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. Author manuscript; available in PMC: 2024 Mar 13.
Published in final edited form as: J Marital Fam Ther. 2023 Sep 26;49(4):958–978. doi: 10.1111/jmft.12671

Parental efficacy after a military parenting program: A dyadic latent growth model

Qiyue Cai 1, Sydni Basha 1, Abigail H Gewirtz 1,2
PMCID: PMC10936559  NIHMSID: NIHMS1970153  PMID: 37752720

Abstract

Parental efficacy is an important aspect of parenting and a key outcome in many parenting programs. However, most studies focus on mothers, and less is known about the relationship between coparents’ parental efficacy over time following intervention, and how parental distress can impact parental efficacy. The current study (N = 271 heterosexual couples; 162 intervention and 109 control) used a dyadic latent growth model to explore the dependence structure of parental efficacy between couples 2 years after assignment to a military parenting program, After Deployment, Adaptive Parenting Tools or a control condition. Results revealed a significant intervention effect, with both mothers and fathers in the intervention group exhibiting quadratic changes over 2 years, while the control group remained relatively stable. Notably, mothers’ baseline emotional distress and fathers’ deployment length emerged as predictors in understanding parental efficacy improvement over time. This research underscores the importance of adopting a family systems perspective and considering emotional distress and environmental stressors in designing targeted interventions to support military families and enhance overall well-being.

Keywords: deployment, dyadic latent growth model, emotional distress, military family, parental efficacy, parenting program

INTRODUCTION

According to Bandura’s (1997) social cognitive theory, self-efficacy is defined as the belief in one’s ability to successfully organize and execute certain actions required in a specific situation. Self-efficacy is domain-specific, and individuals with higher self-efficacy in a specific domain are more likely to engage in domain-specific behaviors and have better performance (Woodruff & Cashman, 1993). Parental efficacy specifically refers to parents’ beliefs and judgments about their own competence in their parenting role (Montigny & Lacharite, 2005). Empirical evidence from the past several decades indicates that parental efficacy is an important predictor of parenting behavior and child adjustment (Albanese et al., 2019; Shumow & Lomax, 2002), and might have a causal impact on future parenting practices and adolescents’ externalizing problems (Dumka et al., 2010; Glatz & Buchanan, 2015a, 2015b).

Thus, parental efficacy has been viewed as an important outcome and even the mechanism of change for many behavioral parenting programs. For example, a meta-analysis based on randomized controlled trials (RCTs) found that group-based parenting interventions can improve parental efficacy with moderate-to-large effect sizes (Wittkowski et al., 2016). Even without face-to-face interactions with professionals, self-directed parenting interventions are sufficient to improve parental efficacy (Tarver et al., 2014). When implemented in community settings, behavioral parenting programs can also improve parental efficacy with moderate to large effects (Lindsay et al., 2011). More importantly, some studies have shown that parenting interventions enhance parenting practices and child behaviors via increased parental efficacy (Piehler et al., 2018; Seabra-Santos et al., 2016). That is, parents feel more confident in their parenting roles after participating in behavioral parenting programs, which leads to future improvements in their parenting behaviors and subsequently, improvements in child behaviors. One study also found that improved parental efficacy after a behavioral parenting program was related to fewer parent difficulties in emotional regulation, less psychological distress, and decreased suicidality (Gewirtz et al., 2016).

Most existing studies about parental efficacy view mothers as the primary caregivers and often ignore other caregivers, even though research has shown differences between maternal and paternal parental efficacy in heterosexual couples. For example, Reece and Harkless (1998) found that mothers reported higher levels of parental efficacy compared to fathers during the transition to new parenthood, and parental efficacy was negatively related to parental stress for mothers, but not fathers. Additionally, Sevigny and Loutzenhiser (2010) found that fathers and mothers reported different sources of parental efficacy. Although relational functioning was important for both parents, parenting stress was specifically salient for fathers and general self-efficacy was important for mothers. Utilizing a sample from Hong Kong, Kwok and Li (2015) found that spousal capital (i.e., marital satisfaction, parenting alliance, and spousal support) indirectly improved the father’s involvement in parenting via parental efficacy. In a study including both parents, Walters (2021) found gender-matching in which fathers’ warmth and self-efficacy were more important for boys’ delinquency and mothers’ warmth and self-efficacy were more important for girls. However, less is known about the relationship between partners’ parental efficacy over time, and the influence that parenting interventions have on long-term change in parental efficacy.

The Family Stress Model (Masarik & Conger, 2017) suggests that external stressors, such as military deployment (Gewirtz et al., 2018a), can lead to parental emotional distress which in turn may disrupt parenting practices, the couple’s relationship, and children’s adjustment. Previous studies (e.g., Freed & Tompson, 2011; Lloyd & Hastings, 2009) have established robust negative relationships between parental emotional distress (especially maternal depression and anxiety) and parental efficacy. However, the existing literature has primarily focused on individual parents’ experiences (mostly mothers) without fully considering the dyad—that is, the impact of a partner’s experiences. From a family systems perspective, individual parents do not function independently but rather are frequently interacting with their partners (Cowan et al., 1998). It is crucial, then, to take emotional distress into consideration to gain a better understanding of the dyadic relationship between couples’ emotional distress and parental efficacy, especially when couples have been exposed to stressful or traumatic events and are at higher risk for developing emotional distress.

After Deployment, Adaptive Parenting Tools (ADAPT)

Studies have shown that the negative impact of combat exposure on service members’ mental health is related to a higher prevalence of PTSD (Fulton et al., 2015), more frequent suicidal ideation and attempts (Stanley & Larsen, 2019), and increased substance abuse (Eisen et al., 2012). The Cognitive-Behavioral Interpersonal Theory (Creech & Misca, 2017) illustrates how compromised family functioning and war-related PTSD symptoms impact each other bidirectionally after family reunification. Gewirtz and Zamir (2014) proposed that parental deployment could impact children’s socioemotional development and academic adjustment from early childhood to adolescence via the mediating role of parenting practices. Thus, parenting interventions specific to military families appear crucial to improve military family functioning.

ADAPT is a trauma-informed adaptation of GenerationPMTO (previously known as Parent Management Training, Oregon Model, or PMTO; Forgatch & Gewirtz, 2018). GenerationPMTO aims to promote child socioemotional development by improving parenting practices across five domains: positive involvement, skill encouragement, problem-solving, monitoring, and appropriate discipline. The ADAPT program modified GenerationPMTO to add one more core component, parental emotion socialization, which included low-dose mindfulness practices, emotion coaching skills, and discussions about specific stressors relevant to military families. In the current RCT, participants were randomly assigned to the ADAPT intervention condition, or a services-as-usual (SAU) comparator (web and print parenting resources). Families in the intervention condition participated in 14 weekly 2-h sessions. In each session, a closed group of 6–15 parents learned and practiced parenting skills led by two or three trained facilitators.

The current study

Although the importance of parental efficacy in parenting practices and child adjustment is well acknowledged, the current literature has several limitations. First, most, if not all, previous studies measured parental efficacy immediately after the intervention, overlooking longer-term change. Second, most studies only included mothers as the primary participants. This leaves paternal parental efficacy as an understudied topic, and the dyadic interaction of efficacy between two parents missing from the literature. Third, less is known about dyadic relationships and change in emotional distress and parental efficacy after participating in a parenting program, such as how one parent’s emotional distress may influence their own and the other’s change in efficacy over time. A family systems perspective emphasizes the interplay between parents; thus, it is essential to explore the dyadic relationships between couples’ emotional distress and parental efficacy over time.

This study aims to address this significant gap in the existing literature to provide a more comprehensive understanding of couple and family dynamics. Specifically, we examined the longitudinal changes in parental efficacy over 2 years after couples participated in the ADAPT intervention, comparing growth trajectories in the intervention group and the control group. Recent research (e.g., Cho & Braaten, 2022; Kang et al., 2022) suggests that postintervention change over time might be more accurately described as following a quadratic rather than a linear pattern, thus, we tested both linear and quadratic models to determine which more accurately fit the observed data (Aim 1). Then, emotional distress at baseline was examined to determine if there were associations with the parent’s individual trajectory (actor effect) or partner’s trajectory (partner effect) of parental efficacy over time (Aim 2).

METHODS

Participants

Data were drawn from N = 336 military families who participated in the ADAPT RCT (Gewirtz et al., 2018b). Eligible families had at least one parent who had been deployed to Iraq and/or Afghanistan since November 9, 2001 and had at least one child between 4 and 12 years old. All data from two-parent families (n = 271 families) were included in the current analysis, regardless of their marital status. Demographic information is available in Table 1. An intentto-treat approach was used to evaluate intervention effects, with data from all participants analyzed regardless of their attendance in the ADAPT program.

TABLE 1.

Demographic information of all two parents' families who had participated in the ADAPT (N =271).

Fathers Mothers
Age, M (SD) 37.44 (6.43) 35.76 (5.87)
Race, n (%)
 Caucasian 232 (85.6%) 249 (91.9%)
 African American 13 (4.8%) 5 (1.8%)
 Pacific Islander 1 (0.4%) 1 (0.4%)
 Asian 6 (2.2%) 3 (1.1%)
 Native American 0 1 (0.4%)
 Multiracial 7 (2.6%) 3 (1.1%)
Marriage status, n (%)
 Married or cohabiting 250 (92.3%) 254 (93.7%)
 Separated or divorced 12 (4.4%) 8 (3.0%)
 Single 2 (0.7%) 5 (1.8%)
Education, n (%)
 High school or less 23 (8.7%) 21 (7.8%)
 Some college/associate degree 118 (44.6%) 106 (39.7%)
 Bachelors' degree 92 (34.8%) 106 (39.7%)
 Master's degree or higher 31 (11.7%) 34 (12.7%)
Income, median $70,000-$79,999
 Ever been deployed, n (%) 259 (95.6%) 34 (12.5%)
 Deployment length, mediana 19–24 months 7–12 months
Children
 Age, M (SD) 8.44 (2.52)
 Girl, n (%) 151 (55.7%)
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Note: Data are shown as mean (SD) or n (%).

Abbreviation: ADAPT, After Deployment, Adaptive Parenting Tools.

a

Deployment length: only calculated for those who had been deployed.

Procedures

A CONSORT diagram is shown in Figure 1. All procedures were approved by the Institutional Review Board at the University of Minnesota (IRB number: 1005S82692). Participants were recruited via multiple methods including presentations at predeployment and reintegration events for National Guard/Reserve families, mailings from the local Veteran’s Administration Medical Center to Operations Iraqi Freedom and Enduring Freedom veterans, media, and word of mouth. Interested participants were given an online screener to determine eligibility. Eligible parents completed consent forms and then were asked to complete a baseline online survey and an in-home interview. After the baseline assessment, 60% of the families (n = 162 in this subdata set) were randomly assigned to the intervention condition and 40% (n = 109 in this subdata set) were randomly assigned to the SAU condition. Follow-up data were collected 6-months postbaseline (T2, postintervention), 1-year postbaseline (T3), and 2 years postbaseline (T4).

FIGURE 1.

FIGURE 1

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A CONSORT diagram of the current study. PLOC, Parenting Locus of Control Scale.

Measures

Parental efficacy

The Parenting Locus of Control Scale (PLOC)—Short Form Revised (modified by Hassall et al. [2005]) was used to measure maternal and paternal parental efficacy from T1 to T4. Four subscales were used to access parents’ locus of control: parental efficacy (e.g., “No matter how hard a parent tries, some children will never learn to mind”), parental responsibility (e.g., there is no such thing as good or bad children—just good or bad parents”), child control of parents’ life (e.g., “My life is chiefly controlled by the child”), and parental control of the child’s behavior (e.g., “I always feel in control when it comes to my child”). Parents rated 24 statements about the parental locus of control on a 5-point Likert scale (1 = strongly agree, 5 = strongly disagree). Parents with a more external locus of control tend to believe they have little impact on their child’s behaviors and feel less efficacious as parents. Items were reversely coded when necessary. A total mean score was calculated where higher scores represented higher levels of parental efficacy. The scale showed good reliability in the current sample (Cronbach’s alpha ranges from 0.76 to 0.80 for mothers and 0.78 to 0.82 for fathers from baseline to T4).

Emotional distress

The Hopkins Symptom Checklist (Parloff et al., 1954) is a widely used self-report symptom inventory to detect the presence and intensity of anxiety and depression symptoms over the previous week. It consists of 25 items, including 10 measuring anxious symptoms (e.g., “Suddenly scared for no reason”) and 15 measuring depressive symptoms (e.g., “Feeling low in energy, slowed down”). Participants rated how much each of the symptoms caused distress in the past week on a 4-point scale (1 = Not at all, 4 = Extremely). An average score was calculated to represent parental emotional distress in the study, where higher scores represented more emotional distress. The scale showed high reliability in the current sample (Cronbach’s alpha = 0.95 for mothers and 0.92 for fathers). A score above 1.75 is viewed as symptomatic of clinical distress in Western countries (Winokur et al., 1984). In our study, 23.1% fathers and 21.5% mothers met the clinical criteria at baseline, and in 7.5% families both parents had clinical-level emotional problems, indicating our sample had a higher prevalence of mental health problems than the community sample.

Covariates

Children’s age (in years), gender (0 = boys, 1 = girls), parents’ education level (1 = high school or less, to 8 = doctoral or professional degree), parent race (0 = parent of color, 1 = Caucasian/White), deployment length (6-month increment ranging from 1 to 7, 1 = 6 months or less, 2 = 7 to 12 months… 7 = 37 months or more), and household income (US$10,000 increments ranging from 1 to 16, 1 = less than US$10,000 per year, 2 = US$10,000 to 19,999… 16 = US$150,000 or more; average scores between fathers and mothers were used) were used as covariates.

Analytic plan

First, descriptive statistics including means, standard deviations, and bivariate correlations were calculated in SPSS 28.0 (IBM Corp. Released, 2021) to examine the relationships among the main variables in the model. Then, dyadic latent growth models (LGMs) were conducted using a structural equation modeling (SEM) framework in Mplus 8.8 (Muthen & Muthen, 2022). The SEM framework was chosen over the multilevel modeling framework based on suggestions from Ledermann and Kenny (2017) that SEM with full information maximum likelihood (FIML) can better handle missing data if not missing completely at random (MCAR), the path coefficients directly to intercept and slope can be easily estimated, and different models can be compared based on multiple model fit indices (listed below).

To examine the impact of ADAPT on parental efficacy over 2 years (Aim 1), linear and quadratic unconditional LGMs were estimated in the intervention group and control group, for mothers and fathers separately. Since we have a relatively small sample size across four-time points (<200) for a complex model, problems such as Heywood cases (e.g., negative variance) can emerge (Moon & Illingworth, 2005; Soloski & Durtschi, 2020). In models with good model fit, a small, nonsignificant negative variance on the slope or quadratic can indicate there is no remaining individual variation in the model, and the variance can be constrained to 0. Next, a dyadic LGM was built using the best-fitting model from Aim 1, to integrate mothers’ and fathers’ parental efficacy growth trajectories. Then, actor and partner emotional distress were included as predictors in the dyadic LGM, controlling for deployment length, child age, child gender, household income, and race (Aim 3, see Figure 2). In all LGM models, time-zero was defined as the baseline assessment. Thus, the latent intercepts represent the initial status, and the latent slopes represent the rate of change over time.

FIGURE 2.

FIGURE 2

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Dyadic latent growth model. The bolded line indicated a significant relationship at p = 0.05 level.

Shapiro–Wilk tests showed that baseline parental efficacy was relatively normally distributed (skewness = −0.28 to −0.03; kurtosis = −0.58 to 0.27), while parental emotional distress was not (skewness = 1.25–1.60; kurtosis = 11.52–3.31). Therefore, a maximum likelihood with robust standard errors estimator was used in Mplus 8.8, as suggested by Asparouhov and Muthén (2014). Multiple model fit indices of each estimated model to the data were evaluated. Good model fit indices include a nonsignificant χ2 value, a comparative fit index (CFI) value bigger than 0.95, a root mean square error of approximation (RMSEA) value smaller than 0.05, and a standardized root mean square residual (SRMR) value smaller than 0.06 (Hu & Bentler, 1999). Acceptable model fit indices include a CFI value greater than 0.90, RMSEA, and SRMR smaller than 0.08.

RESULTS

Preliminary analyses

Descriptive statistics and bivariate correlations among all variables included in the study are shown in Table 2. Results suggested dependence between mothers and fathers on baseline emotional distress (r = 0.202, p = 0.001) and parental efficacy (r = 0.248, p < 0.001). χ2 Tests and independent t-tests were conducted in SPSS 28, to examine whether there were differences between the intervention and control conditions. The results indicated successful randomization, as no significant differences were found between parents in the intervention condition and the control condition on a variety of demographic variables, including parental age, education level, household income, race, marital status, deployment status, deployment length, child gender, and child age (ps > 0.05). Additionally, no differences were found on baseline parental emotional distress or parental efficacy (ps > 0.05) between parents in the intervention condition and the SAU condition.

TABLE 2.

Descriptive statistics and bivariate correlations among main variables.

1 2 3 4 5 6 7 8 9 10
1. Emotional distress T1 (dad) 1 0.221* −0.223* 0.062 −0.260* −0.279* −0.205* 0.049 0.077 −0.136
2. Emotional distress T1 (mom) 0.192* 1 0.012 0.007 0.066 0.035 −0.128 −0.050 −0.011 −0.067
3. Parental efficacy T1 (dad) −0.334** −0.228** 1 0.519** 0.675** 0.658** 0.261** 0.184 0.183 0.083
4. Parental efficacy T2 (dad) −0.256** −0.295** 0.614** 1 0.476** 0.531** 0.225 0.478** 0.321* 0.242
5. Parental efficacy T3 (dad) −0.223* −0.237** 0.696** 0.624** 1 0.772** 0.320** 0.096 0.158 0.078
6. Parental efficacy T4 (dad) −0.223* −0.173 0.714** 0.693** 0.655** 1 0.093 0.022 0.045 0.012
7. Parental efficacy T1 (mom) −0.036 −0.171* 0.242** 0.132 0.170 0.181 1 0.575** 0.643** 0.596**
8. Parental efficacy T2 (mom) −0.023 −0.298** 0.218* 0.276** 0.359** 0.332** 0.648** 1 0.597** 0.541**
9. Parental efficacy T3 (mom) −0.122 −0.314** 0.244** 0.235* 0.250** 0.176 0.662** 0.720** 1 0.696**
10. Parental efficacy T4 (mom) −0.066 −0.268** 0.312** 0.246* 0.300** 0.346** 0.633** 0.725** 0.746** 1
M (intervention group) 1.50 1.47 3.66 3.71 3.77 3.78 3.68 3.85 3.77 3.81
SD (intervention group) 0.50 0.40 0.42 0.48 0.46 0.43 0.40 0.41 0.43 0.43
N (intervention group) 159.00 160.00 159.00 106.00 126.00 118.00 159.00 110.00 130.00 124.00
M (control group) 1.49 1.50 3.66 3.61 3.69 3.72 3.58 3.60 3.63 3.61
SD (control group) 0.44 0.42 0.38 0.48 0.44 0.42 0.44 0.47 0.40 0.38
N (control group) 101.00 105.00 103.00 73.00 82.00 80.00 107.00 91.00 88.00 87.00
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Note: Pearson correlation in the intervention group was shown below the diagonal and the control group was shown above the diagonal.

*

p < 0.05;

**

p < 0.01.

Missing data analysis was conducted in SPSS 28. Results of Little’s MCAR test including all variables revealed that the data were not MCAR (χ2 (614) = 727.21, p = 0.001). FIML, which has been shown to be superior to other methods in longitudinal modeling (e.g., listwise deletion, pairwise deletion, stochastic regression imputation; Newman, 2003) was used to analyze missing data.

Intervention effect

As shown in Table 3, separate linear and quadratic LGMs in intervention and control group were estimated. For mothers in the control group, both linear (slope = 0.01, SE = 0.01, p = 0.23) and quadratic models (slope = 0.04, SE = 0.03, p = 0.17; quadratic = −0.01, SE = 0.01, p = 0.29) showed no significant changes in mothers’ parental efficacy over time.

TABLE 3.

Fit statistics for the dyadic latent growth models.

Model Intercept Slope Quadratic χ2 df p-Value CFI RMSEA SRMR Note
Intervention group
Father models
 Lineara 3.67 (0.03)* 0.03 (0.01)* 7.37 1 0.39 0.99 0.02 0.07
 Quadrica 3.66 (0.03)* 0.08 (0.03)* −0.01 (0.01)** 4.29 6 0.64 1 0 0.08
Mother models
 Linear 3.73 (0.03)* 0.02 (0.01)* 17.70 5 0.003 0.94 0.13 0.18
 Quadrica 3.70 (0.03)* 0.09 (0.03)* −0.02 (0.01)* 16.34 6 0.01 0.95 0.10 0.26
Dyadic models
 Quadric 33.29 27 0.19 0.99 0.04 0.16
 With predictors 131.57 71 <0.001 0.90 0.07 0.097
Control group
Father models
 Linear 3.65 (0.04)* 0.02 (0.01)* 2.65 5 0.75 1 0 0.12
 Quadratica 3.65 (0.04)* 0.006 (0.03) 0.003 (0.01) 10.29 6 0.11 0.97 0.08 0.28
Mother models
 Linear 3.59 (0.04)* 0.01 (0.01) 1.59 5 0.90 1 0 0.03
 Quadratic 3.58 (0.04)* 0.04 (0.03) −0.01 (0.01) 0.39 1 0.53 1 0 0.01
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a

Abbreviations: CFI, comparative fit index; RMSEA, root mean square error of approximation; SRMR, standardized root mean square residual. Variance of slope and quadratic terms were small, nonsignficant negaitve. Fixed to 0 to improve model fit.

*

p < 0.05;

**

p = 0.055.

In the intervention group, mothers demonstrated significant linear change over time in the linear model, (slope = 0.01, SE = 0.01, p = 0.225). The slope and intercept were not significantly correlated (r = 0.004, p = 0.34), indicating the initial status was not related to the rate of change. The variance of the intercept was significant (σ2 = 0.10, SE = 0.02, p < 0.001), while the variance of the slope was not significant (σ2 = 0.01, SE = 0.002, p = 0.58), suggesting variation in initial parental efficacy but no significant variation in the rate of change. A Heywood case was found when adding the quadratic term, such that the variance of the slope (σ2 = −0.029, SE = 0.026, p = 0.27) and the quadratic (σ2 = −0.001, SE = 0.001, p = 0.45) were negative. Since the variances were small and not significant, and the correlation among the intercept, slope, and quadratic were not significant (ps > 0.05), the variances of slope and quadratic were fixed to 0. The quadratic model demonstrated acceptable model fit, (χ2 (6) = 16.34, p = 0.01; RMSEA = 0.10, CFI = 0.95, SRMR = 0.26). For mothers in the intervention group, the quadratic model was selected as the best-fitting model, indicating significant quadratic changes over time (slope = 0.09, SE = 0.03, p = 0.01; quadratic = −0.02, SE = 0.006, p = 0.01).

For fathers in the control group, a statistically significant linear change was found (slope = 0.02, SE = 0.01, p = 0.04). The variances of the intercept (σ2 = 0.10, SE = 0.02, p < 0.001) and the slope (σ2 = 0.10, SE = 0.02, p < 0.001) were significant, suggesting variation in initial parental efficacy and the rate of change. The slope and intercept were not significantly correlated (r = −0.006, p = 0.20). A Heywood case was found when adding the quadratic term, resulting in small negative variances for the slope (σ2 = −0.036, SE = 0.042, p = 0.40) and the quadratic (σ2 = 0, SE = 0.002, p = 0.97). Thus, variances of slope and quadratic were fixed to 0, and the quadratic model (slope = 0.006, SE = 0.03, p = 0.84; quadratic = 0.003, SE = 0.007, p = 0.64) showed no significant changes for father’s parental efficacy over time in the control group.

For fathers in the intervention group, a small negative variance (σ2 = −0.002, SE = 0.002, p = 0.34) was found for the slope and it was thus fixed to 0. Fathers demonstrated significant linear change over time in the linear model, (slope = 0.03, SE = 0.01, p < 0.001). The quadratic model demonstrated good model fit, (χ2 (6) = 4.29, p = 0.64; RMSEA = 0, CFI = 1, SRMR = 0.08). For fathers in the intervention group, the quadratic model was selected as the best-fitting model, indicating a trend of quadratic changes over time (slope = 0.08, SE = 0.03, p = 0.01; quadratic = −0.012, SE = 0.006, p = 0.055).

In summary, the results revealed noticeable differences in the patterns of parental efficacy changes over 2 years between the intervention group and the control group. For mothers in the control group, no significant linear nor quadratic changes were found, while mothers in the intervention group showed significant linear and quadratic changes. Fathers in the control group demonstrated linear growth, while fathers in the intervention group exhibited a similar pattern to mothers in the intervention group, showing significant linear and quadratic change. See Figure 3 for a visual representation of the estimated changes in parental efficacy for mothers and fathers over 2 years.

FIGURE 3.

FIGURE 3

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Estimated mean of parental efficacy trajectory for mothers and fathers in the intervention group and the control group.

Emotional distress and change of parental efficacy

Given the lack of significant changes in parental efficacy among mothers in the control group, the analysis for Aim 2 was focused exclusively on the intervention group. A dyadic LGM (Table 4) was conducted to examine the impact of baseline emotional distress and changes in parental efficacy, controlling for deployment length, child age, child gender, household income, and race. All continuous covariates were mean-centered to enhance interpretability and all categorical variables were dummy coded. The model showed adequate model fit (χ2 (71) = 131.57, p < 0.001, CFI = 0.90, RMSEA = 0.07, SRMR = 0.097). The initial statuses of maternal and paternal efficacy were still correlated with one another (r = 0.03, p = 0.003). Fathers’ and mothers’ baseline emotional distress were positively correlated (r = 0.04, p = 0.05).

TABLE 4.

Predictors of the dyadic latent growth models

Predictors Father
 Mother
Intercept Slope Quadratic Intercept Slope Quadratic
SCL1M −0.15 (0.07)* −0.1 (0.07) 0.03 (0.02) −0.14 (0.08) −0.12 (0.06)* 0.025 (0.014)
SCL1D −0.22 (0.06)*** 0.04 (0.05) −0.01 (0.01) −0.01 (0.07) −0.04 (0.06) 0.01 (0.01)
Deployment_Month 0.02 (0.02) −0.04 (0.02)* 0.01 (0)* 0.03 (0.03) −0.01 (0.02) 0(0)
Child age 0.02 (0.01) −0.01 (0.01) 0(0) 0.02 (0.01) 0 (0.01) 0(0)
Child gender 0.06 (0.06) −0.01 (0.05) 0.01 (0.01) 0.15 (0.06)* −0.07 (0.05) 0.02 (0.01)
Family income 0.01 (0.01) −0.01 (0.01) 0(0) 0.01 (0.01) −0.01 (0.01) 0(0)
Parent race −0.26 (0.09)** 0.12 (0.09) −0.02 (0.02) −0.13 (0.14) 0.21 (0.08) −0.03 (0.02)
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Note: χ2 (71) = 131.57, p < 0.001, comparative fit index = 0.90, root mean square error of approximation = 0.07, standardized root mean square residual = 0.097.

*

p < 0.05;

**

p < 0.01;

***

p < 0.001.

Results showed that mothers’ baseline emotional distress was associated with their own growth trajectory. Specifically, baseline emotional distress was negatively related to the slope (b = −0.12, SE = 0.06, p = 0.04) and marginally related to the intercept (b = −0.14, SE = 0.075, p = 0.06) and the quadratic term (b = 0.025, SE = 0.014, p = 0.077). Figure 4 shows the estimated growth trajectory for mothers, illustrating that those with baseline emotional distress one standard deviation below the mean exhibited a more rapid increase in parental efficacy, while those at or above the mean (to one standard deviation higher) on baseline emotional distress showed more stable trajectories. Father’s emotional distress did not have an impact on mothers’ parental efficacy trajectory. Interestingly, compared to mothers of color, Caucasian mothers (b = 0.07, SE = 0.03, p = 0.018) were more likely to have higher slopes, but no differences were found in the intercepts and the quadratic terms (i.e., Caucasian mothers did not differ from mothers of color in their initial levels of parental efficacy but experienced a more rapid increase in their parental efficacy over 2 years). In addition, mothers of girls demonstrated higher parental efficacy initially compared to mothers of boys (b = 0.15, SE = 0.06, p = 0.02).

FIGURE 4.

FIGURE 4

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Estimated mean of mothers’ parental efficacy trajectory in the intervention group, by different levels of distress. [Color figure can be viewed at wileyonlinelibrary.com]

Fathers’ initial level of parental efficacy was negatively associated with their own baseline emotional distress (b = −0.22, SE = 0.06, p < 0.001) and their partners’ baseline emotional distress (b = −0.15, SE = 0.07, p = 0.04). However, neither fathers’ nor their partners’ baseline emotional distress had an impact on their growth trajectory. Interestingly, father’s deployment length had a significant effect on the slope (b = −0.04, SE = 0.02, p = 0.02) and the quadratic term (b = 0.007, SE = 0.003, p = 0.05). Figure 5 shows the estimated growth trajectory for fathers, revealing that those with shorter deployment exhibited a more rapid increase in parental efficacy, whereas those with mean or longer deployment showed a less rapid increase in parental efficacy. Compared to fathers of color, Caucasian fathers were more likely to have lower initial status (b = −0.26, SE = 0.09, p = 0.009), but no differences in slope or quadratic terms were found.

FIGURE 5.

FIGURE 5

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Estimated means of fathers’ parental efficacy trajectory in the intervention group, by different levels of deployment lengths. [Color figure can be viewed at wileyonlinelibrary.com]

DISCUSSION

To our knowledge, this study is the first to investigate long-term changes in parental efficacy from a dyadic perspective after participation in a military parenting program. Previous research from the same RCT revealed both fathers and mothers demonstrated improvements in parental efficacy as a result of participation in the program (Gewirtz et al., 2016). The current study expanded on these results and demonstrated significant intervention effects by revealing distinct growth trajectories between the intervention groups and the control groups. Both mothers and fathers in the intervention group exhibited a trend of quadratic change, such that their parental efficacy increased after the intervention, and slightly dropped off afterward. Mothers in the control group, who only received a list of parenting resources, did not demonstrate significant changes in parental efficacy over time. However, the finding that fathers in the control group showed linear change, was unexpected and warrants further investigation. It is possible, however, that temporal factors are relevant here—as time passed since their return from deployment, fathers felt more comfortable and competent in their parenting roles, settling into their parenting roles with more confidence. For the intervention group, however, a quadratic pattern is not uncommon, as participants often experience initial gains followed by a leveling off or even a modest decline in their outcomes (e.g., Reedtz & Klest, 2016). The findings support the idea that the program’s effects may extend beyond the immediate postintervention period, leading to continued improvements in parental efficacy over time.

Additionally, this study highlighted the importance of mothers’ baseline emotional distress when examining intervention effects. Specifically, mothers with lower emotional distress at the beginning of the intervention showed a more rapid increase in their parental efficacy. The results further expand the literature showing robust negative relationships between parental distress and parental efficacy in the intervention setting. It is plausible that mothers with less distress were more prepared to learn new parenting skills and felt more competent to practice new skills, thus showing greater improvement in their perceived parenting abilities. Additionally, more distressed mothers might feel less prepared or less competent in their parenting roles even after the program. This suggests that emotional distress can impede mothers’ ability to fully benefit from the intervention, and future studies should explore interventions to address emotional distress before participation and should provide additional support for mothers experiencing higher levels of distress to potentially enhance the effectiveness of the program.

Furthermore, it is important to note that this relationship might be bidirectional. Crnic and Ross (2017) suggested that parental efficacy and parental mental health reciprocally influence and strengthen one another. Parents with more depressive symptoms might perceive parenting to be hard and believe they have little or no control over their children’s behaviors, which can increase their feelings of sadness and hopelessness. This study did not have the capacity to include parental distress as another LGM due to the small sample size and limited number of follow-ups, but future studies should explore these potentially bidirectional relationships over time.

This study also observed a similar pattern for fathers. Fathers with shorter deployment lengths showed more rapid growth in their parental efficacy. The length of time away from their families and exposure to war-related trauma may have had long-lasting negative effects on fathers’ views of their parental efficacy over time. Although longer deployment is generally related to worse mental health for military personnel (Buckman et al., 2011), the impact of deployment length on parental efficacy was not fully captured by emotional distress, nor by depression and anxiety. Other factors, such as posttraumatic symptoms (Creech & Misca, 2017; Darawshy et al., 2022), may be influencing the relationship between deployment length and parental efficacy. Prior data have also found that females in the military are more likely to be single and have higher divorce rates compared to their male counterparts (Institute of Medicine, 2013), suggesting that deployment may differentially impact military fathers and mothers. However, this study could not fully disentangle the relationship between individual parents’ gender, deployment status, and mental health because most families included a deployed father and a civilian mother. This points to the need for additional research on deployed mothers and civilian fathers to further understand the impact of the gender-deployment-mental health relationship on parenting.

Interestingly, while mothers’ initial parental efficacy was only marginally related to their own emotional distress, fathers’ initial parental efficacy was related to both their own and their partners’ baseline emotional distress. The negative relationship between mothers’ emotional distress and fathers’ parental efficacy might indicate that mothers play a more important role in parenting and coparenting, and when mothers are more distressed, both individuals feel less competent in their parenting role. The spillover effect from mothers to fathers seems to be consistent with Kwok and Li’s (2015) study that demonstrated that fathers’, but not mothers’, perceived spousal capital can impact their parental efficacy. Future longitudinal studies are needed to examine the dynamic influence between parental efficacy and parental psychopathology across different children’s developmental stages using dynamic modeling. However, given no spillover effect was found for longitudinal changes over time, the results should be viewed with caution.

Results also indicated some racial differences. Compared to parents of color, Caucasian fathers had lower parental efficacy initially and Caucasian mothers tended to have a faster growth trajectory over time. However, our sample was relatively homogenous and a majority of parents were Caucasian. The relative homogeneity of the sample also limits the generalizability of the findings to more diverse populations and the results should be interpreted with caution.

Strengths, limitations and future research

This study was one of the first to assess dyadic change in couples’ parental efficacy over time and offered insights into the complex dynamics of parental mental health, parenting, and coparenting in military families. The results highlighted the importance of taking a family systems approach to understanding parenting and parental mental health in families longitudinally, particularly those facing unique stressors such as deployment. This research has significant implications for developing targeted interventions to support military families and improve their well-being.

However, the study had several limitations. First, all mean scores were greater than 3.5 on a 5-point Likert scale, suggesting a ceiling effect, that is, that participants’ perceived parental efficacy was relatively high at baseline, leaving limited room for further improvement. Second, we had to constrain the small negative variances to 0 in all the quadratic models. While this is not uncommon in studies with small sample sizes and limited time points, it is crucial to recognize that these constraints might introduce biases and restrict the ability to fully explore the dependency between parents’ trajectories (e.g., correlation between parents’ linear and quadratic changes). Third, this study only included baseline emotional distress and not change in emotional distress over time due to the limited power, which limits our ability to fully understand the dynamic processes or the bidirectionality among environmental stress (deployment), emotional distress, and parental efficacy. As argued by Crnic and Ross (2017), once the detrimental link between a parent’s psychopathology and parental efficacy is built, they may reinforce each other bidirectionally. As such, future studies should treat emotional distress as a time-varying variable. Moreover, given findings showing that emotional distress can impact mothers’ trajectories of parental efficacy while deployment length can improve fathers’ efficacy trajectories more mental health indicators should be considered. Finally, the sample included in the current study was highly demographically homogeneous. Since 92% of the fathers and only 10% of the mothers were deployed, it was impossible for this study to disentangle the effects of deployment and gender in understanding parental efficacy. Future studies should collect data from diverse families to delineate the effects of deployment and gender on family functioning, including among deployed fathers and civilian mothers, deployed mothers and civilian fathers, and dually deployed parents.

CONCLUSION

To our knowledge, this study is the first to examine dyadic longitudinal change in parental efficacy in military families after their participation in a parenting program, with consideration of parental emotional distress and environmental stressors. The findings indicated distinct growth trajectories in parental efficacy between the intervention group and the control group, with both mothers and fathers in the intervention group demonstrating a trend of quadratic change while the control group remained relatively stable. Mothers’ baseline emotional distress emerged as an important predictor of their parental efficacy over time after participating in a parenting program, with lower distress associated with a more rapid increase in perceived parenting abilities. Similarly, fathers’ baseline deployment length was found to be an important predictor of their parental efficacy over time, with shorter deployment periods associated with a more rapid increase in perceived parenting abilities. The findings underscore the importance of adopting a family systems perspective and including both parents in examining change over time to better support parenting and coparenting in families. Finally, the study highlights the importance of considering baseline emotional distress and environmental stressors to maximize intervention benefits. This research provides important insights for developing targeted interventions to support military families and improve their well-being.

ACKNOWLEDGMENTS

The authors would like to express our sincere thanks to all participants in the study. The research was funded by the Department of Defense W81XWH-14–1-0143; W81XWH-16–1-0407 (Abigail Gewirtz, Principal Investigator).

Funding information

U.S. Department of Defense, Grant/Award Numbers: W81XWH-14-1-0143, W81XWH-16-1-0407

Footnotes

The article evolved from the first author’s Master’s thesis. Cai, Q. (2020). Emotional Distress, Deployment Length, and Change in Parental Efficacy After a Military Parenting Program: A Dyadic Longitudinal Model (Order No. 27998037). Available from ProQuest Dissertations & Theses Global. (2425565980).

DATA AVAILABILITY STATEMENT

The data and code used in the current article are available on request from the corresponding author.

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Associated Data

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Data Availability Statement

The data and code used in the current article are available on request from the corresponding author.

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