Resilience research indicates that exposure to a traumatic situation has differential impacts (Masten, 2001) as some people are little affected and maintain stable functioning (i.e. resilience) while others are stressed immediately after a problem and recover (recovery), some may suffer a decline in functioning and never recover (delayed), and others may show constant lower levels of functioning before and after the stressor (chronically low); Bonanno et al. (2011), Masten and Narayan (2012), and Infurna and Luthar (2017) refer to this responses as the different resilience pathways.

The typology approach suggests that people sharing the same personality type have similar profiles but are different when faced with individuals with unalike personality types. This approach allows for personality type identification through categorizations (Specht et al., 2014). Among the pioneers in the study of resilience typologies, Block and Block (1982) theorize three personality profiles: resilient, overcontrolled, and undercontrolled; furthermore, Robins et al. (1996) verified this three-dimensional pattern and indicated that children in the resilient group are characterized by being better adjusted; on the other hand, the overcontrolled group showed lower self-esteem and higher anxiety, while the undercontrolled group presented antisocial behaviors, higher aggressiveness, and lower social acceptance. Personality types have been analyzed with the Big Five personality test, which reports that resilient people have high scores in extroversion (Specht et al., 2014) and greater openness and responsibility (González-Arratia López-Fuentes & Valdez Medina, 2011); the under-controllers present low levels of scrupulousness and kindness; and the controllers show greater introversion and neuroticism (Steca et al., 2010). The inconsistencies thought these profiles might be due to ethnicity, age, educational level and the analytical procedure (Steca et al., 2010). These studies have used adult samples and do not offer enough evidence to assert their similarity with underage individuals.

Latent profile analysis (LPA) is a helpful approach to identify personality profiles and typologies, by examining response patterns (Ferguson & Hull, 2018). Chen and Tang (2021) using a LPA identified four resilient profiles: resilience, growth, moderate-combined, and high-combined in mourning people due to Covid-19; conversely, Masten (2001) demonstrated the differences between resilient and maladjusted people who have lived in a similar situation of adversity. Along these lines, the study by Suriá Martínez et al. (2015) on resilience factors and social skills that result in different combinations in the dimensions of resilience identifies four profiles: 1) high resilience profile, 2) low resilience profile with low social competence and high acceptance, 3) predominance of low self-acceptance and 4) predominance of social competence. These differential patterns suggest the need to design intervention programs in the development of social skills.

Studies with Latin American samples highlight the research of Saavedra (2011), which describes the resilience profile of students aged 14 to 19 years from vulnerable sectors of the seventh region of Chile. His findings distinguish different profiles; those considered highly resilient showed a greater capacity to follow reference models, generativity, and self-efficacy, which are indicators that this group “has the conditions to build learning around problem-solving” (p. 114). Meanwhile, those participants considered less resilient showed less capacity to achieve satisfaction, establish goals, and generate solid affective bonds.

Marenco-Escuderos et al. (2023) analyze different patterns or styles of resilience in Colombian pre-university students. Their results show four profiles: 1) Low resilience groups students with low scores in all dimensions of resilience; these low scores may indicate that they feel insecure about their abilities. This style is shared by 60% of the sample. 2) Resilient in process groups participants with intermediate resilience scores; it grouped 11% of the sample and differentiates them by dissatisfaction with their career choice, low motivation, and low social support. 3) Autonomous resilience groups participants with higher scores in resilience indicators such as identity, autonomy, satisfaction, learning, and generativity; self-confidence was the main characteristic, and they prioritized their resources to overcome academic obstacles, with 13% of the sample. 4) Resilient with network groups students who “showed high scores in all dimensions of resilience, with high social support, such as bonds, networks, models, and affectivity” (p. 237). They comprise 17% of the sample and are distinguished by interpersonal skills oriented to collaborative work and social support. Studies regarding the typology of resilience find differences between groups, which may be due to several factors, including the nature of the trauma, the individual response to traumatic events, the availability of resources such as social support, and changes over time (Shin et al., 2023).

The aforementioned reveals a differentiating scenario of resilience and how research has been directed particularly at identifying typologies of post-traumatic stress symptoms and other clinical entities (Achterhof et al., 2019; Chen & Tang, 2021; Jeffrey & Yamagishi, 2024). As well as the use of resilience profiles, which allow characterizing the intervention needs that are required in cases of Brazilian adolescents with problems with the law (Sette Galinari & Rezende Bazon, 2024), and in academic context such as what was reported by de Andrade et al. (2024) on resilience in university students during the pandemic.

Therefore, this leads to the need to examine the possibility of different resilience trajectories that help to comprehend symptoms, skills, and responsiveness to stressful situations to determine how to prevent and promote children's mental health. In Mexico, no research has investigated latent resilient profiles in children derived from COVID-19 confinement based on daily stressors (Horesh & Brown, 2020), depression (Yamamoto-Furusho et al., 2021), self-efficacy (Luszczynska et al., 2005), and subjective well-being (Lozano-Díaz et al., 2020). The opportunity to identify different shared patterns or profiles of behavior in personality research will be a landmark in the study of resilience in a Latin American scenary (Ferguson & Hull, 2018; Merz & Roesch, 2011); therefore, it is necessary to have empirical evidence regarding the heterogeneity of resilience expression, which will allow laying the foundations to foster it while considering the different needs in accordance to the identified profile to know the differences and similarities between people (Berlin et al., 2014, p.174).

To shed light even further, a child sample is necessary to fully understand resilience in the early life (Tonon, 2001), considering their context and specific stressors (Qvortrup, 1993). Since it is still scarce information about resilience in children during the COVID-19 pandemic confinement, the proposed research can induce insightful analyses on the matter.

Based on the above, the general objective is to identify latent resilience profiles (LPA) based on daily stressors, self-efficacy, subjective well-being (life satisfaction and positive-negative affection), and depression in children during COVID-19 confinement. The expectation is for the resilient profile to be characterized by displays of high self-efficacy, higher life satisfaction, high positive affectivity, and lower negative affection and depression despite daily stressors.

Method

Participants

This investigation is a non-experimental, cross-sectional study. A non-probability purposive sampling was used, with a total sample of 869 participants: 449 boys (51.7 %) and 420 girls (48.3 %), with an age range of 10 to 13 years (M = 11.1, SD = 0.76), who are students enrolled in eight different public institutions in State of Mexico, Mexico. The power analysis used was the t method, which is the most common procedure and “sufficient to perform a power analysis” (Murayama et al., 2022, p.7). The present study resulted on t= 1.96, df = 861, (1- β err prob) 1, effect size f ² = 1 using the G*Power 3.1.9.7 program (Erdfelder et al., 2007). The inclusion criteria were: being a student enrolled in the institution, being students who were in sixth grade at the time of the study, with an age range between 10 and 13 years old, who presented a signed letter of informed consent and assent. Two cases were excluded because they did not meet the criteria and did not complete the scales, leaving 869 participants in the sample. All participants are from central Mexico, 74.5 % indicated that they live with both parents, 21.6 % only with mother, 2.4 % only with father and to a lesser extent with other relatives (1.5 %).

Instruments

The sociodemographic data sheet

Includes information regarding age, sex, schooling, and school of origin prepared for this study.

The Children's Daily Stress Inventory (IIEC, in the original Spanish)

Consists of 25 items and three dimensions concerning health (12 items), school and peers (12 items), and family (17 items) (α = 0.70) and the test-retest reliability α = 0.78 (Huenca, 2013); the total scale was α = 0.76, ω = 0.76 for this study (Torres et al., 2009).

The Children's Depression Inventory (CDI)

Davanzo et al. (2004) version comprises 27 items, three response options, and two dimensions: dysphoric mood (17 items α = 0.86) and self-deprecating ideas (10 items α = 0.78); the scale for this research was α = 0.89 and ω = 0.89. (Kovacs, 1992).

The Resilience Scale

Consists of 32 items using a response format similar to a 5-point Likert scale; it includes three dimensions: internal protective factors (14 items, α = 0.80), external protective factors (11 items, α = 0.73), and empathy (7 items α = 0.78) obtaining an α = 0.93, ω = 0.93 overall (González-Arratia Lopez-Fuentes, 2016).

The Satisfaction with Life Scale (SWLS)

Atienza et al.’s (2000) version is comprised of five items and seven response options, is unidimensional with 58.6% variance (α = 0.87); this study presented an α = 0.83, ω = 0.83 (Diener et al., 1985).

Positive and Negative Affect Schedule (PANAS)

Is comprised of 20 items, 10 for positive affect (α = 0.86) and 10 for negative affect (α = 0.87), using a Likert scale response format with four options (Watson et al., 1988) it resulted in a coefficient of α = 0.82, ω = 0.82 for PA and α = 0.88, ω = 0.88 for NA.

The General Self-Efficacy Scale

Is a unifactorial scale with ten items and four response options (α = .87); the result for this research was α = 0.87, ω = 0.87 (Baessler & Schwarzer, 1996).

Procedure

The information was gathered after receiving authorization from the institution's authorities, the parents or guardians' informed consent, and the children's assent. the aforementioned measures were distributed online using Google Form during the second period of confinement (May to September 2021); the link to the questionnaires was sent to the parents' e-mail, and by clicking on it, the students could log in to answer it. The first display consisted of the informed consent of the parent/guardian and an instruction to explicitly ask for the assent of the child Finally, the answers were automatically sent to the researchers who oversaw their analysis.

This research is a risk-free study under the considerations of the ethical standards indicated by the American Psychological Association (APA, 2020) and the participation was voluntary, anonymous, and confidential. This project is registered (6337/2021SF) and approved by the Ethics Committee (2021/P05).

Data analysis

Cronbach's alpha and McDonald's omega were used to measure internal consistency as evidence of precision. A latent profile analysis (Berlin et al., 2014, p.174) was performed using the maximum likelihood estimation with the following parameters: 1) Akaike information criterion (AIC) and sample-size-adjusted Bayesian Information Criterion (SABIC), being the best model the one with the lowest AIC and SABIC values; 2) Lo-Mendell-Rubin likelihood ratio test (LMRT) and the bootstrap likelihood ratio test (BLRT); 3) Entropy, which evaluates the quality of individuals' classification into groups (Araújo et al., 2018), it ranges from 0 to 1, the value closer to 1 indicates a better classification; 4) Group size, which is recommended to be no less than 5% of the sample (Del Valle et al., 2019, p. 140-141).

3.1 Transparency and openness

Information was provided on how sample size, data exclusions, and study measurements were determined. The results were obtained using SPSS version 23 (IBM, 2016) and Mplus for LPA version 8.9 (Muthén & Muthén, 2017) were used.

Results

As a person-centered approach, the LPA emphasizes grouping individuals with similar characteristics rather than describing relationships among variables; LPA classifies individuals based on the likelihood of everyone being clustered in a particular profile (Orpinas et al., 2015). The LPA resulted in five profiles: the participants on profile 1 (moderate resilience) have the mechanisms to cope with adversity but require stimulation to develop their coping skills and abilities -this group has average scores in the evaluated variables and represents 26% of the sample; participants in profile 2 (vulnerable group) exhibit high scores on daily stressors, depression, and negative affect, as well as low resilience -this profile comprises 12% of the sample; participants in profile 3 (functional or homeostatic) depend on the protective mechanisms available at the time of adversity since it presents lower life satisfaction as well as high self-efficacy and resilience -it composes the lowest proportion of the sample at only 3 %; participants in profile 4 (resilient) showed high stress, depression, and higher life satisfaction -it represents 10% of the sample; finally, participants in profile 5 (well-adjusted or positive adaptation) have low scores for daily stressors, depression, negative affect and high positive affect, life satisfaction, self-efficacy, and resilience; they show no signs of maladjustment and comprise most of the participants in the sample at 49% (Table 1).

Table 2 shows the means and standard deviations for every profile, the classification probabilities for most class membership by profile, and percentages given are within the profile. The Figure 1 shows the chosen solution based on interpretability and statistical significance.

Discussion and Conclusions

This research aimed to analyze the latent profile of resilience using the following variables: self-efficacy, life satisfaction, positive-negative affect, daily stressors, and depression in a sample of schoolchildren during the period of confinement. Based on statistical significance, a model of five profiles is supported. The final model reveals the relationships between variables that generate a pattern that defines the profile (Del Valle et al., 2019; Soriano & Monsalve, 2019). Therefore, it is confirmed that resilience has different trajectory patterns, as Infurna and Luthar (2017) suggest, since not all dimensions of resilience have the same weight in the development of this strength (Gifre et al., 2010; Sette Galinari & Resende Bazon, 2024).

Profiles 4 and 5 obtained in this study are similar to the patterns observed by Merz and Roesch (2011) as a well-adjusted or well-adapted profile, which consists of higher emotional stability, sociability, and self-control, as well as with the resilient subtype described by Herzberg and Roth (2006) which "allows them to thrive despite environmental stressors" (Merz & Roesch, 2011, p. 6). Specifically, profile 4 presents better stress management and less depression, which are indicators related to optimal functioning and mental health (Agudelo Hernández et al., 2023; McCrae & Costa, 1991); this type of profile is associated with a successful adaptation to different life areas (Donnellan & Robins, 2010). Moreover, this profile corresponds to 10% of the sample, which is similar to the proportion reported by Chen and Tang (2021), suggesting a current indicator of the prevalence of low resilience during the pandemic (Janitra et al., 2023).

Profile 3 has a tendency for lower scores in life satisfaction, corresponding to 3% of the sample. It is recognizable that many of the everyday life experiences conditioning life satisfaction were limited during the pandemic, which resulted in low levels of satisfaction in the child community of Barranquilla, Colombia, due to the pandemic, academic demands, not being able to meet needs such as food, play, lack of economic resources, and poor socialization (Albor-Chadid et al., 2022). This tendency for low satisfaction may be because children do not have enough tools to resolve interpersonal conflicts yet (Baird et al., 2010; Verdugo & Sabeh, 2002); however, relying on a different point of view, this low satisfaction may be due to schoolchildren within this profile denoting feelings of unhappiness with the current situation, since they are not able to satisfy their desires as expected, which may be a temporary situation and that in some way this nonconformity may become a motivating factor or stimulus for personal development and growth. It is required to analyze the effect of the multiple psychosocial variables that have an influence on life satisfaction (Alfaro et al., 2016). In this context, it is crucial to note that life satisfaction is linked to both internal elements from their world perception and daily life (Várguez Pasos, 2023) and must also be seen within the framework of each culture (Diener, 2009) since “subjective well-being and its expressions cannot be understood outside the context of a particular culture or subculture” (Anguas Plata, 2005, p. 179). In addition, the fact that subjective well-being depends on various factors such as family, health, interpersonal relationships, age, gender, education, and income, among others (Carrillo Punina et al., 2016; Díaz-Loving et al., 2022) leads to the need for further analysis in these age groups.

These results provide the possibility of understanding the different paths towards resilience as indicated by Infurna and Luthar (2017), which leads to considering a first approach to the characterization of resilience and analyzing the possible effects of confinement on the children's experience (Tran et al., 2023); therefore, thinking in the application of differential intervention strategies (Marenco-Escuderos et al.,2023; Núñez et al., 2021; Sette Galinari & Resende Bazon, 2024; Suriá Martínez et al., 2015).

Covering the heterogeneity of resilient profiles can be complex, and using the LPA allowed us to simplify its understanding; however, it is necessary to keep in mind the objective of the study, as well as the possible biases in the measurement regarding a likely tendency towards social desirability, resulting in an “overestimation of individuals proportion in the classes interpreted as resilient” (Specht et al., 2014, p.34).

The profile number determination was done empirically, allowing us to guarantee the identification of relevant profiles. In addition, the findings of this research constitute a first approximation of the number of empirically and theoretically plausible types; meanwhile, the solution reflects the differences between the participants on the kind of differentiated profile but with calmness, above all. However, it is necessary to analyze whether this structure can be stable in both adolescence and adulthood since maturing processes may manifest in a different type of stress response, and empirical evidence is necessary to assert whether these typologies are different between men and women.

To our knowledge, this research is one of the few studies in Mexico to identify resilience profiles in children according to variables that are indicators of psychological well-being and distress. Thus, the present study contributes theoretically to consider resilience as a multidimensional construct (González-Arratia Lopez-Fuentes & Torres Muñoz, 2022) constituted by personal, social, and contextual factors, both internal and external, which an ecological perspective assumes that when faced with a certain amount of levels or risk factors, protective factors are activated, resulting in a better adjustment in the face of adversity (Barcelata, 2015).

Regarding the practical contribution of our findings, they focus on educational and health contexts; in the former, teachers or other education professionals use them to be alert to the presence of risk factors, for example, high levels of stress and depression, which can result in school and academic difficulties (e.g., low motivation for learning and behavioral problems). Similarly, resilience identification within the educational environment will allow for soft skills and social and vocational competencies currently in a post-pandemic scenario (Quezadas Barahona et al., 2023). Secondly, the identification of profiles with different patterns generates the need to establish specific interventions, from first-level interventions that allow early prevention aimed at increasing emotional well-being, in other cases, it will be necessary to identify psychological disorders and implement strategies to promote mental health (Folke et al., 2019; Jeffrey & Yamagishi, 2024; Sette Galinari & Resende Bazon, 2024; Shin et al., 2023).

Regarding the specific needs, the participants of profile 2 vulnerable, would benefit from the intervention aimed at the development of coping skills in the face of stress, which is proposed from the cognitive behavioral approach so that from cognitive restructuring it allows them to reduce the management of negative emotions and depression. In the case of profile 3, it is considered that the intervention would be aimed at increasing well-being, which is suggested to be from Positive Psychology, which are aimed at improving well-being and growth through the promotion of positive emotions, personal strengths, and optimism (Bohlmeijer et al., 2017).

In general, the differentiation of these profiles demonstrates the variety of responses to daily stress, the various internal resources (life satisfaction, positive emotions, self-efficacy) and sensitivity to events that can trigger mood disorders (depression) in children, so to understand the effect of traumatic events, and we need to identify protective and risk factors due to the multidimensional and dynamic nature of resilience.

Limitations and Future Directions

As this investigation is a cross-sectional study, it is necessary to follow up on the recovery of those cases identified as vulnerable groups and their different evolutions. The non-probabilistic sampling does not allow the generalization of findings; hence, caution is recommended in their interpretation. It must be recognized that the pandemic posed various challenges to children, and these changes might induce different coping and recovering response patterns when facing confinement. We think that this is an important stage to identify different resilience patterns in Latin American children. We also identified that our methodological approach has some backdraw, in terms of generalization. First, children did not response themselves directly, but by intermediation of their parents/guardians. Second, we only have a static picture of the resilience profile; to get a more stable results, it will be compulsory to use a longitudinal sample to identify the stability of the profile. Additionally, it is necessary to identify the resilience profiles between boys and girls, as these may be similar, as proposed by Álvarez-Voces and Romero (2024), or there may be differences, which would be the direction of a future study.

It is necessary to highlight that the typologies were based on the variables evaluated, so it would be important to analyze the profiles in relation to other behavioral, cognitive, and affective variables that allow us to broaden our understanding of the multidimensionality of child resilience. Nonetheless, our results contribute to the theorization and characterization of resilience profile in Mexico and a Latin American sample and to consider that the study of resilience involves a multidimensional analysis and not in isolation (González Arratia Lopez Fuentes, 2016).

Acknowledgments

We would like to thank the authorities of the different institutions and the participants in this study for their support. This study received specific funding from public sector agencies, commercial or non-profit organizations.

References

Notes

^* Research article. Data will be made available on request. Authors declared none-conflict of interests.

Author notes

^aCorrespondence author. Email: nigonzalezarratial@uaemex.mx

Additional information

How to cite: González-Arratia López-Fuentes, N. I., Domínguez Espinosa, A. C., & Torres Muñoz, M. A. (2025). Latent resilience profile in schoolchildren. Universitas Psychologica, 24, 1-13. https://doi.org/10.11144/Javeriana.upsy24.lrps

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