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. 2022 May 10;15(4):1069–1080. doi: 10.1007/s40653-022-00458-1

Comparative Performance of the Resilience Inventory (IRES) and Resilience Scale-14 (RS-14) Spanish Versions Among Postpartum Adolescent Mothers

Oscar F Rojas Perez 1,✉, Sixto E Sanchez 2,3, Victor Cruz 4, Elena Sánchez 3, Elizabeth Levey 5,6, Bizu Gelaye 5,6,7
PMCID: PMC9684388  PMID: 36439676

Abstract

We sought to evaluate the psychometric properties of two resilience scales; the Resilience Inventory (IRES) and the 14-item Resilience Scale (RS-14) among Peruvian postpartum adolescent mothers. This cross-sectional study included 785 adolescent mothers who delivered at a maternity hospital in Lima, Peru. The Spanish versions of IRES and RS-14 were used to evaluate the properties of the measures. We examined reliability using Cronbach’s alpha. We used exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) to assess the construct validity and factor structures of the two scales. Both scales had good internal consistency (Cronbach’s alpha > 0.7). Correlation between IRES and RS-14 scores was fair (r = 0.53). The EFA results of both scales yielded a three-factor structure. EFA including all items from IRES and RS-14 yielded a six-factor structure. CFA results corroborated the original seven-factor structure for IRES and yielded measures indicating a good level of goodness of fit (comparative fit index of 0.93) and accuracy (root mean square error of approximation of 0.07). Overall, Spanish language versions of both the IRES and the RS-14 are reliable and valid scales for assessing resilience among Peruvian postpartum adolescent mothers. Additional research is needed to integrate culturally-specific traits into resilience measures.

Keywords: Adolescent, Peru, Psychometrics, Resilience

Resilience describes an individual’s capacity to respond to stress or trauma and successfully adapt despite challenging or threatening circumstances (Infurna & Luthar, 2017; Masten et al., 1990; Reich et al., 2010). Personal traits of resilient people, as described in the literature include, inner strength, competence, optimism, flexibility, and coping skills to effectively overcome adversity (Herrman et al., 2011; Wagnild, 2011). Additional features of resilience include self-esteem and self-efficacy to withstand or adaptively recover from stressors, while utilizing internal and environmental resources (Rutter, 1987; Wong & Wong, 2012). A given person’s process of resilience will vary throughout their life course, suggesting that the same individual may be more resilient to some stressful life events than others (Reich et al., 2010; Rutter, 2007). Similarly, how an individual responds to adversity will differ from person to person based on risk and protective factors (Drescher et al., 2012, 2014; Park & Slattery, 2014; Zakour, 2012), in addition to cultural background, values, and beliefs that shape methods of coping with adversity (Tweed & Conway, 2006). Yet, little has been written on the resilience process of individuals in low and middle-income countries (LMICs) to overcome adversity, where there are high rates of armed conflict, homicide, intimate partner violence (IPV), and social iniquities (World Health Organization, 2014). As a result, there is a need to understand resilience in LMICs with at risk populations, which can be done through the use of culturally responsive (sensitive and inclusive of different cultural practices, beliefs, and values) and psychometrically sound measures (Ungar, 2008; Ungar et al., 2008).

In the past two decades resilience has gained clinical relevance in medical (e.g., Mealer et al., 2012; Sarre et al., 2014) and psychology disciplines (e.g., Rutter, 1999), and globally (e.g., Mahmoud & Nahla Abd Elaziz, 2016; Nieto et al., 2018; Shrivastava & Desousa, 2016). There is also evidence to suggest resilience promotes psychological and physical well-being across different communities (Bonanno, 2004; Doherty & Clayton, 2011; Shrivastava & Desousa, 2016). Consequently, investigation on resilience continues to grow in an effort to better understand this multifaceted concept across various populations and cultures, including vulnerable populations such as adolescent mothers in LMICs where resources are often limited. Because of its implications for population health, it is critical to have reliable and valid measures to better understand processes of resilience across a range of cultures and contexts (Ungar, 2012).

Adolescent Pregnancy

An estimated 12 million girls between the ages of 15–19 and at least 777,000 girls under 15 years give birth each year in LMICs (Darroch et al., 2016; United Nations Population Fund, 2015). Studies have identified several factors contributing to adolescent pregnancies and birth in LMICs, which include but are not limited to pressure to marry and bear children at a young age (Kozuki et al., 2013; WHO, 2013). Early childbearing has been associated with social and emotional consequences such as stigma, rejection or violence by partner, parents and peers (Raj & Boehmer, 2013). Adolescent pregnancy and childbearing have also been linked to economic challenges and school dropout in LMICs (WHO, 2015). Adolescent mothers are not the only ones at risk of experiencing adversity, as research shows that psychiatric concerns in pregnant women and mothers are associated with psychiatric disturbance in their children (Lahti et al., 2017). However, resilience has been found to mediate the association between adversity and anxiety and depressive symptoms in adolescents (Goldstein et al., 2013; Scali et al., 2012). Thus, resilience in Peruvian mothers who are at high risk for physical violence and early experiences of abuse in childhood has implications for their health and the health of their children, and therefore requires further examination.

Resilience Measures

In general, many resilience measures have been conceptualized and developed on samples that are predominately White and the findings are then generalized to other cultural groups in LMICs without rigorous responsive evaluation of their applicability. These include, and not limited to, the Wagnild and Young Resilience Scale (RS; Wagnild & Young, 1993) Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003), Baruth Protective Factor Inventory (Baruth & Caroll, 2002), Resilience Scale for Adults (RSA; Friborg et al., 2003), and Brief Resilience Coping Scale (BRCS; Sinclair & Wallston, 2004). Many of these measures have been translated to different languages (e.g., Callegari et al., 2016; Jowkar et al., 2010) and their psychometric properties examined in different sociocultural contexts (e.g., Ali-Abadi et al., 2020; Levey et al., 2019). Of the mentioned instruments, the two most commonly used resilience measures globally are the RS-14 and the CD-RISC, with RS-14 (short version of the original RS) being the more widely used assessment (Ahern et al., 2006). However, a systematic review of 15 self-report resilience questionnaires, including the CD-RISC, RSA, BRCS, and the RS, failed to identify any of them as the “best available” (Windle et al., 2011), suggesting that resilience is a complex construct to evaluate since it may be culturally and contextually dependent (Nieto et al., 2018).

Although there is good evidence of the adequate psychometric properties of the above-mentioned measures, these scales were originally designed and developed in Western settings and in the English language. However, an individual’s culture and language may influence how they express their feelings and the resources available to them to cope with challenges (Nieto et al., 2018). A review of studies examining different measures of resilience, conducted by our team, found one resilience measure developed in a Latin American cultural context and in Spanish and validated with a sample of mothers outside the United States, the Resilience Inventory (IRES; Gaxiola Romero et al., 2011). The IRES was developed in Mexico and showed adequate psychometric properties in a sample of Mexican mothers of children six to 11 years old. Given language and cultural differences, there is a need to compare how people experience and display resilience within similar and across sociocultural contexts to better understand which resilience processes can be generalized across settings and which are unique.

Purpose of the Present Study

Given the lack of research on resilience among adolescent mothers in LMICs, we conducted the present study to compare the psychometric properties of the Spanish versions of the IRES and RS-14 among Peruvian postpartum adolescent mothers. Considering the lack of culturally responsive valid measures of resilience in Spanish specifically in Peru, we evaluated the construct validity of the two scales by assessing their factor structure. To further evaluate the performance of the measures, we investigated the concurrent validity between the two scales using factor structure and correlations. As a result of language and cultural differences, we were interested in seeing which traits of resilience U.S. developed and translated measures (English to Spanish; i.e., RS-14) assessed compared to measures developed in a Latin American context and in Spanish (i.e., IRES). Our aim is to further the body of literature of cross-culturally validated resilience measures in Spanish.

Method

Participants and Procedure

The current study was conducted as a part of the Teen Pregnancy Outcomes Maternal and Infant Study (T-PrOMIS) carried out from November 2016 to September 2018. The main objective of the T-PrOMIS was to examine the risk and protective factors associated with trauma exposure and mental health among adolescent mothers in Peru. Eligible participants were postpartum adolescent mothers (N = 785) between 14–18 years of age, who gave birth at Hospital Nacional Docente Madre Niño San Bartolomé in Lima, Peru. All participants provided written informed consent. The institutional review boards of the San Bartolome Hospital, in Lima, Peru and the Harvard T. H. Chan School of Public Health, Office of Human Research Administration, Boston, MA approved all procedures used in this study.

Data Collection

Each participant was interviewed in a private setting at the hospital two or three days after giving birth. The structured interview was designed to elicit information regarding sociodemographic and lifestyle characteristics, history of childhood abuse, symptoms of depression and anxiety, suicidal ideation, and resilience.

Instrument

We selected the IRES and RS-14 for several reasons. The IRES was conceptualized and developed in Spanish within a Latin American (i.e., Mexican) cultural context and validated with mothers, pregnant women, and college students. The RS-14 is one of the oldest and most widely studied measures of resilience.

The Resilience Inventory (IRES)

The IRES was originally developed and administered in Spanish and contains 24 items (Gaxiola Romero et al., 2011). The inventory covers seven dimensions of resilience: (1) positive attitude, (2) sense of humor, (3) perseverance, (4) religiosity, (5) self-efficacy, (6) optimism, and (7) goal orientation. Each item is rated using a Likert-type scale, from 1 = (“not at all”) to 5 (“completely”), with high scores associated with greater resilience. Resilience is calculated by summing participant scores, ranging from 24 to 120. The original study did not establish a cutoff score; the current study utilized a cutoff score of 54 because this was shown to be effective in another study conducted in a sample of pregnant women (Nieto et al., 2018).

The 14-Item Resilience Scale (RS-14)

The RS-14 is a widely used measure for assessing resilience (Wagnild, 2011), an abbreviated version of the 25-item RS (Wagnild & Young, 1993). It has been used in multiple population studies around the world and translated into other languages (e.g., Damásio et al., 2011; Nishi et al., 2010). Participants rate the degree to which they agree or disagree with each item on a 7-point Likert-type scale from 1 (“strongly disagree”) to 7 (“strongly agree”). Resilience is calculated by summing participant scores, ranging from 14 to 98. Levels of resilience are categorized as follows: < 56 very low resilience, 57–64 low resilience, 65–73 moderately low resilience, 74–81 moderate resilience, 82–90 moderately high resilience, > 91 indicates high resilience (Callegari et al., 2016; Pellerone et al., 2015).

Other Covariates

The structured questionnaires included participants’ sociodemographic and reproductive characteristics. Participants’ age was categorized as 14–15, 16–17, and 18 years. Other covariates examined included living status (living with parents vs. living with partner), difficulty paying for basic needs (very hard, hard, somewhat hard), race (Mestizo vs. other), smoking behaviors (before pregnancy, during pregnancy) and alcohol consumption behaviors (before pregnancy, during pregnancy).

Statistical Analysis

First, we assessed the internal consistency of the IRES and RS-14 using Cronbach’s alpha and inter-item correlations. Given the normal distribution, we used the Pearson correlation coefficient to assess the direction and strength of relationship between the IRES and RS-14 total scores. Second, we explored the factor structure of the two scales separately and combined using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The purpose for pooling the items together was to identify potential redundancy or differences in resilience traits across measures. Before conducting the EFA, we assessed the data and found they were suitable for performing factor analysis (Bartlett’s test of sphericity, p-value < 0.001 for both scales; and Kaiser–Meyer–Olkin measure of sampling adequacy, 0.95 for IRES and 0.84 for RS-14). Third, we conducted the EFA using principal component analysis (PCA) with oblique rotation. It is important to note that PCA does not account for measurement error. The scree plot, eigenvalues-greater-than-one rule, and a careful review of each factor solution were used to identify the number of meaningful factors. In addition to theoretical understanding and interpretation of factor solutions. Factor loading of 0.4 or greater we used in the factor designation. Fourth, to complement the EFA approaches and evaluate the fit of the factor models identified in the literature for our EFA, we implemented CFA using maximum likelihood estimation approach. The following fit indices were utilized to determine how well the models explained the observed data (Brown, 2006): likelihood ratio chi-square (χ2), Tucker Lewis Index (TLI), Comparative Fit Index (CFI), Root Mean Square Error of Approximation (RMSEA) along with 90% confidence interval (90% CI), and Standardized Root Mean Squares Residual (SRMR). Previously used fit indicators were employed to determine goodness of fit: Bentler’s Comparative Fit (CFI; Bentler, 1990) and Tucker Lewis Indices (TLI; Tucker & Lewis, 1973) > .90 (Bentler, 1990), Root Mean Squares Error of Approximation (RMSEA) < .07 (Steiger, 2007), and Standardized Root Mean Squares Residual (SRMR) < .08 (Hu & Bentler, 1999). All statistical analyses were performed using SPSS v25 (SPSS Inc., Chicago, IL, USA) and MPlus (version 8.3). Statistical significance was set to p-values < 0.05, and all test were two-sided.

Results

Participants Characteristics

A summary of selected characteristics of study participants is presented in Table 1. A total of 785 participants between ages 14 and 18 years (mean age = 17.1 years, standard deviation = 1.1 years) participated in the study. The majority of participants (68%) self-identified as Mestizo (mixed Amerindian and European descent), 44.5% resided with their parents, and 34.1% reported difficulty paying for basic needs. Approximately 16.6% of participants engaged in smoking behaviors prior to pregnancy, 2.5% during pregnancy; 28.0% endorsed alcohol consumption prior to pregnancy, and 3.4% during pregnancy.

Table 1.

Sociodemographic and lifestyle characteristics of the study population

Characteristics All participantsa
(N = 785)
n %
Age (mean ± standard deviation) 17.06 ± 1.12
Age (years)
14–15 91 11.6
16–17 309 39.4
18 376 47.9
Living with
Parents 211 26.9
Partner 349 44.5
How hard to pay for basics
Very hard 258 34.1
Hard 271 34.5
Somewhat hard 195 24.8
Mestizo ethnicity 534 68.0
Smoke before pregnancy 130 16.6
Smoke during pregnancy 20 2.5
Alcohol consumption before pregnancy 220 28.0
Alcohol consumption during pregnancy 27 3.4
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aDue to missing data, percentages may not add up to 100%

Reliability

Internal consistency of IRES gave a Cronbach’s alpha of 0.93. Correlation between the 24 items of the IRES and the total scores ranged from 0.45 to 0.74 (all p-values < 0.01). The Cronbach’s alpha for RS-14 was 0.75. The correlation between the 14 items of the RS-14 and the total scores ranged from 0.40 to 0.59 (all p-values < 0.01).

Correlation

The interfactor correlations for the IRES were significant and ranged from 0.44 to 0.70 (p-value < 0.01). The interfactor correlations for RS-14 were significant and ranged from 0.06 to 0.44 (p-value < 0.01), with the exception of the correlation between F1 and F2 (see Table 2). Pearson correlation coefficient for IRES and RS-14 scores was r = 0.53 (p-value < 0.01).

Table 2.

Intercorrelationns among factors

Scale and Factors F1 F2 F3 Total
IRES
F1 1
F2 0.70** 1
F3 0.50** 0.44** 1
Total 0.92** 0.87** 0.66** 1
RS-14
F1 1
F2 0.06 1
F3 0.44** 0.37** 1
Total 0.79** 0.67** 0.80** 1
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*p < 0.05; **p < 0.01; p < 0.001

Factor Analyses

The results obtained from the EFA for the IRES indicated a three-factor solution (Table 3). These factors explained 57.4% of the total variance. Factor 1 consisted of 10 items comprising six dimensions from the original model: coping, positive attitude, perseverance, self-efficacy, optimism, and goal orientation. Factor 2 included eight items from five dimensions from the original model: coping, positive attitude, sense of humor, flexibility, and religiosity. Lastly, Factor 3 consisted of three items comprising two dimensions from the original model: flexibility and empathy. Similarly, the EFA of RS-14 resulted in three factors. These factors explained 54.88% of the total variance. Factor 1 consisted of seven items comprising four characteristics of resilience: meaning and purposeful life, equanimity, self-reliance, and existential aloneness. Factor 2 included three items comprising two characteristics of resilience: perseverance and self-reliance. Finally, Factor 3 consisted of four items comprising three characteristics of resilience: meaning and purposeful life, equanimity, and self-reliance. We performed an EFA including all 38 items from both IRES and RS-14 (Table 4). It yielded six factors together explaining 58.04% of the total variance.

Table 3.

Factor loadings resulting from separate exploratory factor analysis for IRES and RS-14a

Scale and Items F1 F2 F3
IRES
1. I see the positive aspects of life and the things that happen to me 0.04 0.54 0.22
2. I look for support from others when I need their help –0.08 0.74 0.15
3. I maintain my sense of humor even during difficult situations 0.01 0.66 0.18
4. I try to understand why some people have hurt me –0.21 0.02 0.86
5. I understand that problems are part of life 0.06 0.17 0.59
6. I consistently try to improve my life 0.39 0.17 0.31
7. When I have problems I address them immediately 0.28 0.48 0.06
8. I try to spend time with people from whom I can learn something positive 0.56 0.19 0.09
9. I try to forgive the people who have hurt me –0.09 –0.17 0.84
10. I try to learning something positive, even from the problems I face 0.31 0.27 0.32
11. If I lose something or someone, I try to focus on what I still have 0.28 0.43 0.08
12. Despite my problems I try to find happiness 0.41 0.42 –0.01
13. My religious beliefs provide meaning to my life –0.22 1.00 –0.14
14. I am capable of smiling despite the problems I am having 0.37 0.33 0.11
15. Regardless of how difficult a situation is, I am able to confront it 0.49 0.42 –0.07
16. I have goals and aspirations in my life 0.98 –0.29 –0.07
17. I think the future will be better than the present 0.84 –0.20 0.07
18. I consider myself capable of resolving or overcoming the problems in my life 0.55 0.17 0.09
19. I am confident in myself in whatever I do 0.74 –0.37 0.20
20. For me, problems are like a challenge to overcome 0.54 0.31 –0.08
21. My religious faith helps me overcome my problems –0.17 0.99 –0.20
22. I continue to fight for what I want until I accomplish it 0.78 0.08 –0.14
23. I try to do everything possible to accomplish my goals and dreams 0.86 0.09 –0.25
24. I often believe that I will be successful in what I attempt to do 0.75 0.14 –0.18
% of Variance 44.10 7.65 5.65
RS-14
1. I usually manage one way or another –0.10 –0.02 0.87
2. I feel proud that I have accomplished things in life –0.12 0.39 0.56
3. I usually take things in stride 0.17 –0.03 0.64
4. I am friends with myself 0.48 0.02 0.16
5. I feel that I can handle many things at a time 0.03 0.59 0.24
6. I am determined 0.07 0.87 –0.05
7. I can get through difficult times because I’ve experienced difficulty before 0.62 0.11 –0.04
8. I have self-discipline 0.00 0.86 –0.12
9. I can usually find something to laugh about 0.85 0.09 –0.12
10. My belief in myself gets me through hard times 0.77 0.00 0.05
11. In an emergency, I’m someone people can generally rely on 0.79 –0.06 0.05
12. I keep interested in things 0.61 –0.11 0.13
13. My life has meaning 0.66 0.06 –0.08
14. When I’m in a difficult situation, I can usually find my way out of it 0.41 –0.12 0.42
% of Variance 30.71 16.61 7.56
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aTwo scale are analyzed in separate factor analysis. The extraction method was principal component factoring with oblique (promax with Kaiser normalization) rotation. Factor loadings > .4 are in bold

Table 4.

Factor loadings resulting from pooled exploratory factor analysis for IRES and RS-14a

Scale and Items F1 F2 F3 F4 F5 F6
IRES
1. I see the positive aspects of life and the things that happen to me 0.21 –0.11 0.35 0.22 –0.06 0.14
2. I look for support from others when I need their help 0.09 –0.12 0.46 0.12 –0.12 0.30
3. I maintain my sense of humor even during difficult situations 0.16 0.04 0.34 0.20 –0.11 0.15
4. I try to understand why some people have hurt me –0.13 –0.19 0.13 0.83 0.20 0.02
5. I understand that problems are part of life 0.15 –0.02 –0.03 0.61 –0.06 0.07
6. I consistently try to improve my life 0.49 0.04 –0.12 0.34 –0.14 0.00
7. When I have problems I address them immediately 0.42 0.06 0.16 0.09 –0.13 0.08
8. I try to spend time with people from whom I can learn something positive 0.60 0.07 0.03 0.10 –0.03 0.04
9. I try to forgive the people who have hurt me –0.04 0.18 –0.16 0.91 0.17 0.09
10. I try to learning something positive, even from the problems I face 0.40 0.14 –0.10 0.34 –0.13 0.17
11. If I lose something or someone, I try to focus on what I still have 0.31 0.22 0.03 0.12 –0.11 –0.06
12. Despite my problems I try to find happiness 0.53 0.10 0.30 0.01 0.07 –0.12
13. My religious beliefs provide meaning to my life –0.05 0.09 0.98 –0.05 0.13 –0.12
14. I am capable of smiling despite the problems I am having 0.52 –0.19 0.27 0.08 –0.18 0.10
15. Regardless of how difficult a situation is, I am able to confront it 0.59 0.00 0.26 –0.08 0.01 0.10
16. I have goals and aspirations in my life 1.03 –0.18 –0.17 –0.01 0.04 –0.16
17. I think the future will be better than the present 0.90 –0.15 –0.05 0.05 0.06 –0.10
18. I consider myself capable of resolving or overcoming the problems in my life 0.66 0.05 0.00 0.11 –0.08 0.06
19. I am confident in myself in whatever I do 0.66 0.10 –0.24 0.22 0.23 –0.17
20. For me, problems are like a challenge to overcome 0.63 –0.05 0.26 –0.11 0.06 0.08
21. My religious faith helps me overcome my problems 0.15 0.07 0.96 –0.11 0.09 –0.15
22. I continue to fight for what I want until I accomplish it 0.80 0.12 –0.11 –0.19 –0.02 0.11
23. I try to do everything possible to accomplish my goals and dreams 0.90 0.00 0.03 –0.29 0.04 0.08
24. I often believe that I will be successful in what I attempt to do 0.75 0.18 0.12 –0.17 0.14 –0.09
RS-14
1. I usually manage one way or another –0.09 –0.09 0.00 –0.05 0.16 0.89
2. I feel proud that I have accomplished things in life 0.07 –0.03 –0.25 –0.01 0.41 0.72
3. I usually take things in stride –0.01 0.16 –0.02 –0.08 0.07 0.68
4. I am friends with myself 0.08 0.55 –0.21 –0.11 –0.05 0.27
5. I feel that I can handle many things at a time –0.20 0.12 0.01 0.06 0.64 0.48
6. I am determined 0.07 0.04 0.06 0.12 0.87 0.15
7. I can get through difficult times because I’ve experienced difficulty before –0.03 0.73 –0.06 0.03 0.10 –0.06
8. I have self-discipline 0.15 –0.10 0.16 0.14 0.85 0.01
9. I can usually find something to laugh about –0.01 0.72 0.23 0.08 0.09 –0.16
10. My belief in myself gets me through hard times 0.05 0.68 0.16 –0.07 0.03 0.01
11. In an emergency, I’m someone people can generally rely on –0.11 0.70 0.28 0.03 –0.02 –0.12
12. I keep interested in things –0.15 0.43 0.27 0.07 –0.07 0.12
13. My life has meaning 0.12 0.64 –0.15 –0.04 –0.08 0.02
14. When I’m in a difficult situation, I can usually find my way out of it –0.03 0.40 –0.03 0.00 –0.08 0.41
% of Variance 34.31 7.64 6.08 3.82 3.30 2.89
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aTwo scales are analyzed in separate factor analysis. The extraction method was principal component factoring with oblique (promax with Kaiser normalization) rotation. Factor loadings > .4 are in bold

For the CFA, we estimated theoretical models informed by the literature and informed by the EFA for both the IRES and RS-14 (Table 5). The first CFA model for IRES assessed whether our data replicated the conceptual model posited by Gaxiola Romero et al. (2011), 10-factor scale with 24 items, which results suggested a poor to acceptable fit to the data: CFI = 0.88, TLI = 0.85, RMSEA = 0.08, and SRMR = 0.05. The second IRES model assessed a seven-factor structure with 16-items, suggested by Gaxiola Romero et al. (2011), with results indicating good fit to the data: CFI = 0.93, TLI = 0.91, RMSEA = 0.07, and SRMR = 0.04. The third IRES model was based on Nieto et al., (2018) 3-factor model with 16-items, which results indicated poor to acceptable fit to the data: CFI = 0.89, TLI = 0.87, RMSEA = 0.09, and SRMR = 0.05. To test the final IRES model, items were constrained to the respective factor based on the EFA results, suggesting poor fit to the data: CFI = 0.81, TLI = 0.79, RMSEA = 0.10, and SRMR = 0.09.

Table 5.

Model fit indices from separate confirmatory factor analysis for IRES and RS-14a

Model CFI TLI RMSEA SRMR
IRES
1 0.88 0.85 0.08 0.05
2 0.93 0.91 0.07 0.04
3 0.89 0.87 0.09 0.05
4 0.81 0.79 0.10 0.09
RS-14
1 0.48 0.38 0.12 0.10
2 0.77 0.72 0.08 0.07
3 0.95 0.91 0.06 0.04
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aCFI > 0.90, TLI > 0.09, RMSEA < 0.07, SRMR < 0.09

CFA confirmatory factor analysis, CFI comparative fit index, TLI Tucker-Lewis index, RMSEA root mean square error of approximation, SRMR standardized root mean residual

Next, we tested the RS-14 models identified in the literature and EFA. The first model assessed for the RS-14 was the one-factor model proposed by Wagnild (2009), which was a poor fit to the data: CFI = 0.48, TLI = 0.38, RMSEA = 0.12, and SRMR = 0.10. To test the second RS-14 model, items were constrained to the respective factor based on the EFA results, which yielded a poor to acceptable fit to the data: CFI = 0.77, TLI = 0.72, RMSEA = 0.08, and SRMR = 0.07. In reviewing the aforementioned models, we tested a third structure in which we eliminated items that cross-loaded and incorporated suggestions based on modification indices (Sörbom, 1989), which yielded a good fit to the data: CFI = 0.95, TLI = 0.91, RMSEA = 0.06, and SRMR = 0.04.

Resilience Ratings

The mean score of IRES was 99.18 (standard deviation = 12.35), while the mean score of RS-14 was 84.49 (standard deviation = 8.51; Figs. 1 and 2). The IRES identified 99% of participants with possible resilience traits (score ≥ 54). On the RS-14, 20% met criteria for moderate resilience (score between 74 and 81), 41% had moderately high resilience levels (score between 82 and 90), and 27% had high resilience (score of > 91). Additional RS-14 scores suggested that 9% of participants indicated their resilience was on the low end (score between 65 and 73), 1% reported low resilience (score between 57 and 64), and 0.6% indicated very low resilience (score of < 56).

Fig. 1.

Fig. 1

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Distribution of the total score of the Spanish-language version of the Resilience Inventory among study participants (n = 785)

Fig. 2.

Fig. 2

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Distribution of the total score of the Spanish-language version of the 14-item Resilience scale among study participants (n = 785)

Discussion

Overall, the Spanish language versions of the IRES and RS-14 demonstrated acceptable to high internal consistency and mixed construct validity, as a result of many poorly fitting models, when administered in this population of adolescent postpartum Peruvian mothers. The EFA results showed that the IRES had a three-factor model made up of items from all ten domains identified in the conceptual model by Gaxiola Romero et al. (2011). Similarly, the RS-14 resulted in a three-factor structure made up of five characteristics of resilience. Finally, factor analysis performed on the pooled items from the two resilience scales together yielded a six-factor model.

The factor structure of IRES in this sample was similar to the one proposed by Gaxiola Romero et al. (2011), assessed in mothers of children ages 6 to 11. Our CFA replicated the original seven-factor structure with 16 items. Factor 1, positive attitude, comprised of four items, reflected postpartum adolescent mothers’ ability to feel happy and see the positive side of things. Positive attitude in adolescents has been positively associated with academic achievement and controlled levels of stress (Malinowska-Cieślik et al., 2019). At the same time, it has been suggested that adolescent mothers with negative parental attitudes are more likely to experience lower levels of self-esteem (Bakiera & Szczerbal, 2018). Factor 2, sense of humor, contained two items reflecting the importance of maintaining a sense of humor during challenging times. Sense of humor has been positively associated with greater life satisfaction and high levels of psychological well-being (Southwick et al., 2005). Factor 3, perseverance, was made up of two items that related to the ability to achieve regardless of obstacles. Perseverance appears to be a common aspect found in other measures of resilience (e.g., Wagnild & Young, 1993). Factor 4, religiosity, was comprised of two items centered on faith. Broadly, research has found spiritual and religious practices to reduce the likelihood of developing depressive symptoms and increasing an individual’s ability to cope with adversity (Ozawa et al., 2017; Southwick et al., 2005). Among the few studies on religious coping in adolescents, results suggested that adolescent mothers highly involved in church were better adjusted, had higher occupational and educational attainment, and were at lower risk of abusing their children than less religious adolescent mothers (Carothers et al., 2005). Factor 5, self-efficacy, was comprised of two items that related to an ability to make decisions and solve problems. Similar to perseverance, self-efficacy appears to be a common aspect of resilience found in other measures (e.g., Friborg et al., 2003). Factor 6, optimism, included two items about future thinking. Among adolescents, optimism has been found to enhance mental health and health-related lifestyle changes (Logi Kristjánsson et al., 2010; Patton et al., 2011). Finally, Factor 7, goal orientation, was comprised of two items rooted in aspirations and attainment. Multiple resilience scales specifically for adolescents have included a similar factor (e.g., Hjemdal et al., 2006).

The factor structure of RS-14 in this sample was not consistent with the one proposed by Wagnild (2011) and other studies that have replicated the model (e.g., Surzykiewicz et al., 2019) with non-U.S. samples. There is also evidence to suggest that the factor structure of the RS-14 has been inconsistent in previous studies (e.g., Aroian et al., 1997; Nishi et al., 2010). The Spanish version of RS-14 in our sample showed a coherent three-dimensional factor structure with excellent fit indices. The four items on Factor 1 represented self-reliance and adaptability. Studies on self-reliance among adolescents have produced mixed results. For example, emotional closeness with one’s parents was associated with self-reliance, and at the same time self-reliance was found to be associated with avoiding close relationships and refusing to ask for help (Addis & Mahalik, 2003; Steinberg & Silverberg, 1986). Moreover, the one item for Factor 2 reflected determination, which has been associated with warm, close relationships with parents, particularly fathers (Suizzo et al., 2017). Lastly, the two items on Factor 3 reflected perseverance and flexibility. Perseverance appears to be a common characteristic across resilience scales, including the Pain Resilience Scale (Slepian et al., 2016) and the Resilience in Midlife Scale (Ryan & Caltabiano, 2009).

A cutoff score of 54 on the IRES identified 99% of adolescents as resilient, while the cutoff score of 74 for moderate resilience on the RS-14 meant 88% of adolescents met criteria. Given the differences in cutoff scores, it was difficult to assess agreement between the two scales. Despite the observed differences, our study results provided strong evidence that the IRES and RS-14 were comparable, but not identical, in identifying aspects of resilience. However, they captured distinct aspects of resilience. For example, the IRES was more likely to detect adolescents who identified religiosity while the RS-14 was more likely to detect adolescents who identified perseverance as the most important characteristic in the process of resilience.

Findings from our study must be interpreted while considering several possible limitations. First, the latent construct of resilience has been conceptualized as a multifaceted process influenced by factors ranging from context to personality characteristics (Herrman et al., 2011; Ungar, 2013; Ungar & Theron, 2020). Different researchers and empirical studies have contributed unique features of the resilience process, with no single measure fully capturing all aspects. In the past two decades, since the positive psychology movement, resilience has gained tremendous interest among researchers and clinical practitioners, yet, to date, there is no gold standard measure to assess the construct. We selected the IRES and RS-14 for several reasons. The IRES was conceptualized and developed in Spanish within a Latin American cultural context and validated in mothers, pregnant women, and college students. The RS-14 is one of the oldest and most widely studied measures, and has been validated in more than 20 countries and in 40 languages, including Spanish. It is also a short measure that can be completed in less than five minutes by most people. Second, resilience was assessed based on self-report. As a result, we cannot rule out the risk of participants responding in a socially desirable way due to the cultural value of simpatia (i.e., politeness and respect, discouraging confrontation or assertiveness), a value found among individuals from Latin America. Third, we conceptualized the study within the framework of classical test theory. It is suggested that further analysis comparing two or more scales needs to be extended and complemented with Item Response Theory approaches to evaluate the performance of items per racial and ethnic groups, age, and gender. Finally, due to the cross-sectional study design, it is possible that the validity of items from the two scales can be influenced by age, context, and delivery. A longitudinal design, beginning in early adolescence and going forward into the first five years of motherhood would provide more information about how adolescent mothers experience resilience across multiple stages of motherhood and life course.

Conclusion

Most studies of resilience have focused on children and adults within a U.S. context, with few studies of resilience among postpartum adolescent mothers in LMICs (e.g., Levey et al., 2019). Generally, pregnancy during adolescence has been found to be associated with low academic achievement, living in poverty, maternal anemia, postpartum depression, and adverse pregnancy outcomes (Fraser et al., 1995; Ganchimeg et al., 2014; Kingston et al., 2012; Maiden et al., 2014). Adverse pregnancy outcomes are worse for adolescents residing in LMICs, as a result of clinics that lack resources, homicide, conflict, and IPV (WHO, 2014). While adapting to motherhood is a tremendous challenge across contexts (Luthar & Ciciolla, 2015; Nelson, 2003), it can be more challenging for adolescent mothers in LMICs, where national and local resources are often limited, placing greater emphasis on the individual and family resilience factors (Theron et al., 2015; Tol et al., 2013). As a result, there is a need to not only compare individuals within a similar cultural context, but also cross-culturally, to better understand how a range of experiences and cultural processes influence an individual’s capacity to respond to adversity.

Overall, the Spanish-language versions of the IRES and RS-14 demonstrated good reliability, but mixed construct and concurrent validity in this population of Peruvian postpartum adolescent mothers. To the best of our knowledge, this study is the first to compare the performance of the Spanish-language versions of the IRES and RS-14 for assessing resilience in a LMIC with such a population and sample size. Furthermore, the current work can inform the development or adaptation of interventions needed to foster resilience in adolescent mothers, as their overall health and inner strength can influence their children. Future research on resilience should be mindful of language, culture and context factors, and how they can inform the utility of the IRES, RS-14, and additional assessment tools.

Declarations

Conflicts of Interest

All authors have no potential conflict, perceived or otherwise to report.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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