Understanding Who Benefits Most from Family-Based Prevention: Differential Intervention Effects for Families with Low Income

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Cooper, Benjamin L. Bayly, Eric K. Layland, Francesca Lupini, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9085268/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Multicomponent family-based interventions can mitigate the adverse effects of poverty on family functioning. However, benefits are not uniform across families. Limited research has examined how distinct constellations of poverty-related risk shape engagement with and responsiveness to preventive interventions. Using a person-centered approach, this study tested whether pre-intervention risk profiles predicted differential engagement with and response to the Fatherhood, Relationship, and Marriage Education (FRAME) intervention, a program based on the Family Stress Model and designed to strengthen parental coping, couple relationships, and parenting practices. Participants were 301 mother-father-child triads with household incomes at or below 200% of the federal poverty level. Building on prior research that identified four latent risk classes, we examined whether class membership predicted session attendance and moderated intervention effects on family relational and behavioral outcomes assessed six months post-intervention using combined mother and father reports. Results indicated heterogeneity in both engagement and intervention response. Families characterized by moderate economic stress and elevated parental depressive symptoms demonstrated the highest attendance and the most favorable response, particularly for couple relationship quality. Families in the lowest and highest risk classes received few benefits, with the lowest risk group experiencing adverse effects on some outcomes. Sensitivity analyses suggested additional gender-specific patterns, indicating that mothers’ and fathers’ responses may differ within certain risk classes. These findings highlight the value of identifying multidimensional risk profiles when evaluating preventive interventions and support precision approaches to intervention delivery. family stress model poverty adversity person-centered approach latent class analysis Introduction Theory and research have established a robust link between poverty, poverty-related stress, and family dysfunction (Conger & Conger, 2002; Landers‐Potts et al., 2015). Family-based prevention programs have demonstrated promise in addressing the negative effects of poverty and promoting well-being, but these programs are not uniformly effective for all families (Lundahl et al., 2006). In fact, the literature remains inconclusive as to who benefits most from prevention programs, with most past studies applying variable-centered methods to identify potential moderators (e.g., Shelleby & Shaw, 2014). Few studies have applied person-centered approaches to examine how exposure to unique clusters of poverty-related adversity, including economic distress and family adversities, such as parental mental and physical health problems and domestic violence, may impact intervention response and engagement. This is an important gap for prevention efforts because families affected by poverty are often experiencing multiple co-occurring adversities, which do not always cluster in predictable patterns, making them harder to capture using traditional variable-centered approaches. The purpose of this study was to examine, using a person-centered approach, whether families differed in both engagement with and benefit from an empirically supported prevention program for economically disadvantaged families based on their unique patterns of poverty-related risk exposure. Strengthening Families Facing Economic Hardship A wealth of literature shows that interventions that produce changes in parenting, marital conflict/distress, or parental coping skills can lead to positive outcomes for children (Compas et al., 2010; Solmeyer et al., 2014; Van Ryzin et al., 2016). This literature is consistent with the Family Stress Model which posits that poverty can lead to a cascade of disruption and disorder beginning with (a) economic hardship and (b) economic strain, which undermine (c) parental psychological functioning and couple relationships, which interfere with (d) parenting skills and parent-child relationships, ultimately leading to (e) negative child outcomes (see Masarik & Conger, 2017 for summary of evidence supporting each model pathway). It follows that interventions targeting all three areas of the Family Stress Model (i.e., coping skills, couple relationships, and parenting) may be especially effective in promoting healthy child and family functioning. However, researchers have most often targeted these areas using separate interventions. For example, positive parenting programs (e.g., Triple P, Incredible Years, GenerationPMTO, Family Check Up) include components that teach effective parenting skills, but do not include substantial content on enhancing couple relationships or managing parental stressors (Cai et al., 2022; Menting et al., 2013; Prinz, 2012; Sanders & Mazzucchelli, 2022). Likewise, relationship education programs, such as Prevention and Relationship Enhancement Program (PREP) and Hold Me Tight, place a strong emphasis on improving the couple relationship, but provide little content on parenting and parent self-regulation (Fawcett et al., 2010; Markman et al., 2022). While these programs have shown efficacy in improving various couple and family outcomes, they typically address parental coping, couple relationship functioning, and positive parenting in isolation rather than within a single integrated program, which may limit opportunities for synergistic or cross-over effects (Smith et al., 2015), increase redundancy across interventions, and reduce feasibility for families whom participation in multiple sequential programs may be unrealistic given significant time and resource demands (Dumas et al., 2007). There remains a dearth of studies combining parental coping skills, couple relationship enhancement, and positive parenting into a single, cohesive program. One of the few such interventions – Fatherhood, Relationship, and Marriage Education (FRAME) – is a family intervention aimed at protecting children and parents from the negative effects of economic strain by improving couple relationship skills, stress management, and child-centered parenting (Wadsworth et al., 2011). FRAME combines the parenting and stress management skills taught in the Families Coping with Economic Strain intervention (Raviv & Wadsworth, 2010) with relationship education content from PREP (Markman et al., 1988). PREP is one of the most extensively tested relationship education interventions, with over 42 studies by a variety of research teams demonstrating consistent short- and longer-term positive effects (e.g., Laurenceau et al., 2004). FRAME is one of the few interventions to apply all the major components of the Family Stress Model (Conger & Conger, 2002). As such, FRAME aims to prevent adverse parent and child mental health outcomes by teaching couples strategies to deal with negative emotions, stress, conflict, and by improving couples’ communication and parenting skills. Demonstrated intervention effects have included sustained improvements in child-centered parenting and a reduction in parental depression (Rienks et al., 2011; Wadsworth et al., 2011). Further, Wadsworth et al. (2011) found that reductions in parent depressive symptoms were due, in part, to improvements in parents’ coping skills and stress management. Identifying who Benefits Most from Family-Based Prevention While family-based preventive interventions built on strong theory and solid empirical evidence have the potential to strengthen family relationships, improve parenting and coping skills, and reduce mental health problems for families living with economic hardship, the effectiveness of these programs is contingent upon families being able to engage with the content. It is well-known that even the most effective treatment and prevention programs do not help everyone, and programs targeting families with low income often have higher than average “non-response” rates (Hackworth et al., 2018). This could be due to the varying types of risks that economically disadvantaged families experience prior to the intervention. In fact, a wealth of family-based prevention research has found that intervention effects vary depending on the level of risk (Prado et al., 2013) and type of risk (Leijten et al., 2018) families were experiencing prior to the intervention. Many studies found that greater levels of baseline risk, especially mental health problems, predicted larger intervention gains (Gardner et al., 2009; Rojas et al., 2023; Theise et al., 2014). However, other studies have shown that families with less baseline risk benefited more from intervention, presumably, because they faced fewer barriers to engagement (Lundahl et al., 2006; Shelleby & Shaw, 2014). Still other studies report that families with moderate levels of risk benefit most (Cooper et al., 2024; Lee et al., 2024; Weber et al., 2024). Furthermore, evidence suggests that certain types of risk factors may be more predictive of intervention response than others (Leijten et al., 2018). For example, mothers’ depression seems to be among the most consistent moderators of intervention effects for family-based prevention programs, such that families that have mothers with higher baseline depressive symptoms tend to benefit more from intervention (Gardner et al., 2010; Leijten et al., 2020). Other types of risk factors, such as sociodemographic (e.g., household income, parent education, race/ethnicity, child age), appear not as consistently related to behavioral intervention response when assessed using traditional variable-centered methods (Cho et al., 2025; Gardner, Leijten, Harris, et al., 2019; Gardner, Leijten, Melendez‐Torres, et al., 2019; Leijten et al., 2018; Shelleby & Shaw, 2014). Using a person-centered approach (that identifies patterns of risk exposure) to test differential intervention effects could help to resolve these discrepancies in the past literature and advance our understanding of intervention moderators (Lanza & Rhoades, 2013). Due to the large number of risk factors experienced simultaneously by economically disadvantaged families (Cleland et al., 2017), it is difficult to disentangle the overlapping effects of different moderators using traditional variable-centered approaches. Assessing moderation using person-centered methods, such as latent class analysis (LCA), provides a more nuanced approach that is better suited for unpacking the effects of multiple co-occurring moderators. Despite the advantages of person-centered methods, most studies still rely on variable-centered methods, and there is a lack of understanding of how pre-intervention exposure to unique clusters of poverty-related adversity may dictate intervention response. In addition to understanding who benefits most from preventive interventions, it is also important to understand whether families are able to meaningfully engage with these programs. Engagement, particularly session attendance, is a critical driver of intervention effects and is likely as important as the intervention content itself (Dishion et al., 2014). Even well-designed, theoretically grounded programs cannot exert their intended effects if families do not attend enough sessions to receive the core components. This issue is particularly salient for families experiencing economic hardship, who face substantial structural and psychological barriers to participation, including inconsistent work schedules, limited transportation, caregiving demands, and higher levels of stress and mental health symptoms (Hackworth et al., 2018). As a result, patterns of engagement frequently differ across subgroups of families (Dumas et al., 2007; LoBraico et al., 2021), and these differences can obscure or magnify true intervention effects. Despite the central role of engagement in determining program success, relatively few studies examine how pre-intervention risk profiles predict intervention attendance. Understanding whether certain constellations of adversity are associated with greater or reduced engagement is essential for interpreting heterogeneity in intervention effects and for designing strategies to support families at risk of low engagement (Lanza & Rhoades, 2013). Identifying latent risk classes that forecast attendance may help clarify inconsistencies in the intervention moderation literature (i.e., differentiating between families who do not benefit because the program content is mismatched versus those who do not benefit because they cannot engage sufficiently) and ultimately strengthen the precision of preventive interventions. The Present Study The purpose of this study was to examine whether families had differential responses to and engagement with the FRAME intervention based on their unique patterns of pre-intervention risk exposure. Building on prior research with this sample, which identified four distinct classes of poverty-related adversity using latent class analysis (Cooper et al., 2025), we examined these risk classes as potential moderators of intervention effects. Consistent with the Family Stress Model that guided FRAME, our outcomes focused on various indicators of family functioning, including parental coping skills, couple relationship quality, parenting practices, and child behavior, each assessed using a combination of mother and father reports. We hypothesized that participant engagement, indexed by session attendance, would vary by risk class, with families in the lowest adversity class demonstrating higher attendance than families in the higher risk classes. Given the substantial heterogeneity in prior differential response findings, we did not make a priori predictions about which risk classes would benefit most or least from the intervention. Instead, we treated these analyses as exploratory tests of whether FRAME effects varied across risk classes. Methods Participants The sample included 602 adults and 301 children (0–17 years old), all of whom were part of 301 couples from low-income, two-parent households participating in the FRAME project (Wadsworth et al., 2011 ). The adults were evenly divided by gender and had a mean age of 32.55 years ( SD = 8.78; range = 18–74). Participants self-identified as Caucasian/White (34.8%), Black/African American (27.8%), Hispanic/Latiné (22.8%), Native American (5.3%), or Biracial/Multiracial/Other (11%). They reported an average annual income of $ 22,745 ( SD = $ 15,815; range = $ 0–72,000). Slightly more than half of the adults (52.6%) were employed, and participants had, on average, completed high school ( M years of schooling = 12.67, SD = 2.37). Most were married (63.3%), with an average relationship length of 6.7 years ( SD = 5.5), and mostly lived in blended families (64.9%). Procedure Couples were recruited from the Denver metropolitan area using several methodologies, including community organizations, direct contact, flyers, media interviews, and newspaper advertisements. Couples interested were screened for: (a) household income at or below 200% federal poverty, (b) being in a committed relationship and cohabiting for six or more months, and (c) coparenting at least one child under age 18. Exclusion criteria included prior experiences with the intervention content, could not fluently read or write in English, or denoted they were uninterested in participating in one of the intervention conditions. Eligible participants were block-randomized into one of four groups: a control group that did not participate in workshops ( n = 72), a couple group with couples attending together ( n = 77), a father-only group ( n = 72), and a mother-only group ( n = 80). Those selected for interventions began attending sessions within two weeks of completing the preassessment. Postintervention assessments were administered two weeks after completion of the intervention and mirrored the preintervention. Finally, follow-up assessments were completed six months after the postintervention assessment. Couples received escalating compensation (i.e., $ 80, $ 120, and $ 140; see Wadsworth et al., 2011 , for further details of study procedures). The present study draws on data collection at the preintervention time point (T1) and six-month follow-up (T3). All study procedures were approved by the Institutional Review Board (IRB Protocol 471720-4; Fatherhood, Relationship, and Marriage Education project). Data can be accessed from the last author upon request. FRAME Workshops The FRAME intervention is a 14-hour father-inclusive family strengthening workshop adapted from the Prevention and Relationship Enhancement Program (PREP; Markman et al., 1988 ). The FRAME intervention was designed specifically for lower socioeconomic status couples and those at risk of relationship strain. The curriculum includes three main sections: relationship education, stress and coping skills training, and child-centered parent training. First, in the relationship education component, couples learn about negative communication styles (e.g., withdrawal), positive communication skills, conflict resolution, and expectation evaluation. Second, the stress and coping skill training component details how to recognize stressors, especially financial stressors, and how to differentiate them from other solvable events. This includes practicing relaxation techniques, exploring the role of social support in buffering stress, identifying problem solving techniques, and focusing on manageable solutions. Then, they learn coping strategies for stressors that lack an immediate solution through acceptance and cognitive reframing (Wadsworth et al., 2011 ). Finally, the child-centered parenting component helps caregivers identify and enforce developmentally appropriate behavior expectations through positive reinforcement and alternatives to physical corrective measures (e.g., spanking). Measures Poverty-Related Adversity Poverty-related adversity, including economic distress and family adversities, was assessed using mothers’ and fathers’ reports at T1. These reports were used to create binary indicators. Reliability estimates are presented in Supplemental File 1 for all multi-item scales. Economic Distress . Two indicators of economic distress were collected: economic hardship and job instability. Economic hardship was assessed using the Economic Hardship Questionnaire (Lempers et al., 1989 ), which asks parents to report changes to their living style. The 11-item scale is rated on a 4-point Likert scale (1 = “never” to 4 = “very often”). Mother and father reports were averaged and dichotomized (0 = below the sample mean; 1 = above the sample mean). Job instability was assessed with a single item from the Major Events Inventory (Conger et al., 1993 ), based on combined parent reports, where 0 = neither parent experienced event and 1 = at least one parent experienced event. Family Adversities . Eleven indicators of family adversities (e.g., domestic violence and family mental and physical health problems) were included (Adjei et al., 2024 ). The Conflict Tactics Scale (Straus et al., 1996 ), a 6-point Likert scale which includes reports from mothers and fathers assessing their exposure to four items measuring psychological aggression (e.g., “my partner insulted or swore at me”), five items measuring physical assault (e.g., “my partner threw something at me that could hurt”), two items measuring injury (e.g., “I had a sprain, bruise, or small cut from my partner”). Responses to each type of domestic violence were dichotomized, where 0 = below the mean and 1 = above the mean. Mother and father reports were not averaged into a combined score as above to differentiate between violence exposure by each partner. Martial strain, family legal problems, and family health problems were measured using items from the Major Events Inventory. Each parent reported major life events over the past 3 months. Each single event item was dichotomized, where 0 = neither parent experienced event and 1 = at least one parent experienced event. For the Center for Epidemiological Studies Depression Scale-20 item (Radloff, 1977 ), parents reported their depressive symptoms (e.g., “I felt lonely”) in the past week on a 4-point Likert scale (1 = “rarely or none of the time” to 4 = “most or all of the time”). For each parent, dichotomized indicators were generated, where 0 = below the clinical cutoff for depression (i.e., score 15). Family Clinical Outcomes All family clinical outcomes reflect the averaged T3 scores of mothers and fathers. Scale scores were calculated by averaging their respective items, permitting inclusion of cases with missing item-level data. When applicable (i.e., scales consisting of more than two items), reliability indicators are presented in Supplemental File 1. Correlations between mothers’ and fathers’ ratings ranged from weak, such as r = .14 for parental inconsistent discipline, to moderate, such r = .45 for child behavior problems. Parent Engagement Coping . The Response to Stress Questionnaire (Connor-Smith et al., 2000 ) was used to assess engagement coping. Participants reported how often they engaged in various coping thoughts and behaviors for eighteen items drawn from the full 57-item measure, using a 4-point scale ranging from 1, “not at all,” to 4, “a lot.” The engagement coping measure was constructed by combining items examining primary control coping (e.g., emotional regulation) and secondary control coping (e.g., active acceptance), which are associated with positive outcomes for those experiencing economic stress (Wadsworth et al., 2011 ). For each domain, proportional scores were calculated by dividing an individual’s score on their primary or secondary dimension respectively by their total measure score. Higher scores indicate higher levels of engagement coping (Connor-Smith et al., 2000 ; Wadsworth et al., 2011 ). Couple Relationship Quality . The Dyadic Adjustment Scale–Short Form (Hunsley et al., 2001 ) is a seven-item measure designed to assess the overall quality of participants’ relationships. Items 1–3 are rated on a 6-point scale ranging from 1 = “always agree” to 6 = “always disagree” and are reverse scored. Items 4–6 are rated on a 6-point scale ranging from 1 = “never” to 6 = “more often than once a day.” Item 7 is rated on a 7-point scale ranging from 1 = “extremely unhappy” to 7 = “perfect.” All items are averaged for a total score, with higher values reflecting more positive relationship quality. Parental Warmth . The Children’s Report of Parent Behavior Inventory (Schludermann & Schludermann, 1970 ) is a 30-item measure designed to assess parenting behaviors. Parents rated how characteristic each behavior was of their interactions with their child, such as talking about their children’s worries or ability to make their child feel better, on a 3-point Likert scale ranging from 1 = “not like you” to 3 = “a lot like you.” Parental warmth was assessed using the 8-item acceptance subscale, where higher scores reflect greater warmth. Parental Inconsistent Discipline . Parental inconsistent discipline was also measured with five items from the Children’s Report of Parent Behavior Inventory (e.g., “I only keep a rule when it suits me”). A mean score was computed, where higher scores reflect higher discipline inconsistency. Child Behavior Problems . Children’s behavioral and emotional difficulties were assessed using the 113-item Child Behavior Checklist (Achenbach, 1991 ). Parents indicated the extent to which each behavior was applicable to their child on a 3-point Likert scale, where 0 = “absent” and 2 = “occurs often.” Raw scores were transformed into norm-referenced T -scores, with higher scores reflecting higher child behavior problems. Session Attendance . Session attendance was assessed as the percentage of workshops the family attended. Analysis Plan Our analytic plan followed a series of steps carried out in R for preliminary data processing and in Mplus 8 for mixture modeling (Muthén & Muthén, 2012 ). First, we examined distributions, correlations, and model assumptions to ensure that variables met criteria for inclusion in subsequent analyses. Second, we estimated latent class models to determine the optimal number of classes by comparing one through seven class solutions and reviewing fit indices, including the Bayesian information criterion and the bootstrapped likelihood ratio test (Nylund et al., 2007 ). Detailed results of the model selection process are provided in Additional File 1. Third, we evaluated differences in demographic characteristics across classes using the modified three-step procedure available through the R3STEP option in Mplus (Asparouhov and Muthén, 2014). Fourth, we applied the BCH three-step method (Asparouhov & Muthén, 2019 ; Bolck et al., 2004 ) to incorporate distal outcomes while adjusting for classification uncertainty. In contrast to our earlier paper (Cooper et al., 2025), the current study extends this framework by examining whether latent class membership moderates intervention effects on the same distal outcomes. Consistent with recommendations for latent class moderation (Bray et al., 2023 ), we used BCH-derived weights to estimate models that included the interaction between latent class membership and intervention condition. After exporting the BCH weights, we fit weighted regression models in which class membership, intervention assignment, and their interaction predicted family outcomes at T3. This approach allowed us to test whether the intervention effect differed across classes by evaluating class-by-condition interaction terms and conducting pairwise comparisons, such as contrasting the intervention effect for families in the highest risk class with the effect for those in the lowest risk class. Missing data conformed to missing at random assumptions (MAR) and were addressed using full information maximum likelihood in latent class estimation and listwise deletion in R3STEP and BCH models. Supplemental File 2 includes sample Mplus syntax illustrating the analytic steps (See Bray et al., 2023 for a full explanation of the BCH approach applied to differential intervention effects). Results Preliminary Analyses & Identifying Latent Classes Results of steps 1–3 of our analysis (i.e., preliminary analyses, identifying latent classes, evaluating demographic differences) were presented previously, but are briefly summarized below for necessary context. Preliminary analyses are presented in Supplemental File 1. Overall, families reported high levels of poverty-related adversity, such as job instability (75% of the sample), parental depressive symptoms (56% of mothers, 41% of fathers), and physical assault by a partner (52% of sample). Bivariate correlations of poverty-related adversities ranged from .01 to .54, and over half were statistically significant (Supplemental File 1). Using LCA, we identified four unique classes of poverty-related family risk based on model fit indices and interpretability of the classes (see Supplemental File 1). Most indicators (i.e., Akaike information criterion, adjusted Bayesian information criterion, entropy, Lo-Mendell-Rubin adjusted likelihood test, and bootstrapped likelihood ratio test statistics) suggested an improvement in model fit as the number of classes approached five, followed by a decrease in model fit for the six- and seven-class solutions. Although the five-class solution showed some evidence of improved fit (e.g., bootstrapped likelihood ratio test) over the four-class solution, the fifth class was small (5.3% of the sample), which can lead to less reliable parameter estimates. Additionally, the Lo-Mendell-Rubin adjusted likelihood test and Akaike information criterion values suggested it was a worse fit than the four-class solution. We, therefore, selected the more parsimonious four-class solution as the overall best fitting model. We named the classes as follows: Low Adversity (moderate levels of job instability, lower on most other poverty-related adversities; 15% of the sample), Mothers At Risk (higher than average scores on mother-reported domestic violence, lower than average father-reported domestic violence; 11%), Economic Stress, Depressive Parents (moderate levels of economic distress and parent depressive symptoms, lower than average levels of domestic violence; 41%), and Extreme Adversity (higher than average scores on most adversities; 33%; see Table 1 ). We then examined the baseline characteristics of each latent class using the R3STEP approach with the Low Adversity class set as the reference group to ease interpretation and minimize pairwise comparisons (Supplemental File 1). Overall, we found that classes were similar across the demographic characteristics we examined, including family size, parent and child age, household income, education level, intervention participation, and relationship status. Table 1 Item Response Probabilities for Family Risk Subgroups Whole Sample ( Range : 0–1) Low Adversity (15%) Mothers At Risk (11%) ESDP (41%) Extreme Adversity (33%) Economic Distress Economic Hardship .48 .13↓ .35 .58 .55 Job Instability .75 .54 .65 .77 .86↑ Family Adversities Victim of Psychological Aggression (mother) .51 .17↓ .81↑ .37↓ .75↑ Victim of Psychological Aggression (father) .50 .07↓ .37 .51 .73↑ Victim of Physical Assault (mother) .52 .32 1.00↑ .10↓ 1.00↑ Victim of Physical Assault (father) .52 .19↓ .00↓ .44 .94↑ Victim of Injury (mother) .25 .06↓ .57↑ .00↓ .55↑ Victim of Injury (father) .29 .06↓ .00↓ .15↓ .66↑ Family Marital Strain .60 .18↓ .62 .61 .77↑ Family Legal Problems .51 .11↓ .73↑ .47 .68↑ Family Health Problems .49 .29 .36 .55 .56 Mother Depression .56 .18↓ .74 .57 .65 Father Depression .41 .08↓ .22↓ .50 .51 Note. Arrows represent significant differences ( p <.05) between the class probabilities and the full sample probabilities. Bold text indicates higher risk than the full sample. ESDP = Economic Stress, Depressive Parents . Item response probabilities are the probabilities of reporting a risk factor given latent class. Example interpretation: 75% of mothers in the Extreme Adversity class experienced above-average levels of psychological aggression from their partners. This proportion was significantly higher than the sample mean. Comparing Intervention Effects Across Latent Classes Using the BCH approach, we found that risk class moderated intervention effects for only one of the five couple-reported outcomes: couple relationship quality. Families in the Economic Stress, Depressive Parents class demonstrated less negative effects on couple relationship quality than those in the Low Adversity class, who showed worse scores in this domain after receiving the intervention. Although other moderation tests were nonsignificant ( p > .05), consistent patterns emerged in the direction of effects. The Economic Stress, Depressive Parents class generally showed the least negative response, and in some cases, trending positive effects, whereas the Low Adversity class showed the least benefit and demonstrated worse functioning than the control condition across several outcomes. See Table 2 for a full report of the class differences in family outcomes. Table 2 Association of Intervention Condition with Family Outcomes at 6-months Moderated by Risk Class (N=301) Couple-report Mother-report Father-report B CI B CI B CI Couple Relationship Quality Intercept 3.93 [3.43, 4.43] 3.97 [3.35, 4.58] 3.90 [3.42, 4.37] Intervention Condition (FRAME) .27 [-.26, .80] .29 [-.37, .94] .25 [-.26, .77] Latent Risk Classes Low Adversity 1.38 [.78, 1.98] .81† [-.08, 1.71] 1.95 [1.37, 2.53] ESPD ref Mothers At Risk -.37 [-1.87, 1.14] -.71 [-2.47, 1.05] -.02 [-1.72, 1.67] Extreme Adversity -.01 [-.60, .58] -.15 [-.88, .58] .13 [-.49, .75] Moderation Low Adversity -.95 [-1.64, -.27] -.41 [-1.41, .59] -1.50 [-2.18, -.81] Mothers At Risk .53 [-1.02, 2.09] .55 [-1.28, 2.39] .51 [-1.22, 2.25] Extreme Adversity -.23 [-.89, .42] -.21 [-1.04, .62] -.26 [-.96, .44] Parental Warmth Intercept 2.63 [2.52, 2.74] 2.75 [2.61, 2.90] 2.51 [2.35, 2.67] Intervention Condition (FRAME) .11 [-.02, .24] .04 [-.12, .20] .17† [-.01, .35] Latent Risk Classes Low Adversity .23 [.03, .44] .06 [-.20, .31] .41 [.18, .64] ESPD ref Mothers At Risk .18 [-.05, .41] -.10 [-.49, .28] .46 [.27, .66] Extreme Adversity .03 [-.11, .18] -.06 [-.24, .13] .11 [-.09, .32] Moderation Low Adversity -.18 [-.43, .06] -.06 [-.36, .24] -.31 [-.58, -.03] Mothers At Risk -.17 [-.43, .09] .07 [-.35, .50] -.41 [-67, -.15] Extreme Adversity -.08 [-.26, .10] -.01 [-.24, .22] -.14 [-.38, .11] Parental Inconsistent Discipline Intercept 1.43 [1.30, 1.56] 1.59 [1.34, 1.83] 1.27 [1.10, 1.43] Intervention Condition (FRAME) -.02 [-.17, .14] -.20 [-.48, .07] .19† [-.01, .39] Latent Risk Classes Low Adversity -.13 [-.41, .15] -.28 [-.75, .19] .12 [-.29, .53] ESPD ref Mothers At Risk -.11 [-.34, .11] -.26 [-.76, .25] .03 [-.27, .32] Extreme Adversity .08 [-.13, .29] -.09 [-.41, .23] .28 [.00, .55] Moderation Low Adversity .01 [-.32, .35] .24 [-.29, .76] -.30 [-.77, .17] Mothers At Risk .27 [-.06, .61] .78 [.14, 1.41] -.24 [-.62, .13] Extreme Adversity -.10 [-.35, .15] .06 [-.30, .42] -.30† [-.63, .02] Note . Bold font represents a significant effect at p < .05. Due to limited power for certain moderation effects, † indicates marginal significance at p < .10. Only outcomes with significant findings are presented here. See Supplemental File 1 for results for other family outcomes. Sensitivity analyses, separating out effects using mother- and father-reported outcomes, revealed both convergence and divergence with the couple-level results. For mothers’ reported outcomes, several moderation findings were consistent (i.e., coping skills and parental warmth), however, new class-specific intervention response differences emerged for inconsistent discipline. Specifically, mothers in the Mothers At Risk class reported significantly worse inconsistent discipline after receiving the intervention compared to the control group, and the Economic Stress, Depressive Parents class reported more favorable effects (i.e., less negative) than the Mothers At Risk class. Mothers in the Economic Stress, Depressive Parents class also showed trending positive effects ( p < .10) in child behavior problems relative to the Extreme Adversity class. For fathers, moderation findings paralleled the couple-level analyses for coping skills, relationship quality, and child behavior problems. However, fathers in the Economic Stress, Depressive Parents class reported uniquely stronger positive effects in parental warmth relative to both the Low Adversity and Mothers At Risk classes. In contrast, fathers in the Extreme Adversity class showed marginally greater positive effects in inconsistent discipline than the Economic Stress, Depressive Parents class. When considered together, these analyses suggest that three of the five outcomes demonstrated some form of differential intervention response across classes, with trending differences for one additional outcome. See Table 2 for specific parameter estimates for the class comparisons separated by mothers’ and fathers’ reports. Comparing Attendance Rates Across Latent Classes We examined whether latent class membership was associated with workshop attendance among families assigned to the intervention condition ( n = 226). The latent class structure replicated within this subsample, with class prevalences and item-response probabilities closely matching those in the full sample. Attendance rates varied across classes. Families in the Economic Stress, Depressive Parents class attended the highest proportion of sessions (74.0%), followed by the Extreme Adversity (58.5%) and Low Adversity (55.5%) classes. The Mothers At Risk class had the lowest attendance (42.9%). Pairwise comparisons indicated that the Economic Stress, Depressive Parents class attended significantly more sessions than the Extreme Adversity ( B = − .16, 95% CI [− .29, − .02]) and Mothers At Risk ( B = − .31, 95% CI [-.53, − .09]) classes. No other class differences in attendance were statistically significant. Discussion This study used a person-centered approach to examine whether certain risk classes uniquely benefited from a family-based prevention program for economically disadvantaged families. Using multiple indicators of poverty-related adversities, including economic hardship and family adversities, such as parental mental and physical health problems and domestic violence, we identified four distinct family risk classes, driven mostly by differences in exposure to domestic violence and parental depressive symptoms. Families in the Low Adversity class (15%) showed moderate levels of job instability but reported relatively few challenges in other areas of economic or psychosocial risk. The Mothers At Risk class (11%) was characterized by elevated mother-reported domestic violence exposure and depressive symptoms paired with comparatively low father-reported domestic violence and depressive symptoms. The largest class, Economic Stress, Depressive Parents (41%), reflected families experiencing moderate economic hardship and higher parental depressive symptoms, with limited exposure to domestic violence. The Extreme Adversity class (33%) included families reporting elevated difficulties across nearly all assessed domains of risk. These risk classes were similar demographically (e.g., household income, education, family size, parent and child age, relationship status), which reduces the likelihood that demographic differences contributed to class variability and strengthens our ability to attribute observed differences to adversity profiles. Findings from distal outcome and moderation analyses revealed important differences in how family risk classes benefited from and engaged with the intervention across five outcomes, based on combined mother and father reports. At the couple level, risk class moderated intervention effects for only one of the five outcomes. Specifically, families in the Economic Stress, Depressive Parents class demonstrated more favorable (i.e., less negative) intervention effects on relationship quality relative to the Low Adversity class. In fact, the Low Adversity class experienced worse couple relationship quality than those randomized into the control condition. For the remaining outcomes, the direction of effects generally followed a similar pattern, with the Economic Stress, Depressive Parents group showing modest advantages (though not reaching significance) relative to the other classes. It is important to note that across all four classes, families randomized into the intervention condition did not have significantly better outcomes than the control group, potentially due to limited power or unmodeled heterogeneity across intervention formats (Wadsworth et al., 2011 ). To better understand the stability of these findings, we conducted sensitivity analyses to determine whether there were additional class differences in intervention effects based on whether the outcomes were reported by mothers or fathers. Although many patterns were consistent with the combined couple-level reports, additional class-specific differences in intervention effects emerged. For example, mothers in the Mothers At Risk class reported significantly greater rates of inconsistent discipline than those in the control group, and showed worse intervention response than the Economic Stress, Depressive Parents class. When examining fathers’ individually reported outcomes, we found similar results to most couple-level reports, with one major exception. Fathers in the Economic Stress, Depressive Parents class reported better intervention-related effects on parental warmth than both the Low Adversity and Mothers At Risk classes. Taken in concert, these patterns indicate that mothers and fathers may experience distinct effects within certain risk classes, underscoring the value of examining individual-level reports in addition to couple-level composites. The overall pattern of results aligns with the growing literature suggesting that family-based interventions may be most beneficial for families experiencing moderate levels of adversity (Cooper et al., 2024; Lee et al., 2024 ; Weber et al., 2024 ), a phenomenon characterized as the goldilocks effect (Miller et al., 2014 ). Families in the Economic Stress, Depressive Parents class, who faced substantial but not extreme hardship, often experienced better intervention responses than families in either the lowest or highest risk groups. It is worth noting that prior research with this sample found that the Economic Stress, Depressive Parents class exhibited some of the least favorable longitudinal family outcomes when examined independent of intervention participation (Cooper et al., 2025). The superior intervention response among the Economic Stress, Depressive Parents class in the current study is, therefore, especially notable, as it suggests that program participation may help interrupt negative developmental trajectories. This pattern is consistent with several recent studies using cluster-based approaches, which find that families with moderate risk often show the greatest capacity to engage with and apply intervention content, whereas families with very low risk may have limited room to improve and families with very high risk may encounter barriers to engagement Cooper et al., 2024; Lee et al., 2024 ; Weber et al., 2024 ). For example, subgroup analysis of a parenting intervention found that parents with moderate initial levels of positive parenting practices showed the greatest improvement relative to those in the highest or lowest functioning classes (Lee et al., 2024 ). Similarly, a study evaluating a relationship education program found that couples with moderate baseline risk (i.e., moderate relationship satisfaction) experienced the largest gains after receiving the intervention (Weber et al., 2024 ). Differences in session attendance offer an additional explanation for the differential intervention effects observed across classes. Attendance rates varied considerably, with the Economic Stress, Depressive Parents class attending nearly three-quarters of sessions, which was substantially higher than the two highest risk classes and almost twice the rate of the Mothers At Risk class. Surprisingly, the lowest and highest risk classes did not differ from one another in attendance, contrary to expectations and past literature suggesting that the lowest risk families may have fewer barriers to participation and thus higher attendance (LoBraico et al., 2021 ). However, several studies have indicated that attendance may be based on factors beyond risk level, such as motivation and perceived time constraints (Dumas et al., 2007 ). The attendance patterns found in our study provide a plausible mechanism for the intervention’s stronger impact among the Economic Stress, Depressive Parents group, who were highly engaged and positioned to benefit from program content. Conversely, lower attendance among the Mothers At Risk and Extreme Adversity classes may help to explain their comparatively limited improvement across outcomes. This intersection of risk profiles and engagement adds an important contribution to the literature by providing insight into how attendance may amplify or constrain intervention effects across differing levels of family adversity. Strengths and Limitations This study had numerous strengths, including multi-informant measures to assess family-level constructs, a comprehensive, person-centered approach to assessing poverty-related adversity, a longitudinal randomized design, and a dual focus on understanding differential responses and engagement with family-based prevention. Several limitations should also be noted. First, the sample does not reflect the full diversity of families experiencing economic hardship, particularly those residing in rural communities or those with family structures not represented here (e.g., single parents living apart from partners or same-sex couples). As a result, the extent to which these findings extend to these groups is uncertain. Second, our measurement of adversity focused on a subset of challenges commonly faced by families with limited financial resources but did not capture other important sources of stress, including experiences of discrimination or structural racism. Incorporating these forms of adversity in future research will be essential, given their well-documented links to parent and child well-being (Cave et al., 2020 ). Third, certain class sizes were relatively small (e.g., Mothers At Risk ), which likely impacted the ability to detect small class differences. Consequently, some null or marginal findings may reflect limited statistical power rather than the true absence of differential effects. Fourth, although the use of mother and father reports is a strength, all family functioning outcomes relied on self-report, which may introduce shared method variance or social desirability bias. Finally, although the intervention was delivered in three formats (mothers-only, fathers-only, and couple dyads), the sample size within each subgroup did not allow for adequately powered tests of differential intervention response across these delivery conditions. Implications and Conclusion The pattern of differential intervention effects has implications for how prevention programs are tailored and implemented. The finding that families experiencing moderate levels of adversity showed the most favorable outcomes suggests that interventions such as FRAME may yield the strongest returns when directed toward families who have identifiable needs yet retain sufficient stability to engage fully with program content. This aligns with precision-prevention frameworks that emphasize the match between families’ needs and the content of the intervention (August & Gewirtz, 2019 ). Notably, the risk class that benefited most from FRAME also demonstrated the highest levels of session attendance, suggesting that differential engagement may play an important role in affecting intervention response. Although the present study was not designed to test attendance as a causal mechanism, this pattern suggests that facilitating consistent participation may be a useful strategy for improving intervention effects for non-responders. Beyond the role of intervention attendance, the limited benefits observed for families at the lowest and highest ends of the risk continuum may suggest that a single intervention approach is not equally well suited for all families. For low-risk families, prevention efforts may require more focused content that is responsive to narrower areas of need rather than broad, multi-component programming. For high-risk families, additional scaffolding may be necessary, such as addressing acute stressors prior to skill-building. Overall, this study demonstrates the value of identifying heterogeneity in how families respond to prevention programs and highlights the utility of latent class methods for uncovering patterns that remain obscured when relying on variable-centered approaches. By demonstrating that families with distinct adversity profiles differ in their engagement with and response to intervention, these findings clarify for whom prevention programs are most (and least) effective. These findings advance the broader goals of prevention science by informing more targeted and efficient approaches to intervention delivery. Continued research in this area will be essential for refining precision prevention strategies and designing programs that better align with families’ needs, thereby promoting more consistent benefits across diverse risk contexts. Declarations Funding and Competing Interests: This project was supported by the National Institute of Mental Health (R03 MH127455; Daniel Cooper) and the National Institute of General Medical Sciences (P20 GM130420; Ronald Prinz). The authors have no relevant financial or non-financial interests to disclose. Ethics Approval and Consent to Participate: All procedures were approved by the University of Denver Institutional Review Board (IRB protocol: 471720-4, FRAME project) and were conducted in accordance with the Declaration of Helsinki. Informed consent was obtained from all individual participants included in the study. Clinical Trial Registration : Not applicable for this secondary analysis. Availability of Data and Materials: Data are available upon reasonable request from the last author. Mplus code used to conduct analyses is available in Supplemental File 2. Author Contributions: DKC: Conceptualization, Methodology, Formal analysis, Writing – original draft, Supervision. BLB & EKL: Methodology, Formal analysis, Writing – review & editing. FL & DP: Writing – review & editing. MEW: Conceptualization, Funding acquisition, Writing – review & editing. References Achenbach, T. M. (with Internet Archive). (1991). Manual for the child behavior checklist/4-18 and 1991 profile . Burlington, VT : Dept. of Psychiatry, University of Vermont. http://archive.org/details/manualforchildbe0000ache_g2r5 Adjei, N. K., Jonsson, K. R., Straatmann, V. S., Melis, G., McGovern, R., Kaner, E., Wolfe, I., Taylor-Robinson, D. C., the ORACLE consortium, Barrett, S., Tubah, S., Forman, J., Hirve, R., Bangisky, M., Boulding, H., Hackett, S., Fox-Rushby, J., Muir, C., Sophie, K., & Salmon, A. (2024). Impact of poverty and adversity on perceived family support in adolescence: Findings from the UK Millennium Cohort Study. European Child & Adolescent Psychiatry , 33 (9), 3123–3132. https://doi.org/10.1007/s00787-024-02389-8 Asparouhov, T., & Muthén, B. (2019). Auxiliary Variables in Mixture Modeling: Using the BCH Method in Mplus to Estimate a Distal Outcome Model and an Arbitrary Secondary Model . https://www.statmodel.com/examples/webnotes/webnote21.pdf August, G. J., & Gewirtz, A. (2019). Moving Toward a Precision-Based, Personalized Framework for Prevention Science: Introduction to the Special Issue. Prevention Science , 20 (1), 1–9. https://doi.org/10.1007/s11121-018-0955-9 Bolck, A., Croon, M., & Hagenaars, J. (2004). Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators. Political Analysis , 12 (1), 3–27. https://doi.org/10.1093/pan/mph001 Bray, B. C., Layland, E. K., Stull, S. W., Vasilenko, S. A., & Lanza, S. T. (2023). Estimating the Effects of a Complex, Multidimensional Moderator: An Example of Latent Class Moderation to Examine Differential Intervention Effects of Substance Use Services. Prevention Science , 24 (3), 493–504. https://doi.org/10.1007/s11121-022-01448-3 Cai, Q., Chan, A. C. Y., Lee, S.-K., Marsalis, S., & Gewirtz, A. H. (2022). Effectiveness of GenerationPMTO to Promote Parenting and Child Adjustment: A Meta-Analytic Review. Clinical Child and Family Psychology Review , 25 (4), 702–719. https://doi.org/10.1007/s10567-022-00400-9 Cave, L., Cooper, M. N., Zubrick, S. R., & Shepherd, C. C. J. (2020). Racial discrimination and child and adolescent health in longitudinal studies: A systematic review. Social Science & Medicine , 250 , 112864. https://doi.org/10.1016/j.socscimed.2020.112864 Cho, E., Chorpita, B. F., Reeder, K., Alegría, M., Price, M. A., Weisz, J. R., & The Research Network on Youth Mental Health. (2025). Ethnicity and income as predictors of clinical outcomes of a youth-focused personalizable modular treatment. Journal of Consulting and Clinical Psychology , 93 (10), 677–689. https://doi.org/10.1037/ccp0000979 Cleland, C. M., Lanza, S. T., Vasilenko, S. A., & Gwadz, M. (2017). Syndemic Risk Classes and Substance Use Problems among Adults in High-Risk Urban Areas: A Latent Class Analysis. Frontiers in Public Health , 5 , 237. https://doi.org/10.3389/fpubh.2017.00237 Compas, B. E., Champion, J. E., Forehand, R., Cole, D. A., Reeslund, K. L., Fear, J., Hardcastle, E. J., Keller, G., Rakow, A., Garai, E., Merchant, M. J., & Roberts, L. (2010). Coping and parenting: Mediators of 12-month outcomes of a family group cognitive–behavioral preventive intervention with families of depressed parents. Journal of Consulting and Clinical Psychology , 78 (5), 623–634. https://doi.org/10.1037/a0020459 Conger, R. D., & Conger, K. J. (2002). Resilience in Midwestern Families: Selected Findings from the First Decade of a Prospective, Longitudinal Study. Journal of Marriage and Family , 64 (2), 361–373. https://doi.org/10.1111/j.1741-3737.2002.00361.x Conger, R. D., Lorenz, F. O., Elder, G. H., Simons, R. L., & Ge, X. (1993). Husband and Wife Differences in Response to Undesirable Life Events. Journal of Health and Social Behavior , 34 (1), 71. https://doi.org/10.2307/2137305 Connor-Smith, J. K., Compas, B. E., Wadsworth, M. E., Thomsen, A. H., & Saltzman, H. (2000). Responses to stress in adolescence: Measurement of coping and involuntary stress responses. Journal of Consulting and Clinical Psychology , 68 (6), 976–992. https://doi.org/10.1037/0022-006X.68.6.976 Dishion, T. J., Brennan, L. M., Shaw, D. S., McEachern, A. D., Wilson, M. N., & Jo, B. (2014). Prevention of Problem Behavior Through Annual Family Check-Ups in Early Childhood: Intervention Effects From Home to Early Elementary School. Journal of Abnormal Child Psychology , 42 (3), 343–354. https://doi.org/10.1007/s10802-013-9768-2 Dumas, J. E., Nissley-Tsiopinis, J., & Moreland, A. D. (2007). From Intent to Enrollment, Attendance, and Participation in Preventive Parenting Groups. Journal of Child and Family Studies , 16 (1), 1–26. https://doi.org/10.1007/s10826-006-9042-0 Fawcett, E. B., Hawkins, A. J., Blanchard, V. L., & Carroll, J. S. (2010). Do Premarital Education Programs Really Work? A Meta‐analytic Study. Family Relations , 59 (3), 232–239. https://doi.org/10.1111/j.1741-3729.2010.00598.x Gardner, F., Connell, A., Trentacosta, C. J., Shaw, D. S., Dishion, T. J., & Wilson, M. N. (2009). Moderators of outcome in a brief family-centered intervention for preventing early problem behavior. Journal of Consulting and Clinical Psychology , 77 (3), 543–553. https://doi.org/10.1037/a0015622 Gardner, F., Hutchings, J., Bywater, T., & Whitaker, C. (2010). Who Benefits and How Does It Work? Moderators and Mediators of Outcome in an Effectiveness Trial of a Parenting Intervention. Journal of Clinical Child & Adolescent Psychology , 39 (4), 568–580. https://doi.org/10.1080/15374416.2010.486315 Gardner, F., Leijten, P., Harris, V., Mann, J., Hutchings, J., Beecham, J., Bonin, E.-M., Berry, V., McGilloway, S., Gaspar, M., João Seabra-Santos, M., Orobio de Castro, B., Menting, A., Williams, M., Axberg, U., Morch, W.-T., Scott, S., & Landau, S. (2019). Equity effects of parenting interventions for child conduct problems: A pan-European individual participant data meta-analysis. The Lancet. Psychiatry , 6 (6), 518–527. https://doi.org/10.1016/S2215-0366(19)30162-2 Gardner, F., Leijten, P., Melendez‐Torres, G. J., Landau, S., Harris, V., Mann, J., Beecham, J., Hutchings, J., & Scott, S. (2019). The Earlier the Better? Individual Participant Data and Traditional Meta‐analysis of Age Effects of Parenting Interventions. Child Development , 90 (1), 7–19. https://doi.org/10.1111/cdev.13138 Hackworth, N. J., Matthews, J., Westrupp, E. M., Nguyen, C., Phan, T., Scicluna, A., Cann, W., Bethelsen, D., Bennetts, S. K., & Nicholson, J. M. (2018). What Influences Parental Engagement in Early Intervention? Parent, Program and Community Predictors of Enrolment, Retention and Involvement. Prevention Science , 19 (7), 880–893. https://doi.org/10.1007/s11121-018-0897-2 Hunsley, J., Best, M., Lefebvre, M., & Vito, D. (2001). The Seven-Item Short Form of the Dyadic Adjustment Scale: Further Evidence for Construct Validity. American Journal of Family Therapy , 29 (4), 325–335. https://doi.org/10.1080/01926180152588734 Landers‐Potts, M. A., Wickrama, K. A. S., Simons, L. G., Cutrona, C., Gibbons, F. X., Simons, R. L., & Conger, R. (2015). An Extension and Moderational Analysis of the Family Stress Model Focusing on African American Adolescents. Family Relations , 64 (2), 233–248. https://doi.org/10.1111/fare.12117 Lanza, S. T., & Rhoades, B. L. (2013). Latent Class Analysis: An Alternative Perspective on Subgroup Analysis in Prevention and Treatment. Prevention Science , 14 (2), 157–168. https://doi.org/10.1007/s11121-011-0201-1 Laurenceau, J.-P., Stanley, S. M., Olmos-Gallo, A., Baucom, B., & Markman, H. J. (2004). Community-Based Prevention of Marital Dysfunction: Multilevel Modeling of a Randomized Effectiveness Study. Journal of Consulting and Clinical Psychology , 72 (6), 933–943. https://doi.org/10.1037/0022-006X.72.6.933 Lee, S.-K., Gewirtz, A. H., & Piehler, T. F. (2024). Parenting Profiles in Military Families: Intervention-Related Transitions and Relationships to Child Adjustment. Prevention Science , 25 (7), 1040–1052. https://doi.org/10.1007/s11121-024-01721-7 Leijten, P., Raaijmakers, M., Wijngaards, L., Matthys, W., Menting, A., Hemink-van Putten, M., & Orobio De Castro, B. (2018). Understanding Who Benefits from Parenting Interventions for Children’s Conduct Problems: An Integrative Data Analysis. Prevention Science , 19 (4), 579–588. https://doi.org/10.1007/s11121-018-0864-y Leijten, P., Scott, S., Landau, S., Harris, V., Mann, J., Hutchings, J., Beecham, J., & Gardner, F. (2020). Individual Participant Data Meta-analysis: Impact of Conduct Problem Severity, Comorbid Attention-Deficit/Hyperactivity Disorder and Emotional Problems, and Maternal Depression on Parenting Program Effects. Journal of the American Academy of Child & Adolescent Psychiatry , 59 (8), 933–943. https://doi.org/10.1016/j.jaac.2020.01.023 Lempers, J. D., Clark-Lempers, D., & Simons, R. L. (1989). Economic Hardship, Parenting, and Distress in Adolescence. Child Development , 60 (1), 25. https://doi.org/10.2307/1131068 LoBraico, E. J., Fosco, G. M., Feinberg, M. E., Spoth, R. L., Redmond, C., & Bray, B. C. (2021). Predictors of Attendance Patterns in a Universal Family-Based Preventive Intervention Program. The Journal of Primary Prevention , 42 (5), 409–424. https://doi.org/10.1007/s10935-021-00636-1 Lundahl, B., Risser, H. J., & Lovejoy, M. C. (2006). A meta-analysis of parent training: Moderators and follow-up effects. Clinical Psychology Review , 26 (1), 86–104. https://doi.org/10.1016/j.cpr.2005.07.004 Markman, H. J., Floyd, F. J., Stanley, S. M., & Storaasli, R. D. (1988). Prevention of marital distress: A longitudinal investigation. Journal of Consulting and Clinical Psychology , 56 (2), 210–217. https://doi.org/10.1037/0022-006X.56.2.210 Markman, H. J., Hawkins, A. J., Stanley, S. M., Halford, W. K., & Rhoades, G. (2022). Helping couples achieve relationship success: A decade of progress in couple relationship education research and practice, 2010–2019. Journal of Marital and Family Therapy , 48 (1), 251–282. https://doi.org/10.1111/jmft.12565 Masarik, A. S., & Conger, R. D. (2017). Stress and child development: A review of the Family Stress Model. Current Opinion in Psychology , 13 , 85–90. https://doi.org/10.1016/j.copsyc.2016.05.008 Menting, A. T. A., Orobio de Castro, B., & Matthys, W. (2013). Effectiveness of the Incredible Years parent training to modify disruptive and prosocial child behavior: A meta-analytic review. Clinical Psychology Review , 33 (8), 901–913. https://doi.org/10.1016/j.cpr.2013.07.006 Miller, E. B., Farkas, G., Vandell, D. L., & Duncan, G. J. (2014). Do the Effects of Head Start Vary by Parental Preacademic Stimulation? Child Development , 85 (4), 1385–1400. https://doi.org/10.1111/cdev.12233 Muthén, L. K., & Muthén, B. O. (2012). Mplus User’s Guide. Seventh Edition. (Version 8) [Computer software]. Nylund, K. L., Asparouhov, T., & Muthén, B. O. (2007). Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study. Structural Equation Modeling: A Multidisciplinary Journal , 14 (4), 535–569. https://doi.org/10.1080/10705510701575396 Prado, G., Huang, S., Cordova, D., Malcolm, S., Estrada, Y., Cano, N., Maldonado-Molina, M., Bacio, G., Rosen, A., Pantin, H., & Brown, C. H. (2013). Ecodevelopmental and Intrapersonal Moderators of a Family Based Preventive Intervention for Hispanic Youth: A Latent Profile Analysis. Prevention Science , 14 (3), 290–299. https://doi.org/10.1007/s11121-012-0326-x Prinz, R. J. (2012). Effective parenting to prevent adverse outcomes and promote child well-being at a population level. In Transformative consumer research for personal and collective well-being (pp. 585–598). Routledge/Taylor & Francis Group. https://doi.org/10.4324/9780203813256 Radloff, L. S. (1977). The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. Applied Psychological Measurement , 1 (3), 385–401. https://doi.org/10.1177/014662167700100306 Raviv, T., & Wadsworth, M. E. (2010). The Efficacy of a Pilot Prevention Program for Children and Caregivers Coping with Economic Strain. Cognitive Therapy and Research , 34 (3), 216–228. https://doi.org/10.1007/s10608-009-9265-7 Rienks, S. L., Wadsworth, M. E., Markman, H. J., Einhorn, L., & Moran Etter, E. (2011). Father Involvement in Urban Low-Income Fathers: Baseline Associations and Changes Resulting From Preventive Intervention. Family Relations , 60 (2), 191–204. https://doi.org/10.1111/j.1741-3729.2010.00642.x Rojas, L. M., Brincks, A., Brown, E. C., Bahamon, M., Estrada, Y., Lee, T. K., Prado, G., & Pantin, H. (2023). Family Functioning in Hispanic Parents of Adolescents: Who Benefits Most from a Family-Based HIV and Substance Use Preventive Intervention? Prevention Science , 24 (2), 249–258. https://doi.org/10.1007/s11121-022-01489-8 Sanders, M. R., & Mazzucchelli, T. G. (2022). Mechanisms of Change in Population-Based Parenting Interventions for Children and Adolescents. Journal of Clinical Child & Adolescent Psychology , 51 (3), 277–294. https://doi.org/10.1080/15374416.2022.2025598 Schludermann, E., & Schludermann, S. (1970). Replicability of Factors in Children’s Report of Parent Behavior (CRPBI). The Journal of Psychology , 76 (2), 239–249. https://doi.org/10.1080/00223980.1970.9916845 Shelleby, E. C., & Shaw, D. S. (2014). Outcomes of Parenting Interventions for Child Conduct Problems: A Review of Differential Effectiveness. Child Psychiatry & Human Development , 45 (5), 628–645. https://doi.org/10.1007/s10578-013-0431-5 Smith, J. D., Montaño, Z., Dishion, T. J., Shaw, D. S., & Wilson, M. N. (2015). Preventing Weight Gain and Obesity: Indirect Effects of the Family Check-Up in Early Childhood. Prevention Science , 16 (3), 408–419. https://doi.org/10.1007/s11121-014-0505-z Solmeyer, A. R., Feinberg, M. E., Coffman, D. L., & Jones, D. E. (2014). The Effects of the Family Foundations Prevention Program on Coparenting and Child Adjustment: A Mediation Analysis. Prevention Science , 15 (2), 213–223. https://doi.org/10.1007/s11121-013-0366-x Straus, M. A., Hamby, S. L., BONEY-McCOY, S., & Sugarman, D. B. (1996). The Revised Conflict Tactics Scales (CTS2): Development and Preliminary Psychometric Data. Journal of Family Issues , 17 (3), 283–316. https://doi.org/10.1177/019251396017003001 Theise, R., Huang, K.-Y., Kamboukos, D., Doctoroff, G. L., Dawson-McClure, S., Palamar, J. J., & Brotman, L. M. (2014). Moderators of Intervention Effects on Parenting Practices in a Randomized Controlled Trial in Early Childhood. Journal of Clinical Child & Adolescent Psychology , 43 (3), 501–509. https://doi.org/10.1080/15374416.2013.833095 Van Ryzin, M. J., Roseth, C. J., Fosco, G. M., Lee, Y., & Chen, I.-C. (2016). A component-centered meta-analysis of family-based prevention programs for adolescent substance use. Clinical Psychology Review , 45 , 72–80. https://doi.org/10.1016/j.cpr.2016.03.007 Wadsworth, M. E., Santiago, C. D., Einhorn, L., Etter, E. M., Rienks, S., & Markman, H. (2011). Preliminary Efficacy of an Intervention to Reduce Psychosocial Stress and Improve Coping in Low-Income Families. American Journal of Community Psychology , 48 (3–4), 257–271. https://doi.org/10.1007/s10464-010-9384-z Weber, D. M., Lavner, J. A., & Beach, S. R. H. (2024). Different trajectories of relationship satisfaction among rural Black couples following preventive relationship intervention. Journal of Consulting and Clinical Psychology , 92 (6), 356–366. https://doi.org/10.1037/ccp0000894 Additional Declarations The authors declare no competing interests. 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Cooper","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIiWNgGAWjYDCCAwzpPz4wMPDwScCFEghqeSA5A6iFjQQtjA+keYA08Vr4jh9OMLbNsZNhk24+JsHwx46Bnz3HAK8WyTNpCcm525J52GSOJRswtiUzSPa8wa/F4AZPwuHcbcxAv+QYPmBsOAAUIWCLwQ3+j82W2+pBWgwOMPw5wGBPWAtDMjPjtsMQWxjYgLZIEPRLQhpj77bjEL8ktiXzSJx5VoBXC9/xA2kMP7dV2/ODQuzDHzs5/vbkDXi1oIIEYJySoHwUjIJRMApGAS4AABPEQU6LY10NAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-7144-8406","institution":"University of South Carolina","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"K.","lastName":"Cooper","suffix":""},{"id":603887524,"identity":"373e3fbd-0391-4374-887f-fafa116d49b8","order_by":1,"name":"Benjamin L. Bayly","email":"","orcid":"","institution":"Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Benjamin","middleName":"L.","lastName":"Bayly","suffix":""},{"id":603887525,"identity":"232e5bb7-b6d8-4224-8659-1342a30d931e","order_by":2,"name":"Eric K. Layland","email":"","orcid":"","institution":"University of Delaware","correspondingAuthor":false,"prefix":"","firstName":"Eric","middleName":"K.","lastName":"Layland","suffix":""},{"id":603887526,"identity":"16d425f1-266a-42a6-9968-507bf9df629a","order_by":3,"name":"Francesca Lupini","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Francesca","middleName":"","lastName":"Lupini","suffix":""},{"id":603887527,"identity":"02a315f5-cb30-4f68-ac10-4bfc0dc553e7","order_by":4,"name":"Darha Ponder","email":"","orcid":"","institution":"University of South Carolina","correspondingAuthor":false,"prefix":"","firstName":"Darha","middleName":"","lastName":"Ponder","suffix":""},{"id":603887528,"identity":"471d2374-986f-4e35-8eef-82ae57149b25","order_by":5,"name":"Martha E. Wadsworth","email":"","orcid":"","institution":"Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Martha","middleName":"E.","lastName":"Wadsworth","suffix":""}],"badges":[],"createdAt":"2026-03-10 14:35:23","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9085268/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9085268/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104781350,"identity":"d23651b1-a805-4fa8-a965-2f1a429883cd","added_by":"auto","created_at":"2026-03-17 07:55:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1178594,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9085268/v1/ea2a5b90-425a-4973-80e9-4c399b2ae547.pdf"},{"id":104487481,"identity":"37034a9f-83ef-4713-84e8-4d71e9c934c9","added_by":"auto","created_at":"2026-03-12 10:43:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":34781,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalFile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9085268/v1/eed7acfa90b969bb4bbb4d13.docx"},{"id":104487482,"identity":"3d5bd01a-a9d8-4bad-8e36-ea0e2f872d4e","added_by":"auto","created_at":"2026-03-12 10:43:30","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":23608,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalFile2DataSyntax.docx","url":"https://assets-eu.researchsquare.com/files/rs-9085268/v1/4cf6bf2c97f17f23d7e15138.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eUnderstanding Who Benefits Most from Family-Based Prevention: Differential Intervention Effects for Families with Low Income\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTheory and research have established a robust link between poverty, poverty-related stress, and family dysfunction (Conger \u0026amp; Conger, 2002; Landers‐Potts et al., 2015). Family-based prevention programs have demonstrated promise in addressing the negative effects of poverty and promoting well-being, but these programs are not uniformly effective for all families (Lundahl et al., 2006). In fact, the literature remains inconclusive as to who benefits most from prevention programs, with most past studies applying variable-centered methods to identify potential moderators (e.g., Shelleby \u0026amp; Shaw, 2014). Few studies have applied person-centered approaches to examine how exposure to unique clusters of poverty-related adversity, including economic distress and family adversities, such as parental mental and physical health problems and domestic violence, may impact intervention response and engagement. This is an important gap for prevention efforts because families affected by poverty are often experiencing multiple co-occurring adversities, which do not always cluster in predictable patterns, making them harder to capture using traditional variable-centered approaches. The purpose of this study was to examine, using a person-centered approach, whether families differed in both engagement with and benefit from an empirically supported prevention program for economically disadvantaged families based on their unique patterns of poverty-related risk exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengthening Families Facing Economic Hardship\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA wealth of literature shows that interventions that produce changes in parenting, marital conflict/distress, or parental coping skills can lead to positive outcomes for children (Compas et al., 2010; Solmeyer et al., 2014; Van Ryzin et al., 2016). This literature is consistent with the \u003cem\u003eFamily Stress Model\u0026nbsp;\u003c/em\u003ewhich posits that poverty can lead to a cascade of disruption and disorder beginning with (a) economic hardship and (b) economic strain, which undermine (c) parental psychological functioning and couple relationships, which interfere with (d) parenting skills and parent-child relationships, ultimately leading to (e) negative child outcomes (see\u0026nbsp;Masarik \u0026amp; Conger, 2017\u0026nbsp;for summary of evidence supporting each model pathway). It follows that interventions targeting all three areas of the Family Stress Model (i.e., coping skills, couple relationships, and parenting) may be especially effective in promoting healthy child and family functioning. However, researchers have most often targeted these areas using separate interventions. For example, positive parenting programs (e.g., Triple P, Incredible Years, GenerationPMTO, Family Check Up) include components that teach effective parenting skills, but do not include substantial content on enhancing couple relationships or managing parental stressors\u0026nbsp;(Cai et al., 2022; Menting et al., 2013; Prinz, 2012; Sanders \u0026amp; Mazzucchelli, 2022). Likewise, relationship education programs, such as Prevention and Relationship Enhancement Program (PREP) and Hold Me Tight, place a strong emphasis on improving the couple relationship, but provide little content on parenting and parent self-regulation\u0026nbsp;(Fawcett et al., 2010; Markman et al., 2022). While these programs have shown efficacy in improving various couple and family outcomes, they typically address parental coping, couple relationship functioning, and positive parenting in isolation rather than within a single integrated program, which may limit opportunities for synergistic or cross-over effects\u0026nbsp;(Smith et al., 2015), increase redundancy across interventions, and reduce feasibility for families whom participation in multiple sequential programs may be unrealistic given significant time and resource demands\u0026nbsp;(Dumas et al., 2007). There remains a dearth of studies combining parental coping skills, couple relationship enhancement, and positive parenting into a single, cohesive program.\u003c/p\u003e\n\u003cp\u003eOne of the few such interventions – Fatherhood, Relationship, and Marriage Education (FRAME) – is a family intervention aimed at protecting children and parents from the negative effects of economic strain by improving couple relationship skills, stress management, and child-centered parenting (Wadsworth et al., 2011). FRAME combines the parenting and stress management skills taught in the Families Coping with Economic Strain intervention (Raviv \u0026amp; Wadsworth, 2010)\u0026nbsp;with relationship education content from PREP\u0026nbsp;(Markman et al., 1988). PREP is one of the most extensively tested relationship education interventions, with over 42 studies by a variety of research teams demonstrating consistent short- and longer-term positive effects (e.g.,\u0026nbsp;Laurenceau et al., 2004). FRAME is one of the few interventions to apply all the major components of the Family Stress Model\u0026nbsp;(Conger \u0026amp; Conger, 2002). As such, FRAME aims to prevent adverse parent and child mental health outcomes by teaching couples strategies to deal with negative emotions, stress, conflict, and by improving couples’ communication and parenting skills. Demonstrated intervention effects have included sustained improvements in child-centered parenting and a reduction in parental depression\u0026nbsp;(Rienks et al., 2011; Wadsworth et al., 2011). Further, Wadsworth et al. (2011) found that reductions in parent depressive symptoms were due, in part, to improvements in parents’ coping skills and stress management.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentifying who Benefits Most from Family-Based Prevention\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhile family-based preventive interventions built on strong theory and solid empirical evidence have the potential to strengthen family relationships, improve parenting and coping skills, and reduce mental health problems for families living with economic hardship, the effectiveness of these programs is contingent upon families being able to engage with the content. It is well-known that even the most effective treatment and prevention programs do not help everyone, and programs targeting families with low income often have higher than average “non-response” rates (Hackworth et al., 2018). This could be due to the varying types of risks that economically disadvantaged families experience prior to the intervention. In fact, a wealth of family-based prevention research has found that intervention effects vary depending on the level of risk\u0026nbsp;(Prado et al., 2013)\u0026nbsp;and type of risk\u0026nbsp;(Leijten et al., 2018)\u0026nbsp;families were experiencing prior to the intervention. Many studies found that \u003cem\u003egreater levels\u003c/em\u003e of baseline risk, especially mental health problems, predicted larger intervention gains (Gardner et al., 2009; Rojas et al., 2023; Theise et al., 2014). However, other studies have shown that families with \u003cem\u003eless\u003c/em\u003e baseline risk benefited more from intervention, presumably, because they faced fewer barriers to engagement (Lundahl et al., 2006; Shelleby \u0026amp; Shaw, 2014). Still other studies report that families with moderate levels of risk benefit most\u0026nbsp;(Cooper et al., 2024; Lee et al., 2024; Weber et al., 2024). Furthermore, evidence suggests that certain types of risk factors may be more predictive of intervention response than others\u0026nbsp;(Leijten et al., 2018). For example, mothers’ depression seems to be among the most consistent moderators of intervention effects for family-based prevention programs, such that families that have mothers with higher baseline depressive symptoms tend to benefit more from intervention (Gardner et al., 2010; Leijten et al., 2020). Other types of risk factors, such as sociodemographic (e.g., household income, parent education, race/ethnicity, child age), appear not as consistently related to behavioral intervention response when assessed using traditional variable-centered methods\u0026nbsp;(Cho et al., 2025; Gardner, Leijten, Harris, et al., 2019; Gardner, Leijten, Melendez‐Torres, et al., 2019; Leijten et al., 2018; Shelleby \u0026amp; Shaw, 2014).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eUsing a person-centered approach (that identifies patterns of risk exposure) to test differential intervention effects could help to resolve these discrepancies in the past literature and advance our understanding of intervention moderators (Lanza \u0026amp; Rhoades, 2013). Due to the large number of risk factors experienced simultaneously by economically disadvantaged families (Cleland et al., 2017), it is difficult to disentangle the overlapping effects of different moderators using traditional variable-centered approaches. Assessing moderation using person-centered methods, such as latent class analysis (LCA), provides a more nuanced approach that is better suited for unpacking the effects of multiple co-occurring moderators. Despite the advantages of person-centered methods, most studies still rely on variable-centered methods, and there is a lack of understanding of how pre-intervention exposure to unique clusters of poverty-related adversity may dictate intervention response.\u003c/p\u003e\n\u003cp\u003eIn addition to understanding who benefits most from preventive interventions, it is also important to understand whether families are able to meaningfully engage with these programs. Engagement, particularly session attendance, is a critical driver of intervention effects and is likely as important as the intervention content itself (Dishion et al., 2014). Even well-designed, theoretically grounded programs cannot exert their intended effects if families do not attend enough sessions to receive the core components. This issue is particularly salient for families experiencing economic hardship, who face substantial structural and psychological barriers to participation, including inconsistent work schedules, limited transportation, caregiving demands, and higher levels of stress and mental health symptoms (Hackworth et al., 2018). As a result, patterns of engagement frequently differ across subgroups of families (Dumas et al., 2007; LoBraico et al., 2021), and these differences can obscure or magnify true intervention effects. Despite the central role of engagement in determining program success, relatively few studies examine how pre-intervention risk profiles predict intervention attendance. Understanding whether certain constellations of adversity are associated with greater or reduced engagement is essential for interpreting heterogeneity in intervention effects and for designing strategies to support families at risk of low engagement (Lanza \u0026amp; Rhoades, 2013). Identifying latent risk classes that forecast attendance may help clarify inconsistencies in the intervention moderation literature (i.e., differentiating between families who do not benefit because the program content is mismatched versus those who do not benefit because they cannot engage sufficiently) and ultimately strengthen the precision of preventive interventions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Present Study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe purpose of this study was to examine whether families had differential responses to and engagement with the FRAME intervention based on their unique patterns of pre-intervention risk exposure. Building on prior research with this sample, which identified four distinct classes of poverty-related adversity using latent class analysis (Cooper et al., 2025), we examined these risk classes as potential moderators of intervention effects. Consistent with the Family Stress Model that guided FRAME, our outcomes focused on various indicators of family functioning, including parental coping skills, couple relationship quality, parenting practices, and child behavior, each assessed using a combination of mother and father reports. We hypothesized that participant engagement, indexed by session attendance, would vary by risk class, with families in the lowest adversity class demonstrating higher attendance than families in the higher risk classes. Given the substantial heterogeneity in prior differential response findings, we did not make a priori predictions about which risk classes would benefit most or least from the intervention. Instead, we treated these analyses as exploratory tests of whether FRAME effects varied across risk classes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eThe sample included 602 adults and 301 children (0\u0026ndash;17 years old), all of whom were part of 301 couples from low-income, two-parent households participating in the FRAME project (Wadsworth et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The adults were evenly divided by gender and had a mean age of 32.55 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.78; range\u0026thinsp;=\u0026thinsp;18\u0026ndash;74). Participants self-identified as Caucasian/White (34.8%), Black/African American (27.8%), Hispanic/Latin\u0026eacute; (22.8%), Native American (5.3%), or Biracial/Multiracial/Other (11%). They reported an average annual income of \u003cspan\u003e$\u003c/span\u003e22,745 (\u003cem\u003eSD\u003c/em\u003e = \u003cspan\u003e$\u003c/span\u003e15,815; range = \u003cspan\u003e$\u003c/span\u003e0\u0026ndash;72,000). Slightly more than half of the adults (52.6%) were employed, and participants had, on average, completed high school (\u003cem\u003eM\u003c/em\u003e years of schooling\u0026thinsp;=\u0026thinsp;12.67, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.37). Most were married (63.3%), with an average relationship length of 6.7 years (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.5), and mostly lived in blended families (64.9%).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eProcedure\u003c/h3\u003e\n\u003cp\u003eCouples were recruited from the Denver metropolitan area using several methodologies, including community organizations, direct contact, flyers, media interviews, and newspaper advertisements. Couples interested were screened for: (a) household income at or below 200% federal poverty, (b) being in a committed relationship and cohabiting for six or more months, and (c) coparenting at least one child under age 18. Exclusion criteria included prior experiences with the intervention content, could not fluently read or write in English, or denoted they were uninterested in participating in one of the intervention conditions. Eligible participants were block-randomized into one of four groups: a control group that did not participate in workshops (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;72), a couple group with couples attending together (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;77), a father-only group (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;72), and a mother-only group (\u003cem\u003en\u0026thinsp;=\u003c/em\u003e\u0026thinsp;80). Those selected for interventions began attending sessions within two weeks of completing the preassessment. Postintervention assessments were administered two weeks after completion of the intervention and mirrored the preintervention. Finally, follow-up assessments were completed six months after the postintervention assessment. Couples received escalating compensation (i.e., \u003cspan\u003e$\u003c/span\u003e80, \u003cspan\u003e$\u003c/span\u003e120, and \u003cspan\u003e$\u003c/span\u003e140; see Wadsworth et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, for further details of study procedures). The present study draws on data collection at the preintervention time point (T1) and six-month follow-up (T3). All study procedures were approved by the Institutional Review Board (IRB Protocol 471720-4; Fatherhood, Relationship, and Marriage Education project). Data can be accessed from the last author upon request.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eFRAME Workshops\u003c/h2\u003e \u003cp\u003eThe FRAME intervention is a 14-hour father-inclusive family strengthening workshop adapted from the Prevention and Relationship Enhancement Program (PREP; Markman et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). The FRAME intervention was designed specifically for lower socioeconomic status couples and those at risk of relationship strain. The curriculum includes three main sections: relationship education, stress and coping skills training, and child-centered parent training. First, in the relationship education component, couples learn about negative communication styles (e.g., withdrawal), positive communication skills, conflict resolution, and expectation evaluation. Second, the stress and coping skill training component details how to recognize stressors, especially financial stressors, and how to differentiate them from other solvable events. This includes practicing relaxation techniques, exploring the role of social support in buffering stress, identifying problem solving techniques, and focusing on manageable solutions. Then, they learn coping strategies for stressors that lack an immediate solution through acceptance and cognitive reframing (Wadsworth et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Finally, the child-centered parenting component helps caregivers identify and enforce developmentally appropriate behavior expectations through positive reinforcement and alternatives to physical corrective measures (e.g., spanking).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003ePoverty-Related Adversity\u003c/h2\u003e \u003cp\u003ePoverty-related adversity, including economic distress and family adversities, was assessed using mothers\u0026rsquo; and fathers\u0026rsquo; reports at T1. These reports were used to create binary indicators. Reliability estimates are presented in Supplemental File 1 for all multi-item scales.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEconomic Distress\u003c/b\u003e. Two indicators of economic distress were collected: economic hardship and job instability. Economic hardship was assessed using the Economic Hardship Questionnaire (Lempers et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1989\u003c/span\u003e), which asks parents to report changes to their living style. The 11-item scale is rated on a 4-point Likert scale (1 = \u0026ldquo;never\u0026rdquo; to 4 = \u0026ldquo;very often\u0026rdquo;). Mother and father reports were averaged and dichotomized (0\u0026thinsp;=\u0026thinsp;below the sample mean; 1\u0026thinsp;=\u0026thinsp;above the sample mean). Job instability was assessed with a single item from the Major Events Inventory (Conger et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1993\u003c/span\u003e), based on combined parent reports, where 0\u0026thinsp;=\u0026thinsp;neither parent experienced event and 1\u0026thinsp;=\u0026thinsp;at least one parent experienced event.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFamily Adversities\u003c/b\u003e. Eleven indicators of family adversities (e.g., domestic violence and family mental and physical health problems) were included (Adjei et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The Conflict Tactics Scale (Straus et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e1996\u003c/span\u003e), a 6-point Likert scale which includes reports from mothers and fathers assessing their exposure to four items measuring psychological aggression (e.g., \u0026ldquo;my partner insulted or swore at me\u0026rdquo;), five items measuring physical assault (e.g., \u0026ldquo;my partner threw something at me that could hurt\u0026rdquo;), two items measuring injury (e.g., \u0026ldquo;I had a sprain, bruise, or small cut from my partner\u0026rdquo;). Responses to each type of domestic violence were dichotomized, where 0\u0026thinsp;=\u0026thinsp;below the mean and 1\u0026thinsp;=\u0026thinsp;above the mean. Mother and father reports were not averaged into a combined score as above to differentiate between violence exposure by each partner. Martial strain, family legal problems, and family health problems were measured using items from the Major Events Inventory. Each parent reported major life events over the past 3 months. Each single event item was dichotomized, where 0\u0026thinsp;=\u0026thinsp;neither parent experienced event and 1\u0026thinsp;=\u0026thinsp;at least one parent experienced event. For the Center for Epidemiological Studies Depression Scale-20 item (Radloff, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e1977\u003c/span\u003e), parents reported their depressive symptoms (e.g., \u0026ldquo;I felt lonely\u0026rdquo;) in the past week on a 4-point Likert scale (1 = \u0026ldquo;rarely or none of the time\u0026rdquo; to 4 = \u0026ldquo;most or all of the time\u0026rdquo;). For each parent, dichotomized indicators were generated, where 0\u0026thinsp;=\u0026thinsp;below the clinical cutoff for depression (i.e., score\u0026thinsp;\u0026lt;\u0026thinsp;15) and 1\u0026thinsp;=\u0026thinsp;above the clinical cutoff (i.e., \u0026gt; 15).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFamily Clinical Outcomes\u003c/h2\u003e \u003cp\u003eAll family clinical outcomes reflect the averaged T3 scores of mothers and fathers. Scale scores were calculated by averaging their respective items, permitting inclusion of cases with missing item-level data. When applicable (i.e., scales consisting of more than two items), reliability indicators are presented in Supplemental File 1. Correlations between mothers\u0026rsquo; and fathers\u0026rsquo; ratings ranged from weak, such as \u003cem\u003er\u003c/em\u003e = .14 for parental inconsistent discipline, to moderate, such \u003cem\u003er\u003c/em\u003e = .45 for child behavior problems.\u003c/p\u003e \u003cp\u003e \u003cb\u003eParent Engagement Coping\u003c/b\u003e. The Response to Stress Questionnaire (Connor-Smith et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e) was used to assess engagement coping. Participants reported how often they engaged in various coping thoughts and behaviors for eighteen items drawn from the full 57-item measure, using a 4-point scale ranging from 1, \u0026ldquo;not at all,\u0026rdquo; to 4, \u0026ldquo;a lot.\u0026rdquo; The engagement coping measure was constructed by combining items examining primary control coping (e.g., emotional regulation) and secondary control coping (e.g., active acceptance), which are associated with positive outcomes for those experiencing economic stress (Wadsworth et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). For each domain, proportional scores were calculated by dividing an individual\u0026rsquo;s score on their primary or secondary dimension respectively by their total measure score. Higher scores indicate higher levels of engagement coping (Connor-Smith et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Wadsworth et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eCouple Relationship Quality\u003c/b\u003e. The Dyadic Adjustment Scale\u0026ndash;Short Form (Hunsley et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2001\u003c/span\u003e) is a seven-item measure designed to assess the overall quality of participants\u0026rsquo; relationships. Items 1\u0026ndash;3 are rated on a 6-point scale ranging from 1 = \u0026ldquo;always agree\u0026rdquo; to 6 = \u0026ldquo;always disagree\u0026rdquo; and are reverse scored. Items 4\u0026ndash;6 are rated on a 6-point scale ranging from 1 = \u0026ldquo;never\u0026rdquo; to 6 = \u0026ldquo;more often than once a day.\u0026rdquo; Item 7 is rated on a 7-point scale ranging from 1 = \u0026ldquo;extremely unhappy\u0026rdquo; to 7 = \u0026ldquo;perfect.\u0026rdquo; All items are averaged for a total score, with higher values reflecting more positive relationship quality.\u003c/p\u003e \u003cp\u003e\u003cb\u003eParental Warmth\u003c/b\u003e. The Children\u0026rsquo;s Report of Parent Behavior Inventory (Schludermann \u0026amp; Schludermann, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1970\u003c/span\u003e) is a 30-item measure designed to assess parenting behaviors. Parents rated how characteristic each behavior was of their interactions with their child, such as talking about their children\u0026rsquo;s worries or ability to make their child feel better, on a 3-point Likert scale ranging from 1 = \u0026ldquo;not like you\u0026rdquo; to 3 = \u0026ldquo;a lot like you.\u0026rdquo; Parental warmth was assessed using the 8-item acceptance subscale, where higher scores reflect greater warmth.\u003c/p\u003e \u003cp\u003e \u003cb\u003eParental Inconsistent Discipline\u003c/b\u003e. Parental inconsistent discipline was also measured with five items from the Children\u0026rsquo;s Report of Parent Behavior Inventory (e.g., \u0026ldquo;I only keep a rule when it suits me\u0026rdquo;). A mean score was computed, where higher scores reflect higher discipline inconsistency.\u003c/p\u003e \u003cp\u003e \u003cb\u003eChild Behavior Problems\u003c/b\u003e. Children\u0026rsquo;s behavioral and emotional difficulties were assessed using the 113-item Child Behavior Checklist (Achenbach, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Parents indicated the extent to which each behavior was applicable to their child on a 3-point Likert scale, where 0 = \u0026ldquo;absent\u0026rdquo; and 2 = \u0026ldquo;occurs often.\u0026rdquo; Raw scores were transformed into norm-referenced \u003cem\u003eT\u003c/em\u003e-scores, with higher scores reflecting higher child behavior problems.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSession Attendance\u003c/b\u003e. Session attendance was assessed as the percentage of workshops the family attended.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis Plan\u003c/h2\u003e \u003cp\u003eOur analytic plan followed a series of steps carried out in R for preliminary data processing and in Mplus 8 for mixture modeling (Muth\u0026eacute;n \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). First, we examined distributions, correlations, and model assumptions to ensure that variables met criteria for inclusion in subsequent analyses. Second, we estimated latent class models to determine the optimal number of classes by comparing one through seven class solutions and reviewing fit indices, including the Bayesian information criterion and the bootstrapped likelihood ratio test (Nylund et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). Detailed results of the model selection process are provided in Additional File 1. Third, we evaluated differences in demographic characteristics across classes using the modified three-step procedure available through the R3STEP option in Mplus (Asparouhov and Muth\u0026eacute;n, 2014). Fourth, we applied the BCH three-step method (Asparouhov \u0026amp; Muth\u0026eacute;n, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bolck et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) to incorporate distal outcomes while adjusting for classification uncertainty. In contrast to our earlier paper (Cooper et al., 2025), the current study extends this framework by examining whether latent class membership moderates intervention effects on the same distal outcomes. Consistent with recommendations for latent class moderation (Bray et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), we used BCH-derived weights to estimate models that included the interaction between latent class membership and intervention condition. After exporting the BCH weights, we fit weighted regression models in which class membership, intervention assignment, and their interaction predicted family outcomes at T3. This approach allowed us to test whether the intervention effect differed across classes by evaluating class-by-condition interaction terms and conducting pairwise comparisons, such as contrasting the intervention effect for families in the highest risk class with the effect for those in the lowest risk class. Missing data conformed to missing at random assumptions (MAR) and were addressed using full information maximum likelihood in latent class estimation and listwise deletion in R3STEP and BCH models. Supplemental File 2 includes sample Mplus syntax illustrating the analytic steps (See Bray et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e for a full explanation of the BCH approach applied to differential intervention effects).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePreliminary Analyses \u0026amp; Identifying Latent Classes\u003c/h2\u003e \u003cp\u003eResults of steps 1\u0026ndash;3 of our analysis (i.e., preliminary analyses, identifying latent classes, evaluating demographic differences) were presented previously, but are briefly summarized below for necessary context. Preliminary analyses are presented in Supplemental File 1. Overall, families reported high levels of poverty-related adversity, such as job instability (75% of the sample), parental depressive symptoms (56% of mothers, 41% of fathers), and physical assault by a partner (52% of sample). Bivariate correlations of poverty-related adversities ranged from .01 to .54, and over half were statistically significant (Supplemental File 1). Using LCA, we identified four unique classes of poverty-related family risk based on model fit indices and interpretability of the classes (see Supplemental File 1). Most indicators (i.e., Akaike information criterion, adjusted Bayesian information criterion, entropy, Lo-Mendell-Rubin adjusted likelihood test, and bootstrapped likelihood ratio test statistics) suggested an improvement in model fit as the number of classes approached five, followed by a decrease in model fit for the six- and seven-class solutions. Although the five-class solution showed some evidence of improved fit (e.g., bootstrapped likelihood ratio test) over the four-class solution, the fifth class was small (5.3% of the sample), which can lead to less reliable parameter estimates. Additionally, the Lo-Mendell-Rubin adjusted likelihood test and Akaike information criterion values suggested it was a worse fit than the four-class solution. We, therefore, selected the more parsimonious four-class solution as the overall best fitting model. We named the classes as follows: \u003cem\u003eLow Adversity\u003c/em\u003e (moderate levels of job instability, lower on most other poverty-related adversities; 15% of the sample), \u003cem\u003eMothers At Risk\u003c/em\u003e (higher than average scores on mother-reported domestic violence, lower than average father-reported domestic violence; 11%), \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e (moderate levels of economic distress and parent depressive symptoms, lower than average levels of domestic violence; 41%), and \u003cem\u003eExtreme Adversity\u003c/em\u003e (higher than average scores on most adversities; 33%; see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We then examined the baseline characteristics of each latent class using the R3STEP approach with the \u003cem\u003eLow Adversity\u003c/em\u003e class set as the reference group to ease interpretation and minimize pairwise comparisons (Supplemental File 1). Overall, we found that classes were similar across the demographic characteristics we examined, including family size, parent and child age, household income, education level, intervention participation, and relationship status.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e\u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eItem Response Probabilities for Family Risk Subgroups\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eWhole Sample\u003c/b\u003e\u003c/p\u003e \u003cp\u003e(\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eRange\u003c/span\u003e: 0\u0026ndash;1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eLow\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eAdversity (15%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eMothers At Risk (11%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eESDP (41%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eExtreme Adversity (33%)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eEconomic Distress\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEconomic Hardship\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.13\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJob Instability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.86\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cspan type=\"BoldUnderline\" class=\"BoldUnderline\" name=\"Emphasis\"\u003eFamily Adversities\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Psychological Aggression (mother)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.17\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.81\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.37\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.75\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Psychological Aggression (father)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.07\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.73\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Physical Assault (mother)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.00\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.10\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.00\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Physical Assault (father)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.19\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.00\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.94\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Injury (mother)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.57\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.00\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.55\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVictim of Injury (father)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.06\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.00\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.15\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.66\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Marital Strain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.18\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.77\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Legal Problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.11\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e.73\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e.68\u0026uarr;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Health Problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMother Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.18\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFather Depression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.08\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.22\u0026darr;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eNote.\u003c/em\u003e Arrows represent significant differences (\u003cem\u003ep\u003c/em\u003e\u0026lt;.05) between the class probabilities and the full sample probabilities. Bold text indicates higher risk than the full sample. ESDP\u0026thinsp;=\u0026thinsp;\u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e. Item response probabilities are the probabilities of reporting a risk factor given latent class. Example interpretation: 75% of mothers in the \u003cem\u003eExtreme Adversity\u003c/em\u003e class experienced above-average levels of psychological aggression from their partners. This proportion was significantly higher than the sample mean.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eComparing Intervention Effects Across Latent Classes\u003c/h2\u003e \u003cp\u003eUsing the BCH approach, we found that risk class moderated intervention effects for only one of the five couple-reported outcomes: couple relationship quality. Families in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class demonstrated less negative effects on couple relationship quality than those in the \u003cem\u003eLow Adversity\u003c/em\u003e class, who showed worse scores in this domain after receiving the intervention. Although other moderation tests were nonsignificant (\u003cem\u003ep\u003c/em\u003e \u0026gt; .05), consistent patterns emerged in the direction of effects. The \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class generally showed the least negative response, and in some cases, trending positive effects, whereas the \u003cem\u003eLow Adversity\u003c/em\u003e class showed the least benefit and demonstrated worse functioning than the control condition across several outcomes. See Table\u0026nbsp;2 for a full report of the class differences in family outcomes.\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e \u003cem\u003eAssociation of Intervention Condition with Family Outcomes at 6-months Moderated by Risk Class (N=301)\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 24px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCouple-report\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMother-report\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 22px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFather-report\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eCI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCouple Relationship Quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e3.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[3.43, 4.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e3.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[3.35, 4.58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e3.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[3.42, 4.37]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntervention Condition (FRAME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.26, .80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.37, .94]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.26, .77]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eLatent Risk Classes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.78, 1.98]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.81\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.08, 1.71]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[1.37, 2.53]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;ESPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.87, 1.14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-2.47, 1.05]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.72, 1.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.60, .58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.88, .58]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.49, .75]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eModeration\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.64, -.27]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.41, .59]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-1.50\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-2.18, -.81]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.02, 2.09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.28, 2.39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.22, 2.25]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.89, .42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-1.04, .62]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.96, .44]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParental Warmth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[2.52, 2.74]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[2.61, 2.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[2.35, 2.67]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntervention Condition (FRAME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.02, .24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.12, .20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.17\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.01, .35]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eLatent Risk Classes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.23\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.03, .44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.20, .31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.18, .64]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;ESPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.05, .41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.49, .28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.46\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.27, .66]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.11, .18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.24, .13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.09, .32]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eModeration\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.43, .06]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.36, .24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-.31\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.58, -.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.43, .09]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.35, .50]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-.41\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-67, -.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.26, .10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.24, .22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.38, .11]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParental Inconsistent Discipline\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[1.30, 1.56]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[1.34, 1.83]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[1.10, 1.43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003eIntervention Condition (FRAME)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.17, .14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.48, .07]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.19\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.01, .39]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eLatent Risk Classes\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.41, .15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.75, .19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.29, .53]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;ESPD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cem\u003eref\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.34, .11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.76, .25]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.27, .32]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.13, .29]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.41, .23]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.00, .55]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cem\u003eModeration\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Low Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.32, .35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.29, .76]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.77, .17]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Mothers At Risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.06, .61]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e.78\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[.14, 1.41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.62, .13]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Extreme Adversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e-.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.35, .15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.30, .42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e-.30\u0026dagger;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13px;\"\u003e\n \u003cp\u003e[-.63, .02]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Bold font represents a significant effect at \u003cem\u003ep\u003c/em\u003e \u0026lt; .05. Due to limited power for certain moderation effects, \u0026dagger; indicates marginal significance at \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .10. Only outcomes with significant findings are presented here. See Supplemental File 1 for results for other family outcomes.\u003c/p\u003e \u003cp\u003eSensitivity analyses, separating out effects using mother- and father-reported outcomes, revealed both convergence and divergence with the couple-level results. For mothers\u0026rsquo; reported outcomes, several moderation findings were consistent (i.e., coping skills and parental warmth), however, new class-specific intervention response differences emerged for inconsistent discipline. Specifically, mothers in the \u003cem\u003eMothers At Risk\u003c/em\u003e class reported significantly worse inconsistent discipline after receiving the intervention compared to the control group, and the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class reported more favorable effects (i.e., less negative) than the \u003cem\u003eMothers At Risk\u003c/em\u003e class. Mothers in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class also showed trending positive effects (\u003cem\u003ep\u003c/em\u003e \u0026lt; .10) in child behavior problems relative to the \u003cem\u003eExtreme Adversity\u003c/em\u003e class. For fathers, moderation findings paralleled the couple-level analyses for coping skills, relationship quality, and child behavior problems. However, fathers in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class reported uniquely stronger positive effects in parental warmth relative to both the \u003cem\u003eLow Adversity\u003c/em\u003e and \u003cem\u003eMothers At Risk\u003c/em\u003e classes. In contrast, fathers in the \u003cem\u003eExtreme Adversity\u003c/em\u003e class showed marginally greater positive effects in inconsistent discipline than the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class. When considered together, these analyses suggest that three of the five outcomes demonstrated some form of differential intervention response across classes, with trending differences for one additional outcome. See Table\u0026nbsp;2 for specific parameter estimates for the class comparisons separated by mothers\u0026rsquo; and fathers\u0026rsquo; reports.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eComparing Attendance Rates Across Latent Classes\u003c/h2\u003e \u003cp\u003eWe examined whether latent class membership was associated with workshop attendance among families assigned to the intervention condition (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;226). The latent class structure replicated within this subsample, with class prevalences and item-response probabilities closely matching those in the full sample. Attendance rates varied across classes. Families in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class attended the highest proportion of sessions (74.0%), followed by the \u003cem\u003eExtreme Adversity\u003c/em\u003e (58.5%) and \u003cem\u003eLow Adversity\u003c/em\u003e (55.5%) classes. The \u003cem\u003eMothers At Risk\u003c/em\u003e class had the lowest attendance (42.9%). Pairwise comparisons indicated that the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class attended significantly more sessions than the \u003cem\u003eExtreme Adversity\u003c/em\u003e (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.16, 95% \u003cem\u003eCI\u003c/em\u003e [\u0026minus;\u0026thinsp;.29, \u0026minus;\u0026thinsp;.02]) and \u003cem\u003eMothers At Risk\u003c/em\u003e (\u003cem\u003eB\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.31, 95% \u003cem\u003eCI\u003c/em\u003e [-.53, \u0026minus;\u0026thinsp;.09]) classes. No other class differences in attendance were statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study used a person-centered approach to examine whether certain risk classes uniquely benefited from a family-based prevention program for economically disadvantaged families. Using multiple indicators of poverty-related adversities, including economic hardship and family adversities, such as parental mental and physical health problems and domestic violence, we identified four distinct family risk classes, driven mostly by differences in exposure to domestic violence and parental depressive symptoms. Families in the \u003cem\u003eLow Adversity\u003c/em\u003e class (15%) showed moderate levels of job instability but reported relatively few challenges in other areas of economic or psychosocial risk. The \u003cem\u003eMothers At Risk\u003c/em\u003e class (11%) was characterized by elevated mother-reported domestic violence exposure and depressive symptoms paired with comparatively low father-reported domestic violence and depressive symptoms. The largest class, \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e (41%), reflected families experiencing moderate economic hardship and higher parental depressive symptoms, with limited exposure to domestic violence. The \u003cem\u003eExtreme Adversity\u003c/em\u003e class (33%) included families reporting elevated difficulties across nearly all assessed domains of risk. These risk classes were similar demographically (e.g., household income, education, family size, parent and child age, relationship status), which reduces the likelihood that demographic differences contributed to class variability and strengthens our ability to attribute observed differences to adversity profiles. Findings from distal outcome and moderation analyses revealed important differences in how family risk classes benefited from and engaged with the intervention across five outcomes, based on combined mother and father reports.\u003c/p\u003e \u003cp\u003eAt the couple level, risk class moderated intervention effects for only one of the five outcomes. Specifically, families in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class demonstrated more favorable (i.e., less negative) intervention effects on relationship quality relative to the \u003cem\u003eLow Adversity\u003c/em\u003e class. In fact, the \u003cem\u003eLow Adversity\u003c/em\u003e class experienced worse couple relationship quality than those randomized into the control condition. For the remaining outcomes, the direction of effects generally followed a similar pattern, with the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e group showing modest advantages (though not reaching significance) relative to the other classes. It is important to note that across all four classes, families randomized into the intervention condition did not have significantly better outcomes than the control group, potentially due to limited power or unmodeled heterogeneity across intervention formats (Wadsworth et al., \u003cspan class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo better understand the stability of these findings, we conducted sensitivity analyses to determine whether there were additional class differences in intervention effects based on whether the outcomes were reported by mothers or fathers. Although many patterns were consistent with the combined couple-level reports, additional class-specific differences in intervention effects emerged. For example, mothers in the \u003cem\u003eMothers At Risk\u003c/em\u003e class reported significantly greater rates of inconsistent discipline than those in the control group, and showed worse intervention response than the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class. When examining fathers’ individually reported outcomes, we found similar results to most couple-level reports, with one major exception. Fathers in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class reported better intervention-related effects on parental warmth than both the \u003cem\u003eLow Adversity\u003c/em\u003e and \u003cem\u003eMothers At Risk\u003c/em\u003e classes. Taken in concert, these patterns indicate that mothers and fathers may experience distinct effects within certain risk classes, underscoring the value of examining individual-level reports in addition to couple-level composites.\u003c/p\u003e \u003cp\u003eThe overall pattern of results aligns with the growing literature suggesting that family-based interventions may be most beneficial for families experiencing moderate levels of adversity (Cooper et al., 2024; Lee et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Weber et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), a phenomenon characterized as the \u003cem\u003egoldilocks effect\u003c/em\u003e (Miller et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). Families in the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class, who faced substantial but not extreme hardship, often experienced better intervention responses than families in either the lowest or highest risk groups. It is worth noting that prior research with this sample found that the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class exhibited some of the least favorable longitudinal family outcomes when examined independent of intervention participation (Cooper et al., 2025). The superior intervention response among the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class in the current study is, therefore, especially notable, as it suggests that program participation may help interrupt negative developmental trajectories. This pattern is consistent with several recent studies using cluster-based approaches, which find that families with moderate risk often show the greatest capacity to engage with and apply intervention content, whereas families with very low risk may have limited room to improve and families with very high risk may encounter barriers to engagement Cooper et al., 2024; Lee et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Weber et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). For example, subgroup analysis of a parenting intervention found that parents with moderate initial levels of positive parenting practices showed the greatest improvement relative to those in the highest or lowest functioning classes (Lee et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). Similarly, a study evaluating a relationship education program found that couples with moderate baseline risk (i.e., moderate relationship satisfaction) experienced the largest gains after receiving the intervention (Weber et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDifferences in session attendance offer an additional explanation for the differential intervention effects observed across classes. Attendance rates varied considerably, with the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e class attending nearly three-quarters of sessions, which was substantially higher than the two highest risk classes and almost twice the rate of the \u003cem\u003eMothers At Risk\u003c/em\u003e class. Surprisingly, the lowest and highest risk classes did not differ from one another in attendance, contrary to expectations and past literature suggesting that the lowest risk families may have fewer barriers to participation and thus higher attendance (LoBraico et al., \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, several studies have indicated that attendance may be based on factors beyond risk level, such as motivation and perceived time constraints (Dumas et al., \u003cspan class=\"CitationRef\"\u003e2007\u003c/span\u003e). The attendance patterns found in our study provide a plausible mechanism for the intervention’s stronger impact among the \u003cem\u003eEconomic Stress, Depressive Parents\u003c/em\u003e group, who were highly engaged and positioned to benefit from program content. Conversely, lower attendance among the \u003cem\u003eMothers At Risk\u003c/em\u003e and \u003cem\u003eExtreme Adversity\u003c/em\u003e classes may help to explain their comparatively limited improvement across outcomes. This intersection of risk profiles and engagement adds an important contribution to the literature by providing insight into how attendance may amplify or constrain intervention effects across differing levels of family adversity.\u003c/p\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study had numerous strengths, including multi-informant measures to assess family-level constructs, a comprehensive, person-centered approach to assessing poverty-related adversity, a longitudinal randomized design, and a dual focus on understanding differential responses and engagement with family-based prevention. Several limitations should also be noted. First, the sample does not reflect the full diversity of families experiencing economic hardship, particularly those residing in rural communities or those with family structures not represented here (e.g., single parents living apart from partners or same-sex couples). As a result, the extent to which these findings extend to these groups is uncertain. Second, our measurement of adversity focused on a subset of challenges commonly faced by families with limited financial resources but did not capture other important sources of stress, including experiences of discrimination or structural racism. Incorporating these forms of adversity in future research will be essential, given their well-documented links to parent and child well-being (Cave et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e). Third, certain class sizes were relatively small (e.g., \u003cem\u003eMothers At Risk\u003c/em\u003e), which likely impacted the ability to detect small class differences. Consequently, some null or marginal findings may reflect limited statistical power rather than the true absence of differential effects. Fourth, although the use of mother and father reports is a strength, all family functioning outcomes relied on self-report, which may introduce shared method variance or social desirability bias. Finally, although the intervention was delivered in three formats (mothers-only, fathers-only, and couple dyads), the sample size within each subgroup did not allow for adequately powered tests of differential intervention response across these delivery conditions.\u003c/p\u003e \u003c/div\u003e "},{"header":"Implications and Conclusion","content":"\u003cp\u003eThe pattern of differential intervention effects has implications for how prevention programs are tailored and implemented. The finding that families experiencing moderate levels of adversity showed the most favorable outcomes suggests that interventions such as FRAME may yield the strongest returns when directed toward families who have identifiable needs yet retain sufficient stability to engage fully with program content. This aligns with precision-prevention frameworks that emphasize the match between families’ needs and the content of the intervention (August \u0026amp; Gewirtz, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Notably, the risk class that benefited most from FRAME also demonstrated the highest levels of session attendance, suggesting that differential engagement may play an important role in affecting intervention response. Although the present study was not designed to test attendance as a causal mechanism, this pattern suggests that facilitating consistent participation may be a useful strategy for improving intervention effects for non-responders. Beyond the role of intervention attendance, the limited benefits observed for families at the lowest and highest ends of the risk continuum may suggest that a single intervention approach is not equally well suited for all families. For low-risk families, prevention efforts may require more focused content that is responsive to narrower areas of need rather than broad, multi-component programming. For high-risk families, additional scaffolding may be necessary, such as addressing acute stressors prior to skill-building. Overall, this study demonstrates the value of identifying heterogeneity in how families respond to prevention programs and highlights the utility of latent class methods for uncovering patterns that remain obscured when relying on variable-centered approaches. By demonstrating that families with distinct adversity profiles differ in their engagement with and response to intervention, these findings clarify for whom prevention programs are most (and least) effective. These findings advance the broader goals of prevention science by informing more targeted and efficient approaches to intervention delivery. Continued research in this area will be essential for refining precision prevention strategies and designing programs that better align with families’ needs, thereby promoting more consistent benefits across diverse risk contexts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding and Competing Interests:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThis project was supported by the National Institute of Mental Health (R03 MH127455; Daniel Cooper) and the National Institute of General Medical Sciences (P20 GM130420; Ronald Prinz). The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Approval and Consent to Participate:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eAll procedures were approved by the University of Denver Institutional Review Board (IRB protocol: 471720-4, FRAME project) and were conducted in accordance with the Declaration of Helsinki.\u0026nbsp;Informed consent was obtained from all individual participants included in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eClinical Trial Registration\u003c/em\u003e\u003c/strong\u003e: Not applicable for this secondary analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of Data and Materials:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eData are available upon reasonable request from the last author. Mplus code used to conduct analyses is available in Supplemental File 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributions:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eDKC: Conceptualization, Methodology, Formal analysis, Writing – original draft, Supervision. BLB \u0026amp; EKL: Methodology, Formal analysis, Writing – review \u0026amp; editing. FL \u0026amp; DP: Writing – review \u0026amp; editing. MEW: Conceptualization, Funding acquisition, Writing – review \u0026amp; editing.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAchenbach, T. M. (with Internet Archive). (1991). \u003cem\u003eManual for the child behavior checklist/4-18 and 1991 profile\u003c/em\u003e. Burlington, VT : Dept. of Psychiatry, University of Vermont. http://archive.org/details/manualforchildbe0000ache_g2r5\u003c/li\u003e\n\u003cli\u003eAdjei, N. K., Jonsson, K. R., Straatmann, V. S., Melis, G., McGovern, R., Kaner, E., Wolfe, I., Taylor-Robinson, D. C., the ORACLE consortium, Barrett, S., Tubah, S., Forman, J., Hirve, R., Bangisky, M., Boulding, H., Hackett, S., Fox-Rushby, J., Muir, C., Sophie, K., \u0026amp; Salmon, A. (2024). Impact of poverty and adversity on perceived family support in adolescence: Findings from the UK Millennium Cohort Study. \u003cem\u003eEuropean Child \u0026amp; Adolescent Psychiatry\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(9), 3123\u0026ndash;3132. https://doi.org/10.1007/s00787-024-02389-8\u003c/li\u003e\n\u003cli\u003eAsparouhov, T., \u0026amp; Muth\u0026eacute;n, B. (2019). \u003cem\u003eAuxiliary Variables in Mixture Modeling: Using the BCH Method in Mplus to Estimate a Distal Outcome Model and an Arbitrary Secondary Model\u003c/em\u003e. https://www.statmodel.com/examples/webnotes/webnote21.pdf\u003c/li\u003e\n\u003cli\u003eAugust, G. J., \u0026amp; Gewirtz, A. (2019). Moving Toward a Precision-Based, Personalized Framework for Prevention Science: Introduction to the Special Issue. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(1), 1\u0026ndash;9. https://doi.org/10.1007/s11121-018-0955-9\u003c/li\u003e\n\u003cli\u003eBolck, A., Croon, M., \u0026amp; Hagenaars, J. (2004). Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators. \u003cem\u003ePolitical Analysis\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 3\u0026ndash;27. https://doi.org/10.1093/pan/mph001\u003c/li\u003e\n\u003cli\u003eBray, B. C., Layland, E. K., Stull, S. W., Vasilenko, S. A., \u0026amp; Lanza, S. T. (2023). Estimating the Effects of a Complex, Multidimensional Moderator: An Example of Latent Class Moderation to Examine Differential Intervention Effects of Substance Use Services. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(3), 493\u0026ndash;504. https://doi.org/10.1007/s11121-022-01448-3\u003c/li\u003e\n\u003cli\u003eCai, Q., Chan, A. C. Y., Lee, S.-K., Marsalis, S., \u0026amp; Gewirtz, A. H. (2022). Effectiveness of GenerationPMTO to Promote Parenting and Child Adjustment: A Meta-Analytic Review. \u003cem\u003eClinical Child and Family Psychology Review\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(4), 702\u0026ndash;719. https://doi.org/10.1007/s10567-022-00400-9\u003c/li\u003e\n\u003cli\u003eCave, L., Cooper, M. N., Zubrick, S. R., \u0026amp; Shepherd, C. C. J. (2020). Racial discrimination and child and adolescent health in longitudinal studies: A systematic review. \u003cem\u003eSocial Science \u0026amp; Medicine\u003c/em\u003e, \u003cem\u003e250\u003c/em\u003e, 112864. https://doi.org/10.1016/j.socscimed.2020.112864\u003c/li\u003e\n\u003cli\u003eCho, E., Chorpita, B. F., Reeder, K., Alegr\u0026iacute;a, M., Price, M. A., Weisz, J. R., \u0026amp; The Research Network on Youth Mental Health. (2025). Ethnicity and income as predictors of clinical outcomes of a youth-focused personalizable modular treatment. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e93\u003c/em\u003e(10), 677\u0026ndash;689. https://doi.org/10.1037/ccp0000979\u003c/li\u003e\n\u003cli\u003eCleland, C. M., Lanza, S. T., Vasilenko, S. A., \u0026amp; Gwadz, M. (2017). Syndemic Risk Classes and Substance Use Problems among Adults in High-Risk Urban Areas: A Latent Class Analysis. \u003cem\u003eFrontiers in Public Health\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 237. https://doi.org/10.3389/fpubh.2017.00237\u003c/li\u003e\n\u003cli\u003eCompas, B. E., Champion, J. E., Forehand, R., Cole, D. A., Reeslund, K. L., Fear, J., Hardcastle, E. J., Keller, G., Rakow, A., Garai, E., Merchant, M. J., \u0026amp; Roberts, L. (2010). Coping and parenting: Mediators of 12-month outcomes of a family group cognitive\u0026ndash;behavioral preventive intervention with families of depressed parents. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e78\u003c/em\u003e(5), 623\u0026ndash;634. https://doi.org/10.1037/a0020459\u003c/li\u003e\n\u003cli\u003eConger, R. D., \u0026amp; Conger, K. J. (2002). Resilience in Midwestern Families: Selected Findings from the First Decade of a Prospective, Longitudinal Study. \u003cem\u003eJournal of Marriage and Family\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(2), 361\u0026ndash;373. https://doi.org/10.1111/j.1741-3737.2002.00361.x\u003c/li\u003e\n\u003cli\u003eConger, R. D., Lorenz, F. O., Elder, G. H., Simons, R. L., \u0026amp; Ge, X. (1993). Husband and Wife Differences in Response to Undesirable Life Events. \u003cem\u003eJournal of Health and Social Behavior\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(1), 71. https://doi.org/10.2307/2137305\u003c/li\u003e\n\u003cli\u003eConnor-Smith, J. K., Compas, B. E., Wadsworth, M. E., Thomsen, A. H., \u0026amp; Saltzman, H. (2000). Responses to stress in adolescence: Measurement of coping and involuntary stress responses. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e68\u003c/em\u003e(6), 976\u0026ndash;992. https://doi.org/10.1037/0022-006X.68.6.976\u003c/li\u003e\n\u003cli\u003eDishion, T. J., Brennan, L. M., Shaw, D. S., McEachern, A. D., Wilson, M. N., \u0026amp; Jo, B. (2014). Prevention of Problem Behavior Through Annual Family Check-Ups in Early Childhood: Intervention Effects From Home to Early Elementary School. \u003cem\u003eJournal of Abnormal Child Psychology\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(3), 343\u0026ndash;354. https://doi.org/10.1007/s10802-013-9768-2\u003c/li\u003e\n\u003cli\u003eDumas, J. E., Nissley-Tsiopinis, J., \u0026amp; Moreland, A. D. (2007). From Intent to Enrollment, Attendance, and Participation in Preventive Parenting Groups. \u003cem\u003eJournal of Child and Family Studies\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(1), 1\u0026ndash;26. https://doi.org/10.1007/s10826-006-9042-0\u003c/li\u003e\n\u003cli\u003eFawcett, E. B., Hawkins, A. J., Blanchard, V. L., \u0026amp; Carroll, J. S. (2010). Do Premarital Education Programs Really Work? A Meta‐analytic Study. \u003cem\u003eFamily Relations\u003c/em\u003e, \u003cem\u003e59\u003c/em\u003e(3), 232\u0026ndash;239. https://doi.org/10.1111/j.1741-3729.2010.00598.x\u003c/li\u003e\n\u003cli\u003eGardner, F., Connell, A., Trentacosta, C. J., Shaw, D. S., Dishion, T. J., \u0026amp; Wilson, M. N. (2009). Moderators of outcome in a brief family-centered intervention for preventing early problem behavior. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e77\u003c/em\u003e(3), 543\u0026ndash;553. https://doi.org/10.1037/a0015622\u003c/li\u003e\n\u003cli\u003eGardner, F., Hutchings, J., Bywater, T., \u0026amp; Whitaker, C. (2010). Who Benefits and How Does It Work? Moderators and Mediators of Outcome in an Effectiveness Trial of a Parenting Intervention. \u003cem\u003eJournal of Clinical Child \u0026amp; Adolescent Psychology\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(4), 568\u0026ndash;580. https://doi.org/10.1080/15374416.2010.486315\u003c/li\u003e\n\u003cli\u003eGardner, F., Leijten, P., Harris, V., Mann, J., Hutchings, J., Beecham, J., Bonin, E.-M., Berry, V., McGilloway, S., Gaspar, M., Jo\u0026atilde;o Seabra-Santos, M., Orobio de Castro, B., Menting, A., Williams, M., Axberg, U., Morch, W.-T., Scott, S., \u0026amp; Landau, S. (2019). Equity effects of parenting interventions for child conduct problems: A pan-European individual participant data meta-analysis. \u003cem\u003eThe Lancet. Psychiatry\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(6), 518\u0026ndash;527. https://doi.org/10.1016/S2215-0366(19)30162-2\u003c/li\u003e\n\u003cli\u003eGardner, F., Leijten, P., Melendez‐Torres, G. J., Landau, S., Harris, V., Mann, J., Beecham, J., Hutchings, J., \u0026amp; Scott, S. (2019). The Earlier the Better? Individual Participant Data and Traditional Meta‐analysis of Age Effects of Parenting Interventions. \u003cem\u003eChild Development\u003c/em\u003e, \u003cem\u003e90\u003c/em\u003e(1), 7\u0026ndash;19. https://doi.org/10.1111/cdev.13138\u003c/li\u003e\n\u003cli\u003eHackworth, N. J., Matthews, J., Westrupp, E. M., Nguyen, C., Phan, T., Scicluna, A., Cann, W., Bethelsen, D., Bennetts, S. K., \u0026amp; Nicholson, J. M. (2018). What Influences Parental Engagement in Early Intervention? Parent, Program and Community Predictors of Enrolment, Retention and Involvement. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(7), 880\u0026ndash;893. https://doi.org/10.1007/s11121-018-0897-2\u003c/li\u003e\n\u003cli\u003eHunsley, J., Best, M., Lefebvre, M., \u0026amp; Vito, D. (2001). The Seven-Item Short Form of the Dyadic Adjustment Scale: Further Evidence for Construct Validity. \u003cem\u003eAmerican Journal of Family Therapy\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e(4), 325\u0026ndash;335. https://doi.org/10.1080/01926180152588734\u003c/li\u003e\n\u003cli\u003eLanders‐Potts, M. A., Wickrama, K. A. S., Simons, L. G., Cutrona, C., Gibbons, F. X., Simons, R. L., \u0026amp; Conger, R. (2015). An Extension and Moderational Analysis of the Family Stress Model Focusing on African American Adolescents. \u003cem\u003eFamily Relations\u003c/em\u003e, \u003cem\u003e64\u003c/em\u003e(2), 233\u0026ndash;248. https://doi.org/10.1111/fare.12117\u003c/li\u003e\n\u003cli\u003eLanza, S. T., \u0026amp; Rhoades, B. L. (2013). Latent Class Analysis: An Alternative Perspective on Subgroup Analysis in Prevention and Treatment. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(2), 157\u0026ndash;168. https://doi.org/10.1007/s11121-011-0201-1\u003c/li\u003e\n\u003cli\u003eLaurenceau, J.-P., Stanley, S. M., Olmos-Gallo, A., Baucom, B., \u0026amp; Markman, H. J. (2004). Community-Based Prevention of Marital Dysfunction: Multilevel Modeling of a Randomized Effectiveness Study. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(6), 933\u0026ndash;943. https://doi.org/10.1037/0022-006X.72.6.933\u003c/li\u003e\n\u003cli\u003eLee, S.-K., Gewirtz, A. H., \u0026amp; Piehler, T. F. (2024). Parenting Profiles in Military Families: Intervention-Related Transitions and Relationships to Child Adjustment. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(7), 1040\u0026ndash;1052. https://doi.org/10.1007/s11121-024-01721-7\u003c/li\u003e\n\u003cli\u003eLeijten, P., Raaijmakers, M., Wijngaards, L., Matthys, W., Menting, A., Hemink-van Putten, M., \u0026amp; Orobio De Castro, B. (2018). Understanding Who Benefits from Parenting Interventions for Children\u0026rsquo;s Conduct Problems: An Integrative Data Analysis. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e19\u003c/em\u003e(4), 579\u0026ndash;588. https://doi.org/10.1007/s11121-018-0864-y\u003c/li\u003e\n\u003cli\u003eLeijten, P., Scott, S., Landau, S., Harris, V., Mann, J., Hutchings, J., Beecham, J., \u0026amp; Gardner, F. (2020). Individual Participant Data Meta-analysis: Impact of Conduct Problem Severity, Comorbid Attention-Deficit/Hyperactivity Disorder and Emotional Problems, and Maternal Depression on Parenting Program Effects. \u003cem\u003eJournal of the American Academy of Child \u0026amp; Adolescent Psychiatry\u003c/em\u003e, \u003cem\u003e59\u003c/em\u003e(8), 933\u0026ndash;943. https://doi.org/10.1016/j.jaac.2020.01.023\u003c/li\u003e\n\u003cli\u003eLempers, J. D., Clark-Lempers, D., \u0026amp; Simons, R. L. (1989). Economic Hardship, Parenting, and Distress in Adolescence. \u003cem\u003eChild Development\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e(1), 25. https://doi.org/10.2307/1131068\u003c/li\u003e\n\u003cli\u003eLoBraico, E. J., Fosco, G. M., Feinberg, M. E., Spoth, R. L., Redmond, C., \u0026amp; Bray, B. C. (2021). Predictors of Attendance Patterns in a Universal Family-Based Preventive Intervention Program. \u003cem\u003eThe Journal of Primary Prevention\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(5), 409\u0026ndash;424. https://doi.org/10.1007/s10935-021-00636-1\u003c/li\u003e\n\u003cli\u003eLundahl, B., Risser, H. J., \u0026amp; Lovejoy, M. C. (2006). A meta-analysis of parent training: Moderators and follow-up effects. \u003cem\u003eClinical Psychology Review\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(1), 86\u0026ndash;104. https://doi.org/10.1016/j.cpr.2005.07.004\u003c/li\u003e\n\u003cli\u003eMarkman, H. J., Floyd, F. J., Stanley, S. M., \u0026amp; Storaasli, R. D. (1988). Prevention of marital distress: A longitudinal investigation. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(2), 210\u0026ndash;217. https://doi.org/10.1037/0022-006X.56.2.210\u003c/li\u003e\n\u003cli\u003eMarkman, H. J., Hawkins, A. J., Stanley, S. M., Halford, W. K., \u0026amp; Rhoades, G. (2022). Helping couples achieve relationship success: A decade of progress in couple relationship education research and practice, 2010\u0026ndash;2019. \u003cem\u003eJournal of Marital and Family Therapy\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(1), 251\u0026ndash;282. https://doi.org/10.1111/jmft.12565\u003c/li\u003e\n\u003cli\u003eMasarik, A. S., \u0026amp; Conger, R. D. (2017). Stress and child development: A review of the Family Stress Model. \u003cem\u003eCurrent Opinion in Psychology\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e, 85\u0026ndash;90. https://doi.org/10.1016/j.copsyc.2016.05.008\u003c/li\u003e\n\u003cli\u003eMenting, A. T. A., Orobio de Castro, B., \u0026amp; Matthys, W. (2013). Effectiveness of the Incredible Years parent training to modify disruptive and prosocial child behavior: A meta-analytic review. \u003cem\u003eClinical Psychology Review\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(8), 901\u0026ndash;913. https://doi.org/10.1016/j.cpr.2013.07.006\u003c/li\u003e\n\u003cli\u003eMiller, E. B., Farkas, G., Vandell, D. L., \u0026amp; Duncan, G. J. (2014). Do the Effects of Head Start Vary by Parental Preacademic Stimulation? \u003cem\u003eChild Development\u003c/em\u003e, \u003cem\u003e85\u003c/em\u003e(4), 1385\u0026ndash;1400. https://doi.org/10.1111/cdev.12233\u003c/li\u003e\n\u003cli\u003eMuth\u0026eacute;n, L. K., \u0026amp; Muth\u0026eacute;n, B. O. (2012). \u003cem\u003eMplus User\u0026rsquo;s Guide. Seventh Edition.\u003c/em\u003e (Version 8) [Computer software].\u003c/li\u003e\n\u003cli\u003eNylund, K. L., Asparouhov, T., \u0026amp; Muth\u0026eacute;n, B. O. (2007). Deciding on the Number of Classes in Latent Class Analysis and Growth Mixture Modeling: A Monte Carlo Simulation Study. \u003cem\u003eStructural Equation Modeling: A Multidisciplinary Journal\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(4), 535\u0026ndash;569. https://doi.org/10.1080/10705510701575396\u003c/li\u003e\n\u003cli\u003ePrado, G., Huang, S., Cordova, D., Malcolm, S., Estrada, Y., Cano, N., Maldonado-Molina, M., Bacio, G., Rosen, A., Pantin, H., \u0026amp; Brown, C. H. (2013). Ecodevelopmental and Intrapersonal Moderators of a Family Based Preventive Intervention for Hispanic Youth: A Latent Profile Analysis. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(3), 290\u0026ndash;299. https://doi.org/10.1007/s11121-012-0326-x\u003c/li\u003e\n\u003cli\u003ePrinz, R. J. (2012). Effective parenting to prevent adverse outcomes and promote child well-being at a population level. In \u003cem\u003eTransformative consumer research for personal and collective well-being\u003c/em\u003e (pp. 585\u0026ndash;598). Routledge/Taylor \u0026amp; Francis Group. https://doi.org/10.4324/9780203813256\u003c/li\u003e\n\u003cli\u003eRadloff, L. S. (1977). The CES-D Scale: A Self-Report Depression Scale for Research in the General Population. \u003cem\u003eApplied Psychological Measurement\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(3), 385\u0026ndash;401. https://doi.org/10.1177/014662167700100306\u003c/li\u003e\n\u003cli\u003eRaviv, T., \u0026amp; Wadsworth, M. E. (2010). The Efficacy of a Pilot Prevention Program for Children and Caregivers Coping with Economic Strain. \u003cem\u003eCognitive Therapy and Research\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(3), 216\u0026ndash;228. https://doi.org/10.1007/s10608-009-9265-7\u003c/li\u003e\n\u003cli\u003eRienks, S. L., Wadsworth, M. E., Markman, H. J., Einhorn, L., \u0026amp; Moran Etter, E. (2011). Father Involvement in Urban Low-Income Fathers: Baseline Associations and Changes Resulting From Preventive Intervention. \u003cem\u003eFamily Relations\u003c/em\u003e, \u003cem\u003e60\u003c/em\u003e(2), 191\u0026ndash;204. https://doi.org/10.1111/j.1741-3729.2010.00642.x\u003c/li\u003e\n\u003cli\u003eRojas, L. M., Brincks, A., Brown, E. C., Bahamon, M., Estrada, Y., Lee, T. K., Prado, G., \u0026amp; Pantin, H. (2023). Family Functioning in Hispanic Parents of Adolescents: Who Benefits Most from a Family-Based HIV and Substance Use Preventive Intervention? \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e24\u003c/em\u003e(2), 249\u0026ndash;258. https://doi.org/10.1007/s11121-022-01489-8\u003c/li\u003e\n\u003cli\u003eSanders, M. R., \u0026amp; Mazzucchelli, T. G. (2022). Mechanisms of Change in Population-Based Parenting Interventions for Children and Adolescents. \u003cem\u003eJournal of Clinical Child \u0026amp; Adolescent Psychology\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(3), 277\u0026ndash;294. https://doi.org/10.1080/15374416.2022.2025598\u003c/li\u003e\n\u003cli\u003eSchludermann, E., \u0026amp; Schludermann, S. (1970). Replicability of Factors in Children\u0026rsquo;s Report of Parent Behavior (CRPBI). \u003cem\u003eThe Journal of Psychology\u003c/em\u003e, \u003cem\u003e76\u003c/em\u003e(2), 239\u0026ndash;249. https://doi.org/10.1080/00223980.1970.9916845\u003c/li\u003e\n\u003cli\u003eShelleby, E. C., \u0026amp; Shaw, D. S. (2014). Outcomes of Parenting Interventions for Child Conduct Problems: A Review of Differential Effectiveness. \u003cem\u003eChild Psychiatry \u0026amp; Human Development\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e(5), 628\u0026ndash;645. https://doi.org/10.1007/s10578-013-0431-5\u003c/li\u003e\n\u003cli\u003eSmith, J. D., Monta\u0026ntilde;o, Z., Dishion, T. J., Shaw, D. S., \u0026amp; Wilson, M. N. (2015). Preventing Weight Gain and Obesity: Indirect Effects of the Family Check-Up in Early Childhood. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(3), 408\u0026ndash;419. https://doi.org/10.1007/s11121-014-0505-z\u003c/li\u003e\n\u003cli\u003eSolmeyer, A. R., Feinberg, M. E., Coffman, D. L., \u0026amp; Jones, D. E. (2014). The Effects of the Family Foundations Prevention Program on Coparenting and Child Adjustment: A Mediation Analysis. \u003cem\u003ePrevention Science\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(2), 213\u0026ndash;223. https://doi.org/10.1007/s11121-013-0366-x\u003c/li\u003e\n\u003cli\u003eStraus, M. A., Hamby, S. L., BONEY-McCOY, S., \u0026amp; Sugarman, D. B. (1996). The Revised Conflict Tactics Scales (CTS2): Development and Preliminary Psychometric Data. \u003cem\u003eJournal of Family Issues\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(3), 283\u0026ndash;316. https://doi.org/10.1177/019251396017003001\u003c/li\u003e\n\u003cli\u003eTheise, R., Huang, K.-Y., Kamboukos, D., Doctoroff, G. L., Dawson-McClure, S., Palamar, J. J., \u0026amp; Brotman, L. M. (2014). Moderators of Intervention Effects on Parenting Practices in a Randomized Controlled Trial in Early Childhood. \u003cem\u003eJournal of Clinical Child \u0026amp; Adolescent Psychology\u003c/em\u003e, \u003cem\u003e43\u003c/em\u003e(3), 501\u0026ndash;509. https://doi.org/10.1080/15374416.2013.833095\u003c/li\u003e\n\u003cli\u003eVan Ryzin, M. J., Roseth, C. J., Fosco, G. M., Lee, Y., \u0026amp; Chen, I.-C. (2016). A component-centered meta-analysis of family-based prevention programs for adolescent substance use. \u003cem\u003eClinical Psychology Review\u003c/em\u003e, \u003cem\u003e45\u003c/em\u003e, 72\u0026ndash;80. https://doi.org/10.1016/j.cpr.2016.03.007\u003c/li\u003e\n\u003cli\u003eWadsworth, M. E., Santiago, C. D., Einhorn, L., Etter, E. M., Rienks, S., \u0026amp; Markman, H. (2011). Preliminary Efficacy of an Intervention to Reduce Psychosocial Stress and Improve Coping in Low-Income Families. \u003cem\u003eAmerican Journal of Community Psychology\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(3\u0026ndash;4), 257\u0026ndash;271. https://doi.org/10.1007/s10464-010-9384-z\u003c/li\u003e\n\u003cli\u003eWeber, D. M., Lavner, J. A., \u0026amp; Beach, S. R. H. (2024). Different trajectories of relationship satisfaction among rural Black couples following preventive relationship intervention. \u003cem\u003eJournal of Consulting and Clinical Psychology\u003c/em\u003e, \u003cem\u003e92\u003c/em\u003e(6), 356\u0026ndash;366. https://doi.org/10.1037/ccp0000894\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of South Carolina","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"family stress model, poverty, adversity, person-centered approach, latent class analysis","lastPublishedDoi":"10.21203/rs.3.rs-9085268/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9085268/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eMulticomponent family-based interventions can mitigate the adverse effects of poverty on family functioning. However, benefits are not uniform across families. Limited research has examined how distinct constellations of poverty-related risk shape engagement with and responsiveness to preventive interventions. Using a person-centered approach, this study tested whether pre-intervention risk profiles predicted differential engagement with and response to the Fatherhood, Relationship, and Marriage Education (FRAME) intervention, a program based on the Family Stress Model and designed to strengthen parental coping, couple relationships, and parenting practices. Participants were 301 mother-father-child triads with household incomes at or below 200% of the federal poverty level. Building on prior research that identified four latent risk classes, we examined whether class membership predicted session attendance and moderated intervention effects on family relational and behavioral outcomes assessed six months post-intervention using combined mother and father reports. Results indicated heterogeneity in both engagement and intervention response. Families characterized by moderate economic stress and elevated parental depressive symptoms demonstrated the highest attendance and the most favorable response, particularly for couple relationship quality. Families in the lowest and highest risk classes received few benefits, with the lowest risk group experiencing adverse effects on some outcomes. Sensitivity analyses suggested additional gender-specific patterns, indicating that mothers’ and fathers’ responses may differ within certain risk classes. These findings highlight the value of identifying multidimensional risk profiles when evaluating preventive interventions and support precision approaches to intervention delivery.\u003c/p\u003e","manuscriptTitle":"Understanding Who Benefits Most from Family-Based Prevention: Differential Intervention Effects for Families with Low Income","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-12 10:43:25","doi":"10.21203/rs.3.rs-9085268/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ccde1f36-dca2-45e1-b03a-b76d93f76618","owner":[],"postedDate":"March 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-12T10:43:25+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-12 10:43:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9085268","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9085268","identity":"rs-9085268","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}