Spanish Adaptation of the Inventory Brief Child Abuse Potential and the Protective Factors Survey

ORIGINAL RESEARCH published: 03 August 2021 doi: 10.3389/fpsyg.2021.705228 Frontiers in Psychology | www.frontiersin.org 1August 2021 | Volume 12 | Article 705228 Edited by: Laura Galiana, University of Valencia, Spain Reviewed by: África Borges, University of La Laguna, Spain Christophe Leys, Université Libre de Bruxelles, Belgium *Correspondence: Arturo Sahagún-Morales [email protected] Specialty section: This article was submitted to Quantitative Psychology and Measurement, a section of the journal Frontiers in Psychology Received: 04 May 2021 Accepted: 30 June 2021 Published: 03 August 2021 Citation: Sahagún-Morales A, Ampudia Rueda A, Chacón-Moscoso S, Sanduvete-Chaves S, Carro Pérez EH and Andrade Palos P (2021) Spanish Adaptation of the Inventory Brief Child Abuse Potential and the Protective Factors Survey. Front. Psychol. 12:705228. doi: 10.3389/fpsyg.2021.705228 Spanish Adaptation of the Inventory Brief Child Abuse Potential and the Protective Factors Survey Arturo Sahagún-Morales1*, Amada Ampudia Rueda1, Salvador Chacón-Moscoso2,3, Susana Sanduvete-Chaves2, Ennio Héctor Carro Pérez4and Patricia Andrade Palos1 1Facultad de Psicología, Universidad Nacional Autónoma de Mexico, Ciudad de Mexico, Mexico, 2Departamento de Psicología Experimental, Universidad de Sevilla, Sevilla, Spain, 3Departamento de Psicología, Universidad Autónoma de Chile, Santiago de Chile, Chile, 4Facultad de Derecho y Ciencias Sociales, Centro de Investigación y Desarrollo Tecnológico Aplicado al Comportamiento, Universidad Autónoma de Tamaulipas, Tampico, Mexico Child maltreatment is a public health problem with different consequences depending on the form of abuse. Measuring risk and protective factors has been a fertile ground for research, without involving instruments with sufficient evidence of validity. The aim of the study was to gather evidence of validity and reliability of the Inventory Brief Child Abuse Potential (IBCAP) and Protective Factors Survey (PFS) in the Mexican population. The instruments were translated into Spanish. In a non-probabilistic sample of 200 participants, the 7-factor model for the IBCAP [comparative fit index (CFI) =0.984; root mean square error of approximation (RMSEA) =0.067] and the 4-factor model for the PFS (CFI =0.974; RMSEA =0.061) were confirmed, showing adequate fit indices. Reliability was estimated and evidence of convergent, divergent, and discriminant validity was collected, controlling for effects of social desirability. We also report interpretability statistics of the scores. We achieved solid progress in the development of instrumentation that allows determining the presence or absence of protective and risk factors for child abuse. Keywords: validity evidences, reliability, norms and interpretation of tests scores, child abuse, protective and risk factors INTRODUCTION The World Health Organization defines child abuse as all forms of physical and/or emotional ill-treatment, sexual abuse, neglect, or negligent treatment or commercial or other exploitation, resulting in actual or potential harm to the health, survival, development or dignity of a child in the context of a relationship of responsibility, trust, or power [Organización Panamericana de la Salud (OPS) Oficina Regional para las Américas de la Organización Mundial de la Salud (OMS), 2003, p. 65], being the most widely used definition worldwide (Chahine, 2014; Weibela et al., 2017; Assink et al., 2018; Hayes and O’Neal, 2018; Cicchetti and Handley, 2019; Kaufman and Torbey, 2019; Marco et al., 2019; Sigad et al., 2019). Studies point to physical abuse as a form of child abuse, which is prevalent in the world (Kessler et al., 2010). However, estimates vary according to the measurement methodologies used. Regarding its prevalence, self-reported physical abuse records 226 victims per 1,000 boys and girls, with no differences in prevalence by sex (Stoltenborgh et al., 2013). Sexual abuse is the most studied form of child abuse and its prevalence by sex worldwide records 180 victims per 1,000 girls and 76 Sahagún-Morales et al. Spanish Adaptation of Two Instruments per 1,000 boys (Stoltenborgh et al., 2011, p. 89). There is little information on the prevalence of emotional abuse compared to physical and sexual abuse [Organización Panamericana de la Salud (OPS) Oficina Regional para las Américas de la Organización Mundial de la Salud (OMS), 2003]; however, the self-reported prevalence of emotional abuse is found to be 363 victims per 1,000 boys and girls (Stoltenborgh et al., 2012a). In prevalence by sex, 363 victims of emotional abuse are reported for every 1,000 boys and 384 for every 1,000 girls (Stoltenborgh et al., 2012a). On the other hand, Stoltenborgh et al. (2012b) reported that only 16 scientific studies have recorded the selfreported prevalence. The worldwide prevalence of child abuse is found to be 163 self-reported victims per 1,000 children in physical neglect, and 184 victims per 1,000 children in emotional neglect (Stoltenborgh et al., 2012b). In Mexico, the System for the Integral Development of the Family conducted in 2014, at the national and state level, an average of 152 children and adolescents for probable cases of child abuse, of which 35% correspond to abuse physical, 27% to neglect of care, 18% to emotional abuse, 15% to abandonment, and 4% to sexual abuse (COMPREVNNA, 2017). The same year, the National Institute of Statistics and Geography (INEGI) reported that 83% of the victims of child violence between the ages of 12 and 17 had as a perpetrator a person known as members of the household, partner, classmates and work, family, close friends, or acquaintances by sight (INEGI, 2016). Between 2010 and 2014, the main victims of child homicide were men aged from 15 to 17 years (INEGI, 2016). The consequences of child abuse vary according to the form of abuse; in addition, there are consequences due to multiple forms of abuse. The OMS (2016) reports that child abuse is a cause of stress and is associated with early brain development disorders. In adults who have been abused in childhood, there is a greater risk of suffering and committing acts of violence, suffering depression and obesity, consuming snuff, showing sexual highrisk behavior, unwanted pregnancies, alcohol and excessive drugs, among others behavioral, physical, and mental problems. Therefore, child abuse indirectly contributes to heart disease, cancer, suicide, and sexually transmitted infections (OMS, 2016). In general, abuse is a risk factor for a wide range of psychiatric disorders, substance abuse, behavioral problems, physical and emotional health problems, decreased well-being, propensity to commit child abuse, impaired cognitive and emotional development in children, feelings of hopelessness, low selfesteem, low self-esteem, low satisfaction with life, low sense of social support, and attachment style problems (Kessler et al., 2010; Stoltenborgh et al., 2011, 2012a, 2013, 2014; INEGI, 2016; Weibela et al., 2017; Kaufman and Torbey, 2019; Liel et al., 2019). Taking into account the different existing definitions of child abuse that hinder the collection of verifiable information, it is considered that the official figures understate (between 50 and 80% of cases of child maltreatment are not recorded) the real prevalence of abuse (Schwab-Reese et al., 2018), so it is important to study the associated factors, both in terms of increased risk and protective factors. Protective factors of child abuse are defined as “characteristics of a family or relationship that reduces the likelihood of child maltreatment” (Sprague-Jones et al., 2019, p. 122). In contrast, the potential factors for child abuse, or risk factors, are understood as the characteristics of a person, environment, or society that increase the probability of occurrence of child abuse (Aschengrau and Seage, 2019). Both protective and risk factors for child abuse include a wide range of environmental characteristics (physical and social), behaviors, thoughts, beliefs, and attitudes occurring in the context of a relationship, which regulate the behaviors of the members of this relationship, in such a way that they are more or less likely to commit, voluntarily or involuntarily, acts that mistreat a minor. Studies have identified recurrent risk and protective factors for child maltreatment (McCoy and Keen, 2014). Family functioning (Thornock et al., 2019), parental relationship (McCoy and Keen, 2014), preparation of parents in parenting strategies and parental knowledge (Albertos et al., 2016; Morrongiello et al., 2019), parental values (McCoy and Keen, 2014), the participation of the child in family activities (McCoy and Keen, 2014), social support (Cutrona et al., 1994; Piko, 2000), and even community environments and characteristics of the physical properties of the home (Labella and Masten, 2018) are some of the most important protective factors (McCoy and Keen, 2014). In terms of risk factors, poverty (Delgado, 2016), family stress (Musitu and Callejas, 2017), family and intimate partner violence (Henry, 2018; Lawson, 2019), among others have been reported (McCoy and Keen, 2014). Measuring risk and protective factors have been fertile grounds for research, without implying these instruments with sufficient validity evidence. In this case, we worked with the second edition of the Protective Factors Survey (PFS; SpragueJones et al., 2019) and the Inventory Brief Child Abuse Potential (IBCAP; Ellonen et al., 2019). The IBCAP is a self-report instrument developed by Ondersma et al. (2005) from the Inventory Child Abuse Potential (ICAI; Milner, 1986). It is answered using dichotomous items of agreement/disagreement. It is a brief inventory that includes 24 items for the risk factor, scales, plus nine items for the ICAI validity scales. Stability has been reported in the factors that make up the IBCAP, showing, in the US population (Ondersma et al., 2005), a structure of seven factors, which include: Distress, Family Conflict, Rigidity, Happiness, Feelings or persecution, Loneliness and Financial insecurity. Likewise, the version by Ondersma et al. (2005) maintains the scale of lies and random response (validity scales) of the ICAI. Although the IBCAP shows acceptable validity evidences in its different versions (Ondersma et al., 2005; Ellonen et al., 2019; Liel et al., 2019), more validity evidences are required that we will seek to collect in this study. For its part, the PFS was developed in 2005 by the FRIENDS National Center in collaboration with the Institute for Educational Research and Public Service at the University of Kansas (FRIENDS National Center for Community Based Child Abuse Prevention, 2021). The creation of PFS responded to the need for a reliable and valid instrument for the evaluation of child abuse prevention programs, given that at that time, there was no adequate instrument for measuring changes in multiple protective factors for child abuse and neglect (SpragueJones et al., 2019). The PFS has 20 items in 7-point Likert scale Frontiers in Psychology | www.frontiersin.org 2August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments and is designed for caregivers of minors, users of prevention of child abuse services. It has a traditional version (nonretrospective self-report) and a retrospective response version and measures the factors: (a) Family Functioning and Resilience, (b) Social Supports, (c) Concrete Supports, and (d) Nurturing and Attachment; in addition to items that indicate knowledge of the development of parenting and child together without enough features to speak of a latent factor. All factors have a good reliability (FRIENDS National Center for Community Based Child Abuse Prevention, 2020). Starting with the first PFS, a Spanish short version has been developed (for the Latino population residing in the United States, Conrad-Hiebner et al., 2015), and the second edition was also in retrospective and non-retrospective selfreport format (Sprague-Jones et al., 2019). Likewise, the relationship of PFS with instruments like the Perceived Stress Scale (PSS), the PRIME-MD Patient Health Questionnaire and the same IBCAP (Counts et al., 2010) has been tested. The second edition of the PFS has 29 items in 5-point Likert scale and measures the following factors: (a) Family Functioning and Resilience, (b) Social Supports, (c) Concrete Supports, (d) Nurturing and Attachment and (e) Caregiver/Practitioner Relationship, this last factor being the only one with poor internal consistency (FRIENDS National Center for Community Based Child Abuse Prevention, 2018); although there is a more recent version and with better levels of internal consistency (SpragueJones et al., 2019), this remains precisely as the one used in this study. In both the IBCAP and the PFS, the psychometric analyzes are limited to the internal consistency determined with the Cronbach’s Alpha coefficient and the Exploratory Factor Analysis (EFA). This aspect is remarkable because they are insufficient and inadequate to determine the reliability and validity of an instrument (Batista-Foguet et al., 2004; Agbo, 2010). Cronbach’s Alpha coefficient adequately estimates only the true internal consistency when the items are at least tau-equivalents, assuming that it is not tested and that it is practically impossible to fulfill, in addition to the fact that unidimensionality is required, which is not fulfilled in multidimensional scales (ContrerasEspinoza and Novoa-Muñoz, 2018). In the EFA, the euphemism for rotation (Batista-Foguet et al., 2004) is an arbitrary element in the decision about matching the items to the latent factor, leading to different interpretations of the same analysis according to the rotation method factor chosen. Another methodological flaw lies in assuming continuity in items that are inherently ordinal (Hoffmann et al., 2013), leading to an indiscriminate use of statistical methods involving measurement levels above the ordinal as Pearson’s correlation. Either the validation studies do not present evidence or they only present correlation matrices between variables of a nomological network without controlling for social desirability effects (Mikulic et al., 2016) or reliability attenuation effects (Domínguez-Lara, 2017) while that with regard to discrimination by item and discriminant validity, there are no indicators that demonstrate them. Finally, although both instruments have versions in different languages, there is no version that presents validity or reliability indices in the Mexican population, a crucial aspect considering that its use is common in child abuse prevention programs (Chacón-Moscoso et al., 2016, 2019). Therefore, this paper aims to gather evidence of validity and reliability of the IBCAP and PFS in the Mexican population, resolving faults present in the previous psychometric studies. MATERIALS AND METHODS IBCAP and PFS Spanish Translation Study Participants A non-probabilistic intentional sample was used. We worked with three translators whose native language is Spanish. The first translator is an expert translator, the second is a licensed psychologist with experience in working with children and parents, and the third is a Doctor of Psychology with experience in measuring the psychological evaluation. Everyone worked independently, without knowing the research objectives to maintain masked the process. Additionally, there was an evaluator of the translations who has experience in the development of psychological measurement instruments. Instruments Inventory Brief Child Abuse Potential The IBCAP (Ellonen et al., 2019) consists of 21 items divided into five factors: Loneliness and distress (LD, nine items), Impact of others (IO, four items), Family conflict (FC, three items), Rigidity (R, three items), and Financial insecurity (FI, two items). Here the Finnish version which responds by dichotomous items of agreement/disagreement and which has a total Cronbach’s Alpha of 0.781 was used for its adaptation. Protective Factors Survey The PFS (Sprague-Jones et al., 2019) consists of 29 items distributed into five factors: Family Functioning and Resilience (FFR, four items), Nurturing and Attachment (NA, seven items), Social Supports (SS, seven items), Concrete Supports (CS, eight items), and Caregiver/Practitioner Relationship (CPR, three items). It is a self-report instrument that is answered through 5-point Likert-type items with labels of 1 =not at all like my life, 2 =not much like my life, 3 =somewhat like my life, 4 = quite a lot like my life, and 5 =just like my life, for the FFR, NA, and SS factors respectively; of 1 =never, 2 =rarely, 3 = sometimes, 4 =often, and 5 =almost always for the CS factor; and 1 =strongly agree, 2 =agree, 3 =neither agree nor disagree, 4=disagree, and 5 =strongly disagree for the CPR factor. Here, the American version of Sprague-Jones et al. (2019) which explains 54.1% of variance and has Cronbach’s aalpha >0.750, was used for its adaptation. It was decided not to use the Spanish short version by Conrad-Hiebner et al. (2015) because, despite having been validated in the Spanish-speaking population, it only has 15 items, an aspect that limits the use of the tool in the evaluation at the individual level due to the high impact of the standard error of measurement (SEM) on short instruments (Sijtsma, 2011). Added to the above is the fact that the validation study was developed in the residents of the United States, a fact that implies important cultural differences within the population living in Mexico. Frontiers in Psychology | www.frontiersin.org 3August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments Format for Translation Translation format was developed with 21 items of the IBCAP (Ellonen et al., 2019) and 29 of the PFS (Sprague-Jones et al., 2019). This instrument is the one that was presented to the translators for the translation of all items. It consists of three columns, one where the original English version, one for the translators to place their version translated into Spanish and another column is placed where the translators make observations about each item if they deem it necessary. Procedure Translation Process Although the use of backward translation design is common, it has been documented that this design frequently generates translations in the target language (Spanish, in this case) that facilitate a reverse translation but do not maximize the suitability of the translation to the target population (International Test Commission, 2017). Considering this disadvantage, a forward translation design with multiple translators and subsequent revision was chosen (Muñiz et al., 2013; Hambleton and Patsula, 2014) because it allows for identifying and eliminating discrepancies between the different direct translations and creating a single version in the target language (International Test Commission, 2017). Translators were contacted via e-mail and the translation form was sent. Translations were performed over a period of 17–33 calendar days. The translators were asked to translate each item from English into Spanish, prioritizing meaning over literality. It was specified to all that the Spanish version should have the colloquial language. Translation Evaluation and Selection Process Concluded translations were compared with the original English version to evaluate and select the best translations. This task was performed by a psychologist with expertise in the subject of child abuse (author of this work) without prior knowledge of the identity of the persons who carried out the translation. He ruled out, one by one, each translation of the 50 items (150 translations in total) choosing the one he considered the best. The reviewers could choose one of the following options: Translation 1 is better, Translation 2 is better, Translation 3 is better, Translations 1 and 2 are better, Translations 1 and 3 are better, Translations 2 and 3 are better, All three translations are just as good. Item Writing Process From Translations With selected translations, drafts of the items of the IBCAP and PFS were developed. The writing consisted of using the terms of the selected translations to write a version that kept the meaning of the original item. At this stage, adaptations of the items to be applicable to people were performed with and without children, and to be answered using the same scale of responses (e.g., 7-point Likert scale). Also, sometimes several items were drawn from a single item because the original version contained more than an idea, something that could generate confusion among respondents. Study Results of Spanish Translation In the translation process, the IBCAP proceeded from 21 to 30 items. After translating the Finnish version of Ellonen et al. (2019), one of the translators recommended using the German version of Liel et al. (2019) as well. It was decided to comply with the recommendation because both the versions have the most recent validation studies up to the moment of doing this research, in addition to sharing 76.19% (16) of the items (the five items that were exclusively part of the German version were translated by the first author of this study focusing on the functional rather than on the literal equivalence and avoiding cultural references, idiosyncratic items, and inadequate response formats as recommended by the International Test Commission, 2017). Therefore, to the 21 items of the Finnish version of Ellonen et al. (2019), translated by the panel of translators (Muñiz et al., 2013; Hambleton and Patsula, 2014), the 5 items of the German version of Liel et al. (2019), translated by the first author of this paper, were added. The integration of both the versions resulted in a 7-factor theoretical structure in which the Impact of Others, Family Conflict, and Rigidity factors of the Finnish version remained intact, but the Loneliness and Distress factor (LD, nine items) was separated into Loneliness (L, four items) and Distress (D, four items) factors, in addition to the Unhappiness factor (U, three items) which was only found in the German version of Liel et al. (2019). Furthermore, when integrating both versions, the Financial Insecurity (FI) factor was made up of a single item, which is why three items were created directly in Spanish that complemented the factor; these items were developed by the first author of this paper. The resulting seven factors are consistent with the original version of Milner (1986). Translations and changes of the two original English versions of the IBCAP and preliminary Spanish version are detailed in Appendix A. In the case of PFS, it proceeded from 29 to 49 items, but the original 5-factor structure of Sprague-Jones et al. (2019) was maintained. It is also possible to find all the translation details and modifications made in Appendix A. Study of Evidence of Validity and Reliability of the IBCAP and PFS Participants An accidental non-probabilistic sample was used (Kerlinger and Lee, 2002). The sample size was determined in 200 participants because it is an amount necessary to obtain classic statistical items as well as a stable correlation matrix for the development of factor analysis (Downing and Haladyna, 2006). Because it was sought to work with a general population, the only inclusion criteria were that the participants were between 18 and 65 years and were residing in Mexico at the time of research. There were no misses in the sample during the development of the research. The sociodemographic characteristics of the sample are presented in Table 1 and the structural characteristics of the families are presented in Appendix B. Instruments Inventory Brief Child Abuse Potential Translated The translated version of the IBCAP developed in the previous phase was used. It is made up of 30 items distributed in Frontiers in Psychology | www.frontiersin.org 4August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments TABLE 1 | Sociodemographic characteristics of the participants (N=200). Characteristic f/M %/SD Characteristic f % Characteristic f % People in the same home 3.84 1.83 Maximum degree of study Total Monthly Income Age 31.79 13.12 Incomplete or in-process high school 3 1.5 Between $0 and 2,699 17 8.5 Sex Complete high school 22 11 Between $2,700 and 6,799 47 23.5 Men 44 22 Incomplete or in-process bachelor’s degree 75 37.5 Between $6,800 and 11,599 60 30 Women 156 78 Completed bachelor’s degree 59 29.5 Between $11,600 and 34,999 64 32 Children Incomplete or in-process specialty 2 1 Between $35,000 and 84,999 11 5.5 Yes 68 34 Completed specialty 4 2 $85,000 or more 1 0.5 Do not 132 66 Incomplete or in-process mastery 11 5.5 Marital status Complete mastery 14 7 Married 39 19.5 Incomplete or in the process PhD 7 3.5 Divorced 7 3.5 Complete PhD 3 1.5 Single 129 64.5 History of alcohol / drug abuse Free Union 22 11 Do not 186 93 Widower 3 1.5 Yes 14 7 f, absolute frequency; %, relative frequency; M, mean; SD, standard deviation. seven factors: Loneliness (L, six items), Distress (D, four items), Impact of Others (IO, four items), Family Conflict (FC, four items), Rigidity (R, four items), Financial Insecurity (FI, five items), and Unhappiness (U, three items). The response options were adjusted to seven points from 1 (Total disagreement) to 7 (Total agreement). Protective Factors Survey Translated The translated version of the PFS developed in the previous phase was used. It is made up of 49 items divided into five factors, which include: FFR, four items; NA, seven items; SS, 15 items; CS, 20 items; CPR, three items. The response options for the different factors were standardized on a 7-point scale from 1 (Total disagreement) to 7 (Total agreement), although in 13 items of the CS factor, the option, not applicable was also added. Balanced Inventory of Desirable Responding To control the effects of social desirability, the BIDR (Mikulic et al., 2016) was used. The BIDR consists of 18 items that make up a single factor, Social Desirability (SDes). It is a selfreport instrument that is answered by Likert-type items with seven points from 1 (False) to 7 (True). In this study, the Spanish version of Mikulic et al. (2016) was validated using Confirmatory Factor Analysis (CFA) with polychoric correlations (Holgado-Tello et al., 2008; Brown, 2015; Desjardins and Bulut, 2018) and estimation of unweighted least squares with robust standard errors and test statistic adjusted to the mean (ULSM; Shi et al., 2018). The results of the validation of the BIDR are presented in this section because they are not part of the central objective of the research, but correspond to a secondary analysis, that is necessary for the fulfillment of the objectives. It was obtained a reduced version (nine items) with good fit [χ2 (26) =38.605, p=0.053; χ2/df =1.485; CFI =0.987; TLI = 0.982; RMSEA =0.049, 95% CI (0.000, 0.090), p=0.466; SRMR =0.049] in a two-factor model (Self-deception and Printing Handling factors), such as that found in the Mexican population by Moral de la Rubia et al. (2012). In this study, evidence of convergent validity was obtained through the average variance extracted (AVE) of the Factors ≥0.500 (Fornell and Larcker, 1981; Cheung and Wang, 2017) as well as the factor loadings (λ)≥0.500 (Cheung and Wang, 2017); evidence of discriminant validity using the rbetween−factors ≤0.700 (Cheung and Wang, 2017) and the r2 betweenfactors <AVE (Fornell and Larcker, 1981); evidence of discrimination by item with the corrected totalelement correlation, (rtec)>0.200 (Abad et al., 2011); and evidence of total internal consistency and by factors with the coefficients, αOrdinal,ωOrdinal, and GLBOrdinal >0.700 (TrizanoHermosilla and Alvarado, 2016; George and Mallery, 2017, see full psychometric properties of Spanish version of BIDR-9 in Appendix C). Procedure For reasons of the quarantine due to the Covid-19 pandemic, the instruments were applied via Google Forms. Digital forms were distributed in 19 states of Mexico using Facebook Ads service (https://www.facebook.com/permalink.php?story_fbid= 104765114762260&id=104716831433755). This system allows sampling by establishing diffusion points in the states of the Mexican Republic with high population density or that are physically very distant from each other, such as Nuevo León and Yucatán, for example. Responses were collected over a period of 31 calendar days. The form included an informed consent and confidentiality statement. The study design was non-experimental, single-group, and cross-sectional. Data Analysis Validity Evidence Concerning the Internal Structure of the Instrument Confirmatory factor analysis taking the matrix, polychoric correlations (Holgado-Tello et al., 2008 Brown, 2015; Desjardins and Bulut, 2018) was used. The estimation method used unweighted least squares with robust standard errors and test Frontiers in Psychology | www.frontiersin.org 5August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments statistic adjusted to the mean (ULSM, Shi et al., 2018) due to the lack of multivariate normality (negative Mardia test, Porras, 2016). For the IBCAP-T a structure of seven correlated latent variables was tested, while in the PFS-T a structure of five correlated latent variables was tested. Correlated factor structures were tested in both the IBCAP-T and the PFS-T because the theoretical background suggests that the structures of both constructs are not independent (Ellonen et al., 2019; Liel et al., 2019; Sprague-Jones et al., 2019). Structures with the independent factors were also tested as rival models. The fit was evaluated using the following fit indices and interpretation criteria (Abad et al., 2011; Kline, 2011): Chi square/degrees of freedom (χ2/df) ≤3 (good fit); CFI ≥0.950 (good fit); Tucker– Lewis Index (TLI) ≥0.960 (good fit); RMSEA ≤0.060 (good fit) with 90% CI and p≥0.050, Standardized Root Mean Residual (SRMR) ≤.080 (good fit). Item Analysis The discrimination capacity of the items was determined using the corrected total-element correlation, (rtec)>0.200 (Abad et al., 2011) calculated on totals by factor. Furthermore, to know the contribution of each item to reliability, the reliability coefficient per item (ri) was calculated, expecting values ≥0.500 (Fornell and Larcker, 1981). Evidence of Validity Regarding the Relationship With Other Variables Evidence of convergent, divergent, and discriminant validity was collected. For convergent validity, the AVE of all factors was calculated, with values ≥0.500 indicative of convergent validity (Fornell and Larcker, 1981; Cheung and Wang, 2017). Also, convergent validity criterion was considered the factor loadings (λ)≥0.500 (Cheung and Wang, 2017). Finally, the pattern of correlations between the IBCAP-T and PFS-T factors was evaluated, expecting positive or negative correlations as theoretically expected (calculating the attenuation by reliability and controlling the effect of the SDes using partial correlations); Spearman’s Rho coefficient was used in this analysis due to the lack of normality (negative Shapiro–Wilk test). For discriminant validity, the rbetween−factors of each pair of factors of the same scale was calculated, where the values ≤0.700 being indicative of discriminant validity (Cheung and Wang, 2017). Also, the r2 between−factors were compared, indicating discriminant validity as <AVE (Fornell and Larcker, 1981). Reliability Evidence McDonald’s Omega (ω) and greatest lower bound (GLB) coefficients were used because they have been shown to be better estimators of internal consistency than Cronbach’s Alpha coefficient (α,Trizano-Hermosilla and Alvarado, 2016). The latter was also calculated because the coefficients, ωand GLB are not yet widely used; therefore, the coefficient, αallows comparison with other works; However, to reduce the impact of non-compliance with the αcoefficient assumptions (BatistaFoguet et al., 2004), the 95% confidence interval (CI) is reported. All internal consistency coefficients were calculated from polychoric correlation matrices (Holgado-Tello et al., 2008; Brown, 2015; Desjardins and Bulut, 2018), and the values >0.700 were considered good (George and Mallery, 2017). Finally, in a complementary way, the maximum and minimum split-half reliability was estimated (Abad et al., 2011) interpreting the scores with the same criteria. Norms and Interpretation of Test Scores As criteria for the interpretability of scores, the following statistics by factor were calculated: mean, standard deviation, skewness and kurtosis coefficients, Shapiro–Wilk test, and SEM. The programming language, R version 4.0.3 was used with lavaan package (R Core Team, 2020) and the software, SPSS v.24 (IBM Corporation, 2016) and Microsoft Excel Professional Plus 2016 (Microsoft Corporation, 2016) were used for the statistical treatment of the data. RESULTS Validity Evidence Concerning the Internal Structure of the Instrument Mardia test indicated no symmetry and kurtosis multivariate indicated both IBCAP-T (symmetry multivariate =4,106.741, p<0.001; kurtosis multivariate =22.255, p<0.001) and PFS-T (symmetry multivariate =2,668.980, p<0.001; kurtosis multivariate =21.461, p<0.001), for which the ULSM estimation was used. Confirmatory models of each are presented in Table 2. Table 2 shows that the IBCAP-T 7-correlated factor model was confirmed by eliminating five items, fitting better than the original model with 30 items and the modified independent model. In the PFS-T, the NA factor was eliminated, achieving a good fit with a model of 4 correlated factors and 25 items. The item deletion was performed by the modification indices. These allow decisions for re-specification of the models and reduce the size of the chi-square statistic by removing parameters (Hair et al., 1999; Escobedo-Portillo et al., 2016). Also, an additional criterion to remove items was to present correlated error variances and have a factor loading <0.40. These criteria were considered important because, together, they allow for identifying those items that may not have a relationship with the construct to which they theoretically belong and those items that have an exogenous source of variance (non-random variance unexplained by the construct). This model of re-specification procedure was chosen because it allows for a more parsimonious model to be generated (Brown, 2015). Therefore, the items with high modification indices and factor loadings <0.40 were eliminated one by one until an acceptable fit was reached in the different fit indices. As can be seen, the contrast of rival models (original vs. modified and correlated vs. modified independent) allows us to safely conclude that the data better fit the theoretical models which include both the elimination of parameters with residuals that covariate with each other (modified models eliminating variables) as a degree of covariation between the factors of the same scale (correlated models). This was true both for IBCAP-T and PFS-T; however, the elimination of NA factor in the PFST may indicate a differential functioning of the items in the Mexican culture, in such a way that Nurturing and Attachment Frontiers in Psychology | www.frontiersin.org 6August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments TABLE 2 | Goodness-of-fit indicators of the IBCAP-T and PFS-T confirmatory models with ULSM estimation and polychoric correlation matrix (N=200). χ2df p(χ2)χ2/df CFI TLI RMSEA (CI 90%) p(RMSEA) SRMR IBCAP-T M1 (30 items) 1,107.976 384 <0.001 2.885 0.968 0.964 0.097 (0.086, 0.109) <0.001 0.062 M2 (25 items) 9,555.120 275 <0.001 34.746 0.350 0.291 0.412 (0.404, 0.420) <0.001 0.338 M3 (25 items) 479.541 254 <0.001 1.888 0.984 0.981 0.067 (0.051, 0.083) 0.045 0.049 PFS-T M4 (49 items) 4,718.315 1,117 <0.001 4.224 0.759 0.747 0.127 (0.123, 0.131) <0.001 0.127 M5 (25 items) 1,138.266 275 <0.001 4.139 0.888 0.878 0.126 (0.118, 0.134) <0.001 0.128 M6 (25 items) 469.795 269 <0.001 1.747 0.974 0.971 0.061 (0.049, 0.073) 0.061 0.066 IBCAP-T, Inventory Brief Child Abuse Potential Translated; PFS-T, Protective Factors Survey Translated; M1, Original 7-factor model; M2, Modified Independent 7-factor model; M3, Modified Correlated 7-factor model; M4, Original 5-factor model; M5, Modified Independent 4-Factor Model; M6, Modified Correlated 4-Factor Model; CFI, Comparative Fit Index; TLI, Tucker–Lewis Index; RMSEA, Root Mean Square Error of Approximation; SRMR, Standardized Root Mean Residual; CI, Confidence Interval; p, p-value. are manifested differently from what is found in the context of the United States. It is worth mentioning that the variance explained by the factor should be taken with caution because they are correlated structures in which there may be an overestimation of the variance explained; However, the theoretical background of the IBCAP and the PFS suggests that a structure of correlated factors is the most expected one (Liel et al., 2019; Sprague-Jones et al., 2019). The factorial structures of the models with the best fit of the IBCAP-T and the PFS-T are presented in Figures 1, 2, respectively. Item Analysis In the item analysis, the results for the IBCAP-T and PFS-T are shown in Tables 3,4. Table 3 shows that the IBCAP-T items had discrimination levels that ranged between 0.258 and 0.943, and reliability levels between 0.326 and 0.944. In the PFS-T items, discrimination ranged between 0.473 and 0.848 and reliability ranged between 0.382 and 892 (Table 4). In both instruments, the levels of discrimination and reliability were good or excellent. For a list of items of both psychometric instruments in English and Spanish, see Appendix D. Evidence of Validity Regarding the Relationship With Other Variables Evidence of convergent validity (λand AVE of the M3 and M6 models) and discriminants (rbf and r2 bf) are presented in Figures 1,2, and in Table 5 for the IBCAP-T and PFS-T, respectively. Also, the correlations between the IBCAP-T and PFS-T factors (convergent and divergent validity) are presented in Table 6. It can be seen in Figures 1,2that the λmeet the criteria (λ>0.50) to assume convergent validity for both instruments (except 1 item from the IBCAP-T and 2 items from the PFS-T). Since the factor loadings are the correlation of the item with its latent factor, it is expected that higher values in λitems indicate convergent validity. Meanwhile, the AVE indicates the amount of variance explained by the construct such that the higher the AVE, the more it is argued that the items contribute to the measurement, i.e., high AVE values indicate the convergence of the items of a construct. In this regard, the AVE show that both for the IBCAP-T and the PFS-T, all factors showed an explained variance <0.50 (see Table 5). In terms of discriminant validity, the correlations between factors (rbf), of the same scale indicates the absence of collinearity, that is, the items of one factor measure the same as the items of a different factor. For this reason, although it is expected that there is a low or medium correlation between the factors that make up a scale, it is expected that these correlations do not reach a value high enough to cause confusion in the dimensions of the construct. In the same sense, the Squared correlation between factors (r2 bf) can be understood as the shared variance between the factors of the same scale, that is, between the dimensions of a construct. Thereupon, it is expected that the items of the same factor shared more variance with each other (AVE) than that they share with another factor (r2 bf), so values of r2 bf must be less than the values of AVE to assert discriminant validity. It can be seen in Table 5 for the IBCAP-T, that only three of the 21 rbf are slightly above 0.700 (see values below the diagonal marked with -); However, when comparing the r2 bf (observe the values above the diagonal marked with -) and the AVE, in each comparison, the AVE values are greater than the r2 bf, which indicates that the variance shared by the items of the same factor is greater than the shared variance between factors. In the PFS-T, all the discriminant validity indicators met the expected criteria. Regarding the correlations between the IBCAP-T factors and the PFS-T factors, Table 6 shows that the crude correlations adjusted for reliability increased in a range that goes from 2.70 to 17.89%, which can be interpreted as the percentage of the true correlation that is not registered due to the measurement error. On the other hand, the bias by SD showed, in most of the correlations, lower values than the crude correlations, which represents a high impact of the SD. In terms of convergent and divergent validity, median correlations were found with pvalues <0.05 and 0.01 even after removing the effect of social desirability, although factor 4 of the PFS-T only moderately correlated with factor 7 of the IBCAPT. In the same sense, factor 6 of the IBCAP-T only moderately correlated with factor 3 of the PFS-T. Frontiers in Psychology | www.frontiersin.org 7August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments FIGURE 1 | Modified correlated 7-factor model of IBCAP-T. The estimates of the presented factor loadings, variances, and covariances are standardized. Frontiers in Psychology | www.frontiersin.org 8August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments FIGURE 2 | Modified correlated 4-factor model of PFS-T. The estimates of the presented factor loadings, variances, and covariances are standardized. Reliability Evidence Tables 3,4show the reliability coefficients by factor. It is notable that the only coefficient that did not obtain a value ≥0.700 was the αcoefficient in factor 7 of the IBCAP-T. On the other hand, both in the IBCAP-T and PFS-T, the relationship α≤ω≤GLB was maintained. Norms and Interpretation of Tests Scores Tables 3,4also show that no factor had measures normally distributed. In the IBCAP-T, all the averages were <4 with SD close to 1, while the PFS-T showed means >4 in the FFR and SS factors, and <4 in the CPR and CS factor, the latter having the lower mean (M) and SD (M =1,458, SD =1,240). Finally, it is Frontiers in Psychology | www.frontiersin.org 9August 2021 | Volume 12 | Article 705228 Sahagún-Morales et al. Spanish Adaptation of Two Instruments Thornock, C. M., Nelson, L. J., Porter, C. L., and Evans, C. A. (2019). There’s no place like home: the associations between residential attributes and family functioning. J. Environ. Psychol. 64, 39–47. doi: 10.1016/j.jenvp.2019.04.011 Trizano-Hermosilla, I., and Alvarado, J. M. (2016). Best alternatives to Cronbach’s alpha reliability in realistic conditions: congeneric and asymmetrical measurements. Front. Psychol. 7:769. doi: 10.3389/fpsyg.2016.00769 Weibela, S., Vidal, S., Olié, E., Hasler, R., Torriani, C., Prada, P., et al. (2017). Impact of child maltreatment on meaning in life in psychiatric patients. Psychiatry Res. 251, 204–211. doi: 10.1016/j.psychres.2017.02.026 Conflict of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Publisher’s Note: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher. Copyright © 2021 Sahagún-Morales, Ampudia Rueda, Chacón-Moscoso, SanduveteChaves, Carro Pérez and Andrade Palos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Frontiers in Psychology | www.frontiersin.org 16 August 2021 | Volume 12 | Article 705228