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. Author manuscript; available in PMC: 2025 May 1.
Published in final edited form as: J Pers Assess. 2023 Sep 27;106(3):328–336. doi: 10.1080/00223891.2023.2258961

The Utility of the Level of Personality Functioning Scale in Maternal Samples: A Brief Report

Jennifer J Phillips 1, Michael J Roche 2, Martha Ann Bell 1
PMCID: PMC10965509  NIHMSID: NIHMS1940514  PMID: 37753946

Abstract

Maternal personality plays a role in how a mother parents her children and adolescents. Current trait-based measures of personality are acceptable for use in maternal samples, but the presence or absence of given personality traits may not be enough to describe how personality relates to parenting. The Level of Personality Functioning Scale (LPFS) may serve as a solution, as it was designed to capture level of dysfunction in personality without being reliant on specific personality traits. Research, however, has yet to demonstrate the LPFS as a useful measure of personality in maternal samples, thus the goal of the current study. A sample of 123 mothers reported on behavioral problems in their adolescent-aged children and their own personality using both a trait-based measure and the LPFS. Our data showed that maternal-reports on the LPFS were associated with maternal perceptions of adolescent behavioral problems, in addition to being an acceptable measure of personality in our maternal sample. We also provide support for incremental validity of the LPFS in our sample, as the LPFS uniquely predicted maternal perceptions of adolescent behavioral problems even after controlling for maternal temperament. Our results are discussed in light of the limitations of the extant work on maternal personality and add to the literature by demonstrating that the LPFS is an acceptable and ubiquitous measure of personality in maternal samples.

Keywords: LPFS, ATQ, adolescence, maternal personality

Personality plays a key role in how mothers parent and perceive their children and adolescents (Belsky, 1984; Gratz et al., 2014; Taraban & Shaw, 2018). Trait-based measures of maternal personality, such as the Adult Temperament Questionnaire (ATQ; Evans & Rothbart, 2007), may be related to maternal parenting behaviors, which could in turn influence maternal perceptions of their children (Atzaba-Poria et al., 2014). The presence or absence of certain personality traits, however, may not be sufficient for understanding these intricate associations between maternal personality, maternal parenting, and maternal perceptions of child outcomes (McCabe, 2014). We propose that The Level of Personality Functioning Scale (LPFS), which moves away from trait-based personality assessments and focuses on level of personality dysfunction (APA, 2013), would be a good measure to aid this understanding. To our best knowledge, research has yet to demonstrate the LPFS as a useful measure of personality in maternal samples. Thus, the goals of our current study were to (1) examine the associations among maternal reports on the LPFS and maternal perceptions of adolescent behavioral outcomes and (2) validate the LPFS as a measure of maternal personality. We also explored the incremental validity of the LPFS in the presence of a commonly used trait-based measure of personality in maternal samples (i.e., the ATQ).

Maternal Personality and Maternal Perceptions of Child Outcomes

The first aim of our study was the examine the association between maternal self-report on the LPFS and maternal-reported adolescent behavioral problems. Belsky (1984) identified personality as a crucial component of maternal parenting behaviors, which may then influence maternal perceptions of child outcomes. Indeed, research with Costa and McCrae’s (1997) Five Factor Model (FFM) and the ATQ support these associations. For example, mothers who report higher levels of positively-valanced personality traits tend to report warm and sensitive parenting behaviors, which in turn predict lower levels of maternal-reported child behavioral problems (Hirvonen et al., 2018; McCabe et al., 2014; Smith et al., 2007). Further, mothers tend to report higher levels of behavioral problems and more negatively-valanced temperament traits in their children when they also report high levels of negatively-valanced personality traits in themselves (De Los Reyes & Kazdin, 2005; Hayden et al., 2010). Understanding the association between maternal personality and child outcomes, regardless of whether maternal personality relates directly to child development or influences maternal perceptions of child outcomes, may have important clinical intervention implications.

The majority of the work done to date on the associations between maternal personality and reports of child outcomes has been done in early childhood samples (e.g, Hayden et al., 2010; Smith et al., 2007). This is likely because early childhood is a time when mothers provide their children with an external source of regulation that is important for child development (Bell et al., 2018); however, mothers continue to contribute to development during later childhood and adolescence (Jabeen et al., 2013). Keeping in mind that maternal personality may actually be influencing maternal perceptions of child outcomes, we aimed to examine how maternal personality influences maternal perceptions of adolescent behavior in an effort to expand this literature base.

The Validity of the ATQ and LPFS in Maternal Samples

The second aim of our study was the demonstrate the LPFS as a valid measure of personality in maternal samples by examining its associations with an already validated measure of maternal personality- the ATQ (e.g., Strathearn et al., 2012). The ATQ assesses four broad factors of adult temperament- negative affectivity, surgency/extraversion, effortful control, and orienting sensitivity- and is associated with FFM traits (Evans & Rothbart, 2007). In maternal samples, the ATQ has been used to indirectly predict maternal-reported and observed child outcomes through parenting behaviors (Atzaba-Poria et al., 2014; Festen et al., 2013). Other work has shown that maternal ATQ, particularly the self-regulatory aspects of effortful control and orienting sensitivity, predicts teacher-reports of effortful in toddler-aged children (Zeytinoglu et al., 2017). The self-regulation aspect of temperament/personality plays a key role in child behavioral problems (Kochanska et al., 2009).

The LPFS represents Criterion A of the Alternative Model of Personality Disorders (AMPD) and explains the degree of severity in personality impairment (APA, 2013). The LPFS was developed to capture the core of personality dysfunction, defined through intrapersonal (i.e., identity and self-direction) and interpersonal (i.e., empathy and intimacy) impairments (APA, 2013; Bender et al., 2011). The LPFS was originally developed as a clinician measure of personality dysfunction for the purpose of identifying personality disorders (in an effort to move away from the trait-based assessment of such; Bender et al., 2011), but several self-report measures of the LPFS have been created, with most demonstrating comparable reliability and validity (Roche & Jaweed, 2021). The LPFS can also be reliably used as a valid measure of personality dysfunction in non-clinical samples (e.g., Roche et al., 2018). We propose that the LPFS would be an appropriate measure of personality in maternal samples, given the associations among the intrapersonal and interpersonal components of both the measure and parenting behaviors. For example, intrapersonal identity impairment, which may be related to cold and harsh parenting behaviors, predicts maternal-reported psychopathology in children (Lewis et al., 2023). Further, the interpersonal factor, namely empathy, may be associated with the development of positive social relationships, which in turn might predict warmer parenting behaviors and maternal- and observer-reported optimal child outcomes (Kochanska et al., 2014; Northrup et al., 2023). Because aspects of both the intrapersonal and interpersonal domains appear to indirectly predict child outcomes and parenting behaviors, the LPFS may be an appropriate measure of personality in maternal samples.

Both the ATQ and the LPFS have been validated by using FFM traits (Evans & Rothbart, 2007; Hopwood et al., 2018; McCabe & Widiger, 2020). Given that there has been substantial work on the ATQ as a measure of maternal personality and that our study is the first to our knowledge to explore the utility of the LPFS in a maternal sample, we examined the LPFS in concordance with the ATQ in order to provide support that these measures are both assessing similar constructs in our maternal sample. We are not aware of any prior work that has examined the relations among the ATQ and the LPFS, but we expected these constructs to be associated, given that they are both related to FFM traits. We also explored the incremental validity of the LPFS. Using the AMPD, there are reports of small, but consistent, incremental validity for personality traits and dysfunction being associated with important outcomes, and these effects are more readily demonstrated when using normal range traits that unconfound personality traits and personality dysfunction (Morey et al., 2022). There is still open debate, however, about how redundant the LPFS is with pathological (and even normal range) personality traits (see Sleep et al., 2019). Thus, our examining the ATQ and the LPFS together in the current study will rigorously test the unique contributions of the LPFS over and above the more commonly used trait measures (e.g., ATQ) in explaining variance in maternal reports of adolescent behavioral problems.

The Current Study

In light of existing research linking maternal personality and maternal perceptions of child outcomes (e.g., Hayden et al., 2010), as well as the similarities among the ATQ and the LPFS (being related through the FFM; e.g., Evans & Rothbart, 2007; Hopwood et al., 2018), the overarching goal of our study was to examine the associations among maternal reports on the LPFS and the ATQ and maternal perceptions of adolescent behavioral problems. Given that prior work has demonstrated associations between maternal personality and maternal perceptions of child outcomes (e.g., Atzaba-Poria et al., 2014), the first aim of our study was to examine these associations with the LPFS. We hypothesized that maternal reports on the LPFS would be positively associated with maternal reports of both adolescent internalizing and externalizing behavior problems. The second aim of our study was to examine the associations between maternal reports on the ATQ and the LPFS in an effort to validate the LPFS as a measure of personality in maternal samples by assessing the degree to which these measures explain similar constructs. Because the ATQ and the LPFS are both correlated with FFM traits (e.g., Evans & Rothbart, 2007; Hopwood et al., 2018), we hypothesized that more maternal-reported dysfunction on the LPFS would be correlated with less adaptive ATQ traits (e.g., more negative affect, less effortful control, less surgency, less orienting sensitivity). Finally, we explored the incremental validity of maternal reported LPFS on maternal perceptions of adolescent behavioral problems by controlling for maternal reported ATQ.

Method

Participants

Mothers in the current study came from the Cognition, Affect, and Psychophysiology (CAP) Study, which was a longitudinal investigation of child cognition and emotions across development. Three cohorts of children and their mothers were recruited for the original longitudinal study when the children were infants using flyers, word of mouth, and mailing lists. Mothers from two cohorts are included in the current study, whom represent half of the original sample and were recruited from a small college town in the mid-Atlantic region of the United States. The third cohort was recruited by a university research lab located in a city in a different mid-Atlantic state. Mothers and children in the third cohort ended the longitudinal study when the children were in middle childhood (T1 for the current study), with no adolescent time point (T2 for the current study). This study was approved by the Virginia Tech IRB (T1 protocol #12–947) and the Biomedical Research Alliance of New York (BRANY) IRB (T2 protocol #19-030-569/19-352).

We focused only on maternal-reported data for the current study. Mothers (n = 123) participated at both T1 and T2. At T1, mothers ranged in age from 26 – 53 years (M = 39.70 years, SD = 5.08 years) and children were in middle childhood (M = 9.93 years, SD = 0.75 years). At T2, mothers ranged in age from 31 – 59 years (M = 45.18 years, SD = 4.89 years) and their children were adolescents (M = 14.76 years, SD = 1.93 years). Child gender was evenly split (63 girls, 60 boys). The majority of mothers identified as White (95.2%) and non-Hispanic (98.4%), and smaller proportions identified as Asian (2.4%) or Multi-Racial (2.4%). By T2, 3.3% of mothers had not completed high school, 12.2% had a 2-year college degree, 32.5% had a 4-year college degree, and 51.2% had a graduate degree (0.8% of mothers did not report their education).

Procedure

Mothers were invited to complete a lab visit at T1 that was separate from their child’s T1 lab visit. Each mother completed a questionnaire about her own temperament and her child’s behavioral problems, as well as other cognitive, affective, and parenting measures that were not included in this current study. At T2, mothers completed questionnaires about their own personality and their adolescent’s behavioral problems. Mothers also completed questionnaires about their own adolescent’s emotional and cognitive functioning that are not included in this current study. At both time points, mothers were compensated monetarily for their participation.

Measures

Adult Temperament Questionnaire- Short Form (ATQ- SF)

Mothers self-reported their own temperament using the ATQ- SF (Evans & Rothbart, 2007) at T1. The ATQ- SF contains 77 items that assess general adult temperament traits across multiple scales that are then used to comprise the four temperamental factors of effortful control (EC; 19 items), negative affect (NA; 26 items), surgency (SUR; 17 items), and orienting sensitivity (OS; 15 items). The items are scored on a 7-point Likert scale and several items are reverse-scored so that higher scores on each of the scales indicate higher levels of the respective trait. Scores from each factor were averaged to create four composite scores. In our sample, each factor demonstrated acceptable internal consistency (EC: α = .76; NA: α = .81; SUR: α = .75; OS: α = .65). For simplicity, we refer to the ATQ-SF as the “ATQ” and descriptive statistics for this measure are shown in Table 1.

Table 1.

Correlations Among Study Variables and Descriptive Statistics (After Winsorizing)

1 2 3 4 5 6 7 8 9
1. ATQ NA --
2. ATQ SUR −.49 ** --
3. ATQ EC −.29 ** .12 --
4. ATQ OS .25 ** −.03 .04 --
5. LPFS .30 ** −.37 ** −.25 ** .11 --
6. T1 INT .20 * −.04 −.03 .04 .41 ** --
7. T1 EXT .04 −.14 −.21 * .05 .22 * .33 ** --
8. T2 INT .11 −.06 −.02 .24 ** .41 ** .58 ** .39 ** --
9. T2 EXT .05 .05 −.08 .19 * .28 ** .35 ** .75 ** .58 ** --
Mean 4.27 4.41 4.63 4.56 19.07 6.15 4.80 7.71 5.24
SD 0.55 0.70 0.64 0.55 5.34 5.07 5.19 6.50 6.25
Minimum 2.73 2.16 2.23 2.80 12.00 0.00 0.00 0.00 0.00
Maximum 5.78 6.30 6.08 5.93 36.00 24.00 28.00 34.00 33.00
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Note.

*

indicates significance at the .05 level.

**

indicates significance at the .01 level. T1 = maternal-report during middle childhood; T2 = maternal-report during adolescence. ATQ NA = maternal-reported ATQ negative affect at T1; ATQ SUR = maternal ATQ surgency at T1; ATQ EC = maternal ATQ effortful control at T1; ATQ OS = maternal ATQ orienting sensitivity at T1; LPFS = maternal LPFS total scores at T2; INT = maternal-reported child/adolescent internalizing behaviors; EXT = maternal-reported child/adolescent externalizing behaviors.

Level of Personality Functioning Scale- Brief Form 2.0 (LPFS- BF 2.0)

Mothers self-reported their personality functioning using the LPFS- BF 2.0 (Weekers et al., 2019) at T2. The LPFS- BF 2.0 is a 12-item measure based on the earlier clinician version of the LPFS that was proposed in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; APA, 2013). The LPFS- BF 2.0 consists of two six-item factors capturing intrapersonal (identity, self-direction) and interpersonal (empathy, intimacy) features. The 12-item LPFS- BF 2.0 is scored on a 4-point Likert scale with a 1 indicating low to no levels of personality dysfunction (i.e., better functioning) and a 4 indicating high, disordered levels of personality dysfunction (i.e., poorer functioning). We created a composite score of all 12 items (α = .84), as the LPFS was designed to capture a single continuum of severity, and bifactor analyses have indicated that measures of personality functioning, including the LPFS- BF 2.0, are best represented through a single dimension (Bliton et al., 2021). Some research has suggested that scoring between a 2 and a 3 on the majority of the LPFS- BF 2.0 items is indicative of personality pathology (Weekers et al., 2019). For simplicity, we refer to the LPFS- BF 2.0 as the “LPFS” and descriptive statistics for the measure are shown in Table 1.

Child Behavior Checklist (CBCL)

Mothers reported on child and adolescent internalizing and externalizing behavior problems at T1 and T2 using the CBCL (Achenbach & Rescorla, 2001). The CBCL consists of 99 items regarding child behaviors that are rated in a 3-point Likert scale, with higher scores indicating that a child engages in a given behavior very often. Of interest to the current study were the internalizing and externalizing behaviors scales of the CBCL. The internalizing behaviors scale contains 31 items that assess a variety of internalizing behavior problems, such as withdrawal and anxious/depressive states. The externalizing behaviors scale contains 34 items that assess a variety of behavior problems, such as attention deficits and aggression. The CBCL uses t-scores to give a clinical context of behavioral problems, with an average score being 50 (Achenbach & Rescorla, 2000). In our sample, t-scores for internalizing problems ranged from 33 to 73 (M = 51.42, SD = 9.86) at T1 and from 33 to 77 (M = 52.82, SD = 9.77) at T2. For externalizing problems, t-scores ranged from 33 to 73 (M = 47.35, SD = 9.34) at T1 and from 34 to 73 (M = 47.00, SD = 9.77) at T2. At the recommendation of the authors of the measure, however, the raw scores of the both scales were used in our analyses (Achenbach & Rescorla, 2001). Our sample demonstrated acceptable internalizing consistency for both scales at T1 (internalizing behaviors: α = .88; externalizing behaviors: α = .90) and T2 (internalizing behaviors: α = .87; externalizing behaviors: α = .91). The descriptive statistics for the CBCL raw scores are shown in Table 1.

Missing Data

Of the 123 mothers in the current study, 17 did not complete the LPFS at T2, as it was not added to the protocol until after the data collection began. Further, 31 mothers did not return the ATQ at T1 (given as a paper questionnaire). Because we used correlation and multiple regression for our analyses, we opted to impute missing data points using the expectation-maximization (EM) algorithm in SPSS, as listwise and pairwise deletion can bias estimates and limit power (Enders, 2001; Schafer & Graham, 2002; Widaman, 2006). To use the EM algorithm, data must meet the Missing Completely at Random (MCAR; Little, 1981) assumption, which ours did [χ2(5) = 20.30, p = .92].

Results

Preliminary Analyses

Prior to analyses, descriptive statistics were examined and the data were inspected for outliers and normality of distributions using IBM SPSS software (Version 27). No evidence of nonnormality was detected, as both skewness and kurtosis of all variables fell within acceptable levels (i.e., skewness ≤ 3 and kurtosis ≤ 10; Kline, 2011). Outliers were defined as values that were ±3SD of the mean, and the number of outliers present in the dataset are as follows: ATQ SUR (1 case ≤ −3SD), ATQ EC (1 case ≤ −3SD), Maternal LPFS (1 case ≥ +3SD), child internalizing behaviors at age 9 (1 case ≥ +3SD) and adolescence (2 cases ≥ +3SD), and child externalizing behaviors at age 9 (4 cases ≥ +3SD) and adolescence (2 cases ≥ +3SD). Our analyses were conducted with the outliers retained and with the outliers handled via Winsorization, which is an outlier management technique that replaces outliers with the next closest score (Salkind, 2010). Because the results and significance levels did not change as a function of outlier treatment, we present our results below with the outliers retained in the dataset. All predictor variables were mean centered prior to conducting the regression analyses.

There were 79 mothers who completed the T2 questionnaires prior to the COVID-19 pandemic (mid-August 2019 through mid-March 2020) and 44 mothers who completed the questionnaires during the COVID-19 pandemic (late-August through early-October 2020). Because of the socioemotional and economic upheavals that the pandemic caused for some in the United States (Prime et al., 2020), we conducted independent samples t-tests among all of the T2 variables used in our study (i.e., maternal LPFS, maternal-reported adolescent behavioral problems). No differences were observed between the prior- and during-COVID groups for maternal LPFS and maternal-reported adolescent internalizing behaviors (ps ≥ .12). There was a group difference, however, for maternal-reported adolescent externalizing behaviors [t(121) = −2.22, p = .01), with mothers reporting more externalizing behaviors in their adolescents during the pandemic (M = 6.89, SD = 7.23) than prior to the pandemic (M = 4.32, SD = 5.47). Thus, we controlled for COVID-19 group in our subsequent analyses (0 = prior, 1 = during).

Hypothesis 1: Maternal Reports on the LPFS and Maternal Perceptions of Adolescent Behavioral Problems

Our first hypothesis was that higher maternal LPFS ratings would be positively associated with maternal perceptions of adolescent internalizing and externalizing behavior problems. The zero-order correlations among these two measures are shown in Table 1. Our data demonstrated positive correlations, such that higher maternal ratings on the LPFS were associated with more maternal-perceived adolescent internalizing and externalizing behaviors.

To ensure that these results were not due to maternal LPFS and maternal perceptions of adolescent behavioral problems being collected concurrently at T2, we also examined zero-order correlations between maternal T1 ATQ and maternal perceptions of child and adolescent internalizing and externalizing behaviors at T1 and T2. ATQ EC and NA were positively associated with T1 maternal perceptions of child internalizing behaviors and ATQ OS was positively associated with maternal perceptions of adolescent internalizing behaviors at T2. These associations were in the expected directions.

Hypothesis 2: Associations Between Maternal ATQ and LPFS

Second, we hypothesized that more maternal personality dysfunction would be associated with less adaptive maternal ATQ traits. The zero-order correlations are shown in Table 1. As expected, our data showed a positive association between ATQ NA and LPFS and negative associations between ATQ SUR and LPFS and between ATQ EC and LPFS.

Incremental Validity of the LPFS

The third aim of our study was to explore the incremental validity of the LPFS as a measure of maternal personality, compared to the ATQ. We did this by using two hierarchical regression models that assessed the associations between the LPFS, ATQ factors, and maternal perceptions of adolescent internalizing behaviors (Model 1) and maternal perceptions of adolescent externalizing behaviors (Model 2). Again, given that maternal ATQ responses were collected, on average, 5.48 years prior to maternal perceptions of adolescent behavioral problems and maternal LPFS responses, we controlled for maternal perceptions of child behavior problems at T1 in Step 1 of their respective models to ensure that our results would not be attributed to the concurrent nature of the maternal LPFS responses and maternal perceptions of adolescent behavioral problems. Both models were run twice, with one controlling for LPFS in Step 2 (Models 1A and 2A) and one controlling for ATQ factors in Step 2 (Models 1B and 2B).

Maternal Perceptions of Adolescent Internalizing Behavior Problems

All three steps of Model 1A were significant and demonstrated medium effect sizes (Cohen’s f2 ≥ 0.50 in all three steps). In Step 2, the LPFS explained was positively associated maternal perceptions of adolescent internalizing behaviors. In Step 3, ATQ factors explained an additional 5.0% of variance in maternal perceptions of adolescent internalizing behaviors, but the only ATQ factor that was associated with maternal perceptions of adolescent internalizing behaviors, was OS (in addition to the LPFS). Likewise, all three steps of Model 1B were significant and demonstrated (Cohen’s f2 ≥ 0.50 in all three steps). In Step 2, ATQ OS was positively associated with maternal perceptions of adolescent internalizing behaviors. In Step 3, the LPFS explained an additional 3.0% of variance in maternal perceptions of adolescent internalizing behaviors and the LPFS and ATQ OS were both positively associated with such. The results of Model 1A and 1B are shown in Table 2.

Table 2.

Incremental Validity of Maternal LPFS in Predicting Adolescent Internalizing Behaviors

DV = T2 Maternal-Reported Adolescent INT
Model 1A: ATQ as predictor, controlling for LPFS
B 95% CI
Step 1 COVID-19 .08 −0.86, 3.12
 T1 INT .57 ** 0.54, 0.92
R = .58, F(120,2) = 31.10, Adj. R2 = .33, p < .001**; Cohen’s f2 = 0.50
Step 2 COVID-19 .10 −0.61, 3.27
 T1 INT .48 ** 0.41, 0.82
 LPFS Total .22 * 0.08, 0.46
R = .62, F(119,1) = 7.87, Adj. R2 = .37, ΔR2 = .04, p = .006*; Cohen’s f2 = 0.59
Step 3 COVID-19 .10 −0.52, 3.33
 T1 INT .49 ** 0.43, 0.83
 LPFS Total .22 * 0.06, 0.47
 ATQ_NA −.11 −3.32, 0.85
 ATQ_SUR −.03 −1.86, 1.33
 ATQ_EC .01 −1.40, 1.69
 ATQ_OS .23 * 0.97, 4.42
R = .66, F(115,4) = 2.57, Adj. R2 = .40, ΔR2 = .05, p = .042*; Cohen’s f2 = 0.73
Model 1B: LPFS as predictor, controlling for ATQ
B 95% CI
Step 1 COVID-19 .08 −0.86, 3.12
 T1 INT .57 ** 0.54, 0.92
R = .58, F(120,2) = 31.10, Adj. R2 = .33, ΔR2 = .34, p < .001**; Cohen’s f2 = 0.50
Step 2 COVID-19 .10 −0.58, 3.37
 T1 INT .58 ** 0.55, 0.93
 ATQ_NA −.11 −3.43, 0.83
 ATQ_SUR −.10 −2.48, 0.60
 ATQ_EC −.03 −1.85, 1.22
 ATQ_OS .25 ** 1.20, 4.71
R = .63, F(116,4) = 2.94, Adj. R2 = .37, ΔR2 = .06, p = .024*; Cohen’s f2 = 0.64
Step 3 COVID-19 .10 −0.52, 3.34
 T1 INT .49 0.43, 0.83
 ATQ_NA −.11 −3.32, 0.85
 ATQ_SUR −.03 −1.86, 1.33
 ATQ_EC .01 −1.40, 1.69
 ATQ_OS .23 * 0.97, 4.42
 LPFS Total .22 * 0.06, 0.47
R = .66, F(115,1) = 6.23, Adj. R2 = .40, ΔR2 = .03, p = .014*; Cohen’s f2 = 0.73
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Note.

*

indicates significance at the .05 level.

**

indicates significance at the .01 level. T1 = maternal-report during middle childhood; T2 = maternal-report during adolescence. ATQ NA = maternal-reported ATQ negative affect at T1; ATQ SUR = maternal ATQ surgency at T1; ATQ EC = maternal ATQ effortful control at T1; ATQ OS = maternal ATQ orienting sensitivity at T1; LPFS = maternal LPFS total scores at T2; INT = maternal-reported child/adolescent internalizing behaviors; EXT = maternal-reported child/adolescent externalizing behaviors.

Maternal Perceptions of Adolescent Externalizing Behaviors

All three steps of model 2A were significant and demonstrated large effect sizes (Cohen’s f2 ≥ 1.28 in all three steps). In Step 2, the LPFS was positively associated with maternal perceptions of adolescent externalizing behaviors. In Step 3, ATQ factors explained an additional 7.0% of variance in maternal perceptions of adolescent externalizing behaviors, with maternal SUR, EC, and OS, in addition to the LPFS, all positively associated with such. Likewise, all three steps of Model 2B were significant and demonstrated large effect sizes (Cohen’s f2 ≥ 1.28 in all three steps). In Step 2, maternal SUR and OS were positively associated with maternal perceptions of adolescent externalizing behaviors. In Step 3, the LPFS explained an additional 3.0% of variance in maternal perceptions of adolescent externalizing behaviors and was positively associated with such, in addition to maternal SUR, EC, and OS. The results of Models 2A and 2B are shown in Table 3.

Table 3.

Incremental Validity of Maternal LPFS in Predicting Adolescent Externalizing Behaviors

DV = T2 Maternal-Reported Adolescent EXT
Model 2A: ATQ as predictor, controlling for LPFS
B 95% CI
Step 1 COVID-19 .15 * 0.46, 3.49
 T1 EXT .74 ** 0.75, 1.03
R = .77, F(120,2) = 84.63, Adj. R2 = .58, p < .001; Cohen’s f2 = 1.38
Step 2 COVID-19 .16 * 0.54, 3.53
 T1 EXT .71 ** 0.72, 1.00
 LPFS Total .12 * 0.01, 0.28
R = .77, F(119,1) = 4.34 , Adj. R2 = .59, ΔR2 = .02, p = .039; Cohen’s f2 = 1.65
Step 3 COVID-19 .14 * 0.37, 3.19
 T1 EXT .75 ** 0.77. 1.04
 LPFS Total .18 * 0.08, 0.36
 ATQ_NA .10 −0.38, 2.64
 ATQ_SUR .24 ** 0.94, 3.26
 ATQ_EC .12 * 0.01, 2.29
 ATQ_OS .12 * 0.13, 2.67
R = .82, F(115,4) = 6.10, Adj. R2 = .65, ΔR2 = .07, p < .001; Cohen’s f2 = 1.87
Model 2B: LPFS as predictor, controlling for ATQ
B 95% CI
Step 1 COVID-19 .15 * 0.46, 3.49
 T1 EXT .74 ** 0.75, 1.03
R = .77, F(120,2) = 84.63, Adj. R2 = .58, , p < .001; Cohen’s F2 = 1.28
Step 2 COVID-19 .14 * 0.39, 3.32
 T1 EXT .77 ** 0.79, 1.07
 ATQ_NA .12 −0.23, 2.88
 ATQ_SUR .18 * 0.46, 2.79
 ATQ_EC .09 −0.32, 2.02
 ATQ_OS .14 * 0.26, 2.88
R = .80, F(116,4) = 4.63, Adj. R2 = .62, ΔR2 = .06, p = .002; Cohen’s f2 = 1.35
Step 3 COVID-19 .14 * 0.37, 3.19
 T1 EXT .74 ** 0.77, 1.04
 ATQ_NA .10 −0.38, 2.64
 ATQ_SUR .24 ** 0.94, 3.26
 ATQ_EC .18 * 0.01, 2.29
 ATQ_OS .12 * 0.13, 2.67
 LPFS Total .19 * 0.08, 0.36
R = .82, F(115,1) = 9.59, Adj. R2 =.65, ΔR2 = .03, p = .002; Cohen’s f2 = 1.87
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Note.

*

indicates significance at the .05 level.

**

indicates significance at the .01 level. T1 = maternal-report during middle childhood; T2 = maternal-report during adolescence. ATQ NA = maternal-reported ATQ negative affect at T1; ATQ SUR = maternal ATQ surgency at T1; ATQ EC = maternal ATQ effortful control at T1; ATQ OS = maternal ATQ orienting sensitivity at T1; LPFS = maternal LPFS total scores at T2; INT = maternal-reported child/adolescent internalizing behaviors; EXT = maternal-reported child/adolescent externalizing behaviors.

Discussion

The overarching goal of our current study was to examine the utility of the LPFS as a measure of personality in maternal samples by assessing the relations between maternal reports on the LPFS and the ATQ and maternal perceptions of adolescent behavioral problems. Our data supported our hypotheses, demonstrating that (1) maternal LPFS reports were positively associated with maternal perceptions of adolescent behavioral problems, and (2) maternal reports of negative temperament traits on the ATQ were associated with greater levels of maternal-reported personality dysfunction on the LPFS. Additionally, our data provided evidence for incremental validity of the LPFS in our maternal sample.

In our current study, we demonstrated that maternal-reported personality dysfunction using the LPFS was associated with greater maternal perceptions of both adolescent internalizing and externalizing behaviors. Maternal personality has been shown to indirectly influence maternal perceptions of child outcomes through parenting (e.g., Hirvonen et al., 2018), perhaps because personality is a key predictor of parenting (Belsky, 1984; Taraban & Shaw, 2018). Others, however, have recently demonstrated maternal personality to directly predict maternal perceptions of child behaviors and outcomes (Wu & Feng, 2021). The prior work, however, has focused on maternal personality traits. We thus added to the literature with our current study by demonstrating that maternal personality dysfunction (via maternal report on the LPFS) was directly associated with maternal perceptions of adolescent behavioral problems, which is an age group that has received less attention in the extant work. Additionally, given that the LPFS places focus on intrapersonal and interpersonal functioning, both of which are important predictors of parenting (e.g., Lewis et al., 2023; Northrup et al., 2023), we suggest that our results support the use of the LPFS in maternal samples. That is, the LPFS may be useful in capturing impairment in areas of personality that may be important for parenting (e.g., capacity and enactment of empathy) that trait-based measures, like the ATQ, may not capture. Because we did not actually assess parenting behaviors in our current study, however, we interpret this result cautiously. With prior work suggesting that maternal personality may alter maternal perceptions of child behavioral problems (De Los Reyes et al., 2005, Hayden et al., 2010), we acknowledge that more research on how maternal reports on the LPFS actually influence both maternal perceptions of child outcomes and actual child developmental outcomes (assessed by outside observers) is necessary.

Our results also support the notion that the LPFS is a valid measure personality in maternal samples. Specifically, our data demonstrated that mothers who reported more dysfunction using the LPFS also reported greater levels of NA and OS and lower levels of SUR and EC on the ATQ. The directions of three of these correlations were expected, as prior work has linked higher levels of NA and lower levels of SUR and EC to personality disorders (e.g., Posner et al., 2003). The positive association between ATQ OS and LPFS, however, was unexpected, as prior work has suggested that OS may protect against personality disorders (Posner et al., 2003). The correlation coefficients that we observed between the LPFS and the ATQ factors, with the exception of that between the LPFS and ATQ SUR (r = −.49), were weaker than what are usually observed in literature on traits and personality dysfunction (e.g., r = .48; Hopwood et al., 2018). Because the magnitude of the association (r = .41) between the LPFS and maternal perceptions of T1 externalizing problems was comparable to what has been observed in prior work, but that between the LPFS and maternal perceptions of T2 externalizing problems (r = .22) was not, we do not have reason to believe that the weaker coefficients between the LPFS and the majority of the ATQ factors in our current study were due to the distance in time between completing the two measures. Rather, we argue that the weaker than typically observed coefficients may suggest that the LPFS and the ATQ were operating more distinctly from each other in our current study, compared to the LPFS and other trait-based measures, like the FFM, in prior work. The comparable association between the LPFS and ATQ SUR in our current study, however, could be due to the high correlation that research has established between ATQ SUR and FFM extraversion (Evans & Rothbart, 2007). More work should be done to fully understand the associations between the LPFS and trait-based measures of personality in maternal samples.

Our current study also provides evidence for incremental validity of the LPFS. There is a central debate in the personality disorder literature about whether or not the LPFS is redundant with pathological traits (Sleep et al., 2019). Given that maternal personality is often assessed through trait-based measures, like the ATQ (e.g., Atzaba-Poria et al., 2014), we used the current study as an opportunity to explore the incremental validity of the LPFS in our maternal sample. Usually, incremental validity is 2–3 times larger for pathological traits than it is for the LPFS (Sleep et al., 2019). Our data arrived at similar results, showing that the LPFS explained additional variance (about 3%) in maternal perceptions of adolescent internalizing and externalizing behaviors and the ATQ incrementing around 5–7%. Despite the ATQ explaining more variance in maternal perceptions of adolescent behavioral problems, our results suggest that the LPFS indeed plays a significant role in explaining such. That is, both the ATQ and the LPFS were shown to be important in describing the association between maternal personality and maternal perceptions of adolescent behavioral problems. Specifically, when considered in tandem, maternal reports on the ATQ OS and LPFS were positively associated with maternal perceptions of adolescent internalizing behaviors and maternal reports on ATQ EC, SUR, and OS and the LPFS positively predicted maternal perceptions of adolescent externalizing behaviors. The directions of all of the correlations were expected, with the exception of the positive association among ATQ OS and maternal perceptions of externalizing behaviors. Prior work has demonstrated that lower levels of OS predict less optimal child outcomes and maternal perceptions of such (Gölcük & Berument, 2021). Out of all of the ATQ factors, OS had the lowest reliability (α = .65) in our sample, which could help explain this unexpected result. Although more work is certainly warranted to fully understand the influences of the LPFS and trait-based personality measures in maternal samples on maternal perceptions of and observed child and adolescent outcomes, our results suggest that personality dysfunction appears to be a unique contributor to such.

Strengths, Limitations, Future Directions, and Conclusion

Our current study is foundational in examining the utility and validity of the LPFS as a measure of personality in maternal samples. One strength was that using the LPFS allowed us to examine maternal personality functioning within the factors of intrapersonal and interpersonal features that may also relate to parenting, which may not be captured through trait-based personality assessments. Another strength was that our results suggest that the LPFS is a unique measure of maternal personality that is distinct from other assessments. Our study also demonstrated that the LPFS has comparable incremental validity as others have demonstrated.

Despite these strengths, we acknowledge the limitations of our current study. First, even though personality remains relatively stable across adulthood (Roberts & Jackson, 2008), we did not examine the ATQ and the LPFS concurrently. Although we attempted to remedy this confound through control of maternal perceptions of child behavioral problems at T1, we would have a stronger argument for the stability and utility of maternal LPFS reports if they were concurrent. Second, we did not assess maternal parenting behaviors of adolescents. Prior work has suggested that maternal personality predicts parenting behaviors (Belsky, 1984; Taraban & Shaw, 2018), which then indirectly predicts child outcomes (e.g., Hirvonen et al., 2018). Although we made the case that the intrapersonal and interpersonal domains of the LPFS contain areas of personality functioning that may be important for parenting (e.g., Lewis et al., 2023; Nortrup et al., 2023), actually assessing maternal parenting behaviors in our adolescent-aged sample would have been beneficial in providing additional evidence in this regard. Third, our study lacked racial and ethnic diversity. Although our sample was representative of the geographical area in which our research was conducted, the lack of overall diversity limits the generalizability of our results. Fourth, we did not assess the FFM in our sample, which makes us limited in our ability to describe the LPFS as comparable to trait-based measures of personality in maternal samples. We based our hypotheses on the premise that both the ATQ and LPFS are associated with the FFM (e.g., Evans & Rothbart, 2007; Hopwood et al., 2018), but having the FFM in our study would have strengthened our conclusion. Finally, we only focused on mothers in our current study. Recent work has suggested that paternal personality traits have an effect on observer-reports of child outcomes (Allen & Laborde, 2022), so it would have been beneficial to incorporate paternal LPFS reports in the current study.

In addition to addressing the limitations above, future work should consider incorporating adolescent-reports of behavioral problems, as well as clinician or teacher reports. Because our study is only able to tell us how maternal LPFS reports influence maternal perceptions of adolescent behaviors, it would be beneficial to include other reports so that actual developmental outcomes can be captured. Further, future work should consider examining the associations between maternal LPFS reports and objective measures of child development (e.g., non-maternal reports), as well as maternal perceptions of child behavior. We focused on adolescents in the current study due to the lack of research on this age group regarding the effects of maternal personality on maternal perceptions of adolescent behavioral problems, but there is no work to our knowledge that has examined the associations between maternal LPFS reports and early childhood outcomes, both maternal- and non-maternal-reported. Given that young children rely on their mothers to help shape their developmental course (Bell et al., 2018), examining maternal reports on the LPFS at this time could be beneficial in understand how maternal personality helps shape outcomes.

To our knowledge, this is the first study that used the LPFS as a measure of personality in maternal samples. This is instrumental to the field, as our results suggest that we can capture maternal personality in a way that is related to functioning in intrapersonal and interpersonal domains, that may in turn be related to parenting. More work is needed to fully understand how maternal LPFS ratings shape maternal perceptions and observer-ratings of child development, but our study serves as an important first step.

Acknowledgments

This research was partially supported by grant R01 HD049878 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NICHD or the National Institutes of Health. The authors have no conflicts of interest to disclose. The data that support the findings of this study are available from the corresponding author upon reasonable request. We are grateful to the families for their participation in our research.

References

  1. Achenbach TM, & Rescorla LA (2001). Manual for the ASEBA school-age forms and profiles. University of Vermont Research Center for Children, Youth, and Families. [Google Scholar]
  2. Allen MS, & Laborde S (2022). Parent personality traits and adolescent sexual behaviour: Cross-sectional findings from the Longitudinal Study of Australian Children. Personality and Individual Differences, 195(6), 111682. https://doi.org/kb9z [Google Scholar]
  3. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). American Psychiatric Publishing. [Google Scholar]
  4. Atzaba-Poria N, Deater-Deckard K, & Bell MA (2014). It takes more than one for parenting: How do maternal temperament and child’s problem behaviors relate to maternal parenting behavior? Personality and Individual Differences, 69, 81–86. https://doi.org/f6c3wd [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bell MA, Broomell APR, & Patton LK (2018). Emotion regulation. In Bornstein M (Ed.), The SAGE encyclopedia of lifespan human development (pp. 732–734). SAGE Publications. [Google Scholar]
  6. Belsky J (1984). The determinants of parenting: A process model. Child Development, 55(1), 83–96. https://doi.org/fcd2k9 [DOI] [PubMed] [Google Scholar]
  7. Bender DS, Morey LC, & Skodol AE (2011). Toward a model for assessing level of personality functioning in DSM–5, part I: A review of theory and methods. Journal of Personality Assessment, 93(4), 332–346. https://doi.org/d2tcg6 [DOI] [PubMed] [Google Scholar]
  8. Bliton CF, Roche MJ, Pincus AL, & Dueber D (2022). Examining the structure and validity of self-report measures of DSM-5 Alternative Model for personality disorders Criterion A. Journal of Personality Disorders, 36(2), 157–182. https://doi.org/gmg247 [DOI] [PubMed] [Google Scholar]
  9. Costa PT, & McCrae RR (1997). Longitudinal stability of adult personality. In Hogan R, Johnson J, & Briggs S (Eds.), Handbook of personality psychology (pp. 269–290). Academic Press. [Google Scholar]
  10. De Los Reyes A, & Kazdin AE (2005). Informant discrepancies in the assessment of childhood psychopathology: A critical review, theoretical framework, and recommendations for further study. Psychological Bulletin, 131(4), 483–509. https://doi.org/b8b352 [DOI] [PubMed] [Google Scholar]
  11. Enders CK (2001). The performance of the full information maximum likelihood estimator in multiple regression models with missing data. Educational and Psychological Measurement, 61(5), 713–740. 10.1177/0013164401615001 [DOI] [Google Scholar]
  12. Evans DE, & Rothbart MK (2007). Developing a model for adult temperament. Journal of Research in Personality, 41(4), 868–888. https://doi.org/cfp5km [Google Scholar]
  13. Festen H, Hartman CA, Hogendoorn S, de Haan E, Prins PJM, Reichart CG, Moorlag H, & Nauta MH (2013). Temperament and parenting predicting anxiety change in cognitive behavioral therapy: The role of mothers, fathers, and children. Journal of Anxiety Disorders, 27(3), 289–297. https://doi.org/f42gqj [DOI] [PubMed] [Google Scholar]
  14. Gölcük M, & Berument SK (2021). The relationship between negative parenting and child and maternal temperament. Current Psychology, 40(1–2), 3596–3608. https://doi.org/kb93 [Google Scholar]
  15. Gratz KL, Kiel EJ, Latzman RD, David Elkin T, Moore SA, & Tull MT (2014). Maternal borderline personality pathology and infant emotion regulation: Examining the influence of maternal emotion-related difficulties and infant attachment. Journal of Personality Disorders, 28(1), 52–69. https://doi.org/f5rn69 [DOI] [PubMed] [Google Scholar]
  16. Hayden EP, Durbin CE, Klein DN, & Olino TM (2010). Maternal personality influences the relationship between maternal reports and laboratory measures of child temperament. Journal of Personality Assessment, 92(6), 586–593. https://doi.org/bd7jgb [DOI] [PubMed] [Google Scholar]
  17. Hirvonen R, Väänänen J, Aunola K, Ahonen T, & Kiuru N (2018). Adolescents’ and mothers’ temperament types and their roles in early adolescents’ socioemotional functioning. International Journal of Behavioral Development, 42(5), 453–463. https://doi.org/gd5g9r [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Hopwood CJ, Good EW, & Morey LC (2018). Validity of the DSM-5 Levels of Personality Functioning Scale-self report. Journal of Personality Assessment, 100(6), 650–659. https://doi.org/ggtp3n [DOI] [PubMed] [Google Scholar]
  19. IBM (2022). SPSS Statistics for Windows, Version 28 (27.0). IBM Corp. [Google Scholar]
  20. Jabeen F, Anus-ul-Haque M, & Rizam MN (2013). Parenting styles as predictors of emotion regulation among adolescents. Pakistan Journal of Psychological Research, 28(1), 85–105. [Google Scholar]
  21. Kline RB (2011). Principles and practice of structural equation modeling. (3rd ed.). Guilford Press. [Google Scholar]
  22. Kochanska G, Barry RA, Jimenez NB, Hollatz AL, & Woodward J (2009). Guilt and effortful control: Two mechanisms that prevent disruptive developmental trajectories. Journal of Personality and Social Psychology, 97(2), 322–333. https://doi.org/djmr6t [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kochanska G, Friesenborg AE, Lange LA, & Martel MM (2004). Parents’ personality and infants’ temperament as contributors to their emerging relationship. Journal of Personality and Social Psychology, 86(5), 744–759. https://doi.org/bv99pc [DOI] [PubMed] [Google Scholar]
  24. Lewis MBE, Slter JJ, McGinley M, & Rote WM (2023). Understanding the link between anxious parental overprotection and academic confidence in emerging adults: Mediation through interpersonal and intrapersonal processes. Journal of Social and Personal Relationships. Advance online publication. https://doi.org/kb96 [Google Scholar]
  25. Little RJA (1988). A test of missing completely at random for multivariate data with missing values. Journal of the American Statistical Association, 83, 1198–1202. https://doi.org/gd23bv [Google Scholar]
  26. McCabe JE (2014). Maternal personality and psychopathology as determinants of parenting behavior: A quantitative integration of two parenting literatures. Psychological Bulletin, 140(3), 722–750. https://doi.org/f5zwwk [DOI] [PubMed] [Google Scholar]
  27. McCabe GA, & Widiger TA (2020). Discriminant validity of the alternative model of personality disorder. Psychological Assessment, 32(12), 1158–1171. https://doi.org/ghcvnz [DOI] [PubMed] [Google Scholar]
  28. Morey LC, Good EW, & Hopwood CJ (2022). Global personality dysfunction and the relationship of pathological and normal trait domains in the DSM-5 alternative model for personality disorders. Journal of Personality, 90(1), 34–46. https://doi.org/gn2k49 [DOI] [PubMed] [Google Scholar]
  29. Northrup JB, Llamas B, Moses-Kolko EL, Phillips ML, Keenan K, & Hipwell AE (2023). Preconception interpersonal personality features predict postpartum maternal parenting behaviors. Journal of Family Psychology. Advance online publication. https://doi.org/kb97 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Prime H, Wade M, & Browne DT (2020). Risk and resilience in family well-being during the COVID-19 pandemic. American Psychologist, 75(5), 631–643. https://doi.org/ggzg88 [DOI] [PubMed] [Google Scholar]
  31. Posner MI, Rothbart MK, Vizueta N, Thomas KM, Levy PN, Fossella J, Silbersweig D, Stern E, Clarkin J, & Kernberg O (2003). An approach to the psychobiology of personality disorders. Development and Psychopathology, 15(4), 1093–1106. https://doi.org/djvq5m [DOI] [PubMed] [Google Scholar]
  32. Roberts BW, & Jackson JJ (2008). Sociogenomic personality psychology. Journal of Personality, 76(6), 1523–1544. https://doi.org/dzd4nk [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Roche MJ, Jacobson NC, & Phillips JJ (2018). Expanding the validity of the Level of Personality Functioning Scale observer-report and self-report versions across psychodynamic and interpersonal paradigms. Journal of Personality Assessment, 100(6), 571–580. https://doi.org/hmqx [DOI] [PubMed] [Google Scholar]
  34. Roche MJ, & Jaweed S (2021). Comparing measures of Criterion A to better understand incremental validity in the Alternative Model of Personality Disorders. Assessment, 1–17. https://doi.org/gnvdh7 [DOI] [PubMed] [Google Scholar]
  35. Salkind N (2010). Encyclopedia of Research Design. SAGE Publications, Inc. https://doi.org/gc9z3d [Google Scholar]
  36. Schafer JL, & Graham JW (2002). Missing data: Our view of the state of the art. Psychological Methods, 7(2), 142–177. https://doi.org/dsvqnz [PubMed] [Google Scholar]
  37. Sleep CE, Lynam DR, Widiger TA, Crowe ML, & Miller JD (2019). An evaluation of DSM–5 Section III personality disorder Criterion A (impairment) in accounting for psychopathology. Psychological Assessment, 31(10), 1181. https://doi.org/kb98 [DOI] [PubMed] [Google Scholar]
  38. Smith CL, Spinrad TL, Eisenberg N, Gaertner BM, Popp TK, & Maxon E (2007). Maternal personality: Longitudinal associations to parenting behavior and maternal emotional expressions toward toddlers. Parenting, 7(3), 305–329. https://doi.org/c7p2b6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Stathearn L, Iyengar U, Fonagy P, & Kim S (2012). Maternal oxytocin response during mother-infant interaction: Associations with adult temperament. Hormones and Behavior, 61(3), 429–435. https://doi.org/fz34b3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Taraban L, & Shaw DS (2018). Parenting in context: Revisiting Belsky’s classic process of parenting model in early childhood. Developmental Review, 48, 55–81. https://doi.org/gdq8sw [Google Scholar]
  41. Weekers LC, Hutsebaut J, & Kamphuis JH (2019). The Level of Personality Functioning Scale-Brief Form 2.0: Update of a brief instrument for assessing level of personality functioning. Personality and Mental Health, 13(1), 3–14. https://doi.org/hmq4 [DOI] [PubMed] [Google Scholar]
  42. Widaman KF (2006). Missing data: What to do with or without them. Monographs of the Society for Research in Child Development, 71(3), 42–64. https://doi.org/d53grj [Google Scholar]
  43. Wu Q, & Feng X (2020). Infant emotion regulation and cortisol response during the first 2 years of life: Associations with maternal parenting profiles. Developmental Psychobiology, 62(8). 1076–1091. https://doi.org/gmn3mx [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Zeytinoglu S, Calkins SD, Swingler MM, & Leerkes EM (2017). Pathways from maternal effortful control to child self-regulation: The role of maternal emotional support. Journal of Family Psychology, 31(2), 170–180. https://doi.org/f9zshv [DOI] [PMC free article] [PubMed] [Google Scholar]

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