Demographics: Participants’ ages varied between 18 and 75 (Mean = 32.63; SD = 14.15). 6.5% of the subjects, did not indicate their educational level, the rest were primary completers or less 4.01%, secondary incomplete 4.37%, completed secondary 16.05%, coursing university or terciarian carriers 43.7%, terciarian or universitarian carrier completed 25.18%). 6.5% of subjects did not indicate their educational level. Regarding marital status, 50.9% of the volunteers were married or in a stable relationship, 42.4% were single or not in a stable relationship and 6.7% did not answer. 35.7% had at least one child.

Confirmatory Factor Analysis: The three models were tested in a CFA performed separately for answers related to the mother and the father, thus 6 different models were tested. The default model showed poor fit in both Mother’s answers χ ² (77) = 328.633; p < 0.001; CFI = 0.762; AIC = 384.633; SRMR = 0.0862; RMSEA = 0.109; 90% confidence interval (CI) [0.097, 0.122]) and Father’s χ ² (77) = 407.773; p < 0.001; CFI = 0.704; AIC = 463.773; SRMR = 0.1009; RMSEA = 0.125; 90% confidence interval (CI) [0.114, 0.138]). Both alternative models showed a better adjustment, (Reduced Model Mother, χ ². (27) = 64.445; p < 0.001; CFI = 0.929; AIC = 100.445; SRMR = 0.0526; RMSEA = 0.071; 90% confidence interval (CI) [0.049, 0.094]; Reduced Model Father, χ ². (27) = 60.494; p < 0.001; CFI = 0.942; AIC = 96.494; SRMR = 0.0532; RMSEA = 0.067; 90% confidence interval (CI) [0.045, 0.09]; 2 Factors Model Mother χ ². (76) = 141.012; p < 0.001; CFI = 0.939; AIC = 199.012; SRMR = 0.0525; RMSEA = 0.056; 90% confidence interval (CI) [0.041, 0.07]; 2 Factors Model Mother X²(76) = 123.528; p < 0.001; CFI = 0.957; AIC = 181.528; SRMR = 0.0541; RMSEA = 0.048; 90% confidence interval (CI) [0.032, 0.063]). Results are summarized in Table 1.

Table 1 Table 1 Model fit statistics for Confirmatory Factor Analysis

Descriptive statistics: Mean and standard deviation of the different measures, along with the alpha coefficient for each of the scales are presented in Table 2. Gender comparisons for each of the variables were performed with a one way ANOVA. Gender differences were detected only for FNR, F(1,272) = 6.927; p < 0.01 and for Family Type Typical, F (1,272) = 7,57; p < 0.01, in both cases males showing higher invalidation levels.

Table 2 Table 2 Means, Standard Deviations, and Internal Consistency of each variable

Correlations between the measures of each instrument are presented in Table 3. Significant correlations (p < 0.01) were observed between every measure except for Family Type Typical and Paternal Overprotection.

Table 3 Table 3 Correlations among variables of the three instruments used Note

*p < 0.05; ** p < 0.005

Linear Regression Analysis: All variables included in the analysis are listed in Table 4. Regression resulted significant (F(10, 273) = 9.345; p < 0.001). The resultant model reached to explain 26% of the variance.

Table 4 Table 4 Multiple Lineal Regression Analysis Note

Bold indicates p < 0.05

The main purpose of the present research was to test the fitness of three different factorial models of the ICES, through a CFA. The default model, originally proposed by the authors, showed poor fit indicators, while two alternative models showed better results. Both, 2 Factor Model and Reduced Model showed good to excellent values of CFI, SRMR and RMSEA indictors. Since the AIC indicator penalizes the number of items, as was expected, it showed better adjustment for the 9 items version than for the 2 factors version. However, we consider that both versions of the instrument can be used: the 9 item version is recommended if items economy is needed, and the 2 factors version, if a broader description of the invalidation is desired.

In comparison to other known factorial studies, our results with a Spanish version of the ICES match the results of a CFA performed in a sample from the United States (Robertson et al., 2013), as well as the CFA performed with the French version (Compagnone & Monaco, 2015), and with the Portuguese version (Vieira et al., 2018) which suggest that ICES factorial structure is consistent across western cultures.

Internal consistency, which in some previous papers using the ICES was reported as low, reached acceptable levels for all the possible scores. Criterial validity was assessed by studying the correlation of the ICES and the PBI. Results were very similar to those observed by Robertson et al. (2013), with high negative correlations between invalidation and care, and moderate positive correlations between invalidation and overprotection. These results are to be anticipated, as it can be inferred that parents who are more caring toward their children are less apt to invalidate them. Similarly, parents who are more controlling of their children may engage in increased invalidation. Family type chaotic, perfect and typical also correlated negatively with care and positively with overprotection, while the opposite was observed for validating families.

BPD symptoms were poorly but significantly associated with the parental behavior with correlations oscillating between 0.154 and 0.355. ICES in general terms showed higher correlation with BSL than PBI, thus invalidation as described by ICES could be more accurate for the study of BT.

The ICES Negative Response sub-scale rates the presence of invalidating responses while Lack of Support the absence of validating responses. Similarly PBI instrument also has one subscale rating desirable parental behavior, Care, and a second subscale that assess undesirable parental behaviors, Control. As can be seen in Table 3, BSL 23 correlated more strongly to items describing undesirable parental behaviors (ICES’ Negative Response, and PBI’s Control) than to items describing desirable behaviors (ICES’ Lack of Support, and PBI’s Care). Additionally, the three invalidating family types also showed a higher association with BSL 23 than the validating type. A rather speculative interpretation could be that, invalidation is stronger as a risk factor than validation as a protective factor. Thus, avoiding invalidation could be a better way to prevent mental disorders than being validating. This hypothesis requires further research.

In a resent experimental study, participants reported more negative emotional reactions to invalidation coming from men than from women (Weber & Herr, 2019). It is not clear if such effect is valid for parental gender since available results are contradictories. In contrast to what was found by Robertson et al. (2013) the model resulting in the linear regression analysis excluded maternal invalidation and included paternal negative responses, as well as the three types of invalidating families. The resulting model also includes age as a predictive factor with a negative beta, which indicates that in this non clinical sample, probability of high BSL levels decrease with age. This result is consistent to the decrement of BPD symptomatology after 10 years, observed in a prospective study with a clinical sample (Álvarez-Tomás et al., 2016). Finally, gender was also selected by the model with a negative beta. As male was codified with 1 and female with 0, the model found that levels of BPD symptoms were reduced in males. Although this result has to be taken with caution since an ANOVA comparing BSL scores between men (ẋ = 9.45) and women (ẋ = 11.05) failed to find differences between genders (p > 0.18).

The model reached to explain only 26% of the variance in the BSL 23 scores. This amount of explained variance does not differ greatly from what was found by other studies using a similar approach (Keng & Wong, 2017; Robertson et al., 2013). In order to generate a better model, other important variables must be included. Hernández, Arntz, Gaviria, Labad, and Gutiérrez-Zotes (2012), using the PBI instead of the ICES to study parental invalidation concluded that traumatic childhood experiences rather than invalidating environment, explained BPD symptomatology better. However, according to BT a big proportion of the variance should presumably be explained by biological variables such as gene polymorphism (Martín-Blanco et al., 2016) or even epigenetics (Dammann et al., 2011; Streit, Colodro-Conde, Hall, & Witt, 2020). In any case, the effect of exposition to invalidation, and neglect during childhood is far from being understood. In fact, parental invalidation was associated with other psychological variables not predicted by Biosocial Therory. For example Gill, Warburton, and Beath (2018) showed that parental invalidation was related to chronic worry, and Arnett, Roach, Elzy, and Jelsone-Swain (2019) founded an association with empathy.

In order to make progress in uncovering the role of childhood invalidation in BPD and development, three types of studies seem to be needed. Studies that assess invalidation in BPD population, general population longitudinal studies, and big samples general population studies with putative gene polymorphism assessment. The results in this paper indicate that the ICES is a reliable instrument potentially useful for any of these proposed studies.