had a higher prevalence of low self-esteem compared to those from functional families. In particular, severe dysfunction was associated with a 147% higher prevalence of low self-esteem (PR: 2.47; 95% CI: 1.83–3.33; p < 0.001). This association persisted in the multiple regression model, where adolescents with moderate and severe dysfunction showed a 111% and 117% increase in the prevalence of low self-esteem, respectively (PR: 2.11; 95% CI: 1.58–2.83 and PR: 2.17; 95% CI: 1.65–2.84). See Table 3.
Other factors were also associated with low self-esteem. In the adjusted analysis, adolescents with a family history of mental illness had a 19% higher prevalence of low self-esteem (PR: 1.19; 95% CI: 1.01–1.40). Regarding lifestyle habits, television use exceeding 6 hours per day was associated with an 18% higher prevalence of low self-esteem (PR: 1.18; 95% CI: 1.04–1.33). Additionally, adolescents who consumed alcohol 4 or more times per week had a 74% higher prevalence of low self-esteem in the simple analysis (PR: 1.74; 95% CI: 1.12–2.69; p = 0.013), although this association did not remain significant in the multiple model. Finally, adolescents in a romantic relationship showed an 18% higher prevalence of low self-esteem compared to those not in a relationship (PR: 1.18; 95% CI: 1.10–1.26; p < 0.001). See Table 3.
DISCUSSION
Prevalence of self-esteem
In our study, we found that 44.7% of secondary school adolescents presented low self-esteem. This finding is consistent with results from a study conducted in Ghana, in a pre-pandemic context, where 47% of adolescents were found to have low self-esteem (63). Similarly, a study conducted among adolescents in Nigeria reported that 32.1% of them had low self-esteem (64). Likewise, in Vietnam, also in a pre-pandemic context, 19.4% of secondary school students were found to have low self-esteem (13). Similarly, a study conducted in India in a pre-pandemic context reported considerably lower figures, with only 8.33% of adolescents presenting low self-esteem (65). In adolescents from the United States, a pre-pandemic study using the Rosenberg scale found that the prevalence of low self-esteem reached 30% (7). Likewise, a study carried out in Brazil, also in a pre-pandemic context, found that 33.8% of adolescents had low self-esteem (66). This supports the possibility that, in our context, low self-esteem may be related to negative body image, limited social support, or psychosocial environmental factors (66). The high frequency observed could be explained by body dissatisfaction, which is common among adolescents—especially females—and is closely related to low self-esteem (66). This dissatisfaction is influenced by sex, BMI, social pressure regarding aesthetic ideals, and the internalization of beauty standards, all of which can lead to discomfort with one’s own image and negatively affect self-esteem (66). In Ecuador, a study conducted among secondary school students in a post-pandemic context found that 36.1% had low self-esteem according to the Rosenberg scale (67). In Colombia, 47.9% of students showed “low or very low” self-esteem in a study carried out in a pre-pandemic context (68). In a school in Puerto Maldonado, Peru, 44.7% of students presented a moderate level of self-esteem in a study conducted during the COVID-19 pandemic (69). Similarly, in Puno, Peru, a pre-pandemic study found that 57.7% of adolescents had what was considered “regular” self-esteem, and 21.2% had low self-esteem (70). On the other hand, in Trujillo, Peru, a pre-pandemic study found a prevalence of low self-esteem of 10.9% among the adolescents evaluated (71).
The observed prevalence may be related to specific contextual conditions affecting school-aged adolescents, such as a dysfunctional family environment, living arrangements with parents, academic pressure, and cultural norms linked to self-image (13). Likewise, several additional factors can negatively influence self-esteem during adolescence, including physical and/or mental health history (69), experiences of school violence (72), prolonged exposure to social media promoting unrealistic beauty ideals (18, 28), as well as the impact of the COVID-19 pandemic (73). For example, a study conducted in Spain compared secondary school students evaluated before and after the pandemic and found that, in the post–COVID-19 group, there was a significant increase in the proportion of adolescents with low self-esteem (score ≤ 25 on the Rosenberg scale) compared to the pre-pandemic group (73). The differences observed between studies could be explained by geographic, cultural, and methodological factors (13, 74).
Resilience and Self-Esteem
In our study, adolescents with a high level of resilience were associated with a lower prevalence of low self-esteem. This finding is consistent with research in Nigeria that reported an association between self-esteem and resilience against peer pressure in adolescents, suggesting that higher levels of self-esteem positively influence adolescents’ ability to resist social pressure, with 75% of participants presenting high self-esteem (74). Similarly, a study in China among adolescents with hearing disabilities found that resilience significantly predicted self-esteem (B = 2.031) (75). Another study in China, conducted among left-behind adolescents, reported that self-esteem significantly predicts resilience (β = 0.448) (23). Similarly, a study in Poland showed that resilience influences emotional regulation, and that this relationship is strengthened when adequate levels of self-esteem and perceived social support are present (24). Furthermore, research in Turkey identified that self-esteem, along with school belonging and social support, explains 33% of the variance in resilience (R² = 0.33), while these same factors explain 35% of the variance in self-esteem (R² = 0.35) (76). In Mexico, a study in basic education adolescents concluded that the total resilience score correlates positively with self-esteem (r = 0.59) and with positive affect (r = 0.48). These results support the idea that positive self-esteem acts as an internal predictor of resilience (77). Similarly, in Argentina it was concluded that self-esteem and resilience are closely related during adolescence, suggesting that strengthening one favors the development of the other (78). In Arequipa, a region in southern Peru, a low but significant inverse correlation was found (rho ≈ − 0.33, p = 0.001), indicating that adolescents with greater resilience tended to present higher levels of self-esteem (79). Along the same lines, a study conducted in Lima, Peru, confirmed a significant relationship between resilience and self-esteem across various dimensions, such as confidence and perseverance (80). Likewise, different life events influence coping styles both directly and indirectly, with this effect being mediated 34.37% by resilience and self-esteem (81).
This association could be explained by the fact that resilience provides emotional protection against psychosocial stress, fosters stable family relationships and support networks, and enhances coping strategies such as self-efficacy and emotional regulation (82). At the neurobiological level, it has been linked to increased activity in the prefrontal cortex (83) and reduced reactivity in the amygdala, facilitating better emotional control (84). This helps mitigate the impact of adverse situations, such as those generated by the pandemic, and contributes to preserving healthier self-esteem in adolescents (85). For example, a study conducted in the United States of America found that greater brain resilience—reflected in stronger functional connectivity between regions such as the prefrontal cortex and the amygdala—was associated with lower stress and sadness during the pandemic, reinforcing its protective role over emotional well-being (85).
Male sex
A
In our study, male adolescents showed a lower prevalence of low self-esteem. This finding is consistent with a meta-analysis that found adolescent males tend to have slightly higher self-esteem than females, reporting a positive and significant correlation between sex and self-esteem (r = 0.21), with higher scores in males (86). Similarly, studies conducted in Oregon and San Francisco, USA, among adolescent students found a significant difference in standardized self-esteem between sexes (d = 0.22), with males showing higher self-esteem levels (r = 0.21) (87), while females scored higher in relationality and in several self-esteem domains (88). In Spain, higher self-esteem was also observed in male than in female adolescents (r = 0.23) (89), possibly due to the greater negative impact of pubertal changes on females (90). Internationally, a cross-cultural analysis including data from 48 countries—among them Peru, Brazil, Argentina, Bolivia, and Ecuador—identified a consistent gender effect (B = − 1.85; average r ≈ 0.20), with males reporting higher self-esteem levels compared to females, and with self-esteem increasing with age in both genders, particularly at the end of adolescence and the beginning of adulthood (91). This contrasts with findings from a study of adolescents in Michigan, USA, which reported no significant differences in mean self-esteem between sexes or across cohorts, with an explained variance below 2% (R² < 0.02) (92). Similarly, another study in adolescents from California, USA, found no differences in self-esteem perception according to sex (93). A national longitudinal study based on the National Longitudinal Survey of Youth 1979 (NLSY79) also suggests that differences in self-esteem between sexes during adolescence and early adulthood are small or statistically nonsignificant (94). This finding is relevant, as the common belief that males have higher self-esteem could lead parents and teachers to underestimate self-esteem problems in adolescent boys (95). On the other hand, a longitudinal study in African American adolescents from Atlanta found that females reported higher self-esteem levels, possibly due to better development of the self-system, while males from female-headed households exhibited more risk behaviors that could affect their self-esteem and academic performance (96). Similarly, a study conducted in Argentina concluded that there are no significant differences in self-esteem scores between males and females (44).These differences could be explained by factors such as life satisfaction, identified in a Chilean study as the main determinant of adolescent self-esteem, followed by perceived educational quality and self-image. It was observed that a positive evaluation of the family and school environment fosters the development of self-esteem, even in precarious educational contexts (97). In males, self-concept and global self-esteem are associated with values such as achievement, competence, and self-direction, while in females, communal and prosocial values predominate (98). Gender stereotypes and family and cultural socialization processes also play a role, as they often expand opportunities more for males (99). A study in the United States supports this idea, noting that men tend to accept more positive statements about themselves, whereas women are more likely to accept negative statements (100). Likewise, the differences in self-esteem between males and females are explained by biological, cultural, socioeconomic, and sociodemographic factors (91). Biologically, hormonal and neurological variations influence self-perception and emotional regulation (91). Culturally, gender expectations reinforce values of autonomy and competence in men, while communal values predominate in women (91). From a socioeconomic perspective, countries with greater development and gender equity tend to show more marked gaps, suggesting that access to opportunities also plays a role. Finally, social roles, family structure, and stereotypes influence self-esteem, with smaller differences observed in contexts with more flexible gender norms (91).
Family member with mental health disorder
In our study, having a family member with a mental health disorder was associated with a higher prevalence of low self-esteem among adolescents. This is similar to what has been reported in adolescents in the United States, where having a family member with special health care needs was found to be associated with a higher likelihood of low self-esteem (Odds Ratio (OD): 1.37) (7). Similarly, a Norwegian study showed that children of parents with depression have lower self-esteem levels than those whose parents do not have this diagnosis (101). In Indonesia, a study reported that pasung—a practice that involves the deprivation of physical, mental, and social integrity through restraint or confinement—applied to individuals with mental disorders has a profound impact on children living with the patient. These effects include feelings of helplessness and shame, psychological disturbances such as depression, substance use, school dropout, and social isolation (102), factors that collectively constitute fertile ground for the development of impaired self-esteem (7, 103, 104). A study conducted among school adolescents in Huánuco, Peru, found that low self-esteem was significantly associated with the presence of depression. Specifically, 39.4% of participants had low self-esteem, while 16.4% showed depressive symptoms, demonstrating a statistically significant relationship between both variables (105). However, a study conducted in the United States reported a contrasting finding, identifying that higher self-esteem in children of parents with depression was the main predictor of the absence of a psychiatric diagnosis and of a high level of global functioning at 2, 10, and 20 years of follow-up (106). This association could be explained by the presence of social or family support networks (7). In contexts with protective structures, such as cohesive families, strong educational institutions, or assistance programs, the impact of having a family member with a mental disorder may be mitigated, reducing its negative effect on the adolescent’s self-esteem (7). In contrast, in less protective environments, exposure to a family member’s mental illness may increase emotional vulnerability and contribute to low self-esteem (106).
Partner
In our study, having a romantic partner was associated with a higher prevalence of low self-esteem. This finding is consistent with a study conducted among university students in Houston (USA), which found that relationship-contingent self-esteem (RCSE) was negatively associated with global self-esteem (r = − 0.29) (107). This suggests that students whose self-worth depends on the status of their relationship tend to experience lower and more vulnerable self-esteem in response to the ups and downs of relationship dynamics (107). This finding contrasts with a study in German adolescents, where entering into a romantic relationship significantly increased self-esteem, particularly when the relationship lasted at least one year (d ≈ + 0.10). It was also observed that a breakup reduced self-esteem (d ≈ − 0.16), although this effect was temporary and disappeared within a year, even without entering a new relationship (108). This could be explained by a study conducted in the Netherlands, which evaluated the effect of initiating and ending a romantic relationship. The results support the dynamic equilibrium model of personality development, which posits that traits such as self-esteem and self-perception can temporarily change in response to significant life experiences but tend to return to an individual set point influenced by both genetic and environmental factors (109). In this regard, if self-esteem is based exclusively on performance within the relationship (contingent self-esteem), there is a greater risk of experiencing low self-esteem when the relationship is not emotionally satisfying (107). However, when the relationship is solid and functional, it can serve as a positive reinforcement for self-esteem (108). Moreover, few aspects of social life have as much potential to significantly impact self-esteem and well-being as the success or failure of romantic relationships. Nevertheless, not all individuals are equally affected by the ups and downs of their romantic relationships (108).
Middle and late adolescence
In our study, being in middle and late adolescence was associated with a 20% and 39% reduction in low self-esteem, respectively, compared to early adolescence. This finding is consistent with a study conducted in Spain, which observed that self-esteem tends to increase as adolescents grow older; adolescents aged 15 to 19 years showed significantly lower rates of low self-esteem compared to those aged 12 to 14 years (110). Similarly, a study in Germany found that self-esteem was high in childhood, declined in early adolescence, and then progressively increased until young adulthood, with a significant medium effect size between the ages of 13 and 29 years (d = 0.29) (111). In the same vein, a study in Kentucky, USA, concluded that during middle and late adolescence—and even into early adulthood—self-esteem tends to stabilize or even increase; in fact, more than half of the participants remained at the same self-esteem level from one year to the next, with significant correlation coefficients ranging from 0.59 to 0.87 for measures such as the Rosenberg scale (112). Likewise, a cross-cultural analysis using data from 48 countries—including several in South America, such as Peru, Brazil, Argentina, Bolivia, and Ecuador—found that adolescent self-esteem tends to increase progressively with age, particularly toward the end of adolescence and the beginning of adulthood. Using multilevel models, a positive and significant association between age and self-esteem was found (B = 0.80), even after controlling for gender and country (91). Another study conducted in Ecuador among adolescents showed that the proportion of those with high self-esteem was greater in the 15–19-year-old group (51%) compared to the 12–14-year-old group (estimated at 45%), suggesting a trend toward increasing self-esteem with advancing age (15). This contrasts with what was reported in a study conducted among adolescents in the United States, where late-stage adolescents showed stable self-esteem levels over time, with minimal cohort differences accounting for less than 2% of the total variance (η² < 0.02) (92). Along the same lines, a study in New York found that although self-esteem may fluctuate, it tends to stabilize from the age of 12, such that those who exhibit high self-esteem in early stages are likely to maintain it through middle and late adolescence (113).
This association could be explained by cultural differences, social contexts, and the level of family or school support, all of which significantly influence self-image perception and the way adolescents cope with the challenges inherent to each stage of development (7). These variations are linked to biological, cultural, socioeconomic, and sociodemographic factors, which change as the adolescent grows older (91). Furthermore, in late adolescence, the increase in responsibilities and social expectations may impact self-esteem differently depending on the environment in which the individual develops (114). It has also been argued that self-esteem tends to be higher in late adolescence compared to early adolescence due to greater self-awareness; however, it is still lower than in early adulthood, likely as a consequence of the maturational processes and social changes that characterize this developmental stage (115).
Family dysfunction
In our study, mild, moderate, and severe family dysfunction were associated with a 66%, 115%, and 165% increase, respectively, in the prevalence of low self-esteem. This finding is consistent with a study in Greek adolescents, which found that factors characteristic of dysfunctional family functioning, such as low cohesion, were strongly linked to lower self-esteem. In particular, self-esteem significantly mediated the relationship between family cohesion and both state anxiety levels (p = 0.005) and trait anxiety levels (p = 0.011), highlighting its protective role in youth mental health (116). Similarly, a study conducted among adolescents in the United States found that low maternal responsiveness was associated with a higher prevalence of low self-esteem (26.7% vs. 12.4%). Likewise, low maternal demandingness was associated with more cases of low self-esteem (24.9% vs. 13.4%), highlighting the role of parenting style in the formation of self-concept during adolescence (7). Similarly, a meta-analysis conducted in 31 countries demonstrated that parental hostility—including rejection, neglect, abuse, punishment, and verbal or physical aggression—was negatively associated with self-esteem, with moderate to large effect sizes (r = − .33 for maternal hostility and r = − .37 for paternal hostility) (117). Along the same lines, a study in Spain showed that the family environment, as well as close peer relationships, are fundamental for the development of healthy self-esteem (118). Furthermore, a study in China found that father absence was associated with lower self-esteem: adolescents without a father figure reported a mean score of 24.63 (Standard Deviation (SD) = 3.22), compared to 33.12 (SD = 6.03) among those living with their father, a highly significant difference (F = 770.23) (119). Possibly because this absence is interpreted as a sign of lack of love or acceptance, which reduces the perception of meaningful emotional support within the family environment (120). This contrasts with findings from various studies conducted in the United States. One study—carried out among university adolescents—did not show a direct relationship between family dysfunction and low self-esteem (121). Similarly, a longitudinal study in the United States of America found no significant effect of parental supervision on children’s self-esteem (122). Likewise, a study in Mexican adolescents living in the United States did not find a significant impact of parental hostility on children’s self-esteem (120). The association between family dysfunction and low self-esteem may be explained by psychobiological and contextual factors (123). The lack of secure emotional bonds and a stressful family environment hinder emotional regulation and foster the development of a negative self-concept (119). In addition, constant exposure to criticism reinforces the perception of not being valuable (124). At the neurobiological level, chronic stress activates the hypothalamic–pituitary–adrenal axis, affecting brain areas related to self-evaluation (125, 126). During the pandemic, this vulnerability was intensified by the reduction of emotional support in dysfunctional family contexts (127).
Presence of acne
In our study, adolescents with grade 4 facial acne were found to have a higher prevalence of low self-esteem. This finding is consistent with an analytical study conducted in Norway, which found that male adolescents with acne were more likely to have low self-esteem (OR: 2.07), while in females, a significant association was also found between acne and lower self-esteem (OR: 1.88) (128). This aligns with a study in California (USA), which highlighted the negative impact of acne—particularly when perceived as severe—on self-esteem, self-image, and socialization. However, it was a descriptive study without adjusted association measures or multivariate analysis (129). Moreover, a literature review covering data from 11 countries concluded that women with acne are more likely to experience low self-esteem, heightened shyness, greater perceived stress, feelings of worthlessness, body dissatisfaction, and lower self-worth. However, as this was a synthesis of descriptive studies, it did not provide multivariate association measures or adjusted analyses (130). Nevertheless, these findings contrast with those reported in a study conducted in India, where only 6.8% of adolescents with acne had low self-esteem, while the majority (67.6%) showed normal levels of self-esteem (131). Similarly, a study carried out in Turkey found no significant differences in self-esteem levels or social anxiety between adolescents with and without acne (132). Likewise, research conducted in Brazil found no significant association between acne severity—including grade IV—and self-esteem, as measured by the Rosenberg scale (133). This association could be explained by the fact that, in this age group, many adolescents have not yet developed the maturity to adequately cope with the emotional impact of the visible lesions caused by acne (134). This impact has been documented in the literature as low self-esteem, dissatisfaction with physical appearance, shame, and shyness (135). In addition, dissatisfaction with physical appearance during adolescence has been systematically associated with multiple psychosocial health problems, including low self-esteem, sleep disturbances, nervousness, stress, depressive symptoms, and lower quality of life (114). Furthermore, adolescents with acne do not necessarily experience self-esteem problems solely due to their self-image; they may also be affected by the psychosocial judgments of their social environment, which reinforces the emotional and social impact of this dermatological condition (132).
Living in urban–marginal areas
In our study, adolescents residing in urban–marginal areas were associated with a lower prevalence of low self-esteem compared to those living in rural areas. This finding is consistent with a study in China, which observed that children of rural migrant parents had more mental health problems than local children, with higher proportions in abnormal ranges (21% vs. 9.8%) and borderline ranges (18.8% vs. 13.8%) (136). In the analysis of this study, being part of a single-parent family (OR = 3.13; 95% CI: 1.42–6.89), having insufficient household income (OR = 2.61; 95% CI: 1.33–5.13), and having a poor perception of health status (OR = 6.22; 95% CI: 1.13–34.08) were significantly associated with a higher likelihood of self-esteem problems among migrant children (136). However, this contrasts with findings from a study conducted in India, which observed a higher prevalence of low self-esteem in urban adolescents (66.7%) compared to rural adolescents (56.7%), with a statistically significant difference (t = 13.4; p = 0.0001) and a prevalence ratio of 1.18 (137). Along the same lines, a study in Australia found that rural adolescents showed significantly higher self-esteem levels than their urban peers, according to multivariate analyses based on the Rosenberg scale (p < 0.05) (138). In addition, this study found a moderate positive correlation between age and self-esteem among urban adolescents (r = + 0.30), whereas the correlation was negative among rural adolescents (r = − 0.34) (138). Similarly, a study conducted in Peru found that self-esteem was positively associated with other conditions in adolescents, with this association being stronger in rural areas (r = 0.8) than in urban areas (r = 0.5) (139). This finding suggests that adolescents from rural settings may develop stronger self-esteem, possibly due to a more cohesive social environment and reduced exposure to comparative social pressures (139). On the other hand, a study conducted in Mexico found no significant differences in body dissatisfaction between adolescents from rural and urban areas (140). Given that body dissatisfaction has been associated with low self-esteem, this finding suggests that the geographical setting alone does not determine self-esteem levels related to body image in this population (66).
Television
In our study, adolescents who watched between 6 and 10 hours of television were associated with a higher prevalence of low self-esteem. This finding is consistent with a study in Germany, where greater screen time between the ages of 11 and 13 was associated with lower self-esteem at age 13, even after statistical adjustments. Among males, computer and phone use was significantly associated with lower self-esteem (b = − 2.93), and this association persisted after controlling for prior self-esteem (b = − 2.82) (141). Similarly, a study in the United States conducted among university students found that frequent social media use was associated with lower self-esteem (r = − 0.20) (142). Likewise, a systematic review including data from 71 countries found that greater screen time was consistently associated with lower self-esteem in children and adolescents, although a single pooled effect measure was not calculated due to methodological heterogeneity among the studies, and the evidence was considered to be of moderate quality (143). A hierarchical regression analysis conducted among adolescents in the United States found that watching more television during follow-up was associated with a decrease in self-esteem (β = − 0.94) (144). Finally, a study in adolescents from China reported an inverse association between television time on school days and adolescent self-esteem (β = − 0.935), as well as lower life satisfaction (145). This contrasts with a study conducted in Germany, where, among female adolescents, more television viewing at age 11 was associated with lower self-esteem at that time (β = − 3.96) but predicted a significant increase at age 13 (β = +5.08), provided that viewing was low or moderate (< 2 h/day) (138). Similarly, a study among adolescents in Hong Kong identified an inverted-J–shaped relationship, in which those who watched television moderately (between 1 and ≤ 2 hours per day) reported higher self-esteem levels compared with both those who watched less than one hour and those with greater daily exposure (146). This association could be explained by the influence of unrealistic body ideals conveyed by the media, which can negatively affect physical self-concept and body satisfaction, thereby reducing overall self-esteem (147). Although this hypothesis is supported by some studies (141, 148) and a meta-analysis (149), the results are not conclusive. Moreover, the association between screen time and low self-esteem could be overestimated by the omission of variables such as obesity or sedentary behavior, which also affect self-esteem (141). Obesity, associated with body dissatisfaction, can negatively influence self-esteem (67). Therefore, it is not necessarily television viewing time that directly causes low self-esteem; rather, this relationship could be mediated by other factors that are not always considered (141). It has also been suggested that the effect of television consumption on self-esteem could be transitory (144). However, this interpretation contrasts with research emphasizing how body ideals promoted in the media, particularly among adolescents, could have more persistent effects on self-esteem, especially in girls (147).
Limitations and strengths
This study has some limitations that should be considered when interpreting the results. First, its cross-sectional design precludes establishing causal relationships between the factors analyzed and low self-esteem; therefore, the associations observed should not be interpreted as causal. Moreover, certain variables such as television use may act as both potential causes and consequences of low self-esteem, making temporal directionality uncertain. Likewise, the findings cannot be generalized to the entire adolescent population, as the sample is limited to students from specific educational institutions, excluding non-school-attending adolescents. Another relevant limitation is the use of self-report instruments, which may introduce social desirability bias or errors derived from the participants’ subjective perception. In addition, some potentially influential variables—such as parents’ educational level (150), sleep quality (115), overall academic performance (151), experiences of violence or bullying (152), and perceived emotional support from family members or teachers (153)—were not considered in the analyses, which could act as confounding factors. These factors have previously been associated with both mental health and self-esteem in adolescents (115, 151, 152, 153), so their omission may limit a full understanding of the observed associations. Likewise, the lack of longitudinal follow-up prevents the evaluation of the evolution of self-esteem over time and its relationship with significant events in adolescent life. Finally, complex constructs such as family dysfunction or relationship-contingent self-esteem may not have been fully explored (7, 118, 119), given the use of general instruments that do not capture all their dimensions.
Nevertheless, the study also presents important strengths. One of them is the inclusion of multiple factors associated with self-esteem, such as resilience, family environment, facial acne, type of residence, and screen time, which allows the phenomenon to be approached from a broad and multifactorial perspective. In addition, the subgroup analyses—such as by sex (86, 88, 90), family structure (91, 119, 121), and urban or rural context (136)—provide a greater level of detail and understanding of the dynamics involved. The study also stands out for contextualizing its findings through comparison with previous research conducted in different countries, thereby strengthening the external validity of its results. Finally, this work contributes original empirical evidence on self-esteem in adolescents living in urban–marginal areas, a population underrepresented in the scientific literature, thus expanding the available knowledge on this vulnerable group.
Relevance of findings in mental health
The findings of this study are relevant to the field of mental health, as they highlight multiple contextual, personal, and social factors associated with low self-esteem in adolescents—a key variable in emotional and psychological development during this stage. The identification of protective variables such as resilience (74, 75, 77), as well as risk factors such as family dysfunction (119, 121), the presence of severe acne (128, 134, 135), or prolonged screen exposure (141), makes it possible to guide psychoeducational and community interventions aimed at promoting adolescent well-being. In addition, the association between low self-esteem and relational or contextual characteristics (such as having a romantic partner (107, 108), living in rural areas (136), or being in the early stages of adolescence (110, 111, 112)) underscores the need for a comprehensive approach that considers the family, school, and social environments. From a public health perspective, these findings help to identify at-risk groups and prioritize early prevention strategies, fostering the strengthening of self-concept and emotional regulation as fundamental elements for the healthy development of adolescents.
Conclusions
In this study, resilience was identified as a significant protective factor against low self-esteem among secondary school adolescents, even after adjusting for multiple sociodemographic, family, and behavioral factors. Furthermore, family dysfunction, a family history of mental illness, excessive television use, and being in a romantic relationship were independently associated with a higher prevalence of low self-esteem.
These findings underscore the need to implement school- and community-based programs aimed at strengthening resilience and fostering coping skills, as well as to develop family-focused interventions to improve communication and emotional support. Regulating screen-related habits and conducting early school-based screenings are key strategies to prevent self-esteem problems. An intersectoral approach involving education, health, and community sectors is essential to promote psychological well-being during adolescence.
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Abbreviations
1. BMI
Body Mass Index
2. REDCap
Research Electronic Data Capture
3. CD-RISC
Connor–Davidson Resilience Scale
4. APGAR
Adaptability, Partnership, Growth, Affection, Resolve
5. GLM
generalized linear models
6. PR
prevalence ratios
7. CI
confidence intervals
8. VIF
variance inflation factor
9. USA
United States of America
10. NLSY79
National Longitudinal Survey of Youth 1979
11. OD
Odds ratio
12. RCSE
Relationship-contingent self-esteem
13. SD
Standard Deviation
Declarations
Ethics approval and consent to participate
A
The Research Ethics Committee of Universidad San Martín de Porres in Lima, Peru, reviewed and approved this study on March 21, 2023, under approval code Official Letter No. 348–2023 (01–3652300 Anexo 160 / etica_fmh@usmp.pe), confirming compliance with ethical standards for research involving human participants. An additional video file provides more details [see Additional file 1]. To safeguard privacy and confidentiality, data were gathered through anonymous questionnaires that did not request any identifying details. A
Informed assent was obtained from all adolescent participants, and written informed consent was provided by their parents or legal guardians before enrollment. Further details about this process are included in additional video files [see Additional files 2 and 3]. It was also assured that all collected information would be used solely for research purposes, without endangering participants’ integrity or well-being. A
Every phase of the study was carried out in line with the principles of respect, beneficence, and justice, as outlined in the Declaration of Helsinki and relevant national regulations.Consent for publication
Not applicable.
Availability of data and materials
The datasets generated and/or analyzed during the current study are not publicly available due to data confidentiality restrictions, but are available from the corresponding author on reasonable request.
Competing interests
The authors declare that they have no competing interests.
A
Funding
The authors declare that this study was self-funded.
A
A
Author Contribution
MV, MC, OG, LA, JV, AV, VV, and CP contributed equally to drafting the manuscript, data collection, and interpretation of the results. In addition, MC was responsible for translation, reference formatting, and table preparation, while MV performed the data analysis.
A
Acknowledgement
We express our sincere gratitude to Universidad Señor de Sipán, Universidad Peruana Cayetano Heredia, Universidad Privada Antenor Orrego, Universidad San Martín de Porres, Universidad Nacional de Piura, Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas, and Universidad Continental for their valuable institutional support.