Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Abstract

Parental competencies constitute core components of family support initiatives. Although there are self-reported measures to assess parental competencies among the Spanish-speaking population, few instruments applicable to families at psychosocial risk, from a comprehensive understanding of said competencies, have been rigorously validated. The main aim of this study was to develop and validate an instrument to measure parental competencies with caregivers that benefit from family support initiatives in the child welfare setting. Over an initial version of the Interview for the Assessment of Parental Competencies (ECP-12), we conducted an expert judgment and analyzed the internal structure of the instrument using exploratory and confirmatory factor analysis (EFA, CFA), exploratory structural equation modeling (ESEM), reliability analyses, and validity evidence based on relationships with other variables. The results supported an ESEM bifactor model comprising 53 items, which proved to be valid and reliable for assessing 12 parental competencies and the overall construct.

Keywords

parental competencies positive parenting validation scale development factor analysis

A positive and responsible exercise of parenting requires a broad set of parental competencies, as well as the ability to reflect on one’s own parental role, which are aspects that are not developed by everyone satisfactorily without formal support (Daly et al., 2015). Recommendation 19 Positive Parenting Support Policy took on board this assumption and encouraged governments to create legislative, administrative, and financial measures to promote the best possible conditions for positive parenting, as well as to support parents in their childrearing tasks through the provision of family support programs, particularly for those at psychosocial risk (Council of Europe, 2006). In this line, family support initiatives aimed at promoting parental competencies have increased significantly during the last years (Jiménez et al., 2019).

Parental competencies refer to the set of capacities that allow parents to meet the developmental needs of their children in an adaptive and socially acceptable way (Rodrigo et al., 2009). This definition reflects a multidimensional and broad understanding of competence construct. Thus, it is understood that a competent exercise of parenting includes behavioral, emotional and cognitive components (Coleman & Karraker, 2000) related to educational skills and personal resources (Hoghughi, 2004). Moreover, such competent exercise is not limited to a specific and isolated parental action, but it implies an adequate parenting exercise sustained in time and in different situations (Conley, 2004).

Relevance of parental competencies is widely recognized from an ecological-transactional perspective of parenting in both assessing and intervening with families (Bornstein et al., 2022). Nevertheless, there is no clear and agreed framework about the dimensions that integrate this construct. The dimensions addressed are different depending on the purpose of the assessment of parental competencies (e.g., decision-making processes or family support interventions) (Azar & Cote, 2002) and whether they come from clinical psychology or the field of social work (White, 2005). Despite these differences, the most analyzed dimensions of parental competencies are those necessary to meet the physical, emotional and social needs of the children, that is, skills related to childcare, control and stimulation (Hoghughi, 2004). In the field of child welfare and family support, the parental beliefs, the self-efficacy perception, the parenting practices and the characteristics of the parent–child relationships are the most studied contents (Barudy & Dantagnan, 2010; Budd, 2005; Conley, 2005; Woodcock, 2003). In a recent systematic review about the specific dimensions that are used to assess the construct of parental competencies, we identified three general domains: personal competencies (e.g., parental satisfaction, knowledge and use of resources, beliefs and expectations about the child’s development, self-esteem), interpersonal competencies (e.g., parental practices, co-parenting) and those related to family system (e.g., organization of the family environment, emotional climate) (Lorence et al., 2025).

In order to adequately implement the interventions aimed at promoting parental competencies while guaranteeing their effectiveness, it is essential to develop validated evaluation tools that allow for a rigorous analysis of said competencies (Gottfredson et al., 2015). In the Spanish-speaking context, there are numerous self-administered scales that assess specific parental competencies, both originally developed in Spanish or adapted from other languages. Moreover, since the formulation of Recommendation 19 on Positive Parenting, there has been an increase in the development of comprehensive tools that can provide a holistic evaluation of parental competencies in an efficient manner and from a strengthening approach. Most of these scales have been validated through rigorous validation processes that included literature reviews and experts’ consultation, as well as dimensionality, reliability and validity analyses.

The Positive Parenting Scale − PPS (Escala de Parentalidad Positiva in Spanish) (Suárez et al., 2016), is an 18-item self-administered Likert scale that assesses parental competencies in families that participate in an on-line parenting initiative, namely: involvement in family life, affection and recognition, communication and stress management, and shared activities. The Parenting Competence Scale for Parents with Young Children − PCS-YC (Escala de Competencias Parentales para Padres y Madres con Niños/as Pequeño/as in Spanish) (Martínez-González & Iglesias-García, 2018), is a self-administered 15-item Likert scale aimed at assessing needs in terms of parenting competencies for participants of preventive community-based parenting programs, namely: self-regulation, self-esteem, promotion of child’s self-esteem, imposition (firmness) for conflict resolution, and non-assertive communication. In the Chilean context, Gómez and Muñoz (2015) developed the Positive Parenting Scale − E2P (Escala de Parentalidad Positiva in Spanish), a self-administered 54-items Likert scale that assesses parental competencies for family support or research purposes, namely: establishment of secure attachment, stimulation of child’s learning and development, protection of the physical, emotional and sexual integrity of the child, and reflective parental role.

Despite the usefulness of these measures to assess parental competencies in family support initiatives, their self-administered nature introduces a challenge for their use as practice tools to support case planning and process evaluation (Asmussen, 2011). When supporting families at psychosocial risk, another challenge emerges, as vulnerable parents might find difficulties in self-reporting through Likert scales (Menéndez et al., 2018) and social desirability might increase in an attempt of “faking good” in front of family support workers (Conley, 2004).

As a consequence, in the field of child welfare and family support, the evaluation frameworks commonly follow an expert judgment approach, by including a set of indicators reported by the case practitioner with information driven from reports, interviews and direct observation (White, 2005). In Spain, Martín et al. (2013) developed the Parental Competence and Resilience Scale – PCRS (Escala de Competencia y Resiliencia Parental in Spanish), a set of indicators to be reported by the family support worker assessing personal development and resilience, educational competence and household organization, seek of support, and community competence. This scale was developed specifically for social services following a rigorous methodological process, although it does not have an administration system that facilitates the collection of information on the evaluated indicators (such as a semi-structured interview or guiding questions).

There are other scales reported by family support workers and widely used in social services for assessing the family context more globally that include some indicators of parental competencies. This is the case of the Child Well-Being Scales − CWB (Magura & Moses, 1986; validated in Spanish by Arruabarrena & De Paul, 1999), widely used in assessing child wellbeing in cases of maltreatment, which incorporate indicators related to the adequacy of the parental role and family capacities. The Home Observation Measurement Environment – HOME inventory (Caldwell & Bradley, 2003; translated into Spanish by Moreno, n.d) has been widely used in family support services to assess the quality of stimulation and support available in the home environment for children and adolescents, including stimulation, environment structuration, parental responsivity and family interaction aspects. The North Carolina Family Assessment Scale – NFCAS (Reed-Asjcraft et al., 2001) was designed in the context of family preservation services, and it includes a parental competencies subscale that assesses parenting practices and supervision, stimulation, and caregivers’ health status. The Haezi-Etxadi Scales (i.e., HES-2 (Arranz et al., 2018), HES-4 (Sánchez et al., 2022) and HES 7-11 (Barreto et al., 2018)) are aimed at evaluating the quality of the family context in families with children of different ages, including the assessment of parental competencies that promote the development and structuring of both the physical and social environments. With the exception of the HOME inventory (Ciria et al., 2016) and the HES (Arranz et al., 2018; Barreto et al., 2018; Sánchez et al., 2022), neither these measures nor the PCRS have an administration system that facilitates the collection of information on the evaluated indicators. Moreover, despite the empirical evidence on their methodological soundness, their development process does not include all the methodological requirements imposed by academia (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014).

With the aim of contributing to overcoming the aforementioned gaps, we developed the Interview for the Assessment of Parental competencies − ECP-12 (Entrevista para la Evaluación de Competencias Parentales in Spanish), to assess parental competencies in families receiving support in the child welfare setting (Hidalgo et al., 2020). We followed a rigorous validation process, which is described in this paper.

The Present Study

This paper includes results from two sequential projects aimed at validating a parental competencies instrument and advising practitioners from Red Cross family support services (Study 1, Code CP3279-CGT0925, Study 2, Code CP4094-CGT0985). The first study included a literature review on theoretical models on parental competencies and a systematic review about available tools to measure this construct, an expert judgment process to evaluate different aspects related to the measurement instrument, and a pilot test of the initial version of the scale in family support services from the Red Cross. The second study included an Exploratory Factor Analysis (EFA), several Confirmatory Factor Analyses (CFA), reliability analyses and a report of additional evidence of validity to propose a final instrument to measure parental competencies. Both studies are cross-sectional, with multi-informant data collection and a quantitative methodological strategy. We used the STROBE cross sectional checklist when writing our report (von Elm et al., 2008).

Study 1

Materials and Methods

Participants

The expert judgment sample consisted of 24 experts: 71% were practitioners from family support services with experience in family intervention, and 29% were reputed researchers in the field of positive parenting, within the area of social sciences. These were professionals with training in the scope of social sciences (Degree or PhD in Psychology, Social Work, Social Education, Pedagogy or Sociology); most of them were women (79%), their age ranged between 25 and 67 years (M = 43.88), and they had an average professional experience of 16.89 years, particularly 12.48 years in the study subject or family intervention.

The sample of families for the pilot study was composed of 496 caregivers with an average age of 41.42 years (SD = 10.83); 83.40% were the parents, 92.30% were women, 52.80% were immigrants, 87.50% had a low-medium education level, 73.40% were unemployed, 54.80% were single parents, and the average age of their children was 8.90 years (SD = 2.99). Practitioners from the Red Cross that interviewed the families were 91.50% women, their average age was 35.71 years (SD = 7.73), and they had an average professional experience of 9.70 years (SD = 7.18); specifically, they had worked in family intervention programs for an average of 4.06 years (SD = 5.30), with 51.50% of them being in charge of those programs.

Procedure

First, to develop the ECP-12 we reviewed the evaluation procedures used in family preservation services from the Red Cross in Spain as well as theoretical models on parental competencies. Later, we performed a systematic review of the empirical literature on available tools (as described in Lorence et al., 2025).

With a first draft of the instrument we performed an expert judgment to obtain evidence of content-related validity, where relevant academic experts in positive parenting and practitioners from family preservation services were inquired to analyze different aspects related to the measurement instrument. Potential participants were contacted via e-mail and reminders were sent after two weeks, according to Dillmann’s recommendations (2000). They received the survey in an excel format, which required 30 min for completion.

Next step consisted in piloting the initial version of the scale in family support services from the Red Cross. A pre-pilot process with two experts and researchers of the project was developed to verify their consensus level regarding the coding of the categories of each indicator and the adequacy of the interview script. For the pilot study, we used a stratification strategy to guarantee representativeness of the population of families being attended to by family support services in the Red Cross.

Red Cross practitioners with previous training in the ECP-12 interview administered the questionnaires to the participants in a semi-structured interview format for about 45 min, as part of the initial assessment of the families at the service. Each service was asked to have at least one of the interviews codified by two practitioners independently, in order to examine the inter-observer reliability, which would show the extent to which different codifiers responded in a similar manner to the valuation of the same family.

All the participants in this study signed an informed consent according to the guidelines of the Declaration of Helsinki (The World Medical Association, 2013). There were no monetary or other incentives for participation. The Ethics Committee of University Loyola Andalucía provided approval for this project on the fifth of July of 2021.

Measures

The Expert Judgement on the Parental Competencies Interview

A survey was designed ad hoc for this study with the aim of assessing, through expert judgment, the parental competencies instrument under construction. The survey was composed of two parts. The first part included 9 items about the sociodemographic profile of the expert (gender, age, workplace, job title, work experience, qualification and email), with open-ended questions (such as work institution) and dichotomous questions (such as sex). The second part was consisted of 120 items (e.g., “Becoming a parent has been a positive experience for adults”) divided into 11 dimensions (in brackets, number of items for each dimension): adequate perception of the parental role (11), emotional self-regulation (11), stress and problem coping strategies (10), adequate beliefs and expectations about the child’s development (10), affection and warmth in parent-child relationships (10), inductive control and supervision (12), development stimulation (10), involvement in the child’s life (11), household management (10), structuring of family life (15) and social support (10). The experts assessed the items through a 3-point scale, regarding their representativeness (from –1 = no representative indicator to +1 = representative indicator), usefulness (from –1 = unnecessary indicator to +1 = key indicator) and clarity (from –1 = confusing indicator to +1 = clear and understandable indicator), and they were encouraged to provide critical comments about both the items and the dimensions in open-ended questions (e.g., “Do you think there are any relevant indicators we should have included to assess the dimension of ‘Adequate perception of parental role’ that we have not collected? If so, please include them below”). Moreover, they were allowed to make suggestions for improvement regarding the detection of semantic or grammatical errors, the understandability of the items, the possible semantic inconsistencies, the adequacy of the dimensions of the construct, etcetera.

For the pilot study, the following measures were administered:

Sociodemographic profile. A survey was designed ad hoc for this study to collect information on the sociodemographic profile of the families and the practitioners. The family profile collected family sociodemographic information about the main caregiver (bonding with the child, sex, age, education level, country of origin, professional situation) and the family system (family structure, number of people living together, age and sex of each family member). The professional profile included both sociodemographic (sex, age) and work-related information (academic degree, specific training in family intervention, years of experience with families, work entity, and job position). Around 10 min were required to fill in the questionnaire.

The initial version of the Interview for the Assessment of Parental Competencies (ECP-12) (initial version). The pilot version of the interview included 81 remaining indicators from the expert judgment, to be rated on a 5-point Likert-type scale (1 = Nothing; 5 = Totally), related to the following dimensions: adequate perception of the parental role (APP), emotional self-regulation (ESR), stress coping strategies (SCS), adequate beliefs and expectations about the child’s development (ABE), affection and communication in parent-child relationships (AC), inductive control and supervision (ICS), development stimulation (DS), involvement in the child’s life (ICL), household management (HM), structuring of family life (SFL), and social support (SOS). This version of the interview took approximately 45 min to complete. The instrument revealed Cronbach’s alpha reliability values between .79 and .92 for the dimensions, with an overall score of .98.

The Parenting competencies scale for parents with young children (PCS-YC) (Martínez-González & Iglesias-García, 2018). This scale assesses the needs for parental support through a 15-item self-report (e.g., “I know how to relax and control my emotions”, “I have a good opinion of myself about how I raise my children”, “I tell my children how I feel with their behavior”), measuring the following subscales: self-regulation, self-esteem, promotion of children’s self-esteem, imposition for conflict resolution, and non-assertive communication. Each item is assessed in a 4-point Likert scale from 1 (totally disagree) to 4 (totally agree), with higher scores showing higher levels of the measured variable. This scale required about 10 min to be filled in. This instrument revealed Cronbach’s alpha reliability values between .72 (promoting children’s self-esteem) and .83 (self-regulation).

The Positive Parenting Scale (PPS) (Suárez et al., 2016). This instrument measures positive parenting dimensions as reported by parents. The scale has 18 items (e.g., “I encourage problems to be solved together”, “I let my children know that I trust them”), and four subscales: family involvement, affection and recognition, communication and stress management, and shared activities. The items are assessed with a Likert scale from 1 (never) to 5 (always), with higher scores expressing higher levels of the evaluated dimension. Ten minutes were required to fill in the questionnaire. The instrument revealed Cronbach’s alpha reliability values between .71 (shared activities) and .88 (affection and recognition).

The KIDSCREEN-10 index (European Kidscreen Group, 2006). The Spanish and 10-item proxy version of this instrument was used to evaluate child well-being as reported by both parents and practitioners. This scale is composed of 8 direct items (e.g., “Has your child felt full of energy?” or “Has your child had fun with his/her friends?”) assessed in a 5-point Likert scale, ranging from 1 (never; not at all) to 5 (always; extremely), with higher scores indicating better child well-being, and 2 reverse items, (i.e., “Has your child felt sad?” and “Has your child felt lonely?”). This scale was completed in about 5 minutes. The KIDSCREEN-10 index revealed acceptable Cronbach’s alpha reliability values for both parents (.73) and practitioners (.78).

Data Analyses

For the expert judgment, the degree of agreement among experts regarding representativeness, usefulness and understandability was quantified through the Osterlind index (Osterlind, 1998). Adequate consensus was considered when the value obtained was equal to or greater than .5. Complementarily, the usefulness of each item was analyzed through the Content Validity Ratio (CVR) (Lawshe, 1975). The critical CVR for 24 experts was .417 (Ayre & Scally, 2014).

Once the initial version of the instrument was depurated, it was piloted in a sample of family support services from the Red Cross. For each indicator (item) we analyzed: (1) inter-coder reliability through Intraclass Correlation Coefficients, whose results indicate satisfactory reliability if they are higher than .75 (Rosner, 2006); and (2) their psychometric properties through the asymmetry, kurtosis and discrimination indices, which must be equal to or higher than .30 to show adequate discrimination (Muñiz, 2018; Raykov, 2009).

Later, to explore the latent structure of the instrument as well as the psychometric properties of the items, we performed an Exploratory Factor Analysis (EFA) using Polycoric matrixes, Unweighted Least Squares (ULS) as factor extraction, and Promin rotation (Ferrando & Anguiano-Carrasco, 2010; Ferrando et al., 2022). The appropriateness of the sample was examined through the Barlett’s sphericity test (p ≤ .05; Bartlett, 1950) and Kaiser-Meyer-Olkin (KMO) test (Kaiser, 1970), which can be considered appropriate for values >.70 (Osborne et al., 2014). We analyzed missing data patterns through Little’s Test (Ferrando et al., 2022).

The model fit was assessed by examining the Goodness of Fit Index (GFI >.90) and the Root Mean Square of Residuals (RMSR), which should be lower than the expected mean value of RMSR for an acceptable model (Kelley’s criterion) (Hooper et al., 2008). Complementarily, with respect to item adequacy, we analyzed communalities and the Measure of Sampling Adequacy (MSA) (Lorenzo-Seva & Ferrando, 2021) through the Item Adequacy index, with MSA values below .50 indicate that the item should be removed because it does not assess the same construct as the other items. The internal consistency was evaluated through McDonald’s Omega and Cronbach’s Alpha, with values equal to or higher than .70 being considered acceptable (Dunn et al., 2013; McDonald, 1999; Viladrich et al., 2017).

Pearson’s correlations were computed to examine evidence of validity based on relations to other variables that measure related constructs (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014).

The Osterlind index and the CVR were computed using formulae in Excel; the EFA was executed with Factor 12.03.01 (Ferrando & Lorenzo-Seva, 2017) and the rest of analyses were performed with SPSS v.27 software (IBM, 2021). All statistical procedures were examined according to a significance level of p ≤ .05.

Results

After review of the state of the art (as described in Jiménez et al., 2021; Lorence et al., 2025), we proposed a provisional instrument consisted of 120 indicators, three times longer than the desired final instrument, since, in this pilot phase, the items are debugged, selecting those with a better psychometric functioning (DeVellis, 2017). The flow chart presented below gathers each of the steps followed for the development of the tool, emphasizing the refining aspects up to the attainment of its final version (Figure 1).

Figure 1.

Flowchart of the steps for the development of the tool.

Detailed results about this process can be consulted in Appendix A.

To prepare the next study (Study 2), the interview script was adjusted to ensure that each block of questions referred to each of the dimensions obtained. The result was a total of 12 main questions to assess the 12 dimensions that were finally established for the ECP-12: stimulation and structuring (SS), shared family time (FAM), parental co-responsibility (CO), adequate beliefs and expectations about the child’s development (ABE), affection, communication and acceptance (ACA), school involvement (SI), rules and supervision (RS), emotional self-regulation (ESR), adequate perception of the parental role (APP), stress coping strategies (SCS), social support (SOS), and household management (HM). The final version of the questionnaire to be administered in Spanish is available at this link: https://www2.cruzroja.es/documents/5640665/662926586/Manual+ECP-12_Web+definitivo.pdf/8156699d-13a1-d50f-055e-8249bbf78033?t=1617004923515.

Study 2

Materials and Methods

Participants

We used a convenience sample constituted by families attended to by family support services in the child welfare setting in Spain, who were recruited to participate in a positive parenting program. We obtained a sample of 518 caregivers (96.30% parents, 1.70% legal guardians, 1.40% grandparents, and 0.40% aunts/uncles) with missing data representing less than 5% of the total data. The main caregiver in the household was, in most cases, female (84.00%), with a mean age of 42.14 years (SD = 7.94; range: 18–72 years). They were unemployed in 44.90% of the cases. Regarding their education level, 6.00% had not completed primary education, 42.90% had finished only primary education, 23.80% had managed to complete secondary education and 27.30% had university education. Regarding nationality, 75.50% of the sample was originally from Spain; as for non-Spanish participants, 35.20% were from Africa, 45.60% were born in Central or South America, and the remaining 19.20% were from other European countries. Regarding the children for whom information was provided for this research, their mean age was 11.87 years (SD = 3.30), ranging from 1 to 17 years and with an equal distribution according to gender (55.10% boys).

A total of 168 practitioners participated from family support services in the child welfare setting in Spain that interviewed the families. They were aged between 20 and 65 years (M = 39.88, SD = 9.87), mainly women (89.20%), with a bachelor’s degree in social sciences (such as psychology 41.00%, social work 30.40%, and social education 16.80%). They had 8.57 years as the average of experience working with families (SD = 7.33; ranging from 0 to 32), with 64.80% reporting previous specific training in positive parenting.

Procedure and Measures

The procedure was similar to the one explained for the pilot study at Study 1. We administered the same survey already used in Study 1, the last version of the ECP-12 and the Strength and Difficulties Questionnaire (SDQ) (Goodman, 1997 adapted to Spanish by García et al., 2000). This instrument is aimed at examining emotional and behavioral problems, as well as prosocial behaviors through 25 items and 5 subscales: emotional symptoms, conduct problems, hyperactivity, peer relationship problems and prosocial behavior; with 5 items each (e.g., “Often lies or cheats”) assessed in a 3-point Likert scale (0 = not true, 1 = somewhat true, 2 = yes, absolutely true). A total difficulties score can be computed including emotional symptoms, hyperactivity, conduct problems, and peer relationship problems dimensions. Higher values indicate higher levels of the (sub)scale. Cronbach’s α in this study was: total difficulties score .83, emotional symptoms .68, conduct problems .76, hyperactivity/inattention .74, peer relationship problems .55 and prosocial behavior .74. The full questionnaire was completed in approximately 10 min.

The study 2 followed the same guidelines of the Declaration of Helsinki mentioned before. The Ethics Committee of University Loyola Andalucía provided approval for this project on the fifth of July of 2021.

Data Analyses

Descriptive Statistics and Preliminary Analyses

Firstly, the data matrix was reviewed. We screened data for outliers and analyzed normality through Mardia’s test (1970), inter-correlations between items, and between the global score and factor scores. Full Information Maximum Likelihood was the method used to handle missing data, which uses all data that are available to estimate the model. As descriptive statistics, we computed percentages, means, and standard deviations.

Dimensionality

Firstly, as in Study 1, we analyzed the adequacy of the sample to be factorized. Then, the sample of 518 participants was randomly split into two datasets to be analyzed independently in order to replicate the Exploratory Factor Analysis with this new sample (EFA, n = 251) and confirm the results via Confirmatory Factor Analysis (CFA, n = 267).

With the first half, the EFA was replicated as in Study 1. Additionally, the factor solution was assessed considering: the H index or construct replicability (Hancock & Mueller, 2000), with values higher than .70 manifesting that the latent variable is well defined by their corresponding items and would have more stability across studies; the Factor Determinacy Index (FDI) (Gorsuch, 2003), with values higher than .90 allowing the use of factor score estimates in research (Rodriguez et al., 2016); simplicity indices, such as Bentler’s Simplicity (S) index (Bentler, 1977) and the Loading Simplicity (LS) index (Lorenzo-Seva, 2003), which measure the tendency of the items to load on only one dimension and consider that, the higher the values, the simpler the solution. We carefully analyzed factor loadings, considering that items loading should score higher than .40 on their target factor and below .30 on alternative factors (Howard, 2015). We examined various elements to determine the number of factors to retain, as factor loadings, the total explained variance, the inter-correlations among dimensions, and the coherence with the theoretical model proposed (Ferrando et al., 2022; Ferrando & Lorenzo-Seva, 2014).

With the second half, we developed several CFAs to clarify the measurement model that best fitted the data (Byrne, 2010). As a first step, we estimated the unidimensional model, which provides only a general parental competencies score. We also analyzed the 12-factor multidimensional model derived from Study 1. Complementarily, we explored alternative models (i.e., correlated, second-order, bifactor, and ESEM) to retain the solution that best fitted the data. The correlated factor model assumed oblique-related dimensions. Both the higher-order model and the bifactor models “consider the ability hierarchy in its entirety, containing a mix of general and specific constructs” (Brunner et al., 2012, p. 813). The second-order model assumed that the factors are uncorrelated and representative of a general construct. As a combination of the unidimensional and multidimensional approaches, the bifactor model emerged, which allows items to load on both subfactor dimensions and a general factor. For each model, Modification Indices (MI) were analyzed. We allowed covarying item errors when both MI was high (at least higher than 20) and the item content or format was similar. We carefully analyzed each MI to determine whether the covariation could be caused by certain words or expressions and, in that case, if the covariation was allowed (Byrne, 2010).

In order to capture the complexity of the theoretical model that feeds the scale (due to the large number of dimensions, the expected correlations among parental competencies, and the fact that several items affect different domains of parental competencies), we tested two ESEM models. ESEM models are suggested when the theory aligns with the conceptualization of two layers of constructs (Marsh et al., 2014), such as the specific parental competencies and the expected global construct in this case. The ESEM models simultaneously enable cross-loadings among items and factors, but they also compute goodness-of-fit indices and allow estimating error terms and invariance tests (Howard et al., 2018; Morin et al., 2013). We estimated the ESEM and bifactor ESEM, which could help us to understand the complex reality of data and to retain all the items in the scale (Morin et al., 2020).

We employed a sequential approach to assess and compare plausible models, as suggested by Morin et al. (2020) and followed by researchers such as Van Zyl and ten Klooster (2022). Firstly, we compared the CFA and the ESEM. If both models yield a satisfactory match with the data, the standard solutions should be compared to their bifactor counterparts. Then, if model fit, factor loadings, and correlations are similar between the CFA and the ESEM, it is prospective to select the more parsimonious bifactor CFA model. Nevertheless, if the ESEM is the model that provides an adequate fit to the data (but not the CFA), only the bifactor ESEM must be pursued. Alamer and Marsh (2022) provided a decision tree that is very useful to lead the better model selection (CFA or ESEM). The final model should be selected based on empirical results and theoretically justified.

To compare the models, the ESEM should be the preferred option if: (1) the fit indices improve (ΔCFI and ΔTLI increase at least by .01, ΔRMSEA decreases at least by .015, and BIC and AIC are lower in the ESEM model); (2) decreased of factor correlations; (3) only minor to moderate cross-loadings, which are straightforward to justify; and/or (4) items adequately define the factors, especially the general factors (Morin et al., 2020).

Following the recommendations of Morin et al. (2020), it is preferable for factor loadings on the intended factors to exceed .50; however, values between .30 and .50 may be acceptable under specific circumstances, such as when there is prior psychometric evidence supporting the retention of the item. Scores beneath .30 warrant reconsideration in future validation studies. Keep in mind that when a bifactor specification is integrated, as seen in bifactor ESEM, a loading is considered satisfactory if it adheres to the guidelines, particularly on the general factors. Convergent and discriminant validity are assessed in distinctive ways within ESEM models. According to Alamer and Marsh (2022), establishing convergent validity involves confirming that item factor loadings on their target factors, whether specific or general, are not only significant but also stronger than their loadings on unrelated factors. Discriminant validity is indicated when ESEM demonstrates more modest factor correlations compared to the inflated correlations observed in CFA.

The CFA models were fit to the data using the Mplus software v.8 (Muthén & Muthén, 2017) using the robust method of estimation Weighted Least Squares Means and Variance adjusted (WLSMV), due to the non-multivariate normality of the data (Finney & DiStefano, 2006; Rhemtulla et al., 2012). The model fit was evaluated by verifying the RMSEA (lower than .06) and the SRMR (lower than .08). The RMSEA 90% confidence interval (CI) was included (Schermelleh-Engel et al., 2003). In ESEM models, the aim is to minimize cross-loadings as much as possible, aligning with the confirmatory nature of ESEM (Morin et al., 2020).

Reliability

Point-estimate composite reliability (upper-bound; ρ > .80; Raykov, 2009) or McDonald’s Omega (ω > .70; Hayes & Coutts, 2020) were used to assess the reliability across factorial models. For the bifactor CFA models, we analyzed, as supplementary indicators of reliability and measurement quality, the explained common variance (ECV), the H-factor, the Factor Determinacy indicator, the Item level ECV, the Percent of Uncontaminated Correlations (PUC), and the Average Relative Bias Parameters (Dueber, 2017). A scale is considered predominantly unidimensional when the overarching factor accounts for a minimum of 70% of the overall shared variance. Given the absence of specific guidelines on integrating cross-loadings for bifactor ESEM models in Omega estimation (Morin et al., 2020), the recommended approach by these authors is to disregard cross-loadings when calculating Omega in bifactor ESEM models. As a result, in the case of ESEM models, Omega alone may not fully capture the reliability of a construct and, therefore, should not be relied upon as the sole indicator (Van Zyl & ten Klooster, 2022).

To analyze validity evidence based on relations to other variables that measure related constructs (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014), Pearson’s correlations were performed considering the ECP-12 and the SDQ (García-Garzón et al., 2000).

The analyses were performed using Factor 12.03.01 for the EFA (Ferrando & Lorenzo-Seva, 2017), MPlus v.8 to calculate CFA (Muthén & Muthén, 2017), the SLiDapp Application to obtain the syntax for the bi-factor ESEM (García-Garzón et al., 2020), a Microsoft Excel-based tool to calculate various indices relevant to bifactor CFA models (Dueber, 2017), and SPSS v.27 (IBM, 2021) for the rest of analyses. All the statistical procedures were examined according to a significance level of p ≤ .05.

Results

Descriptive Statistics and Preliminary Analyses

The matrix was adequate for factorization. The KMO verified the sample adequacy for the analysis (KMO = .94) and Bartlett’s Test of Sphericity was appropriate for factor analysis (χ2 = 5405.3, df = 1378, p < .001). All kurtosis and skewness scores for items fell within the range between −2 and +2 (Byrne, 2010), although Mardia’s multivariate normality test (1970) revealed significant kurtosis (M_k = 66.38, p < .001). Inter-correlations among items were all significant but lower than .90, suggesting no multicollinearity (see Appendix B) (Tabachnick & Fidell, 2001). Appendix C shows descriptive statistics for the global score and their proposed dimensions, as well as inter-correlations among dimensions, presenting moderate-to-strong relationships.

Dimensionality and Reliability

Exploratory Factor Analysis

The 12-factor model showed a good fit (GFI = .997, RMSR = .022, <.065 - Kelley’s criterion-). All communalities were higher than .50 and values of MSA scored over .50, meaning that each item measures the same domain as the remaining items in the pool, thus no item was removed (see Appendix D).

Factor loadings are reported in Appendix E, where it can be observed that most of the items loaded higher than .40 in the target factor and lower than .40 in all other factors. The model explained 80% of the cumulative proportion of the variance, and the inter-correlations among dimensions were appropriate (ranging from .11 to .66). The average item score ranged between 2.71 (SD = .95) and 4.20 (SD = .84), with acceptable values of asymmetry (−.86, .33) and kurtosis (−1.13, .44).

We observed H index values higher than .70, proving that the dimensions were well-defined by their indicators and will have more stability across studies. FDI scores were higher than .90, allowing the use of the factor score estimates in research. The items showed a very satisfactory internal consistency (McDonald’s ordinal Omega = .98; Standardized Cronbach’s alpha = .98). Bentler’s S was .74 and LS was .54; these values are not very high, highlighting the tendency of the items to load not only in one dimension, and indicating that the solution was not simple.

At this stage, we recognized that finding a balance between identifying the best-fitting factor solution for the data and accurately reflecting the theoretical framework was challenging. Firstly, the theoretical model was complex, with numerous items designed to capture both specific domains of parental competencies as well as the instrument as a whole. All items showed significant correlations, with strong and significant intercorrelations among the dimensions and the global score (ranging from .58 to .85). Secondly, factor loadings fixed clearly to dimensions 1 (SOS), 2 (SI), 3 (HM), 4 (SS), 5 (FAM), 6 (ACA), 9 (CO), 10 (RS), and 11 (ABE), but other dimensions included items related to various competencies, such as dimensions 7 (mainly SCS plus APP), 8 (mainly ESR plus APP) and 12 (mainly ESR plus ACA). Complementarily, H and FDI indexes were adequate and reflected the consistency of the dimensions. Considering this information altogether, we decided to keep all the items for the CFA and to test different factor structures, from the simplest structures to other options that were more adaptable to complex data.

Confirmatory Factor Analyses

We tested 6 possible factor structures: unidimensional model, factors correlated, second-order factors, bifactor CFA, ESEM, and bifactor ESEM (see Table 1). The unidimensional model did not show a satisfactory fit to the data (RMSEA = .114, 90% IC = .111–.117; CFI = .801; TLI = .794; SRMR = .098). The IM reported several parameters that were prospective to include, namely the correlations between items CO2 and CO4 (MI = 476.70), CO2 and CO3 (MI = 688.72), CO3 and CO4 (MI = 248.39), CO1 and CO2 (MI = 113.98), CO1 and CO3 (MI = 103.52), SOS1 and SOS2 (MI = 557.51), HM1 and HM2 (MI = 123.70), HM1 and HM3 (MI = 270.45), and HM2 and HM3 (MI = 236.24). The model fit improved, but it was not the best model, and MI showed latent structures (RMSEA = .080, 90% CI = .077–.083; CFI = .903; TLI = .899; SRMR = .073). The 12-factor model showed an adequate fit to the data (RMSEA = .061, 90% CI = .057–.064; CFI = .947; TLI = .942; SRMR = .056); nevertheless, MI reported one significant parameter: the correlations between items SOS1 and SOS2 (MI = 127.504). The model fit improved when this parameter was included (RMSEA = .058, 90% CI = .054–.061; CFI = .952; TLI = .947; SRMR = .054). However, the magnitudes of factor correlations seemed to be larger in CFA (12-factor correlated CE) than in ESEM (see Appendix F), which, together with the worst fit of the CFA, led to the discarding of this 12-factor correlated model. The second-order factor model did not fit the data (RMSEA = .165, 90% CI = .163–.168; CFI = .583; TLI = .566; SRMR = .137) and MI suggested the correlation between several dimensions, as well as 27 correlations between items, proving that this was not the best model solution. The bifactor CFA showed adequate fit indices (RMSEA = .057, 90% CI = .053–.060; CFI = .952; TLI = .949; SRMR = .058), although both the ESEM and bifactor ESEM showed the best fit indices (see Table 1).

Table 1.

Fit Indices for the Interview for the Assessment of Parental Competencies Factor Models.

Model	RMSEA (90% CI)	CFI	TLI	SRMR
Unidimensional	.11 (.11–.12)	.80	.79	.10
Unidimensional (CE)	.08 (.08–.08)	.90	.90	.07
Twelve-factor	.06 (.06–.06)	.95	.94	.06
Twelve-factor (CE)	.06 (.05–.06)	.95	.95	.05
Second-order	.17 (.16–.17)	.58	.57	.14
ESEM CFA	.04 (.03–.04)	.99	.98	.02
Bifactor	.06 (.05–.06)	.95	.95	.06
Bifactor ESEM	.04 (.03–.04)	.99	.98	.02

Note. CE, correlated errors; RMSEA, root mean square error of approximation; RMSEA CI, root mean square error of approximation confidence interval at 90%; SRMR, standardized root mean square residual.

Considering that the ESEM and the bifactor ESEM models showed a satisfactory and very similar fit, we focused on standardized factor loadings, cross-loadings and ancillary indices for these models. In the ESEM, the majority of the items loaded on their target factor (see Appendix G); nevertheless, several items loaded significantly on other factors (such as SS6, ACA3, or ESR1). Indeed, we noticed several substantial cross-loadings, suggesting potential evidence for the existence of a general factor. Consequently, adopting the bifactor ESEM model could be advantageous (Morin et al., 2020).

When we focused on the bifactor ESEM, we observed that, despite the model’s complexity, the structure became clearer. The factors were more distinctly identified, with significantly fewer cross-loadings. In fact, the cross-loadings in the bifactor ESEM were smaller than those in the standard ESEM, with mean cross-loadings of .041 in the ESEM and .001 in the bifactor ESEM, respectively. The omega index was adequate for all the dimensions (except for SCS in the ESEM model) and higher in most of the dimensions in the bifactor ESEM compared to the ESEM. Considering ancillary indices, we can conclude that the bifactor ESEM fitted the data better, since the existence of a global dimension is clear. As is shown in Appendix H, all the items were adequate to measure the construct, with item uniqueness values (measured through the residual error variances) higher than .01 and lower than .9 (except for item CO3), and all the items showed a significant R². Moreover, as was previously commented regarding Appendix G, the standardized factor loadings were higher than .30 in most of the items in their target factor, and the items that exhibited insignificant loadings on their designated factors did, however, show loadings on the global factor, forming a clearly defined global factor of parental competencies.

The common variance explained by the general factor was 66% (ECV = .66); total scores can be considered essentially unidimensional (OmegaH = .95 > .80); the global factor is a well-defined latent variable (H index = .98 > .80); and global factor score can be estimated (FD = .99 > .90). As is shown in Appendix I, when accounting for the presence of the general factor, the specific factors did not produce adequate Omegahs levels (Omegahs <.70), but construct replicability and factor determinacy were adequate for CO, SOS, and HM. Nevertheless, Omega indices should be used with caution, since cross-loadings were ignored in the calculation (Morin et al., 2020). Consequently, Omega cannot entirely reflect the reliability of the constructs.

In Table 2, we have reported correlations between the ECP-12 and SDQ. Total scores and dimensions are significantly correlated, which supports the existence of validity evidence based on relations with other variables for the ECP-12.

Table 2.

Correlations Between the Dimensions of the ECP-12 and the SDQ (N Between 478 and 516).

	SDQ Emotional Symptoms	SDQ Conduct Problems	SDQ Hyperactivity	SDQ Peer relationship Problems	SDQ Total Difficulties Score	SDQ Prosocial Behavior
SS	−.22	−.30	−.25	−.13	−.33	.15
SS	<.001	<.001	<.001	.003	<.001	.001
FAM	−.18	−.37	−.24	−.12	−.33	.26
FAM	<.001	<.001	<.001	.007	<.001	<.001
CO	−.24	−.19	−.19	−.05	−.25	.08
CO	<.001	<.001	<.001	.312	<.001	.088
ABE	−.21	−.25	−.21	−.15	−.30	.19
ABE	<.001	<.001	<.001	.001	<.001	<.001
ACA	−.24	−.47	−.30	−.19	−.43	.33
ACA	<.001	<.001	<.001	<.001	<.001	<.001
SI	−.14	−.17	−.15	<.01	−.18	.12
SI	.001	<.001	.001	.927	<.001	.007
RS	−.23	−.28	−.24	−.11	−.31	.19
RS	<.001	<.001	<.001	.014	<.001	<.001
ESR	−.15	−.28	−.22	−.10	−.28	.21
ESR	.001	<.001	<.001	.031	<.001	<.001
APP	−.19	−.30	−.26	−.10	−.31	.21
APP	<.001	<.001	<.001	.019	<.001	<.001
SCS	−.16	−.21	−.22	−0.06	−.24	.15
SCS	<.001	<.001	<.001	.164	<.001	.001
SOS	−.07	−.06	−0.08	−0.02	−.09	.02
SOS	.129	.174	.084	.613	.048	.736
HM	−.11	−.15	−.13	−.10	−.17	.09
HM	.017	.001	.003	.031	<.001	.053
ECP-12	−.26	−.33	−.25	−.13	−.36	.21
ECP-12	<.001	<.001	<.001	.005	<.001	<.001

Note. ECP-12, global score; SS, stimulation and structuring; FAM, shared family time; CO, parental co-responsibility; ABE, adequate beliefs and expectations; ACA, affection, communication and acceptance; SI, school involvement; RS, rules and supervision; ESR, emotional self-regulation; APP, adequate perception of the parental role; SCS, stress coping strategies; SOS, social support; HM, household management.

Collectively, the findings indicate that the bifactor-ESEM model demonstrated a superior fit to the data compared to alternative models and yielded slightly improved parameter estimates.

Discussion

The main aim of this study was to develop and obtain validity evidence to support that the scores of the ECP-12 measure adequately parental competencies in caregivers through a rigorous validation process (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education, 2014; DeVellis, 2017).

As was shown in Study 1, based on a review of the state of the art and considering the perspective of both family support experts (practitioners and researchers) and families, we elaborated a first version of the instrument that allowed us to understand the functioning of the items and how they were grouped. This process was useful mainly due to the possible existence of specific factors and also a global factor. Furthermore, we analyzed the correlations with self-reported measures of parental competencies and child’s quality of life, obtaining evidence of validity. In Study 2, using the refined version of the ECP-12, we developed an EFA and several CFA, concluding that the bifactor ESEM was the model that best fitted the data. The psychometric analyses indicated that this solution is valid and reliable for measuring both a global score and 12 specific parental competencies in Spanish caregivers that benefit from family support initiatives in the child welfare setting, namely: global parental competencies, stimulation and structuring, shared family time, parental co-responsibility, adequate beliefs and expectations about the child’s development, affection, communication and acceptance, school involvement, rules and supervision, emotional self-regulation, adequate perception of the parental role, stress coping strategies, social support, and household management. The parental competencies that integrate the ECP-12 match, to a large extent, those assessed by other existing tools. In particular, educational competencies relate to parental beliefs, stimulation, affection and supervision form the core of both the most widespread international tools (CWB, Magura & Moses, 1986; HOME inventory, Caldwell & Bradley, 2003; NFCAS, Reed-Asjcraft et al., 2001) and those specifically designed in Spain (PCRS, Martín et al., 2013; PSS, Suárez et al., 2016; PCS-YC, Martínez-González et al., 2018). In addition to integrating educational competencies, the ECP-12 includes personal competencies of parents (emotional self-regulation, adequate perception of the parental role, stress coping strategies), competencies related to the family system (shared family time, parental co-responsibility, household management) and the ability to seek and receive social support related to parenting. Although these dimensions have been highlighted at the theoretical level, as relevant aspects of the construct of parental competencies, they are not assessed in many of the existing instruments (Azar, 2002; Conley, 2005). In this sense, the ECP-12 is a comprehensive tool that integrates the different domains of parental competencies.

An in-depth look of the final bifactor ESEM solution showed that most of the items loaded on their specific dimension, and items such as ACA8, APP5, or SCS2, which did not exhibit high loadings on their respective specific factors, demonstrated loadings on the global factor. On the flip side, the limited number of items that did not display high loadings on the global factor exhibited higher loadings on their specific factors, exemplified by SOS1 and SOS2. These results support the use of a global score of parental competencies, as well as specific scores for the different dimensions. The data obtained show a high robustness and consistency of the dimensions of co-responsibility, stress coping strategies and household management, probably since these contents are clearly delimited and well-differentiated from other aspects of parenting (Hoghughi, 2004). The other dimensions show adequate indices (as can be observed in Appendix G), but these factor scores should be used with slight caution. In this line, some items loaded very similarly or higher on other dimensions, such as: ACA3 in school implication; ESR1 both in emotional self-regulation and adequate perception of the parental role; APP2 and APP5 in affection and communication and acceptance; and SCS2 in adequate perception of the parental role. These results are in line with the ecological-transactional perspective of parenting (Bornstein, 2016), which would explain the interdependence of the different dimensions of parental competencies, and the difficulty to isolate specific behaviors or practices. Affection, communication and acceptance, emotional self-regulation and adequate perception of the parental role are the dimensions in which one or more items have higher cross-loadings. These results may show that these dimensions are less delimited and that they integrate practices and behaviors related to different competencies. This idea could apply especially to the dimension of affection, communication and acceptance, which integrates differentiated practices that are clearly related to positive parenting (Daly et al., 2015). In the case of the perception of the parental role, there is clear evidence of the relationship of this aspect with competent parenting practices (Okagaki & Bingham, 2005).

The study has some limitations that should be pointed out. Due to the difficulty of gathering a sufficient number of participants, subsequent research endeavors should duplicate this validation study in comparable settings, employing more substantial sample sizes, exploring similarities and differences in the factor structure based on variables such as origin (being a migrant or a native citizen) and the age of the children. Moreover, the current study utilized cross-sectional data, and it would be pertinent to employ longitudinal data to address the measure’s invariance over time. Finally, future research is needed to understand and refine, if necessary, those items that seem to fit well in more than one dimension.

In conclusion, the obtained results show the validity of the ECP-12 for assessing parental competencies in the Spanish-speaking population. In contrast to other existing instruments, the ECP-12 is a comprehensive tool that allows for a differentiated assessment of the different domains of parental competencies and provides an overall score of this construct. Specially developed to be used in the field of child welfare and family support, the ECP-12 adopts an expert judgment format and uses a semi-structured interview to help the practitioners in the collection of information. The interview format proved to be a non-intrusive tool for families, and the semi-structured script allows practitioners to easily obtain information in a short period of time and without the need to know the families in depth. Therefore, the ECP-12 can be considered a useful resource to assess parental competencies from a positive approach in families receiving support in the child welfare setting.

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material for Validation of the Interview for the Assessment of Parental Competencies (ECP-12) by Lucía Jiménez, Milagrosa Sánchez-Martín, Bárbara Lorence, Ester Herrera-Collado, and Victoria Hidalgo in Journal of Family Issues

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Supplemental Material

Supplemental Material - Validation of the Interview for the Assessment of Parental Competencies (ECP-12)

Footnotes

Acknowledgments

We thank Adriana Díaz, Carmen San Martín and Carlos Chana for their support from Red Cross Spain on the development of the study.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by Spanish Red Cross (CP3279-CGT0925, CP4094-CGT0985); Spanish Ministry of Science, Innovation and Universities, Predoctoral grant (FPU 19/00125).

ORCID iDs

Lucía Jiménez

Milagrosa Sánchez-Martín

Ester Herrera-Collado

Victoria Hidalgo

Data Availability Statement

Raw data are not publicly available due restrictions specified in the Research Agreement of the projects (Codes CP3279-CGT0925 & CP4094-CGT0985). Specific usage can be considered upon request to the contact author by any member of the scientific community.*

Supplemental Material

Supplemental material for this article is available online.

References

Alamer

Marsh

(2022). Exploratory structural equation modeling in second language research: An applied example using the dualistic model of passion. Studies in Second Language Acquisition, 44(5), 1477–1500. https://doi.org/10.1017/S0272263121000863

American Educational Research Association, American Psychological Association, & National Council on Measurement in Education . (2014). Standards for educational and psychological testing. American Educational Research Association.

Arranz

Sánchez de Miguél

M. N.

Olabarrieta

Ibarluzea

Santa Marina

(2018). “Haezi-Etxadi Scale” HES-2 Factorizada. Escala para la evaluación del contexto familiar de niños/as de 2 años [“Haezi-Etxadi Scale” Factored HES-2. Scale for the assessment of the family context of 2 year olds]. Faculty of Psychology, University of Basque Country.

Arruabarrena

M. I.

De Paul

(1999). Escalas de bienestar infantil de Magura y Moses. Un primer estudio para la validación de la versión española [Child well-being scales of Magura and Moses. A first study for the validation of the Spanish version]. Psychosocial Intervention, 8(1), 89–108. https://www.bienestaryproteccioninfantil.es/imagenes/tablaContenidos03SubSec/47562.pdf

Asmussen

(2011). The evidence-based parenting practitioner’s handbook. Routledge.

Ayre

Scally

A. J.

(2014). Critical values for Lawshe’s content validity ratio: Revisiting the original methods of calculation. Measurement and Evaluation in Counseling and Development, 47(1), 79–86. https://doi.org/10.1177/0748175613513808

Azar

S. T.

(2002). Parenting and child maltreatment. In Bornstein

M. H.

(Ed.), Handbook of parenting (Vol. 4, pp. 361–388). Erlbaum.

Azar

S. T.

Cote

L. R.

(2002). Sociocultural issues in the evaluation of the needs of children in custody decision making: What do our current frameworks for evaluating parenting practices have to offer? International Journal of Law and Psychiatry, 25(3), 193–217. https://doi.org/10.1016/s0160-2527(02)00102-4

Barreto

F. B.

González

Roncallo

C. P.

Acha

Sánchez

(2018). Family context assessment and positive parenting policies. Early Child Development and Care, 188(11), 1605–1618. https://doi.org/10.1080/03004430.2018.1499624

10.

Bartlett

M. S.

(1950). Tests of significance in factor analysis. British Journal of Statistical Psychology, 3(2), 77–85. https://doi.org/10.1111/j.2044-8317.1950.tb00285.x

11.

Barudy

Dantagnan

(2010). Los desafíos invisibles de ser madre o padre. Manual de evaluación de las competencias y la resiliencia parental [The invisible challenges of being a mother or father: a manual for assessing competences and parental resilience]. Gedisa.

12.

Bentler

P. M.

(1977). Factor simplicity index and transformations. Psychometrika, 42(2), 277–295. https://doi.org/10.1007/bf02294054

13.

Bornstein

M. H.

(2016). Determinants of parenting. In Cicchetti

(Ed.), Developmental psychopathology: Risk, resilience and intervention (pp. 180–270). Wiley. https://doi.org/10.1002/9781119125556.devpsy405

14.

Bornstein

M. H.

Kotler

J. A.

Lansford

J. E.

(2022). The future of parenting programs: An introduction. Parenting, 22(3), 189–200. https://doi.org/10.1080/15295192.2022.2086808

15.

Brunner

Nagy

Wilhelm

(2012). A tutorial on hierarchically structured constructs. Journal of Personality, 80(4), 796–846. https://doi.org/10.1111/j.1467-6494.2011.00749.x

16.

Budd

K. S.

(2005). Assessing parenting capacity in a child welfare context. Children and Youth Services Review, 27(4), 429–444. https://doi.org/10.1016/j.childyouth.2004.11.008

17.

Byrne

B. M.

(2010). Structural equation modeling with AMOS (2nd ed.). Routledge.

18.

Caldwell

B. M.

Bradley

R. H.

(2003). Home observation for measurement of the environment: Administration manual. Family & Human Dynamics Research Institute, Arizona State University.

19.

Ciria

Rivera

Moreno

(2016). Validación de modelos alternativos del inventario EA-HOME en adolescentes españoles [Validation of alternative models of the EA-HOME inventory in Spanish adolescents]. Apuntes de Psicología, 34(2–3), 189–200. https://doi.org/10.55414/ap.v34i2-3.610

20.

Coleman

P. K.

Karraker

K. H.

(2000). Parenting self-efficacy among mothers of school-age children: Conceptualization, measurement, and correlates. Family Relations, 49(1), 13–24. https://doi.org/10.1111/j.1741-3729.2000.00013.x

21.

Conley

(2004). A review of parenting capacity assessment reports. Journal of the Ontario Association of Children’s Aid Societies, 47(3), 16–23. https://www.oacas.org/pubs/oacas/journal/2003_2004winter/2003_2004winter.pdf

22.

Council of Europe . (2006). Recommendation of the Committee of Ministers to member states on policy to support positive parenting. https://wcd.coe.int/ViewDoc.jsp?id=1073507

23.

Daly

Bray

Bruckauf

Byrne

Margaria

Pecnik

Samms-Vaughan

(2015). Family and parenting support: Policy and provision in a global context. Innocenti Insight, UNICEF Office of Research.

24.

DeVellis

R. F.

(2017). Scale development: Theory and applications (4th ed.). Sage.

25.

Dillmann

D. A.

(2000). Mail and internet surveys: The tailored design method. Wiley and Sons.

26.

Dueber

D. M.

(2017). Bifactor indices calculator: A Microsoft excel-based tool to calculate various indices relevant to bifactor CFA models. https://doi.org/10.13023/edp.tool.01

27.

Dunn

T. J.

Baguley

Brunsden

(2013). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 295–441. https://doi.org/10.1111/bjop.12046

28.

European Kidscreen Groupe . (2006). The KIDSCREEN questionnaires. Quality of life questionnaires for children and adolescents. Pabst Science Publishers.

29.

Ferrando

P. J.

Anguiano

(2010). El análisis factorial como técnica de investigación en Psicología [Factor analysis as a research technique in Psychology]. Papeles del Psicólogo, 31(1), 18–33. https://www.redalyc.org/articulo.oa?id=77812441003

30.

Ferrando

P. J.

Lorenzo-Seva

(2014). El análisis factorial exploratorio de los ítems: algunas consideraciones adicionales [Exploratory factor analysis of the items: Some additional considerations]. Anales de Psicología, 30(3), 1170–1175. https://doi.org/10.6018/analesps.30.3.199991

31.

Ferrando

P. J.

Lorenzo-Seva

(2017). Program FACTOR at 10: Origins, development and future directions. Psicothema, 29(2), 236–240. https://doi.org/10.7334/psicothema2016.304

32.

Ferrando

P. J.

Lorenzo-Seva

Hernández-Dorado

Muñiz

(2022). Decálogo para el Análisis Factorial de los Ítems de un Test [Decalogue for the factorial analysis of the items of a test]. Psicothema, 34(1), 7–17. https://doi.org/10.7334/psicothema2021.456

33.

Finney

S. J.

DiStefano

(2006). Nonnormal and categorical data in structural equation models. In Hancock

G. R.

Mueller

R. O.

(Eds.), A second course in structural equation modeling (pp. 269–314). Information Age.

34.

García

Goodman

Mazaira

Torres

Rodríguez-Sacristán

Hervas

Fuentes

(2000). El cuestionario de Capacidades y Dificultades [The Strengths and Difficulties questionnaire]. Revista de Psiquiatria Infanto-Juvenil, 1, 12–17. https://aepnya.eu/index.php/revistaaepnya/article/view/443.

35.

García-Garzón

Nieto

M. D.

Garrido

L. E.

Abad

F. J.

(2020). Bi-factor exploratory structural equation modeling done right: Using the SLiDapp application. Psicothema, 32(4), 607–614. https://doi.org/10.7334/psicothema2020.179

36.

Gómez

Muñoz

(2015). Escala de Parentalidad Positiva e2p. Manual [Positive Parenting Scale e2p. Manual] (2a ed.). Ideas Para la Infancia Foundation.

37.

Goodman

(1997). The strengths and difficulties questionnaire: A research note. The Journal of Child Psychology and Psychiatry and Allied Disciplines, 38(5), 581–586. https://doi.org/10.1111/j.1469-7610.1997.tb01545.x

38.

Gorsuch

R. L.

(2003). Factor analysis. In Schinka

J. A.

Velicer

W. F.

(Eds.), Handbook of psychology: Research methods in psychology (Vol. 2, pp. 143–164). John Wiley & Sons.

39.

Gottfredson

D. C.

Cook

T. D.

Gardner

F. E.

Gorman-Smith

Howe

G. W.

Sandler

I. N.

Zafft

K. M.

(2015). Standards of evidence for efficacy, effectiveness, and scale-up research in prevention science: Next generation. Prevention Science: The Official Journal of the Society for Prevention Research, 16(7), 893–926. https://doi.org/10.1007/s11121-015-0555-x

40.

Hancock

G. R.

Mueller

R. O.

(2001). Rethinking construct reliability within latent variable systems. In Cudeck

Jöreskog

K. G.

Sörbom

Du Toit

(Eds.), Structural equation modeling: Present and future—a festschrift in honor of Karl Joreskog (pp. 195–216). Scientific Software International.

41.

Hayes

A. F.

Coutts

J. J.

(2020). Use omega rather than Cronbach’s alpha for estimating reliability. But…. Communication Methods and Measures, 14(1), 1–24. https://doi.org/10.1080/19312458.2020.1718629

42.

Hidalgo

Jiménez

Lorence

Sánchez

(2020). ECP- 12. Entrevista para la evaluación de las Competencias Parentales. Manual técnico [ECP- 12. Interview for the evaluation of parenting competences. Technical manual]. Cruz Roja Española. https://www2.cruzroja.es/documents/5640665/662926586/Manual+ECP-12_Web+definitivo.pdf/8156699d-13a1-d50f-055e-8249bbf78033?t=1617004923515

43.

Hoghughi

(2004). Parenting – an introduction. In Hoghughi

Long

(Eds.), Handbook of parenting: Theory and research for practice (pp. 1–18). Sage.

44.

Hooper

Coughlan

Mullen

M. R.

(2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60. https://doi.org/10.21427/d7cf7r

45.

Howard

Gagné

Morin

Forest

(2018). Using bifactor exploratory structural equation modeling to test for a continuum structure of motivation. Journal of Management, 44(7), 2638–2664. https://doi.org/10.1177/0149206316645653

46.

Howard

M. C.

(2015). A review of exploratory factor analysis decisions and overview of current practices: What we are doing and how can we improve? International Journal of Human-Computer Interaction, 32(1), 51–62. https://doi.org/10.1080/10447318.2015.1087664

47.

IBM . (2021). IBM SPSS statistics for windows. IBM Corp.

48.

Jiménez

Antolín-Suárez

Lorence

Hidalgo

(2019). Family education and support for families at psychosocial risk in Europe: Evidence from a survey of international experts. Health & Social Care in the Community, 27, 449–458. https://doi.org/10.1111/hsc.12665

49.

Jiménez

Hidalgo

Lorence

Sánchez-Martín

(2021, July 11). Validation of the Interview for the Assessment of Parental Competencies [Paper presentation]. World Education Research Association - Focal Meeting 2020+1, University of Santiago de Compostela, Santiago de Compostela, Spain.

50.

Kaiser

H. F.

(1970). A second generation little jiffy. Psychometrika, 35(4), 401–415. https://doi.org/10.1007/BF02291817

51.

Lawshe

C. H.

(1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x

52.

Lorence

Hidalgo

Grasmeijer

A. J.

Jiménez

(2025). Parental competencies for positive parenting and their measurement: A systematic review. Professional Psychology: Research and Practice, 56(3), 222–231. https://doi.org/10.1037/pro0000608

53.

Lorenzo-Seva

(2003). A factor simplicity index. Psychometrika, 68(1), 49–60. https://doi.org/10.1007/bf02296652

54.

Lorenzo-Seva

Ferrando

P. J.

(2021). Msa: The forgotten index for identifying inappropriate items before computing exploratory item factor analysis. Methodology, 17(4), 296–306. https://doi.org/10.5964/meth.7185

55.

Magura

Moses

(1986). Outcome measures for child welfare services. Child Welfare League of America.

56.

Mardia

K. V.

(1970). Measures of multivariate skewness and kurtosis with applications. Biometrika, 57(3), 519–530. https://doi.org/10.1093/biomet/57.3.519

57.

Marsh

H. W.

Morin

A. J.

Parker

P. D.

Kaur

(2014). Exploratory structural equation modeling: An integration of the best features of exploratory and confirmatory factor analysis. Annual Review of Clinical Psychology, 10, 85–110. https://doi.org/10.1146/annurev-clinpsy-032813-153700

58.

Martín

J. C.

Cabrera

León

Rodrigo

M. J.

(2013). La Escala de Competencia y Resiliencia Parental para madres y padres en contextos de riesgo psicosocial [The Parental Competence and Resilience Scale for Mothers and Fathers in psychosocial risk contexts]. Anales de Psicología, 29(3), 886–896. https://doi.org/10.6018/analesps.29.3.15098

59.

Martínez-González

R. A.

Iglesias-García

M. T.

(2018). Validation of the parenting competence scale for parents with young children (PCS-YC). Early Child Development and Care, 188(11), 1593–1605. https://doi.org/10.1080/03004430.2018.1490897

60.

McDonald

R. P.

(1999). Test theory: A unified treatment. Lawrence Erlbaum Associates.

61.

Menéndez

Lorence

Sánchez

Pérez-Padilla

(2018). Orientações e recursos para a avaliação psicológica do contexto familiar em situações adversas e risco psicossocial [Guidelines and resources for psychological assessment of the family context in adverse situations and psychosocial risk]. In Nunes

Ayala-Nunes

(Eds.), Famílias em risco: Avaliação e intervenção psicoeducativa (pp. 147–174). Silabas & Desafios.

62.

Moreno

(n.d.). Cuestionario de la Vida Cotidiana para Hogares de Adolescentes (11-15 años) [Daily Life Questionnaire for Adolescent Households (11-15 years)]. University of Seville.

63.

Morin

Myers

Lee

(2020). Modern factor analytic techniques: Bifactor models, exploratory structural equation modeling (ESEM) and bifactor-ESEM. In Tenenbaum

Eklund

R. C.

(Eds.), Handbook of sport psychology (4th ed., pp. 1044–1073). Wiley.

64.

Morin

Marsh

Nagengast

(2013). Exploratory structural equation modeling. In Hancock

Mueller

(Eds.), Structural equation modeling: A second course (pp. 395–436). Information Age.

65.

Muñiz

(2018). Introducción a la Psicometría. Teoría Clásica y TRI [Introduction to Psychometrics. Classical Theory and IRT]. Pirámide.

66.

Muthén

L. K.

Muthén

B. O.

(2017). Mplus user’s guide (6th ed.). Muthén & Muthén.

67.

Okagaki

Bingham

G. E.

(2005). Parents social cognitions and their parenting behaviors. In Luster

Okagaki

(Eds.), Parenting an eco-logical perspective (pp. 3–33). Lea.

68.

Osborne

J. W.

Costello

A. B.

Kellow

J. T.

(2014). Best practices in exploratory factor analysis. CreateSpace Independent Publishing Platform. https://doi.org/10.4135/9781412995627.d8

69.

Osterlind

S. J.

(1998). Constructing test items: Multiple-choice, constructed-response, performance, and other formats (2nd ed.). Kluwer Academic Publishers.

70.

Raykov

(2009). Evaluation of scale reliability for unidimensional measures using latent variable modeling. Measurement and Evaluation in Counseling and Development, 42(3), 223–232. https://doi.org/10.1177/0748175609344096

71.

Reed-Ashcraft

Kirk

R. S.

Fraser

M. W.

(2001). The reliability and validity of the North Carolina family assessment scale. Research on Social Work Practice, 11(4), 503–520. https://doi.org/10.1177/104973150101100406

72.

Rhemtulla

Brosseau-Liard

P. É.

Savalei

(2012). When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychological Methods, 17(3), 354–373. https://doi.org/10.1037/a0029315

73.

Rodrigo

M. J.

Martín

J. C.

Cabrera

Máiquez

M. L.

(2009). Parental competences in psychosocial risk context. Psychosocial Intervention, 18(2), 113–120. https://doi.org/10.5093/in2009v18n2a3

74.

Rodriguez

Reise

S. P.

Haviland

M. G.

(2016). Evaluating bifactor models: Calculating and interpreting statistical indices. Psychological Methods, 21(2), 137–150. https://doi.org/10.1037/met0000045

75.

Rosner

(2006). Fundamentals of biostatistics (6th ed.). Thomson Brooks/Cole.

76.

Sánchez

Baigorri

Barreto

F. B.

Santa-Marina

Arranz-Freijo

E. B.

(2022). Positive parenting assessment in 4-year-old children. Early Child Development and Care, 192(3), 345–361. https://doi.org/10.1080/03004430.2020.1756793

77.

Schermelleh-Engel

Moosbrugger

Müller

(2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23–74. https://www.stats.ox.ac.uk/∼snijders/mpr_Schermelleh.pdf.

78.

Suárez

Byrne

Rodrigo

M. J.

(2016). Validación de la Escala de Parentalidad Positiva (EPP) para evaluar programas presenciales y online de apoyo parental [Validation of the Positive Parenting Scale (PPS) for evaluating face-to-face and online parenting support programs]. Revista de Estudios e Investigación en Psicología y Educación, 3(2), 112–120. https://doi.org/10.17979/reipe.2016.3.2.1883

79.

Tabachnick

B. G.

Fidell

L. S.

(2007). Using multivariate statistics (5th ed.). Harper & Row.

80.

The World Medical Association . (2013). WMA Declaration of Helsinki – Ethical principles for medical research involving human subjects. World Medical Association. https://www.wma.net/policies-post/wma-declaration-of-helsinki-ethical-principles-for-medical-research-involving-human-subjects/

81.

Van Zyl

L. E.

ten Klooster

P. M.

(2022). Exploratory structural equation modeling: Practical guidelines and tutorial with a convenient online tool for Mplus. Frontiers in Psychiatry, 12, 795672. https://doi.org/10.3389/fpsyt.2021.795672

82.

Viladrich

Angulo-Brunet

Eduardo

(2017). A journey around alpha and omega to estimate internal consistency reliability. Anales de Psicología, 33(3), 755–782. https://doi.org/10.6018/analesps.33.3.268401

83.

von Elm

Altman

D. G.

Egger

Pocock

S. J.

Gøtzsche

P. C.

Vandenbroucke

J. P.

STROBE Initiative . (2008). The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. Journal of Clinical Epidemiology, 61(4), 344–349. https://doi.org/10.1016/j.jclinepi.2007.11.008

84.

White

(2005). Assessment of parenting capacity (literature review). Centre for Parenting and Research.

85.

Woodcock

(2003). The social work assessment of parenting: An exploration. British Journal of Social Work, 33(1), 87–106. https://doi.org/10.1093/bjsw/33.1.87

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.29 MB

0.47 MB

0.03 MB

0.25 MB

0.07 MB

0.03 MB

0.42 MB

0.25 MB

0.41 MB