This study was conducted using snowball sampling, immediately after the 2020 confinement (by Sars-Cov-2). The link to the questionnaire, to be completed online, was sent by email and via WhatsApp. The questionnaire was available to complete during the first weeks of June and took about 10 minutes. All the questions required responses. Participants were 438 Spanish parents who completed the questionnaire about themselves, their family and children. Most participants were mothers (90.2%) and they mostly were between 35 and 44 years old. From the participants, 21.9% had one child from 0 to 3 years old, 41.6% had one child from 4 to 10 years old, and 36.5% had one child from 10 to 16 years old. In most cases (89.2%) both parents lived together at home. Most of the participants have university studies (69.2%) and live in houses of more than 50 m2 (98.7%). During confinement, mothers continue to work in the company, or telework, to a lesser extent than fathers (55.3% and 75.6%, respectively). The study met ethical standards of the Helsinki Declaration (Williams, 2008) and has been approved by the Ethics Committee of the University of Oviedo (COPRAMO240/18). Participation in the study was voluntary, and the anonymity and ethical treatment of the data were guaranteed.

Data were collected online through a link. The questionnaire could be completed using a smartphone or any other internet-connected device. It included a section for participants to provide informed consent. The questionnaire included, among other variables, the Parental Burnout Assessment (PBA; Roskam et al., 2018). The PBA has four factors: (i) Exhaustion in one's parental role (9 items; α = .94, ω = .94, rxx = .95; e.g., “I feel completely run down by my role as a parent”), (ii) Contrast with previous parental self (6 items; α = .93, ω = .93, rxx = .90 ; e.g., “I don't think I'm the good father / mother that I used to be to my child (ren)”), (iii) Feelings of being fed up with one's parental role (5 items; α = .90, ω = .91, rxx = .88; e.g., “I can't stand my role as father / mother anymore”), and (iv) Emotional distancing from one's children (3 items; α = .77, ω = .78, rxx = .82; e.g., “I do what I'm supposed to do for my child (ren), but nothing more”). Participants responded on a 5-point scale from 1 (never) to 5 (always). Roskam et al. (2018) obtained evidence of an acceptable fit of this model (CFI = .94; TLI = .93; RMSEA = .07; SRMR = .04).

Data was analyzed in several phases. Using Mplus7.11 (Muthén & Muthén, 1998-2012), confirmatory factor analyzes were run to examine the factorial structure of the Spanish version of the PBA. Two models were fit: unidimensional and multidimensional (i.e., factorial structure of four factors similar to that obtained by Roskam et al., 2018). Afterwards, models fit was assessed as follows: the statistics AIC, BIC, and SSABIC were used to select the best model, and the statistics χ2, CFI, TLI, RMSEA, and SRMR were used to analyze the fit model. The best model is the one with lower AIC, BIC, and SSABIC, showing χ2p > .05, CFI and TLI ≥ .95, and RMSEA and SRMR ≤ .60. The selection of the best model was carried out based on different criteria as follows: the formal test of the adjusted maximum likelihood ratio of Lo, Mendell, and Rubin -LMRT, the Akaike information criteria (AIC), the Bayesian of Schwarz (BIC), and the BIC adjusted for the sample size (SSA-BIC), as well as the value of the entropy and the size of each subgroup or class. Significant p-values associated with LMRT indicated significant improvement in model fit regarding the solution with one less class. Lower AIC, BIC, and SSA-BIC values indicate a better fit of the model. These criteria should complement the information provided by the formal conditional adjustment test. Likewise, it should be noted that small classes (n < 5%), although typically considered spurious classes, sometimes constitute a profile of interest. In order to determine the classification accuracy of the selected model, the posteriori probabilities and the entropy statistic were calculated. This statistic takes values between zero and one; the closer it is to one, the more accurate the classification is (values higher than .80 indicate good classification quality). Finally, for selecting the best model, the theoretical significance of the classes, or profiles, was taken into account. For CFA and LPA, maximum likelihood estimation with robust standard error (MLR) was used.

Finally, our best PBA model was the multifactorial one. Afterwards, based on the four dimensions of PBA, a Latent Profile Analysis (LPA) was carried out to group parents based on their potential profiles of burnout (Lanza et al., 2003). When fitting the models, due to its potential interference on data, gender was included as a covariate (effect of gender on the establishment of classes and the allocation of individuals to them). SAVE = CPROBABILITIES was included in the Mplus syntax to create a variable with the assignment of the subjects to the groups.

Table 1 shows the descriptive statistics and Pearson's correlation matrix corresponding to the 23 items of the PBA. All correlations between items were statistically significant at p <.001. The mean of the items was between 1.46 and 2.55, and the skewness and kurtosis values were within parameters for normality.

Three factorial models were fit: one-dimensional –PBA_1F- (a single factor explains the variability in the 23 items), multidimensional –PBA_4F- with four first-order factors (Exhaustion -9 items-, Contrast in parental self -6 items-, Feelings of being fed up -5 items-, and Emotional distancing -3 items), and hierarchical –PBA_J- with four first-order factors and one second-order factor (general PBA). Data show an evident lack of fit of the three models: unidimensional (χ2230 = 2826.01, p < .001; CFI = .736; TLI = .710; RMSEA = .161; SRMR = .066), multidimensional (χ2224 = 2030.18, p < .001; CFI = .816; TLI = .792; RMSEA = .136; SRMR = .050), and hierarchical (χ2226 = 2075.62, p < .001; CFI = .812; TLI = .789; RMSEA = .137; SRMR = .055). However, considering the values of AIC and BIC, the first order multidimensional model (PBA_4F) was the best fit model of the three: PBA_1F (AIC = 2911.55; BIC = 3099.33), PBA_4F (AIC = 2134.18, BIC = 2346.46), PBA_J (AIC = 2175.62, BIC = 2379.73).

Acknowledging the information provided by the modification indices and the residuals, we learned that the model's lack of a good fit was mainly due to the existence of covariance between some variances. Therefore, the best fitting model (PBA_4F) was re-estimated after including some covariances. The result shows a good fit of the model (χ2207 = 501.93, p < .001; CFI = .970; TLI = .963; RMSEA = .057; SRMR = .036). Consequently, the results suggest the acceptance of the multidimensional model as adequate.

Table 2 shows that the variability of each of the 23 items is significantly explained by their respective theoretical factors. It is observed that the factorial weights are high in most of the items. On the other hand, the reliability of the subscales is high for exhaustion in parental role, contrast in parental self, and feelings of being fed up; and acceptable for the emotional distancing subscale.

Table 3 shows the descriptive statistics and the Pearson correlation matrix corresponding to the four dimensions of PBA and gender. In relation to the four dimensions of the PBA, the skewness and kurtosis data indicate a normal distribution. Taking into account the entire sample, the mean data show medium-low levels in the four dimensions of burnout. The correlation matrix shows that mothers, compared to fathers, present a higher level in two of the four factors of the PBA (exhaustion and contrast in parental self). Moreover, the four factors of the PBA were strongly related.

Several latent profile models were fitted. The variables for class formation were the four dimensions of the PBA. Two, three, four, and five class models were successively fitted. The process was stopped at the five-class model because it was no better than the four-class model (see Table 4).

The four-class model was selected as it presents better fit statistics than the three or the five-class models. On the one hand, the AIC, BIC, and SSA-BIC statistics of the four-class model are lower than those of the three-class model. Furthermore, the LMRT-test of the four-class model was statistically significant, suggesting that this model fits data better than did the three-class model. Likewise, none of the four classes have a number of individuals less than 5%, and the quality of the classification (entropy) of the subjects of the four-class model is better than that of the three-class model. In this model, the parents were very well assigned to the corresponding class (class 1 = .965; class 2 = .934; class 3 = .935; class 4 = .967). On the other hand, although the AIC, BIC, and SSA-BIC statistics of the five-class model were lower than those of the four-class model, the LMRT test indicates that, statistically, the five-class model was no better than the four-class model. However, one of the five classes contains an excessively small number of individuals (1.5%); consequently, the four-class model has been selected as the best fit model.

Table 5 provides the statistics corresponding to the four-class model (profiles), both raw and standardized scores. Figure 1 offers the graphic representation of the four profiles based on the standardized scores.

Figure 1.

Parental burnout profiles based on the combination of the four dimensions of the Parental Burnout Assessment (PBA): EXHAUST (Exhaustion in one's parental role), PARENTSELF (Contrast with previous parental self), FEELINGS (Feelings of being fed up with one's parental role), and EMDISTANCING (Emotional distancing from one's children).

(0.15MB).

The four classes correspond to four different profiles, with a very different number of subjects in each (χ2 (3, 438) = 153.84; p < .001). Specifically, almost half of the sample (46.6%) shows a low profile in the four dimensions of PB (close to a typical score, below the average). This profile was termed Low Parental Burnout Profile -LPBP. Another group of parents was identified (over 28.5%) with a medium PB profile (the standardized scores of the four dimensions of the PBA are around zero). This profile was termed Medium Parental Burnout Profile –MPBP. As for the remaining 25% of fathers and mothers that made up the sample of this study, they constitute two different profiles, both sharing levels higher than the expected average with respect to the dimensions of the PBA. Specifically, 18.9% of fathers and mothers were identified as having high levels of burnout (around a standard deviation above the mean), which we termed High Parental Burnout Profile –HPBP. Finally, the remaining 6% of parents show a very high profile in burnout (about two standard deviations above the mean) and, consequently, were termed Very High Parental Burnout Profile –VHPBP. Also note that the four profiles, in the four dimensions, are statistically different: exhaustion (F (3, 434) = 644.1; p < .001; ηp2 = .817), parental self (F (3, 434) = 477.26; p < . 001; ηp2 = .767), feelings of being fed up (F (3, 434) = 838.55; p < .001; ηp2 = .853), and emotional distancing (F (3, 434) = 191.02; p < .001; ηp2 = .569). Finally, all the comparisons (Bonferroni method) between profiles within each of the four burnout dimensions were statistically significant at p < .001.

The prevalence of PB was estimated based on two procedures, depending on whether a variable-centered perspective (PB) or a person-centered perspective (parental burnout profile) was used. From a variable-centered perspective (PBA total score), Roskam et al. (2021) used the cutoff score of 92 (on a scale from 0 to 138). In our case, since the scale ranges from 23 to 115, the cutoff point was 76. According to this criterion, the prevalence of PB reaches 26.1% (M = 84.87; SD = 9.42). The current study followed a person-centered perspective; data indicate that around 18.9% of the sampled parents present high and 6% very high levels of PB.