Resilience among Women of Childbearing Age from Arequipa, Peru: Psychometric and Associative Analysis ()
1. Introduction
Resilience is a human quality that does not necessarily separate normal from deficient individuals, but is characteristic of people who adapt, and develop despite suffering personal, family, or social harassment or aggression; pathologies, tragic events, inhumane situations, aversion, repudiation, abandonment, hunger, etc. (Truffino, 2010) . It is defined as a capacity, attribute, or ability of the human being that implies effective adaptation to events, environmental changes, or adverse situations (Araujo & Centenaro, 2013) , the development of positive behaviors with socially acceptable responses (Campos et al., 2012; López & Calvete, 2016) , and continuous improvement and competitiveness (Rutter, 2012) . It is initiated during fetal life (Cyrulnik, 2005) by the dynamic interaction of risk and protection factors (Rutter, 2012) , individual, family, and social (Fernández & Bermúdez, 2015) .
The concept of resilience has evolved from a vertical or individual approach to a transversal approach aimed at collective health encompassing families, institutions, communities, cities, etc. (Soares & Oliveira, 2006) including sustainable human environments, ecological balance, ethical and equitable aspects (Rocha et al., 2009) . Hence, it is possible to speak today of resilient families, resilient workers, resilient teams, resilient universities, resilient communities, etc. (Barlach et al., 2008) . This approach explains the interaction of man with his environment through four nuclei: individual bio-psychological condition, interaction with other people, interaction with his environment and experience lived during his life cycle (Truffino, 2010) . For the purposes of our study, we focused on the latter to understand the resilience of women of childbearing age.
Resilience in women, as well as in men (González-Arratia & Valdez, 2013) , forms its foundations during pregnancy, from early interactions of the sensory channels (Cyrulnik, 2005) . During childhood resilience develops from favorable internal factors such as self-esteem and satisfaction with life (Rodríguez et al., 2016) , in adolescence by factors of identity and self-regulation of behavior, emotions and cognitive strategies (Diaz & Cadime, 2017; González-Arratia & Valdez, 2013) and by external factors, such as a good family environment (Amar et al., 2013; Pesce et al., 2005) , parental orientation (Gómez et al., 2015) and the presence of affective support from a family figure (González-Arratia & Valdez, 2013) . Family violence is harmful due to the accompanying humiliation, rejection and criticism; and in this sense, by promoting fear, aggressiveness, passivity, hyperactivity, depression, low self-esteem (Avanci et al., 2014; Lázaro, 2009) . Additional issues such as family overcrowding and poverty (Morelato, 2014) also contribute to these difficult behaviors and emotions
In adult women, resilience is presented as a capacity to recover from adverse experiences (Truffino, 2010) such as family violence that includes death threats toward the woman or children. There are a range of protective factors that support resilience in the face of these experiences, such as seeking help from formal or informal social support networks to cope (Fornari & Labronici, 2012; Gopal & Nunlall, 2017; López & Calvete, 2015) , as well as emotional, psychological, physical and spiritual practices that contribute to alleviating suffering and pain (Canaval et al., 2007) . In addition, self-sufficiency training (Rodríguez, 2013) , and adequate housing and income can assist in the exercise of resilience.
Resilience, defined as the ability to grow or develop in difficult contexts (Truffino, 2010) in women, supports mothering devoted to the love and care of children (Fornari & Labronici, 2012) , both in stable situations or in the face of adversity (López & Calvete, 2015; Gonzales et al., 2016) . Likewise, the so-called affective prediction by children avoids social loneliness and highlights satisfaction with family life (Martínez et al., 2017) , emotional intelligence in interpersonal relationships, and problem-solving, the ability to perceive, assimilate and manage one’s own emotions, as well as detect and interpret the emotions of others (Veloso et al., 2013) , talk about the trauma experienced in cases of violence in order to overcome it (Barrera, 2020; Fornari & Labronici, 2012; Lazo, 2021) , meaning of life (Smedena & Modenes, 2018) ; and other factors such as physical activity, rediscovering oneself, altruism, control over life, creativity, focusing on the present, a sense of humor, introspection, optimism, life projects and personal work, and related professional goals (Canaval et al., 2007; López & Calvete, 2015) .
Thus, research related to the protective behavior of women towards pregnancy and the unborn child that demonstrates an association between resilience and compliance with prenatal care and with the active participation by the couple and the surrounding social context (Ulloque et al., 2015) is scarce in our region as family violence is frequent (Arias et at., 2017; Castro & Rivera, 2015; Castro et al., 2017; Zeballos et al., 2020) . However, we believe that pregnancy should be focused on, since it is in this context that resilience can be promoted because various complications usually occur with implications for the moods of women both during and after pregnancy (Masías & Arias, 2018) . In fact, most of the reasons for consultation in health services by women in Arequipa city are related to prenatal and postnatal motives that sum 30% of them (Capaquira et al., 2020) , considering, also, that early sexual experiences and sociodemographic data interact to conditionate the current status of fertile or pregnant women about aspects such as number of pregnancies, number of births, number of abortions and number of deaths of unborn children during different stages of pregnancy (Arias & Rivera, 2021; Seperak & Rivera, 2018; Zeballos et al., 2020) .
But a problem related to the limited research on resilience, in general, and particularly in pregnant women, is the lack of duly validated instruments. Therefore, the objective of this research is to validate the Wagnild and Young Resilience Scale, which includes personal satisfaction, equanimity, good feelings by being alone, self-confidence and perseverance (Wagnild & Young, 1993) among fertile women in the city of Arequipa. In addition, we comparatively analyze the levels of resilience according to occupation, marital status, place of origin, grade instruction and mistreatment; and correlatively assess the dimensions of resilience with the data of the obstetric history of the patients. All this information is relevant, considering that women in Peru are constantly postposed with respect to educational, labor, social and health access or attention (Miró Quesada & Ñopo, 2020) .
2. Method
2.1. Research Design
The study is instrumental, insofar as the psychometric properties of the Wagnild and Young Resilience Scale (RS) are assessed; and associative, insofar as the associations between the study variables are analyzed at different levels, covering a descriptive, comparative, correlational, and predictive level (Montero & León, 2002) .
2.2. Sample
The sample consisted of 248 women of childbearing age who attended the Independence Health Center in the Alto Selva Alegre district of the City of Arequipa. The participants were between 15 and 49 years old (M = 28.6; SD = 7.9), of which 24.2% were married, 64.9% cohabiting and 8.5% single, and the remaining 2.4% widowed or divorced. Regarding the level of education, 57.7% had secondary studies, 31.5% had higher studies, 9.7% had primary studies and 1.2% were illiterate. The number of pregnancies was up to 7 children (M = 2.02; SD = 1.4), five births (M = 1.59; SD = 1.2), two abortions (M = 0.2; SD = 0.5), death up to one (M = 0.03; SD = 0.1); 52% of the participants state that their pregnancy was desired, however, 69% indicate that they suffered physical and psychological abuse during pregnancy. The sample was selected in a non-probabilistic way, using the quota sampling technique (Hernández et al., 2010) .
2.3. Instrument
The participants answered a demographic questionnaire, as well as the Resilience Scale (RS) developed by Wagnild & Young (1993) , which was later validated in Peru by Castilla et al. (2014) , on adolescents, youth and adults in the city of Lima. The scale is made up of 25 items with a 7-point Likert score (from 1, disagree to 7, strongly agree). The range of the scale scores is between 25 and 175 points. The higher scores are considered an indicator of greater resilience. As a result of this validation, four factors were obtained that present high levels of reliability (α = 0.906). A sociodemographic data sheet was also applied that collects information on age, level of education, occupation, marital status, area of origin, number of pregnancies, number of births, number of abortions, number of deaths, number of children alive, number of wanted pregnancies, mistreatment during pregnancy by the partner.
2.4. Procedures
Authorization was requested from the management team of the Independence Health Center of the Alto Selva Alegre district for its performance, and it was also approved by the Ethics Committee of the Research Directorate of the San Pablo Catholic University. Women of childbearing age participated voluntarily and signed an informed consent form prior to responding to the items on the instrument assessing resilience and sociodemographic information in the obstetrics area of the health center. In general, all patients were informed of the purpose of the study, the confidentiality of their data was guaranteed and they signed an informed consent form, although, in the case of minors, the consent of their parents was also required.
2.5. Analysis of Data
To explore the items of the Resilience Scale, the mean, standard deviation, asymmetry, kurtosis, and item test correlation were used, and multivariate normality was established through the Mardia coefficient (Mardia, 1970) . The data were submitted to confirmatory factor analysis with the statistical program AMOS version 23 (Arbuckle, 2014) , and the maximum likelihood method was used to adjust the multidimensional model of five latent variables. The model was verified through the goodness-of-fit measures, and the relative chi-square criterion χ2/df > 2 or χ2/df < 5 was used as a measure of fit (Schumacker & Lomax, 2010) . The Goodness of Fit Index (GFI) and the Comparative Fit Index (CFI) where values greater than 0.90 indicate a good fit (Byrne, 2010) . The root mean square error of approximation (RMSEA), where values up to 0.08 indicate a reasonable fit (Kline, 2005) . In relation to the standardized factor loads (λ), values ≥ 0.5 were considered adequate (Pérez-Gil et al., 2000) . To estimate the reliability of the observed scores, Cronbach’s alpha coefficient (α) was calculated with its confidence intervals (CI) (Dominguez-Lara & Merino-Soto, 2015) and the reliability for each factor was estimated with the coefficient omega (ω) (Ventura-León & Caycho-Rodríguez, 2017) . Likewise, the descriptive and inferential numerical data of the variable and its dimensions were analyzed according to a place of origin, desired pregnancy and mistreatment in pregnancy with the Student t-test for independent samples, the measures of the effect size (ES) were calculated with the Cohen’s d coefficient (Cohen, 1988) , the values for its interpretation are 0.20, 0.50 and 0.80 expressing a small, moderate and large TE; respectively (Ferguson, 2009) . The data referring to occupation, marital status and educational level were analyzed with the one-factor ANOVA, the effect size was calculated with the eta squared coefficient (η2), where the values of 0.01, 0.06 and 0.14 expressed a small, moderate and large TE; respectively. Likewise, to correlate age with the dimensions and the variable, Pearson’s r was used. Finally, a multivariate regression was estimated to determine the variables that explain resilient behavior in women of childbearing age.
3. Results
In the descriptive analysis of the items (Table 1), high arithmetic means and low variability are observed, except for item 20 (M = 5.09; SD = 1.5) which presents variability. None of the items presents high values of asymmetry and kurtosis (< ±1.5) (Yáñez et al., 1999) , so the distributions are not excessively non-normal. The assumption of multivariate normality found with the Mardia coefficient indicates a value of 168.4, which is less than 675.0, as suggested by Bollen (1998)
Note: n = 248; M = Mean; σ = Standard Deviation; g1 = Asymmetry; g2 = Kurtosis; c_item-test = item-test correlation.
based on the formula p (p + 2), where p is the quantity of observed variables indicate multivariate normality.
The internal structure of the Resilience Scale was established with the CFA, where 25 items were analyzed revealing five latent variables (Table 2). Goodness-of-fit indices indicate an acceptable model (χ2 = 580.419, df = 262; χ2/df = 2.215; GFI = 0.885; CFI = 0.903; RMSEA = 0.070 [CI 95% 0.062, 0.078]). The standardized factor loadings (λ) for the multidimensional model were significant (except item 11) and in the expected direction, the average factor loadings were 0.621 (Pérez-Gil et al., 2000) . Likewise, the correlations between the items on the scale were not greater than 0.9, which would indicate that there is no multicollinearity.
Figure 1 shows that the factor loads of the proposed model are greater than 0.50 (except item 11, λ = 0.39) and the Omega coefficients for each factor are acceptable (Personal satisfaction ω = 0.70; Equanimity ω = 0.65; feeling good alone ω = 0.66; self-confidence ω = 0.86; perseverance ω = 0.81) and the reliability of the entire test was α = 0.939 (95% CI, 0.928 - 0.950). The results confirm the 25-item model proposed by the authors (Wagnild & Young, 1993) .
Figure 1 shows that the factor loads of the proposed model are greater than 0.50 (except item 11, λ = 0.39) and the Omega coefficients for each factor are acceptable (Personal satisfaction ω = 0.70; Equanimity ω = 0.65; feeling good alone ω = 0.66; self-confidence ω = 0.86; perseverance ω = 0.81) and the reliability of the entire test was α = 0.939 (95% CI, 0.928 - 0.950). The results confirm the 25-item model proposed by the authors (Wagnild & Young, 1993) .
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Table 2. Internal structure of the Wagnild and young resilience scale.
Note: GFI = Goodness of Fit Index; CFI = Comparative Fit Index; RMSEA = root mean square error of approximation; AIC = Akaike Information Criteria.
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Figure 1. Confirmatory factor analysis of the Wagnild and young resilience scale in women of childbearing age.
Table 3 shows the levels of resilience in women of childbearing age, cuts presented by Novella (2002) , where it is observed that 46.8% (accumulated percentage) are at very low and low levels, however, there is 35.9% of participants who are at the high level.
Table 4 shows the differences in Resilience and its dimensions according to the occupation of women of childbearing age, where statistically significant differences are observed in the Personal Satisfaction dimension (F(3, 244) = 3.243; p = 0.013), where the participants whose occupation is various professions present higher resilience scores than the other occupations, however, the effect size is small (η2 = 0.051), which would indicate that these differences would indicate the possibility of committing a Type I error.
Table 5 shows statistically significant differences in resilience and its dimensions according to occupation, where married and widowed/divorced participants score higher than single and cohabiting. In addition, in the dimensions of fairness (η2 = 0.057), self-confidence (η2 = 0.055) and the Resilience variable (η2 = 0.058) there is an effect size close to being moderate.
When analyzing resilience and its dimensions according to place of origin, whether urban or rural (Table 6), statistically significant differences are observed in the dimensions of Personal Satisfaction (t = 2.414; p = 0.017) and Feeling good alone (t = 2.177; p = 0.030), where the participants from the urban area score slightly higher than those from the rural area, however, the effect size
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Table 3. Resilience levels in women of childbearing age.
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Table 4. Descriptive and inferential analysis of differences in resilience and its dimensions according to occupation.
Note: n = sample size; M = average; SD = Standard deviation; F = one-factor ANOVA; p = p value; η2 = eta squared (effect size).
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Table 5. Descriptive and inferential analysis of differences in resilience and its dimensions according to marital status.
Note: n = sample size; M = average; SD = Standard deviation; F = one-factor ANOVA; p = p value; η2 = eta squared (effect size).
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Table 6. Descriptive and inferential analysis of differences in resilience and its dimensions according to place of origin.
Note: n = sample size; M = average; SD = Standard deviation; t = student’s t; p = p value; d = Cohen’s d (effect size).
is small (d < 0.5) which would indicate a small difference between the participants from the urban and rural areas in the investigated dimensions.
Table 7 shows statistically significant differences in resilience and its dimensions according to the level of education, where illiterate participants and those with a higher level of education score higher than those with a primary and secondary level of education. However, these differences have a moderate effect size in the dimensions Feeling good alone (η2 = 0.071), Perseverance (η2 = 0.058) and in the Resilience variable (η2 = 0.063).
When analyzing resilience and its dimensions according to whether or not there was abuse during pregnancy (Table 8), statistically significant differences are observed in all dimensions and in the resilience variable (p < 0.001), however, these differences have a moderate effect (d < 0.8), that is, the participants who were abused present higher scores in resilient behaviors than those who did not receive abuse.
When analyzing resilience and its dimensions according to whether there was
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Table 7. Descriptive and inferential analysis of differences in resilience and its dimensions according to level of education.
Note: n = sample size; M = average; SD = Standard deviation; F = one-factor ANOVA; p = p value; η2 = eta squared (effect size).
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Table 8. Descriptive and inferential analysis of differences in resilience and its dimensions according to abuse in pregnancy.
Note: n = sample size; M = average; SD = Standard deviation; t = Student’s t; p = p value; d = Cohen’s d (effect size).
abuse during pregnancy (Table 8), statistically significant differences are observed in all dimensions and in the resilience variable (p < 0.001), however, these differences have a moderate effect (d < 0.8), that is, the participants who were abused present higher scores in resilient behaviors than those who did not receive abuse.
When analyzing resilience and its dimensions regarding whether the pregnancy was desired or not (Table 9), statistically significant differences are observed in all dimensions and in the resilience variable (p < 0.001), however, these differences have an effect small (d < 0.5), where it is evident that the participants who indicate that their pregnancy was wanted score higher than those who indicate that the pregnancy was not wanted.
When correlating resilience and its dimensions with age, number of pregnancies, births, abortions, death and number of children (Table 10), it is observed that there are no statistically significant correlations (p > 0.05), except for the
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Table 9. Descriptive and inferential analysis of differences in resilience and its dimensions according to desired pregnancy.
Note: n = sample size; M = average; SD = Standard deviation; t = Student’s t; p = p value; d = Cohen’s d (effect size).
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Table 10. Pearson’s correlations of age, number of pregnancies, births, abortions, deaths, and number of children with the dimensions of resilience.
*The correlation is significant at level 0.05 (bilateral).
self-confidence dimension that correlates with the age, positively low, that is, the older the participants of childbearing age, the greater their self-confidence.
A regression model was also proposed in order to assess which of the sociodemographic variables (age, job, partner, area of residence, level of education) and others related to pregnancy (number of pregnancies, number of deliveries, number of abortions, number of deaths, number of living children, number of wanted pregnancies, abuse during pregnancy by the partner), predict resilience, following the following equation:
. As can be seen in Table 11, the regression model was highly significant (p = 0.000), however, only two variables have positive predictive power on resilience. These variables are the level of education (p = 0.002) and mistreatment during pregnancy (p = 0.000); that is, those women who have a higher level of education and who have suffered abuse from their partners, are the ones with the highest scores in resilience.
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Table 11. Multiple regression and confidence intervals explaining resilience in women of childbearing potential.
4. Discussion
The Wagnild & Young (1993) scale, used in the research, is based on a theoretical model which postulates that resilience is developed through personal competence generated by self-confidence, independence, decision, invincibility, power, ingenuity, and perseverance, as well as by the acceptance of oneself and of life, generated by adaptability, flexibility, balance, and a stable life perspective. First, the psychometrical results indicated that the internal structure and reliability were adequate for its use among the Peruvian population of women, and the associative results of the research, indicated that 35.7% of women presented a high level of resilience, while 17.3% are at an average level, 18.5% at a low level and 28.5% at a very low level of resilience. This means that 47% of the sample does not have adequate skills to face and overcome daily difficulties or others derived from their situation as mothers or pregnant women, which could affect their mental health and, consequently, their physical health.
On the other hand, low or very low levels of resilience have been observed in 59.1% of adolescents, 47.4% of adult women and 40.7% of elderly women. In other words, in the women of childbearing age interviewed, higher levels of resilience were observed as they advance in age, which is consistent with the fact that resilience is a capacity that changes progressively beginning in the womb, then to the development of the mother-child-father affective bond, and, depending on the quality of interaction, envolves in the early years in a transcendental way, and later continues its development thanks to lived experience (Cyrulnik, 2005) .
Likewise, in adolescents, the average level of resilience was 131.1, which is similar to that reported by Ulloque et al. (2015) in Colombia, who evaluated 406 pregnant adolescents and found low levels of resilience in 43.2% and a mean of 125.0 for this variable; being risk factors for low resilience not feeling happy, not having family support and not having support from a partner. In this sense, Mendoza & Saldivia (2015) have indicated that lack of support and social prejudices are an important source of postpartum depression in women who have to face their pregnancy alone.
Thus, we can verify that the pregnant adolescent woman presents with less resilience and greater vulnerability than the adult woman, since it is perceived, that pregnancy hinders her development, conditions school dropout and subsequently hinders employment with the birth of the child. The adolescent enters motherhood with the consequent family and social stigmatization, implicit feelings of guilt, shame, low self-esteem and a certain impossibility of feelings, emotions, decisions and positive evaluations (Salinas, 2019) . This usually happens because early motherhood is often determined by limited family support (Álvarez et al., 2015; Amar et al., 2013; Pesce et al., 2005) , the absence or violent intervention of the father in the home; aspects that hinder the formation of adolescent self-regulation (Artuch et al., 2017) , poverty, marginalization, low educational level, family violence and sexual ignorance (Arias & Rivera, 2021; Catacora, 2011) . In contrast, some authors have identified some protective factors for early motherhood, such as good interpersonal communication, high self-esteem, having an elaborated and internalized life project, having a well-established internal locus of control, an elaborated sense of life, assistance to school and a high level of resilience (Páramo, 2011) .
According to our results, adult women have more and better resources to develop resilience, since, as other studies report, they are empowered by motherhood, the verbal expression of their experiences, spirituality (Canaval et al., 2007; Fornari & Labronici, 2012) , work and production capacity (González-Arratia & Valdez, 2013) , marital experience, resource management, decision making (Páramo, 2011) ; in addition, the support of internal supports in the family or external in their community context or social networks (López & Calvete, 2015) .
Regarding marital status, the average resilience for single women is 140.4, 134.4 for cohabiting women, 145.2 for married women, 148.5 for widows. In other words, married women and widows are the ones who have greater resilience than single women and cohabitants; data that coincides with the associations reported between the marital status of married women and greater economic power, higher level of education (Afifi et al., 2006) ; better health (Simó et al., 2015) ; on the other hand, in single mothers, there is a higher risk of presenting antisocial personality, drug abuse, post-traumatic disorders and dysthymia, in the same way widowed or divorced women in whom anxiety and depression are added (Afifi et al., 2006) . In a controversial way, in the research, a higher level of resilience has been observed among separated or widowed women, and it is that according to the approach of other authors, resilience is presented thanks to the greater incidence of adverse situations, the decrease in economic resources, the conflict with the ex-partner, the search for a new home, the lack of emotional support, the loss of contact with the children or having to face their upbringing alone (García & Solsona, 2011) .
The level of resilience according to origin reaches an average of 139.3 for the urban area and 134.2 for the rural area, with an insignificant difference in favor of the urban area. In this sense, the development of households in the rural area of other countries is similar to our rural and/or urban reality; finding organizational characteristics that generate personal resilience such as the functioning of patriarchal families, trigenerational coexistence, solidarity and support from parents to children, and from children to parents (Camareno & Del Pino, 2014) . This family support occurs in our species in a very particular way, due to the vulnerability that human beings have and that translates into proximity to the original and/or extended family until a few years after reaching adulthood (Barudy & Dantagnan, 2009) .
Regarding occupation, the resilience averages are 135.5 for housewives, 139.3 for women merchants, 142.5 for students, 146.6 for professionals, and 145.3 for women engaged in other trades. Thus, a higher level of resilience is observed among women who develop some productive activity, possibly due to the fact that resilience is nourished by the relationships established at work, reciprocity, labor empowerment, interpersonal relationships with bosses and co-workers; that contribute to raising morale and spreading a positive attitude, developing a greater sense of belonging (Villalobos & Budnick, 2018) , having more autonomy in decision-making, developing administrative and technical skills, as well as having more freedom (Gajardo, 2018; Urquieta & Tepichin, 2009) .
We note that 66.3% of the sample are housewives who do not contribute cash to the home, however they carry out a number of unpaid activities, generators of goods and services that contribute to family well-being and consumption that, if not carried out by part of the woman, should be provided by a third party in exchange for a fee. However, frequently these women are forced to work, especially in situations of single parenthood, households where the woman assumes the leadership, conditioned by the scarcity of resources, and at the same time freed from the inhibiting factor that the couple represents (Rodríguez & Munoz, 2017) .
The majority of the studied sample are mothers and for them resilience is a difficult construction process since they are in constant tension between motherhood, the couple and the private and public sphere, with questions about their role as mother and working woman, since the culture itself considers that its main priority is to be next to the children (Gajardo, 2018) , due to this women spend more hours caring for the home in relation to men, whether they work or do not work (National Institute for Women, 2007) .
Regarding the level of education, it was observed that illiterate women obtained a mean resilience of 146.0, those with a primary level 122.4, secondary level 138.9 and higher education 140.4. So, the higher the level of resilience is, the higher the degree of instruction is. However, that trend was contradicted as the highest resilience occurred among illiterate women, who are generally socially and economically disadvantaged (Miró Quesada & Ñopo, 2020) . Perhaps this finding was due to biases when marking the resilience scale, or because they have developed a solid support around their families. This result, however, must be investigated in greater depth, since it reveals an inconsitancy that is subject to other variables of study, that go beyond the purposes of this work.
Regarding the desired pregnancy, an average resilience of 141.7 has been found when the woman wants the pregnancy and 133.7 when she does not want it, thus evidencing the greater resilience when pregnancy is desired, and that leads to a greater exercise of autonomy and making decisions relevant to their lives, aspects that have been negatively related to postpartum depression and various mental disorders in pregnant women (Huamani & Serruto, 2017; Masías & Arias, 2018; Mendoza & Saldivia, 2015) . In this sense, the prevalence of unwanted pregnancy can rise to 49.8% for Latin America, and has been associated with factors of poverty, overcrowding, young age of the woman, being single, low income, not using MAC, having had other children, father’s reaction, previous abortions, low schooling, history of violence, etc. (Martínez & Otero, 1996) In addition, not wanting a child is associated with other risk behaviors for the baby, such as PAS consumption, opting for abortion maneuvers and the configuration of an inadequate attachment (Muñoz et al., 2015) .
Finally, an important fact is that the regression analysis revealed that the factors that have the greatest impact on resilience are the level of education and abuse during pregnancy; and that finding, in fact, indicated significant differences and moderate effect sizes at a descriptive level in all dimensions of resilience. Although the level of education, as stated above, contributed to the empowerment of women, their autonomy and independence in various aspects of life such as family, work, personal and professional (Gajardo, 2018; Rodríguez & Muñoz, 2017; Villalobos & Budnick, 2018) . It is noteworthy that the violence received during pregnancy has a positive effect on resilience, since most studies indicate that violence during pregnancy was associated, in a statistically significant way, with postpartum depression, anxiety, low self-esteem, sleep disorders, loss of appetite, etc.; both in meta-analytical studies that include research from various countries (Howard et al., 2013; Mendoza & Saldivia, 2015) , and in national studies (Aramburú et al., 2004; Escobar et al., 2009; Zeballos et al., 2020) . A tentative explanation for this finding could be that women victims of violence or who have been violated during pregnancy have developed resilient capacities, but more research is needed to clarify this conjecture.
We conclude that it is beneficial to promote resilience in both children and adolescents, but from the point of view of current obstetrics and under the social circumstances in countries like Peru, the transcendental meeting point is the mother-child binomial, to achieve the formation of a new being in a resilient and adequate space. We also think that the promotion of resilience can be offered to young people to improve their coping skills, their social skills, their self-esteem, their sense of life, their locus of control (preferably internal), etc. (Macedo et al., 2011) . Therefore, it is important to keep in mind that resilience requires certain protective factors such as guaranteed access to quality education, stable socioeconomic status, high levels of social inclusion, family support and understanding, bonds of attachment and affection offered by parents during the childhood; all of these aspects, which are basic for future emotional relationships, self-esteem and a sense of responsibility, etc. All of them aspects, which must be fully promoted by various professionals related to the obstetric specialty, with a preventive sense such as psychology and education (Artuch et al., 2017) .