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Cascade effects of a parenting-focused program for divorced families on three health-related outcomes in emerging adulthood

Published online by Cambridge University Press:  04 October 2024

Sharlene A. Wolchik*
Affiliation:
Arizona State University, Tempe, AZ, USA
Jenn-Yun Tein
Affiliation:
Arizona State University, Tempe, AZ, USA
C. Aubrey Rhodes
Affiliation:
Arizona State University, Tempe, AZ, USA
Irwin N. Sandler
Affiliation:
Arizona State University, Tempe, AZ, USA
Linda J. Luecken
Affiliation:
Arizona State University, Tempe, AZ, USA
Michele M. Porter
Affiliation:
Arizona State University, Tempe, AZ, USA
*
Corresponding author: Sharlene Wolchik; Email: [email protected]
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Abstract

Using data from a 15-year longitudinal follow-up of a randomized controlled trial of a parenting-focused preventive intervention for divorced families (N = 240) with children aged 9–12, the current study examined alternative cascading pathways through which the intervention led to improvements in offspring’s perceived health problems, BMI, and cigarette smoking in emerging adulthood. It was hypothesized that the program would lead to improvements in these health-related outcomes during emerging adulthood through progressive associations between program-induced changes in parenting and offspring outcomes, including mental health problems, substance use, and competencies. Intervention-induced improvements in positive parenting at posttest led to improvements in mental health problems in late childhood/early adolescence, which led to lower levels of mental health and substance use problems as well as higher levels of competencies in adolescence, which led to improvements in the health-related outcomes. Academic performance predicted all three health-related outcomes and other aspects of adolescent functioning showed different relations across outcomes. Results highlight the potential for intervention effects of preventive parenting interventions in childhood to cascade over time to affect health-related outcomes in emerging adulthood.

Type
Regular Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press

Introduction

There is compelling evidence that prevention programs that target improvements in parenting have long-term effects on offspring’s health-related behaviors, such as the use of alcohol, cannabis, illicit substances, and non-prescribed narcotics as well as their engagement in risky sexual behavior (e.g., Brody et al., Reference Brody, Kogan, S., Murry and Brown2010; DeGarmo et al., Reference DeGarmo, J., Reid and Fetrow2009; Spoth et al., Reference Spoth, Shin, Greenberg, M., Feinberg and Trudeau2017; Reference Spoth, Redmond, Shin, Trudeau, Greenberg, Feinberg and Welsh2022; Zhou et al., Reference Zhou, Sandler, Millsap, Wolchik and Dawson-McClure2008). However, these specific behaviors represent only a subset of potential health-related outcomes. Very few researchers have examined the effects of parenting-focused programs on other health-related behaviors.

Four studies that focused on other health-related outcomes investigated the effects of parenting-focused programs on body mass index (BMI) or obesity. Studying an adaptation of the Incredible Years Program and Parent Corps for preschoolers, Brotman et al. (Reference Brotman, Dawson-McClure, Huang, Theise, Kamboukos, Wang, Petkova and Ogedegbe2012) found program-induced reductions in BMI, blood pressure, and odds of obesity an average of five years after participation. In a sample of at-risk toddlers, Smith et al. (Reference Smith, Montaño, Dishion, Shaw and Wilson2015) found that the Family Check-Up (FCU) led to a less steep increase in BMI scores and prevented children from progressing to overweight or obese status in early to late childhood. Van Ryzin and Nowicka (Reference Van Ryzin and Nowicka2013) found indirect effects of the FCU for high-risk adolescents on obesity in young adulthood. Brody et al. (Reference Brody, Yu, Miller, Ehrlich and Chen2019) found that participation in Strong African American Families in early adolescence reduced BMI for females eight to 14 years after participation. Only two research groups have examined the effect of prevention programs that target parenting on cigarette smoking. Spoth and his colleagues found that the Strengthening Families Program as well as this program combined with Life Skills Training when provided to youth between 10 and 14 years of age reduced cigarette use in both late adolescence (Spoth et al., Reference Spoth, Randall, Trudeau, Shin and Redmond2008) and young adulthood (Spoth et al., Reference Spoth, Trudeau, Redmond and Shin2016; Reference Spoth, Redmond, Shin, Trudeau, Greenberg, Feinberg and Welsh2022). Examining the effects of Linking the Interests of Families and Teachers, DeGarmo et al. (Reference DeGarmo, J., Reid and Fetrow2009) found that children who participated in the program during fifth grade had less tobacco use in grade 12. Only one study has examined the impact of a preventive parenting intervention on perceptions of physical health. In a sample of children aged 5 to 11 from families involved with the child welfare system, Lanier et al. (Reference Lanier, Dunnigan and Kohl2018) found that compared to services-as-usual, the Triple P Parenting intervention did not improve the physical health component of a measure of health-related quality of life.

The current study provides a rare opportunity to expand this limited literature by examining whether a parenting-focused prevention program delivered in late childhood/early adolescence, which did not explicitly target improvements in health, led to improvements in health-related outcomes in emerging adulthood. More specifically, it examines direct as well as cascade effects models of the effects of the New Beginnings Program, a parenting-focused program for divorced parents that was delivered when the offspring were in late childhood to early adolescence, on three health-related outcomes in emerging adulthood: perceived health problems, Body Mass Index (BMI), and cigarette smoking. Below, we discuss the prevalence of parental divorce and its effects on health-related outcomes and describe the New Beginnings Program. We then discuss the cascade effects model as well as empirical support and possible mechanisms for the theorized pathways through which program-induced improvements in offspring’s internalizing and externalizing problems, substance use and competencies in adolescence may affect the physical health-related outcomes that were examined. We then describe the current study.

Prevalence and effects of parental divorce on development of physical health-related outcomes

In 2020, there were 18.6 million children living with a single, divorced parent in the United States (Statista, 2022). Compelling evidence demonstrates that parental divorce confers risk for multiple physical health problems. Relative to their counterparts in two-parent families, children from divorced families have poorer self-rated health (Thuen et al., Reference Thuen, Breivik, Wold and Ulveseter2015), more accidental injuries (O’Connor et al. Reference O’Connor, Davies, Dunn and Golding2000), greater rates of asthma (Thompson et al., Reference Thompson, Filipp, Mack, Mercado, Barnes, Bright, Shenkman and Gurka2020), and higher BMI index and increased risk for obesity (Kyler et al., Reference Kyler, Hall, Halvorson and Davis2021).

Adults with a history of parental divorce report poorer self-rated health (e.g., Thomas & Högnäs, Reference Thomas and Högnäs2015) and health practices (Larson & Halfon, Reference Larson and Halfon2013), such as increased likelihood of cigarette smoking (e.g., Amiri et al., Reference Amiri, Fathi-Ashtiani, Sedghijalal and Fathi-Ashtiani2021), and are more likely to have obesity (Font & Maguire-Jack, Reference Font and Maguire-Jack2016). They also demonstrate increased chronic (e.g., Maier & Lachman, Reference Maier and Lachman2000) and acute health problems (e.g., Maier & Lachman, Reference Maier and Lachman2000), including increased inflammation (Lacey et al., Reference Lacey, Kumari and McMunn2013), diabetes (Varis et al., Reference Varis, Hagnäs, Mikkola, Nordström, Puukka, Taanila and Keinänen-Kiukaanniemi2022), and heart attacks (Monnat & Chandler, Reference Monnat and Chandler2015), as well as increased mortality risk (Larson & Halfon, Reference Larson and Halfon2013). The high prevalence of divorce and its broad, lasting effects mean that the impact of parental divorce on population rates of physical health problems is substantial and that interventions that mitigate its effects could significantly reduce its public health burden.

Effects of the New Beginnings Program

Based on a risk and protective factor model of the development of problem outcomes and person–environment frameworks (Cicchetti & Schneider-Rosen, Reference Cicchetti, Schneider-Rosen, Rutter, Izard and Read1986; Sameroff, Reference Sameroff1975), the New Beginnings Program targeted the four risk and protective factors that were most strongly associated with children’s outcomes in correlational studies of children in divorced families in the research available at the time the program was developed: parent-child relationship quality, effective discipline, exposure to interparental conflict, and father-child contact. From the perspective of a developmental cascade model (e.g., Cicchetti & Sroufe, Reference Cicchetti and Sroufe2000), program-induced changes in these processes at posttest are theorized to decrease offspring’s problem outcomes and increase their competencies in subsequent periods of development through their effect on short-term reductions in internalizing and externalizing problems (Wolchik et al., Reference Wolchik, Sandler, Weiss and Winslow2007). The majority of the program focused on improving positive parenting, defined as high-quality parent-child relationships and effective discipline.

Three randomized controlled trials involving over 1,500 children found positive short-term effects of the New Beginnings Program on children’s internalizing and externalizing problems (Sandler et al., Reference Sandler, Gunn, Mazza, Tein, Wolchik, Kim, Ayers and Porter2018, Reference Sandler, Yun-Tien, Zhang, Wolchik and Thieleman2021; Tein et al., Reference Tein, Mazza, Gunn, Kim, Stuart, Sandler and Wolchik2018; Wolchik et al., Reference Wolchik, West, Westover, Sandler, Martin, Lustig, Tein and Fisher1993, Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000). For one of the samples (Wolchik et al., Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000), 6-year and 15-year follow-ups were conducted. These follow-ups found program effects, including reductions in diagnoses of mental disorders, substance use disorders, and time in jail, as well as improvements in self-esteem and grade point average (GPA), with effect sizes at the 6- and 15-year follow-ups ranging from .20 to .67 (mean = .44) and .40 to .61 (mean = .51), respectively (Herman et al., Reference Herman, Mahrer, Wolchik, Porter, Jones and Sandler2015; Sandler et al., Reference Sandler, Yun-Tien, Zhang, Wolchik and Thieleman2021; Wolchik et al., Reference Wolchik, Sandler, Weiss and Winslow2007). Several studies showed that the program-induced effects to improve positive parenting mediated the effects of the New Beginnings Program on multiple outcomes at posttest and the six-month and six-year follow-ups (Tein et al., Reference Tein, Sandler, MacKinnon and Wolchik2004; Vélez et al., Reference Vélez, Wolchik, Tein and Sandler2011; Wolchik et al., Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000; Zhou et al., Reference Zhou, Sandler, Millsap, Wolchik and Dawson-McClure2008). To understand the long-term fiscal impact of the program, a rigorous cost-benefit analysis was performed that examined the individual and societal costs associated with mothers’ and emerging adult offspring’s mental health service use and prescription drug use as well as offspring’s encounters with the adult justice system. Using service use data for the one-year period before the 15-year follow-up, analyses showed a $1,600 savings per family in the New Beginnings Program compared to the control condition (Herman et al., Reference Herman, Mahrer, Wolchik, Porter, Jones and Sandler2015).

Developmental cascade models

A central scientific goal of developmental psychopathology is to unravel the developmental pathways that lead to positive and negative adaptation outcomes (e.g., Cicchetti & Sroufe, Reference Cicchetti and Sroufe2000). One approach to studying these pathways is to model cascading effects, or the progressive associations among various domains of functioning over time (Masten & Cicchetti, Reference Masten and Cicchetti2010; Rutter & Sroufe, Reference Rutter and Sroufe2000). In these models, change in a particular area of functioning is viewed as initiating a domino effect of consequences, impacting both the initial area of adaptation and other areas of adaptation in subsequent developmental stages (Sameroff, Reference Sameroff2000). Studies with the New Beginnings Program data set found support for cascade effects models in which program-induced improvements in positive parenting led to decreases in offspring’s internalizing and externalizing problems in late childhood/early adolescence, which then led to lower mental health and substance use problems and higher work, academic, and peer competencies in adolescence, which in turn led to more adaptive functioning in emerging adulthood (Wolchik et al., Reference Wolchik, Tein, Sandler and Kim2016; Reference Wolchik, Tein, Winslow, Minney, Sandler and Masten2021). The current study tests a direct effects model and as well as cascade effects models of the links between program-induced improvements in positive parenting in late childhood/early adolescence, internalizing problems and externalizing problems in late childhood/early adolescence; internalizing problems and externalizing problems, alcohol/marijuana use, adaptive coping, self-esteem and grade point average (GPA) in adolescence that were affected either directly or indirectly by the New Beginnings Program and three health-related outcomes in emerging adulthood: perceived health problems, BMI and cigarette smoking.

Support for pathways between adolescent functioning and health-related outcomes in emerging adulthood

There is a theoretical basis and empirical support for six domains of functioning in adolescence predicting health-related outcomes in adulthood: internalizing problems, externalizing problems, alcohol/marijuana use, GPA, adaptive coping, and self-esteem.

Internalizing problems. Researchers have found that internalizing problems in adolescence predict subsequent adverse health outcomes, including perceived health problems and general physical health (e.g., Hoyt et al., Reference Hoyt, Chase-Lansdale, McDade and Adam2012; Keenan-Miller et al., Reference Keenan-Miller, Hammen and Brennan2007; Naicker et al., Reference Naicker, Galambos, Zeng, Senthilselvan and Colman2013; Patton et al., Reference Patton, Carlin, Coffey, Wolfe, Hibbert and Bowes1998), cigarette smoking (e.g., Dierker et al., Reference Dierker, Hedeker, Rose, Selya and Mermelstein2015; McKenzie et al., Reference McKenzie, Olsson, Jorm, Romaniuk and Patton2010) and BMI (e.g., Hasler et al., Reference Hasler, D., Kleinbaum, Gamma, Luckenbaugh, Ajdacic, Eich, Rössler and Angst2005; Roberts and Duong., Reference Roberts and Duong2013). For example, Keenan-Miller et al. (Reference Keenan-Miller, Hammen and Brennan2007) found that depression at age 15 was associated with poorer interviewer-rated health, poorer self-perceived general health, higher healthcare utilization, and increased work impairment due to physical health problems at age 20. Internalizing problems in adolescence may lead to adverse health behaviors through several mechanisms. Correlates of depression, such as unhealthy eating (e.g., Huang et al., Reference Huang, Momma, Cui, Chujo, Otomo, Sugiyama, Ren, Niu and Nagatomi2017) and infrequent exercise (Roshanaei-Moghaddam, Reference Roshanaei-Moghaddam, Katon and Russo2009) could contribute to adverse health-related behaviors. Other possible mechanisms include the compounding bidirectional effects of chronic stress and rumination, which are common features of both physical and internalizing problems, as well as inflammatory responses triggered by stress, rumination, and heightened fear responses associated with internalizing problems (van de Pavert et al., Reference van de Pavert, Sunderland, Luijten, Slade and Teesson2017).

Externalizing problems. Studies have found that externalizing problems in adolescence predict smoking (e.g., Alaie et al., Reference Alaie, Svedberg, Ropponen and Narusyte2023; Fergusson et al., Reference Fergusson, Horwood, Boden and Jenkin2007; Jester et al., Reference Jester, Glass, Bohnert, Nigg, Wong and Zucker2019) and higher BMI (e.g., Slane et al., Reference Slane, Burt and Klump2010) in adulthood. To our knowledge, the relations between externalizing in adolescence and perceived health problems in emerging adulthood have not been examined. One plausible explanation for the association between externalizing problems and smoking involves deviance theories. Deviance theories view various deviant behaviors as reflecting a unified syndrome characterized by alternate manifestations of a propensity to violate normative standards of behavior that remains cohesive into adulthood (Donovan et al., Reference Donovan, Jessor and Costa1988). Another possibility, which is based on the Self-Medication Theory (Khantzian, Reference Khantzian1997), is that individuals with high levels of externalizing problems smoke to reduce the frequency of their anger experiences (Jamner et al., Reference Jamner, Shapiro and Jarvik1999), improve attentional problems, or both (e.g., McClernon & Kollins, Reference McClernon and Kollins2008; Van Amsterdam et al., Reference van Amsterdam, van der Velde, Schulte and van den Brink2018). Affective lability and impulsivity, which are associated with externalizing problems, may contribute to cigarette smoking as well as overeating that is associated with higher BMI. It is possible that externalizing problems could affect perceived health problems through exposure to high-risk environments, which could promote behaviors that lead to poor health-related outcomes.

Alcohol/Marijuana use. Research has shown positive associations between both alcohol use (e.g., Paavola et al., Reference Paavola, Vartiainen and Haukkala2004; Riala et al., Reference Riala, Hakko, Isohanni, Järvelin and Räsänen2004) and cannabis use (e.g., Patton et al., Reference Patton, Coffey, Carlin, Sawyer and Lynskey2005; Taylor et al., Reference Taylor, Collin, Munafò, MacLeod, Hickman and Heron2017) in adolescence and cigarette smoking in adulthood. For example, cannabis use in non-cigarette-smokers in adolescence has been found to predict cigarette smoking initiation in young adulthood (e.g., Coffey & Patton, Reference Coffey and Patton2016). Cannabis use in adolescence has also been shown to relate to poorer self-reports of overall physical health in adulthood (Terry-McElrath et al., Reference Terry-McElrath, O’Malley, Johnston, Bray, Patrick and Schulenberg2017). Alcohol use in adolescence has been related to greater health problems (Oesterle et al., Reference Oesterle, Hill, Hawkins, Guo, Catalano and Abbott2004) as well as better self-reported health status (French & Zavala, Reference French and Zavala2007). The research on the relations between cannabis use in adolescence and BMI in early adulthood is inconsistent. Some researchers have found non-significant relations (e.g., Capaldi et al., Reference Capaldi, Tiberio, Kerr and Owen2022), others have found positive relations (e.g., Ellickson et al., Reference Ellickson, Martino and Collins2004; Huang et al., Reference Huang, Lanza and Anglin2013) and others have found inverse relations (e.g., Meier et al., Reference Meier, Schriber, Beardslee, Hanson and Pardini2019). The research examining alcohol use in adolescence and BMI in emerging adulthood is also inconsistent (e.g., Huang et al., Reference Huang, Lanza and Anglin2013; Oesterle et al., Reference Oesterle, Hill, Hawkins, Guo, Catalano and Abbott2004; Pajari et al., Reference Pajari, Pietilainen, Kaprio, Rose and Saarni2010). Plausible mechanisms for the positive association between adolescent alcohol and cannabis use and later problematic health-related outcomes include its association with the development of detrimental lifestyles, such as unhealthy diet, which may heighten the risk of obesity (Pasch et al., Reference Pasch, Velazquez, Cance, Moe and Lytle2012) and continued exposure to high-risk environments that could promote behaviors that could lead to more health problems, higher BMI, and smoking. Possible mechanisms for the inverse relations between cannabis use and BMI may occur because cannabis increases one’s metabolism and raises the amount of fat the body burns (Huang et al., Reference Huang, Lanza and Anglin2013) by reducing the number and signaling efficiency of cannabinoid receptors that play a role in the regulation of food intake and energy expenditure (Meier et al., Reference Meier, Schriber, Beardslee, Hanson and Pardini2019). It has been suggested that the inverse relations between alcohol use and BMI may be due to a positive relation between moderate alcohol use and physically active lifestyles (Smothers & Bertolucci, Reference Smothers and Bertolucci2001), such that the energy intake through alcohol is offset by the extra energy consumed through physical activity (French et al., Reference French, Popovici and Maclean2009).

Academic performance. Higher academic performance has been shown to predict smoking (e.g., Crane et al., Reference Crane, Langenecker and Mermelstein2021; White et al., Reference White, Pandina and Chen2002), BMI (e.g., Alatupa et al., Reference Alatupa, Pulkki-Råback, Hintsanen, Ravaja, Raitakari, Telama, Viikari and Keltikangas-Järvinen2010; Sobol-Goldberg & Rabinowitz, Reference Sobol-Goldberg and Rabinowitz2016) and perceived health problems (e.g., Herd, Reference Herd2010; Maggs et al., Reference Maggs, Frome, Eccles and Barber1997). For example, Sobol-Goldberg and Rabinowitz (Reference Sobol-Goldberg and Rabinowitz2016) found that poorer academic achievement in adolescence predicted higher BMI in early adulthood. Academic performance in adolescence may affect health-related behaviors in emerging adulthood through several mechanisms. It may increase the probability of obtaining higher paying jobs, which may make healthy foods more affordable (Drewnowski, Reference Drewnowski2010), facilitate access to preventive health care, promote healthier lifestyles as well as reduce economic stress that can lead to smoking and emotional eating (Tan & Chow, Reference Tan and Chow2014). Academic success may also be associated with “learned effectiveness” (Mirowsky & Ross, Reference Mirowsky and Ross2005), which can lead to perceptions that a healthy lifestyle is within one’s control and increased knowledge about behaviors that promote healthy choices. In addition, higher academic performance may increase access to health-related information, increase the ability to comprehend and act on the information, allow a clearer understanding of the risk related to behaviors like smoking (Clausen, Reference Clausen1991) and provide knowledge and skills that increase personal control and agency that lead to healthy behaviors and a healthy lifestyle (Herd, Reference Herd2010; Hitlin & Kirkpatrick Johnson, Reference Hitlin and Kirkpatrick Johnson2015; Mirowsky & Ross, Reference Mirowsky and Ross2007). Further, if youth are highly involved in academic and school-related activities, they may have fewer potential opportunities to experiment with tobacco, and may derive more a positive view of themselves, which in itself may be protective (e.g., Kaplan et al., Reference Kaplan, Johnson and Bailey1987).

Adaptive coping. Research has provided support for inverse relations between adaptive coping and perceived health problems (e.g. Park & Alder, Reference Park and Adler2003; Schreuder et al., Reference Schreuder, C.A., Groothoff, van der Klink, Magerøy, Pallesen, Bjorvatn and Moen2012) and cigarette smoking (e.g., Carvajal & Granillo, Reference Carvajal and Granillo2006; Steiner et al., Reference Steiner, Erickson, Hernandez and Pavelski2002). Avoidant coping has been shown to be related to unhealthy eating behaviors (Martyn-Nemeth et al., Reference Martyn‐Nemeth, Penckofer, Gulanick, Velsor‐Friedrich and Bryant2009), which could increase BMI. Also, an increase in stress has been associated with an increase in the consumption of high calorie foods (O’Connor & O’Connor, Reference O’Connor and Conner2011) and stress-related eating has been positively related to BMI (Jääskeläinen et al., Reference Jääskeläinen, Nevanperä, Remes, Rahkonen, Järvelin and Laitinen2014). In a sample of medical students, Park and Adler (Reference Park and Adler2003) found that the use of adaptive coping strategies, such as planful problem solving and positive reappraisal, was prospectively associated with better physical health (Steiner et al., Reference Steiner, Erickson, Hernandez and Pavelski2002). Adaptive coping may promote the effective management of negative affect, potentially preventing behaviors like smoking and overeating (Herren et al., Reference Herren, Agurs-Collins, Dwyer, Perna and Ferrer2021) which, in turn, could lead to worsened perceived health problems. It is also possible that adolescents with higher levels of adaptive coping experience less stress, which could affect their perceived health problems, cigarette smoking and eating habits.

Self-esteem. It is well documented that self-esteem in adolescence is inversely, longitudinally related to cigarette smoking (e.g., Boden et al., Reference Boden, Fergusson and Horwood2008), obesity (e.g., Park, Reference Park and Adler2003; Trzesniewski et al., Reference Trzesniewski, Donnellan, Moffitt, Robins, Poulton and Caspi2006) and perceived health problems (e.g., Arsandaux et al., Reference Arsandaux, Michel, Tournier, Tzourio and Galéra2019; Jafflin et al., Reference Jafflin, Pfeiffer and Bergman2019; Trzesniewski et al., Reference Trzesniewski, Donnellan, Moffitt, Robins, Poulton and Caspi2006). For example, Trzesniewski et al. (Reference Trzesniewski, Donnellan, Moffitt, Robins, Poulton and Caspi2006) found that adolescents with low self-esteem were more likely to have poor cardiorespiratory health, high waist-to hip ratios, and poor self-perceived health 11 years later than those with high self-esteem, controlling for gender, SES, adolescent depression, and childhood BMI. Higher self-esteem may increase opportunities for mastery and enable individuals to make better choices, including adopting healthy behaviors (Kliewer & Sandler, Reference Kliewer and Sandler1992), which could affect health-related outcomes. It is also possible that higher self-esteem regulates responses to the threat of rejection in a manner that can benefit health or help individuals recover from stress more quickly (Stinson & Fisher, Reference Stinson and Fisher2020). Higher self-esteem may also increase the use of adaptive coping strategies, reduce exposure to stressors, or both (Lo, 2002), which could affect health-related outcomes.

Contributions of the current study and hypotheses

Assessing the cascade effects of the New Beginnings Program on health-related outcomes in emerging adulthood is particularly important because physical health and lifestyle factors in this developmental stage have important implications for health problems later in life. For example, having an unhealthy weight in emerging adulthood has significant physical health implications, such as increased risk of hypertension, diabetes, cardiovascular disease, and higher mortality (Cheng et al., Reference Cheng, Medlow and Steinbeck2016; Guo et al., Reference Guo, Yue, Li, Song, Yan, Zhang, Gui, Chang and Li2016; Hirko et al., Reference Hirko, Kantor, Cohen, Blot, Stampfer and Signorello2015). Also, interventions with parents that are intended to trigger positive and progressive effects over time offer compelling experimental tests of predictions of cascade models that are based on developmental systems theory as well as resilience theory (Masten & Cicchetti, Reference Masten and Cicchetti2010). Two features of this study increase the rigor of these tests. First, the longitudinal design provides temporal precedence between the proposed antecedents, mediational processes, and the outcomes, which allows one to rule out interpreting significant paths in the model as being due to a reverse order of causation (Cole & Maxwell, Reference Cole and Maxwell2003; Kraemer et al., Reference Kraemer, Wilson, Fairburn and Agras2002). Second, the current study examined multiple mediators and tested the impact of each pathway while controlling for other potential pathways.

Based on past research, intervention-induced improvements in positive parenting were expected to lead to improvements in internalizing problems and externalizing problems in late childhood/early adolescence, which were expected to relate to improvements in internalizing problems and externalizing problems, alcohol/marijuana use, adaptive coping, self-esteem and GPA in adolescence, which were expected to be associated with lower perceived health problems, lower BMI and less cigarette smoking. Internalizing problems and externalizing problems were expected to be related to higher perceived health problems, BMI and cigarette smoking. Higher adaptive coping, self-esteem and GPA were expected to be related to lower perceived health problems, BMI, and cigarette smoking. Alcohol/marijuana use was predicted to be associated with higher cigarette smoking and lower perceived health problems. Based on past research that has shown inconsistent relations between alcohol/marijuana use and BMI, a directional hypothesis was not made.

Method

Participants

The sample included 240 offspring of divorced parents who participated in a randomized controlled trial of the New Beginnings Program in late childhood/early adolescence (9-12 years old). Potential participants were identified primarily through court records of divorce decrees in a large Southwestern metropolitan county; 20% were recruited by media advertisements or word of mouth. Eligibility criteria are provided in Wolchik et al. (Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000). In families with multiple children in the age range, one was randomly selected as the target child for assessments to ensure independence of responses.

Families were randomly assigned to: (a) a mother-only program (MP, n = 81 families), (b) a mother-plus-child program (MPCP; separate, concurrent groups for mothers and children, n = 83 families), or (c) a literature control condition (LC, n = 76 families). Given the lack of differences between the MP and MPCP programs on almost all of the variables at each of the six assessments (tests included all mediators and outcome variables in this study), these conditions were combined and labeled as the New Beginnings Program.

At pretest, children averaged 10.4 years old (SD = 1.1; range = 9–12); 49% were girls. Mothers’ mean age was 37.3 years (SD = 4.8); 98% had at least a high school education. Mothers’ ethnicity was 88% non-Hispanic White, 8% Hispanic, 2% Black, 1% Asian or Pacific Islander, and 1% other. Parents had been separated and divorced an average of 2.2 years (SD = 1.4) and 1.0 year (SD = 0.5), respectively, before program entry. The average age of the offspring was 16.9 at the six-year follow-up (SD = 1.1, range = 15.1–19.1) and 25.6 at the 15-year follow-up (SD = 1.2, range = 24–28). Educational attainment at the 15-year follow-up was: Less than high school – 2.6%; High school – 22.1%; Some college – 45.4%; College graduate – 29.4%; Postgraduate – 3.1%. Fifty-one percent were married or living as if married. Median annual income was $30,000 ($5,000 categories ranging from ≤$5,000 to ≥$200,000).

Intervention conditions

The mother program consisted of 11 group sessions (1.75 hours) and two individual sessions that focused on improving mother-child relationship quality and effective discipline, decreasing barriers to father-child contact, and reducing children’s exposure to interparental conflict. Based on social learning and cognitive behavioral theories, the highly structured program used active learning methods, videotaped modeling, and roleplays in the sessions, and parents were assigned practice of the program skills.

In the mother-plus-child program, mothers participated in the mother program and children participated in a concurrently run 11-session group program. The child program targeted active coping, avoidant coping, threat appraisals of divorce stressors, and mother–child relationship quality. Didactic presentations, videotapes, leader modeling, role plays, and games were used to teach the program skills; homework to practice the program skills was assigned. For more information about the programs, see (Wolchik et al., Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000, Reference Wolchik, Sandler, Weiss and Winslow2007).

In the literature control, mothers and children received three books about children’s divorce adjustment over a three-month interval. Mothers and children reported reading about half of the books.

Procedure

Families were interviewed at: pretest (T1), posttest (T2), and 3-month (T3), 6-month (T4), 6-year (T5), and 15-year (T6) follow-ups. Participation at the offspring level was 100% at T1, 98.3% at T2 and T3, 97.5% at T4, 90.8% at T5, and 80.8% at T6. The cascade effects models used data from all waves. Trained staff conducted separate interviews with parents and offspring. Confidentiality was explained, and the parent and offspring signed consent/assent forms. Families received $45 at T1 to T4; parents and offspring each received $100 at T5. At T6, offspring received $225; parents received $50. Study procedures were approved by the Arizona State University Institutional Review Board.

Measures

We describe the measures and Cronbach alphas (α’s), when applicable, by the developmental period in which they were administered. Nearly all measures used the timeframe of the last month; exceptions are noted. We report reliability coefficients of the measures at the assessments used in this study.

Late childhood/early adolescence (T1, 2, 3, 4)

Demographics and pretest risk

At the pretest, mothers completed information on demographic variables (e.g., ethnicity, age, length of divorce). Because several studies have shown that the New Beginnings Program had stronger effects for youth who had higher risk at pretest (Dawson-McClure et al., Reference Dawson-McClure, Sandler, Wolchik and Millsap2004; Wolchik et al., Reference Wolchik, Sandler, Weiss and Winslow2007, Reference Zhou, Sandler, Millsap, Wolchik and Dawson-McClure2021), we included a measure of pretest risk as a covariate for all mediators and outcomes and tested whether it moderated the intervention effect on the mediators and outcomes. The risk score was a composite of (a) environmental stressors (i.e., composite of interparental conflict, negative life events that occurred to the child, capita annual income) and (b) mother and child reports of child externalizing problems at pretest as described below.

Positive parenting

T1 and T2 positive parenting was a composite of mother and child reports of mother-child relationship quality and effective discipline on several measures. Zhou et al. (Reference Zhou, Sandler, Millsap, Wolchik and Dawson-McClure2008) used confirmatory factor analysis to examine the two-factor parenting constructs (mother-child relationship quality, effective discipline) at T1 and T2 and showed adequate fit of the models. The two constructs were strongly related (r = .70 at T1; r = .69 at T2 (see Zhou et al., Reference Zhou, Sandler, Millsap, Wolchik and Dawson-McClure2008)).

Mother-child relationship quality

Mothers and children completed shortened (10-item) versions of Teleki et al.’s (Reference Teleki, Powell and Dodder1982) adaptation of the Child Report of Parenting Behavior Inventory (CRPBI; Schaefer, Reference Schaefer1965) Acceptance and Rejection subscales; α’s at T1 and T2 were .78 and .81, respectively for mother reports and .84 and .89 child reports. Mothers and children completed the 10-item Open Family Communication subscale of the Parent–Adolescent Communication Scale (Barnes & Olson, Reference Barnes, Olson and Olson1982); α’s were .72 and .75 for mother reports and .82 and .87 for child reports at T1 and T2, respectively. Mothers completed a 7-item adaptation of the Family Routines Inventory (Jensen et al., Reference Jensen, James, Boyce and Hartnett1983) that assessed mother-child dyadic interactions (T1 α = .67, T2 α = .63). These scales have adequate reliability and validity (e.g., Barnes & Olson, Reference Barnes and Olson1985; Capaldi, Reference Capaldi1991; Cohen et al., Reference Cohen, Taborga, Dawson and Wolchik2000; Demo et al., Reference Demo, Small and Savin-Williams1987; Fogas et al., Reference Fogas, Wolchik and Braver1987; Schaefer, Reference Schaefer1965; Wolchik et al., Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000). Consistent with other studies on the New Beginnings Program, mother and child report scales were standardized and averaged to create a composite. The weighted α’s (Rozeboom, 1969) of the composite were .88 (T1) and .90 (T2).

Effective discipline

Mothers and children completed the 8-item Inconsistent Discipline subscale of CRPBI (Schaefer, Reference Schaefer1965); α’s were .81 and .80 for mother reports at T1 and T2, and .72 and .73 for child reports at T1 and T2, respectively. Mothers also completed the 14-item appropriate/inappropriate discipline subscale (T1 α = .70, T2 α = .71) and the 11-item follow-through subscale (T1 α = .80, T2 α = .76) of the Oregon Discipline Scale (Oregon Social Learning Center, 1991). These scales have adequate reliability and validity (e.g., Fogas et al., Reference Fogas, Wolchik and Braver1987; Schaefer, Reference Schaefer1965). These scales were standardized and averaged to create a composite. The weighted α’s were .84 and .89 at T1 and T2.

Internalizing and externalizing problems

At T1, T3, and T4, mothers completed the 31-item internalizing and 33-item externalizing subscales of the Child Behavior Checklist (CBCL; Achenbach & Edelbrock, Reference Achenbach and Edelbrock1983). Adequate reliability and validity have been reported (Achenbach, Reference Achenbach1991). The α’s for internalizing problems were between .85 and .88; the α’s for the externalizing problems were all .87.

Child report of depression during the last two weeks was measured with the 27-item Child Depression Inventory (CDI; Kovacs, Reference Kovacs1981; α’s ranged from .76 to .80). The CDI has adequate reliability and validity (e.g., Saylor et al., Reference Saylor, Finch, Spirito and Bennett1984). Child report of anxiety was assessed with the 28-item Revised Children’s Manifest Anxiety Scale (RCMAS; Reynolds & Richmond, Reference Reynolds and Richmond1978; α’s ranged from .88 to .91). The RCMAS has adequate reliability and validity (e.g., Reynolds & Paget, Reference Reynolds and Paget1981). A composite of the mean of the standardized scores of the CDI and RCMAS (r = .58–.67 across assessments) was used.

Child externalizing problems were assessed with the 30-item aggression and delinquency subscales of the Youth Self Report (YSR; Achenbach, Reference Achenbach1991; α’s ranged from .86 to .88). Reliability and validity of these subscales have been demonstrated (Achenbach, Reference Achenbach1991).

Given the short interval between T3 and T4, scores at these assessments were averaged. The correlations of mother and child reports across assessments were .26–.32 for internalizing problems and .25–.34 for externalizing problems. Composite scores of internalizing and externalizing problems, separately, were constructed by averaging the standardized scores of mother and child reports.

Adolescence (T5)

Except for self-esteem and adaptive coping, all adolescent measures were administered only at T5.

Externalizing and internalizing problems

Adolescents’ mental health problems were assessed by symptoms of externalizing and internalizing disorders endorsed by either the parent or adolescent over the past year on the Diagnostic Interview Schedule for Children (DIS-C; Shaffer et al., Reference Shaffer, Fisher, Lucas, Dulcan and Schwab-Stone2000). Scores were computed separately for internalizing disorders (i.e., agoraphobia, generalized anxiety disorder, obsessive–compulsive disorder, panic disorder, post-traumatic stress disorder, social phobia, specific phobia, eating disorders, and major depression) and externalizing disorders (i.e., conduct disorder, oppositional defiant disorder, and attention-deficit/hyperactivity disorder) using symptom scores endorsed by either the parent or adolescent. The DIS has been validated against the WHO Schedules for Clinical Assessment in Neuropsychiatry (Wing, Reference Wing1990).

Alcohol and cannabis use

Cannabis use and alcohol use in the past year were assessed using the Monitoring the Future Scale (Bachman et al., Reference Bachman, Johnston and O’Malley1993). This scale has adequate reliability and validity (e.g., Bachman et al., Reference Bachman, Johnston and O’Malley1993). The mean of the frequency of cannabis and alcohol use was used.

Self-esteem

The six-item global self-worth subscale of Harter’s (Reference Harter1985) Self-Perception Profile for Children was used to assess global self-esteem at T5 (α = 0.86) and T1 (α = 0.71). This measure has adequate reliability and validity (e.g., Muris et al., Reference Muris, Meesters and Fijen2003).

Adaptive coping

Adaptive coping was assessed with the 24-item active coping subscale of the Children’s Coping Strategies Checklist–Revised (Ayers et al., Reference Ayers, Sandier, West and Roosa1996; T1 α = .88, T5 α = .92) and 7-item Coping Efficacy Scale (Sandler et al., Reference Sandler, Tein, Mehta, Wolchik and Ayers2000; T1 α = .71, T5 α = .82). These measures have adequate reliability and validity (e.g., Sandler et al., Reference Sandler, Tein and West1994, Reference Sandler, Tein, Mehta, Wolchik and Ayers2000). The correlation between active coping and coping efficacy was .53 at T1 and .55 at T5, so these measures were standardized and averaged.

Grade point average (GPA)

High school cumulative GPA (unweighted based on 4.0 scale) was obtained for all participants regardless of current school enrollment. GPA has been shown to predict college grades (e.g., Westrick et al., Reference Westrick, Le, Robbins, Radunzel and Schmidt2015) as well as educational attainment and earnings in adulthood (e.g., French et al., Reference French, Homer, Popovici and Robins2015).

Emerging adulthood (T6)

All of the emerging adulthood measures were administered only at T6.

Perceived health problems

Perceived health problems were assessed with a multidimensional latent construct comprised of the following measures: the 12-item Somatization subscale from Symptom Checklist-90R (α = .82; Derogatis & Savitz, Reference Derogatis, Savitz and Maruish1994), which assessed distress arising from perceptions of bodily dysfunction in the last 7 days, and three subscales from the Short Form Health Survey (SF-36; Ware & Sherbourne, Reference Ware and Sherbourne1992): general health perception (6 items; α = .76), limitations in usual role activities because of physical health problems (4 items; α = .80), and bodily pain (2 items; α = .71). These measures have adequate reliability and validity (e.g., Brazier et al., Reference Brazier, Harper, Jones, O’Cathain, Thomas, Usherwood and Westlake1992). A confirmatory factor analysis showed that a one-dimension factor fit the data well [χ2 (df = 2) = .776, CFI = 1.00, root-mean-square error of approximation (RMSEA) = 0]. The latent construct was used in the model. The standardized factor loadings ranged from .52 to .78. Higher scores indicate more perceived health problems.

Body Mass Index (BMI)

During the in-home interviews, weight was measured by trained interviewers using a standard scale and height was measured using a tape measure. BMI was calculated based on weight and height using the standard formula (i.e., weight (kg) / [height (m)]2). BMI in young adulthood has been shown to predict premature mortality later in life (Hirko et al., Reference Hirko, Kantor, Cohen, Blot, Stampfer and Signorello2015; Park et al., Reference Park, Wilkens, Murphy, Monroe, Henderson and Kolonel2012).

Cigarette smoking

Number of days on which cigarettes were smoked in the past 30 days was assessed using the Tobacco subscale from the Youth Risk Behavior Survey (Centers for Disease Control and Prevention, 2008). Higher rates of smoking have been shown to relate wide array of health problems including cancer, stroke, coronary heart disease, and diminished overall health (U.S. Department of Health and Human Services, 2014).

Statistical analysis

This is a secondary data analysis using data from a multi-wave longitudinal study to examine the direct effects of the New Beginnings Program and the cascade mediation processes from the New Beginnings Program on promoting positive parenting in late childhood/early adolescence (T2) to outcomes in late childhood/early adolescence (T3, T4) to outcomes in adolescence (T5) to health-related outcomes in emerging adulthood (T6). We first applied multiple regression to test the overall intervention effects on the health-related outcomes 15 years after the intervention, including whether the intervention effects were modified by pretest risk or offspring gender. We then conducted the mediation models to test the hypothesis that the effects of the New Beginnings Program on posttest (T2) positive parenting would lead to fewer internalizing and externalizing problems three and six months after the intervention (T3 & T4), which would lead to fewer internalizing and externalizing symptoms, less substance use, as well as higher adaptive coping, self-esteem, and GPA six years following the intervention (T5), which in turn, would affect health-related outcomes fifteen years following the intervention (T6). The variables administered at the same assessment point were correlated with each other. We examined each 15-year outcome separately to reduce the number of parameter estimates with the limited sample size. In general, for a model having more than one outcome in a model, the effects on one outcome have little effect on another outcome.

For each post-intervention late childhood/early adolescent, adolescent, and emerging adulthood mediator and outcome measure, we included direct paths from intervention condition to test direct intervention effects as well as pretest risk, and the intervention condition × risk interaction to examine possible moderated intervention effects by risk. In addition, we added the pretest positive parenting × intervention interaction in predicting posttest positive parenting given that Wolchik et al. (Reference Wolchik, West, Sandler, Tein, Coatsworth, Lengua, Weiss, Anderson, Greene and Griffin2000) showed that the program effect on parenting was stronger for families with lower pretest parenting scores. We also included pretest internalizing problems and self-esteem as covariates for all health-related outcomes given that Wolchik et al. (Reference Wolchik, Sandler, Tein, Mahrer, Millsap, Winslow, Vélez, Porter, Luecken and Reed2013) found participants in the 15-year follow-up had higher internalizing problems and lower self-esteem at pretest than non-participants. We controlled for T1 covariates of the same or similar measure if available. For each health-related outcome, we included a proxy variable at T5 as a covariate. We included mother report of the somatic complaints subscale of CBCL (α = .63; Achenbach & Edelbrock, Reference Achenbach and Edelbrock1983) as the covariate for perceived health problems, the overweight item from CBCL as the covariate for BMI, and an item about frequency of smoking cigarettes in the past month from the Monitoring the Future Scale (Bachman et al., Reference Bachman, Johnston and O’Malley1993) as the covariate for smoking. Further, we included offspring gender as a covariate for each mediator and outcome.

The cascade mediation models were tested using structural equation modeling with Mplus 8 (Muthén & Muthén, Reference Muthén and Muthén1998). Full information maximum likelihood method was applied to handle missing data. We examined mediation effects using the bias-corrected bootstrapping method, which has been shown to have good statistical power and excellent control of Type I error rates for 2-path or 3-path mediated effects (MacKinnon et al., Reference MacKinnon, Lockwood, Hoffman, West and Sheets2002; Taylor et al., Reference Taylor, MacKinnon and Tein2008). Power for 4-path mediated effects is smaller than power for 2-path or 3-path mediated effects. If zero were not included in the 90 or 95% confidence interval (CI), it was assumed that the mediated effect was statistically significant.

Results

The correlations among the study variables and their means and standard deviations are included in Table 1.

Table 1. Correlations and descriptive statistics of study variables

Note: Group was coded such that 0=Literature Control and 1=New Beginnings Program.

Direct effects

Multiple regression analyses showed that the main effects of intervention condition (New Beginnings Program vs. LC) on perceived health problems, BMI, and smoking at the 15-year follow-up were not significant. However, there was a significant interaction of condition × gender on BMI (standardized) β = 0.27; b = 3.40, SE = 1.52, z = 2.24, p = .03), which favored females in the intervention program. Post-hoc probing analysis showed that there was a marginally significant improvement on BMI for females (β = −.16; b = −2.02, SE = 1.04, z = 1.94, p = .053; Cohen’s d = .38) but not for males (β = .11; b = 1.38, SE = 1.09, z = 1.27, p = .20).

Cascade effects

Figures 13 show the cascade models for a) perceived health problems, b) BMI, and c) cigarette smoking. The figures present standardized regression coefficients for the paths along the mediation pathway that were significant (i.e., excluding the significant paths from the covariates to the mediators and outcomes). The size of these significant effects, including the interactions, were mostly between small to medium range (M = .28, range = .13–.53; where βsmall = .14, βmedium = .39, and βlarge = .59; Fritz & MacKinnon, Reference Fritz and MacKinnon2007). Omitted from the figures were correlations of the variables administered at the same assessment point. The complete list of the path coefficients is provided in Table 2 in the Supplementary Material. All models fit the data adequately (e.g., comparative fit index (CFI) ≥.95, RMSEA ≤.05; Standardized root-mean-square residual ≤.05; Hu & Bentler, Reference Hu and Bentler1999).

Childhood to adolescent mediators

The parameter estimates of the pathways from intervention condition to posttest and short-term follow-up (i.e., late childhood/early adolescence) variables to 6-year follow-up (i.e., adolescence) variables were mostly consistent across outcomes; the slight differences were due to using maximum likelihood method with models that had different outcome variables.

Figure 1. Cascade effects of adolescent mental health problems, substance use, and competencies on perception of health problems in emerging adulthood.

Figure 2. Cascade effects of adolescent mental health problems, substance use, and competencies on BMI in emerging adulthood.

As expected, the pathways from the New Beginnings Program to positive parenting and internalizing problems and externalizing problems in late childhood/early adolescence and to internalizing and externalizing, substance use, self-esteem, active coping, and GPA in adolescence were consistent with the findings of the pathways in Wolchik et al.’s (Reference Wolchik, Tein, Sandler and Kim2016, Reference Wolchik, Tein, Winslow, Minney, Sandler and Masten2021) studies. Specifically, the New Beginnings Program increased positive parenting at posttest; this increase was greater for families with lower pretest scores. Posttest positive parenting was associated with fewer internalizing problems and externalizing problems at short-term (three- and six-month) follow-up. Internalizing problems and externalizing problems in late childhood/early adolescence were significantly related to internalizing symptoms and externalizing symptoms in adolescence, respectively. In addition, internalizing problems in late childhood/early adolescence were significantly related to lower self-esteem in adolescence and externalizing problems in late childhood/early adolescence were significantly related to higher substance use and lower GPA in adolescence. There were also significant moderated (by pretest risk) intervention effects on internalizing symptoms, externalizing symptoms, substance use, self-esteem, and adaptive coping, and GPA in adolescence. For each moderated effect, the New Beginnings Program had larger effects for those with higher pretest risk.

Adolescent mediators to health-related outcomes in emerging adulthood

Figure 1 presents the cascade mediation model for perceived health problems. Higher internalizing symptoms in adolescence were related to higher perceived health problems (β = 0.26; b = 0.08, SE = 0.03, z = 2.43, p = .02) and higher GPA was associated with lower problems (β = −0.25; b = −0.09, SE = 0.04, z = −2.25, p = .02). After controlling for the covariates and all the mediators in adolescence, positive parenting was positively related to perceived health problems (β = 0.21; b = 0.09, SE = 0.04, z = 2.03, p = .04). Testing the mediation effects showed three significant mediation pathways to perceived health problems in emerging adulthood in the expected direction: 1) intervention to posttest positive parenting to internalizing problems in late childhood/early adolescence to internalizing symptoms in adolescence to perceived health problems ([unstandardized] mediation effect = −0.001, 90% CI = [−0.004, −0.001]), 2) intervention to positive parenting at posttest to externalizing problems in late childhood/early adolescence to GPA in adolescence to perceived health problems (mediation effect = −0.001, 90% CI = [−0.005, −0.001]), and 3) intervention directly to GPA in adolescence to perceived health problems (mediation effect = −.021, 95% CI = [−.064, −.002]) for youth who had high pretest risk scores. The significant mediation effect from intervention to positive parenting at posttest to perceived health problems (mediation effect = .017, 95% CI = [0.001, 0.040]) was in the unexpected direction. Follow-up analyses suggested that this unexpected effect might reflect suppression effects or multicollinearity due to the linear or non-linear correlations of the parenting variable with the other predictors or covariates of perceived health problems. For example, the correlations of posttest positive parenting and the four indicators of perceived health problems were not significant (i.e., r mean = −.005) and the regression coefficient from posttest positive parenting to perceived health problems was not significant in the model that included only posttest positive parenting (β = 0.03) and intervention condition (β = −0.03) as predictors of perceived health problems. Yet, when adding certain sets (e.g., adding all T5 mediators except T5 adaptive coping or except T5 self-esteem) but not other sets (e.g., adding all T5 mediators except T5 GPA or except T5 internalizing problems) of covariates and/or mediators as predictors, beyond posttest positive parenting and intervention condition, the path from posttest positive parenting to perceived health problems became marginal or significant in a positive direction.

Figure 2 presents the cascade mediation model for BMI. Substance use was negatively associated with BMI (β = −0.19; b = −0.69, SE = 0.23, z = −3.06, p = .002). In addition, higher adaptive coping (β = −0.13; b = −0.81, SE = 0.38, z = −2.15, p = .03) and higher GPA (β = −0.27; b = −2.37, SE = 0.65, z = −3.63, p < .001) were significantly associated with lower BMI. There were two significant mediation effects to BMI in emerging adulthood through posttest positive parenting: 1) intervention to positive parenting at posttest to externalizing problems in late childhood/early adolescence to substance use in adolescence to BMI (mediation effect = 0.021, 95% CI = [0.003, 0.075]), and 2) intervention to positive parenting at posttest to externalizing problems in late childhood/early adolescence to GPA in adolescence to BMI (mediation effect = −0.039, 95% CI = [−0.137, −0.010]) and three through direct intervention effects on adolescent mediators for those with high pretest risk scores (i.e., at + 1SD of risk score): 1) intervention to substance use in adolescence to BMI (mediation effect = 0.685, 95% CI = [0.067, 1.838]), 2) intervention to adaptive coping in adolescence to BMI (mediation effect −0.335, 95% CI = [−0.973, −.012]), and 3) intervention to GPA in adolescence to BMI (mediation effect = −1. 079, 95% CI = [−2.329, −0.262]).

Figure 3 presents the cascade mediation model for cigarette smoking. Adolescents with higher externalizing symptoms smoked cigarettes more often (β = 0.20; b = 0.20, SE = 0.10, z = 2.04, p = .04) and adolescents with higher GPA smoked fewer cigarettes (β = −0.24; b = −0.89, SE = 0.30, z = −2.96, p = .003). There were three significant mediation pathways to smoking in emerging adulthood: 1) intervention to positive parenting at posttest to externalizing problems in late childhood/early adolescence to externalizing symptoms in adolescence to smoking (mediation effect = −.011, 95% CI = [−.038, −.001]), 2) intervention to positive parenting at posttest to externalizing problems in late childhood/early adolescence to GPA in adolescence to smoking (mediation effect = −.013, 95% CI = [−.042, −.003]), and 3) intervention directly to GPA in adolescence to smoking (mediation effect = −0.397, 95% CI = [−0.937, −0.093]) for youth who had high pretest risk scores.

Figure 3. Cascade effects of adolescent mental health problems, substance use, and competencies on smoking cigarettes in emerging adulthood.

Discussion

This study expands upon the research that has examined the effects of parenting-focused preventive interventions delivered during late childhood/early adolescence on three understudied health-related outcomes in emerging adulthood: perceived health problems, BMI, and cigarette smoking. Cascade effects of the New Beginnings Program from positive parenting at posttest led to lower internalizing problems and externalizing problems in late childhood/early adolescence, which led to lower levels of internalizing problems, externalizing problems and substance use as well as higher levels of competencies in adolescence. Several adolescent outcomes mediated the effects of intervention-induced improvements in positive parenting on the health-related outcomes. Although the pathways associated with each health-related outcome differed, academic performance predicted all three outcomes. Below, we discuss how these findings relate to those of other research, the unique contributions of the study, its limitations, and directions for future work.

Direct and indirect effects on health-related outcomes

Perceived health problems

To our knowledge, this is the first study to show direct or indirect effects of a parenting-focused program delivered in childhood or adolescence on perceived health problems in emerging adulthood. This finding has important public health implications given findings that measures of perceived health problems similar to the current one have been related to seeking medical care, increased doctor visits, and health-related quality of life (Barsky et al., Reference Barsky, Orav and Bates2005).

The indirect effect of internalizing symptoms in adolescence on perceived health problems in emerging adulthood is consistent with those of studies that found internalizing problems in adolescence predicted perceived health problems, overall poor health, asthma, and diabetes in adolescent and young adult populations (e.g., Bardone et al., Reference Bardone, Moffitt, Caspi, Dickson, Stanton and Silva1998; Hoyt et al., Reference Hoyt, Chase-Lansdale, McDade and Adam2012; Naicker et al., Reference Naicker, Galambos, Zeng, Senthilselvan and Colman2013). GPA was also a significant mediator of the effects of the New Beginnings Program on perceived health problems. This finding is consistent with that of other research that found GPA in adolescence predicted perceived health problems later in development (e.g., Herd, Reference Herd2010; Maggs et al., Reference Maggs, Frome, Eccles and Barber1997).

After the cascade effects of the intervention-induced improvements in parenting were accounted for, the path from positive parenting to perceived health problems was significant in an unexpected direction. In contrast to findings that show a positive relation between positive parenting in adolescence and physical health in young adulthood (e.g., Beach et al., Reference Beach, Lei, Brody, Dogan and Philibert2015; Doom et al., Reference Doom, Gunnar and Clark2016), emerging adults in this study who experienced more positive parenting in childhood/early adolescence reported more health problems. As discussed in the results section, follow-up analyses suggested that this finding may be explained by suppression effects due to certain combinations of T1 covariates and/or predictors. It is also possible the significant effect occurred by chance or was due to unmeasured confounders that were related to both parenting and perceived health problems or other mediators between parenting and perceived health problems that were not included in the study.

BMI

The current findings augment those of two other studies that have shown that parenting-focused prevention programs delivered in early adolescence reduced BMI in emerging adulthood (Brody et al., Reference Brody, Yu, Miller, Ehrlich and Chen2019; Van Ryzin & Nowicka, Reference Van Ryzin and Nowicka2013). It is important to note that, like these two programs, the New Beginnings Program did not include components related to nutrition, physical activity, or physical health.

In their evaluation of the indirect effects of the FCU, Van Ryzin and Nowicka (Reference Van Ryzin and Nowicka2013) found that effects of parent–youth relationship quality on the likelihood of obesity, as measured by BMI, were mediated through maladaptive eating attitudes. In the current study, the effect of the New Beginnings Program on BMI was mediated through an increase in adaptive coping for adolescents in the high-risk group. These findings are consistent with those of an earlier study with this sample that found that adaptive coping in adolescence was inversely related to binge eating in emerging adulthood (Wolchik et al., Reference Wolchik, Tein, Sandler and Kim2016). GPA was also a significant mediator of the effects of the New Beginnings Program to lower BMI for those in the high-risk group.

Substance use was inversely related to BMI for those at high-risk. Previous research has found non-significant associations, positive associations and negative associations between substance use and BMI. It is possible that variability in terms of the assessment of use (e.g., amount, frequency, trajectory of use) and sample (e.g., size, representativeness, age) as well as moderators that have not yet been identified may explain these conflicting results. Additional research is needed to understand the inconsistencies in the findings.

Cigarette smoking

To our knowledge, this is the fourth parenting-focused prevention program delivered in childhood or adolescence to show effects on cigarette smoking in emerging adulthood. The New Beginnings Program had indirect effects on reducing cigarette smoking through GPA and externalizing problems. According to the Center for Disease Control and Prevention (2008), from 2000 to 2004, cigarette smoking and exposure to tobacco smoke resulted in at least 443,000 premature deaths, about 5.1 million years of potential life lost, and $96.8 billion in productivity losses annually in the United States. Given the association between smoking and various diseases (Amiri et al., Reference Amiri, Fathi-Ashtiani, Sedghijalal and Fathi-Ashtiani2021), including rheumatoid arthritis (Di Giuseppe et al., Reference Di Giuseppe, Discacciati, Orsini and Wolk2014), heart failure (Aune et al., Reference Aune, Schlesinger, Norat and Riboli2019), erectile dysfunction (Cao et al., Reference Cao, Yin, Wang, Zhou, Song and Lu2013) and infertility in women (Augood et al., Reference Augood, Duckitt and Templeton1998), widespread implementation of prevention programs that increase academic performance and decrease externalizing problems in adolescence could help to reduce the public health burden of cigarette smoking. Findings of a recent meta-analysis that showed that parental divorce increased smoking in adulthood by 45% (Amiri et al., Reference Amiri, Fathi-Ashtiani, Sedghijalal and Fathi-Ashtiani2021) indicate that the public health benefits for offspring in divorced families participating in these programs could be substantial.

Contributions

This is the third in a series of tests of the cascade effects of the New Beginnings Program, which was delivered in late childhood/early adolescence, on outcomes in emerging adulthood. The other studies focused on the domains of mental health problems and substance use (Wolchik et al., Reference Wolchik, Tein, Sandler and Kim2016) and competence (Wolchik et al., Reference Wolchik, Tein, Winslow, Minney, Sandler and Masten2021). In these studies, strengthening parenting led to improvements in internalizing problems and externalizing problems, which had radiating pathways to multiple outcomes in adolescence, including externalizing problems, internalizing problems, GPA, substance use, adaptive coping and self-esteem, which in turn were linked to multiple mental health, competence, and health-related outcomes in emerging adulthood. For all three domains of functioning assessed in emerging adulthood, lower levels of externalizing problems, higher GPA, and higher levels of adaptive coping in adolescence were significantly, uniquely associated with two or more positive outcomes in emerging adulthood. Further, higher GPA was significantly related to multiple outcomes across domains of functioning; it predicted internalizing problems, externalizing problems, cigarette smoking, perceived health problems and BMI as well as work competence and academic competence in emerging adulthood. These findings highlight the importance of examining the long-term effects of intervention-induced improvements in academic performance in high school on multiple domains of functioning in later stages of development and identifying the mechanisms through which these effects occur. They also indicate that including a focus on increasing school performance in parent-focused prevention programs could lead to reductions in the public health burden of both mental health and physical health problems.

This study extends the large body of cross-sectional and longitudinal research that has identified positive parenting as a key resilience resource (e.g., Masten & Palmer, Reference Masten, Palmer and Bornstein2019; Roisman et al., Reference Roisman, Masten, Coatsworth and Tellegen2004; Sandler et al., Reference Sandler, Ingram, Wolchik, Tein and Winslow2015) by its use of a randomized experimental design that provides a much more rigorous examination of this protective resource by disentangling the effects of positive parenting from variables that are naturally correlated in nonexperimental studies (e.g., maternal personality, shared genes, preexisting economic stress).

This study also contributes to the literature on the long-term effects of prevention programs by examining the direct and indirect effects of the New Beginnings Program on three understudied health-related outcomes in emerging adulthood. In the context of a growing body of studies that have demonstrated long-term effects of parenting-focused programs on a wide range of outcomes not specifically targeted by the programs (Doty et al., Reference Doty, Davis and Arditti2017), these findings highlight the importance of broad assessments of these programs. As Masten (Reference Masten2015) notes, prevention scientists are interested in interventions that will set in motion cascade effects with broad and lasting effects on development that may account for significant return-on-investment. Given the emphasis on containing costs and return-on-investment of prevention programs (National Academies of Sciences, Engineering, and Medicine, 2019; O’Connell et al., Reference O’Connell, Boat and Warner2009) demonstrating positive effects of parenting programs on multiple domains of functioning can provide support for funding such programs.

The findings also further our knowledge about the developmental processes that explain the long-term effects of prevention programs on health-related outcomes. Using a cascade effects model, the current study found that intervention-induced improvements in positive parenting led to a progression of improvements in multiple aspects of children’s and adolescent’s functioning, which led to improvements in three health-related outcomes in emerging adulthood. This model is similar to Smith and his colleagues’ (2018) developmental cascade model for pediatric obesity that includes risk and protective factors over several developmental stages and highlights the role of parental influences and family management practices in escalating or inhibiting the cascading effects.

This study contributes to research on the effects of parental divorce in two ways. To our knowledge, this is only the second study to show that a program for divorced families affected health-related problems. The other study found that a child-focused, school-based intervention reduced visits to the school health office (Pedro-Carroll et al., Reference Pedro-Carroll, Sutton and Wyman1999). Also, these findings extend research on the long-term effects on the New Beginnings Program that has shown direct and indirect program effects on mental health problems and disorders, substance use and disorders, competence, involvement with the criminal justice system, mental health service utilization in emerging adulthood, and attitudes toward parenting (Herman et al., Reference Herman, Mahrer, Wolchik, Porter, Jones and Sandler2015; Wolchik et al., Reference Wolchik, Sandler, Tein, Mahrer, Millsap, Winslow, Vélez, Porter, Luecken and Reed2013, Reference Wolchik, Tein, Sandler and Kim2016, Reference Wolchik, Tein, Winslow, Minney, Sandler and Masten2021).

Limitations and directions for future research

There are several limitations of this study that need to be noted. First, the sample was almost exclusively non-Hispanic White. Second, the families were enrolled in a trial of a preventive intervention for divorced families. Third, at the assessment in adolescence, we did not use the same measure as was used in the assessment in emerging adulthood for two of the three health-related outcomes. Fourth, the sample was relatively modest, which limited the power to detect direct and indirect effects of the program as well as interactive effects.

There are several areas that could advance our understanding of the interplay between positive parenting, competencies, mental health problems, substance use and health-related outcomes over development. First, replicating the current findings with larger, community-based samples that are more diverse would be important. Second, examining cascade effects models of parenting programs for other at-risk groups would be a key step in generalizing our understanding of the long-term effects of these programs. Third, it would be important to examine intrapersonal and interpersonal processes that account for the relations between internalizing problems, externalizing problems, substance use, academic performance, adaptive coping, and self-esteem and subsequent health-related problems. Finally, studies that assess the indirect effects of parenting-focused programs on health-related outcomes in later developmental stages would be valuable.

Summary

The New Beginnings Program, a parenting-focused intervention for divorced parents, led to improvements on three health-related outcomes (BMI, perceived health problems, and cigarette smoking) in emerging adulthood. Improvements in positive parenting in late childhood/early adolescence led to reductions in internalizing problems and externalizing problems in childhood/early adolescence, which led to improvements in several aspects of adolescent functioning, which then led to improvements in health-related outcomes in emerging adulthood. Academic performance in adolescence predicted all three health-related outcomes. These findings underscore the radiating effects of improvements in positive parenting and highlight the importance of examining the developmental cascades that lead to long-term effects of parenting-focused prevention programs.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0954579424000889

Funding statement

Funding for this research was provided by the following grants from the National Institute of Mental Health: 5R01MH071707, 5P30MH068685, and 5P30MH039246 (Trial Registration: clinicaltrials.gov; Identifier: NCT01407120) and National Institute on Drug Abuse (DA09757). C. Aubrey Rhodes’ work on this paper was supported by a T32 fellowship provided by the National Institute on Drug Abuse (AWD30160).The authors thank the mothers and their offspring for their participation; Monique Lopez, Toni Genalo, and Michele McConnaughay for their assistance with data collection; and the interviewers for their commitment to this project. The authors also thank the group leaders and graduate students for their assistance with implementing the program.

References

Achenbach, T. M. (1991). Manual for the child behavior checklist/4-18 and 1991 profile. Dept. of Psychiatry, University of Vermont.Google Scholar
Achenbach, T. M., & Edelbrock, C. (1983). Manual for the child behavior checklist and revised child behavior profile. University of Vermont, Department of Psychiatry.Google Scholar
Alaie, I., Svedberg, P., Ropponen, A., Narusyte, J. (2023). Associations of internalizing and externalizing problems in childhood and adolescence with adult labor market marginalization. JAMA Network Open, 6(6), E2317905e2317905. https://doi.org/10.1001/jamanetworkopen.2023.17905 CrossRefGoogle ScholarPubMed
Alatupa, S., Pulkki-Råback, L., Hintsanen, M., Ravaja, N., Raitakari, O. T., Telama, R., Viikari, J. S. A., & Keltikangas-Järvinen, L. (2010). School performance as a predictor of adulthood obesity: A 21-year follow-up study. European Journal of Epidemiology, 25(4), 267274. https://doi.org/10.1007/s10654-010-9428-6 CrossRefGoogle ScholarPubMed
Amiri, S., Fathi-Ashtiani, M., Sedghijalal, A., & Fathi-Ashtiani, A. (2021). Parental divorce and offspring smoking and alcohol use: A systematic review and meta-analysis of observational studies. Journal of Addictive Diseases, 39(3), 388416. https://doi.org/10.1080/10550887.2021.1886576 CrossRefGoogle ScholarPubMed
Arsandaux, J., Michel, G., Tournier, M., Tzourio, C., Galéra, C. (2019). Is self-esteem associated with self-rated health among French college students? A longitudinal epidemiological study: The i-Share cohort. British Journal of Medicine, 9(6), e024500e024500. https://doi.org/10.1136/bmjopen-2018-024500 Google ScholarPubMed
Augood, C., Duckitt, K., & Templeton, A. A. (1998). Smoking and female infertility: A systematic review and meta-analysis. Human Reproduction, 13(6), 15321539. https://doi.org/10.1093/humrep/13.6.1532 CrossRefGoogle ScholarPubMed
Aune, D., Schlesinger, S., Norat, T., & Riboli, E. (2019). Tobacco smoking and the risk of heart failure: A systematic review and meta-analysis of prospective studies. European Journal of Preventive Cardiology, 26(3), 279288. https://doi.org/10.1177/2047487318806658 CrossRefGoogle ScholarPubMed
Ayers, T. S., Sandier, I. N., West, S. G., & Roosa, M. W. (1996). A dispositional and situational assessment of children’s coping: Testing alternative models of coping. Journal of Personality, 64(4), 923958. https://doi.org/10.1111/j.1467-6494.1996.tb00949.x CrossRefGoogle ScholarPubMed
Bachman, J. M., Johnston, L. D., & O’Malley, P. M. (1993). In: Monitoring the Future: Questionnaire Responses from the Nation’s High School Seniors, Annual Vols., 1975-1992. University of Michigan, Institute for Social Research.Google Scholar
Bardone, A. M., Moffitt, T. E., Caspi, A., Dickson, N., Stanton, W. R., & Silva, P. A. (1998). Adult physical health outcomes of adolescent girls with conduct disorder, depression, and anxiety. Journal of the American Academy of Child & Adolescent Psychiatry, 37(6), 594601. https://doi.org/10.1097/00004583-199806000-00009 CrossRefGoogle ScholarPubMed
Barnes, H. L., & Olson, D. H. (1985). Parent-adolescent communication and the circumplex model. Child Development, 56(2), 438. https://doi.org/10.2307/1129732 CrossRefGoogle Scholar
Barnes, H. L., & Olson, D. L. (1982). Parent-adolescent communication scale. In Olson, D.H., et al. (Eds.), Family inventories: Inventories used in a national survey of families across the family life cycle (pp. 33, 48). St. Paul: Family Social Science, University of Minnesota.Google Scholar
Barsky, A. J., Orav, E. J., & Bates, D. W. (2005). Somatization increases medical utilization and costs independent of psychiatric and medical comorbidity. Archives of General Psychiatry, 62(8), 903. https://doi.org/10.1001/archpsyc.62.8.903 CrossRefGoogle ScholarPubMed
Beach, S. R. H., Lei, M. K., Brody, G. H., Dogan, M. V., & Philibert, R. A. (2015). Higher levels of protective parenting are associated with better young adult health: Exploration of mediation through epigenetic influences on pro-inflammatory processes. Frontiers in Psychology, 6. https://doi.org/10.3389/fpsyg.2015.00676 CrossRefGoogle ScholarPubMed
Boden, J. M., Fergusson, D. M., & Horwood, L. J. (2008). Does adolescent self-esteem predict later life outcomes? A test of the causal role of self-esteem. Development and Psychopathology, 20(1), 319339. https://doi.org/10.1017/S0954579408000151 CrossRefGoogle ScholarPubMed
Brazier, J. E., Harper, R., Jones, N. M., O’Cathain, A., Thomas, K. J., Usherwood, T., & Westlake, L. (1992). Validating the SF-36 health survey questionnaire: New outcome measure for primary care. British Journal of Medicine, 305(6846), 160164. https://doi.org/10.1136/bmj.305.6846.160 CrossRefGoogle ScholarPubMed
Brody, Chen, Kogan, Y.-F., S., M., Murry, V. M., & Brown, A. C. (2010). Long-term effects of the strong African American families program on youths’ alcohol use. Journal of Consulting and Clinical Psychology, 78(2), 281285. https://doi.org/10.1037/a0018552 CrossRefGoogle ScholarPubMed
Brody, G. H., Yu, T., Miller, G. E., Ehrlich, K. B., & Chen, E. (2019). Preventive parenting intervention during childhood and young black adults’ unhealthful behaviors: A randomized controlled trial. Journal of Child Psychology and Psychiatry, 60(1), 6371. https://doi.org/10.1111/jcpp.12968 CrossRefGoogle Scholar
Brotman, L. M., Dawson-McClure, S., Huang, K.-Y., Theise, R., Kamboukos, D., Wang, J., Petkova, E., & Ogedegbe, G. (2012). Early childhood family intervention and long-term obesity prevention among high-risk minority youth. Pediatrics, 129(3), e621e628. https://doi.org/10.1542/peds.2011-1568 CrossRefGoogle ScholarPubMed
Cao, S., Yin, X., Wang, Y., Zhou, H., Song, F., & Lu, Z. (2013). Smoking and risk of erectile dysfunction: Systematic review of observational studies with meta-analysis. PLoS ONE, 8(4), e60443. https://doi.org/10.1371/journal.pone.0060443 CrossRefGoogle ScholarPubMed
Capaldi, D. M. (1991). Co-occurrence of conduct problems and depressive symptoms in early adolescent boys: I. Familial factors and general adjustment at Grade 6. Development and Psychopathology, 3(3), 277300. https://doi.org/10.1017/S0954579400005319 CrossRefGoogle Scholar
Capaldi, D. M., Tiberio, S. S., Kerr, D. C., & Owen, L. D. (2022). Associations of cannabis use across adolescence and early adulthood with health and psychosocial adjustment in early adulthood and Midadulthood in men. Substance Abuse: Research and Treatment, 16, 117822182210961. https://doi.org/10.1177/11782218221096154 Google ScholarPubMed
Carvajal, S. C., Granillo, T. M. (2006). A prospective test of distal and proximal determinants of smoking initiation in early adolescents. Addictive Behaviors, 31(4), 649660. https://doi.org/10.1016/j.addbeh.2005.05.047 CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention (CDC) (2008). Smoking-attributable mortality, years of potential life lost, and productivity losses—United States, 2000-2004. MMWR. Morbidity and Mortality Weekly Report, 57(45), 12261228.Google Scholar
Cheng, H. L., Medlow, S., & Steinbeck, K. (2016). The health consequences of obesity in young adulthood. Current Obesity Reports, 5(1), 3037. https://doi.org/10.1007/s13679-016-0190-2 CrossRefGoogle ScholarPubMed
Cicchetti, D., & Schneider-Rosen, K. (1986). An organizational approach to childhood depression. In Rutter, M., Izard, C. E., & Read, P. B. (Eds.), Depression in young people: Developmental and clinical perspectives (pp. 71134). Guilford Press.Google Scholar
Cicchetti, D. & Sroufe, L. (2000). Editorial: The past as prologue to the future: The times, they’ve been a-changin. Development and Psychopathology, 12(3), 255264. https://doi.org/10.1017/S0954579400003011 CrossRefGoogle Scholar
Clausen, J. S. (1991). Adolescent competence and the shaping of the life course. American Journal of Sociology, 96(4), 805842. https://doi.org/10.1086/229609 CrossRefGoogle Scholar
Coffey, C., Patton, G. C. (2016). Cannabis use in adolescence and young adulthood: A review of findings from the victorian adolescent health cohort study. Canadian Journal of Psychiatry, 61(6), 318327. https://doi.org/10.1177/0706743716645289 CrossRefGoogle Scholar
Cohen, J. M., Taborga, M., Dawson, S., & Wolchik, S. (2000). Do family routines buffer the effects of stressful divorce events on children’s symptomatology? [Presentation]. The Society for Prevention Research.Google Scholar
Cole, D. A., & Maxwell, S. E. (2003). Testing mediational models with longitudinal data: Questions and tips in the use of structural equation modeling. Journal of Abnormal Psychology, 112(4), 558577. https://doi.org/10.1037/0021-843X.112.4.558 CrossRefGoogle ScholarPubMed
Crane, N. A., Langenecker, S. A., & Mermelstein, R. J. (2021). Risk factors for alcohol, marijuana, and cigarette polysubstance use during adolescence and young adulthood: A 7-year longitudinal study of youth at high risk for smoking escalation. Addictive Behaviors, 119, 106944. https://doi.org/10.1016/j.addbeh.2021.106944 CrossRefGoogle Scholar
Dawson-McClure, S. R., Sandler, I. N., Wolchik, S. A., & Millsap, R. E. (2004). Risk as a moderator of the effects of prevention programs for children from divorced families: A six-year longitudinal study. Journal of Abnormal Child Psychology, 32(2), 175190. https://doi.org/10.1023/B:JACP.0000019769.75578.79 CrossRefGoogle ScholarPubMed
DeGarmo, E., J., M., Reid, J. B., & Fetrow, R. A. (2009). Evaluating mediators of the impact of the Linking the Interests of Families and Teachers (LIFT) multimodal preventive intervention on substance use initiation and growth across adolescence. Prevention Science, 10(3), 208220. https://doi.org/10.1007/s11121-009-0126-0 CrossRefGoogle ScholarPubMed
Demo, D. H., Small, S. A., & Savin-Williams, R. C. (1987). Family relations and the self-esteem of adolescents and their parents. Journal of Marriage and the Family, 49(4), 705. https://doi.org/10.2307/351965 CrossRefGoogle Scholar
Derogatis, L., & Savitz, K. (1994). SCL-90—R, Brief Symptom Inventory, and matching clinical rating scales. In Maruish, M.E. The use of psychological testing for treatment planning and outcomes assessment (pp. 217248). Lawrence Erlbaum Associates Publishers.Google Scholar
Di Giuseppe, eD., Discacciati, A., Orsini, N., & Wolk, A. (2014). Cigarette smoking and risk of rheumatoid arthritis: A dose-response meta-analysis. Arthritis Research & Therapy, 16(2), R61R61. https://doi.org/10.1186/ar4498 CrossRefGoogle ScholarPubMed
Dierker, L., Hedeker, D., Rose, J., Selya, A., Mermelstein, R. (2015). Early emerging nicotine dependence symptoms in adolescence predict daily smoking in young adulthood. Drug and Alcohol Dependence, 151, 267271. https://doi.org/10.1016/j.drugalcdep.2015.03.009 CrossRefGoogle ScholarPubMed
Donovan, J. E., Jessor, R., & Costa, F. M. (1988). Syndrome of problem behavior in adolescence: A replication. Journal of Consulting and Clinical Psychology, 56(5), 762765. https://doi.org/10.1037/0022-006X.56.5.762 CrossRefGoogle ScholarPubMed
Doom, J. R., Gunnar, M. R., & Clark, C. J. (2016). Maternal relationship during adolescence predicts cardiovascular disease risk in adulthood. Health Psychology, 35(4), 376386. https://doi.org/10.1037/hea0000285 CrossRefGoogle ScholarPubMed
Doty, J. L., Davis, L., & Arditti, J. A. (2017). Cascading resilience: Leverage points in promoting parent and child well-being: Cascading resilience. Journal of Family Theory & Review, 9(1), 111126. https://doi.org/10.1111/jftr.12175 CrossRefGoogle Scholar
Drewnowski, A. (2010). The Nutrient Rich Foods Index helps to identify healthy, affordable foods. The American Journal of Clinical Nutrition, 91(4), 1095S1101S. https://doi.org/10.3945/ajcn.2010.28450D CrossRefGoogle ScholarPubMed
Ellickson, P. L., Martino, S. C., Collins, R. L. (2004). Marijuana use from adolescence to young adulthood: Multiple developmental trajectories and their associated outcomes. Health Psychology, 23(3), 299307. https://doi.org/10.1037/0278-6133.23.3.299 CrossRefGoogle ScholarPubMed
Fergusson, D. M., Horwood, L. J., Boden, J. M., & Jenkin, G. (2007). Childhood social disadvantage and smoking in adulthood: Results of a 25-year longitudinal study. Addiction, 102(3), 475482. https://doi.org/10.1111/j.1360-0443.2006.01729.x CrossRefGoogle ScholarPubMed
Fogas, B. S., Wolchik, S. A., & Braver, S. L. (1987). Parenting behavior and psychopathology in children of divorce: Buffering effects. In The 95th Annual Convention of the American Psychological Association, New York.Google Scholar
Font, S. A., & Maguire-Jack, K. (2016). Pathways from childhood abuse and other adversities to adult health risks: The role of adult socioeconomic conditions. Child Abuse & Neglect, 51, 390399. https://doi.org/10.1016/j.chiabu.2015.05.013 CrossRefGoogle ScholarPubMed
French, M. T., Homer, J. F., Popovici, I., & Robins, P. K. (2015). What you do in high school matters: High school GPA, educational attainment, and labor market earnings as a young adult. Eastern Economic Journal, 41(3), 370386. https://doi.org/10.1057/eej.2014.22 CrossRefGoogle Scholar
French, M. T., Popovici, I., Maclean, J. C. (2009). Do alcohol consumers exercise more? Findings from a national survey. American Journal of Health Promotion, 24(1), 210. https://doi.org/10.4278/ajhp.0801104 CrossRefGoogle ScholarPubMed
French, M. T., Zavala, S. K. (2007). The health benefits of moderate drinking revisited: Alcohol use and self-reported health status. American Journal of Health Promotion, 21(6), 484491. https://doi.org/10.4278/0890-1171-21.6.484 CrossRefGoogle ScholarPubMed
Fritz, M. S., MacKinnon, D. P. (2007). Required sample size to detect the mediated effect. Psychological Science, 18(3), 233239. https://doi.org/10.1111/j.1467-9280.2007.01882.x CrossRefGoogle ScholarPubMed
Guo, Y., Yue, X., Li, H., Song, Z., Yan, H., Zhang, P., Gui, Y., Chang, L., & Li, T. (2016). Overweight and obesity in young adulthood and the risk of stroke: A meta-analysis. Journal of Stroke and Cerebrovascular Diseases, 25(12), 29953004. https://doi.org/10.1016/j.jstrokecerebrovasdis.2016.08.018 CrossRefGoogle ScholarPubMed
Harter, S. (1985). Manual for the self-perception profile for children: (revision of the perceived competence scale for children). University of Denver.Google Scholar
Hasler, Pine, D., S., Kleinbaum, D. G., Gamma, A., Luckenbaugh, D., Ajdacic, V., Eich, D., Rössler, W., & Angst, J. (2005). Depressive symptoms during childhood and adult obesity: The Zurich Cohort Study. Molecular Psychiatry, 10(9), 842850. https://doi.org/10.1038/sj.mp.4001671 CrossRefGoogle ScholarPubMed
Herd, P. (2010). Education and health in late-life among high school graduates: Cognitive versus psychological aspects of human capital. Journal of Health and Social Behavior, 51(4), 478496. https://doi.org/10.1177/0022146510386796 CrossRefGoogle ScholarPubMed
Herman, P. M., Mahrer, N. E., Wolchik, S. A., Porter, M. M., Jones, S., & Sandler, I. N. (2015). Cost-benefit analysis of a preventive intervention for divorced families: Reduction in mental health and justice system service use costs 15 years later. Prevention Science, 16(4), 586596. https://doi.org/10.1007/s11121-014-0527-6 CrossRefGoogle ScholarPubMed
Herren, O. M., Agurs-Collins, T., Dwyer, L. A., Perna, F. M., Ferrer, R. (2021). Emotion suppression, coping strategies, dietary patterns, and BMI. Eating Behaviors: An International Journal, 41, 101500. https://doi.org/10.1016/j.eatbeh.2021.101500 CrossRefGoogle ScholarPubMed
Hirko, K. A., Kantor, E. D., Cohen, S. S., Blot, W. J., Stampfer, M. J., & Signorello, L. B. (2015). Body mass index in young adulthood, obesity trajectory, and premature mortality. American Journal of Epidemiology, 182(5), 441450. https://doi.org/10.1093/aje/kwv084 CrossRefGoogle ScholarPubMed
Hitlin, S., & Kirkpatrick Johnson, M. (2015). Reconceptualizing agency within the life course: The power of looking ahead. American Journal of Sociology, 120(5), 14291472. https://doi.org/10.1086/681216 CrossRefGoogle ScholarPubMed
Hoyt, L. T., Chase-Lansdale, P. L., McDade, T. W., & Adam, E. K. (2012). Positive youth, healthy adults: Does positive well-being in adolescence predict better perceived health and fewer risky health behaviors in young adulthood? Journal of Adolescent Health, 50(1), 6673. https://doi.org/10.1016/j.jadohealth.2011.05.002 CrossRefGoogle ScholarPubMed
Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 155. https://doi.org/10.1080/10705519909540118 CrossRefGoogle Scholar
Huang, C., Momma, H., Cui, Y., Chujo, M., Otomo, A., Sugiyama, S., Ren, Z., Niu, K., Nagatomi, R. (2017). Independent and combined relationship of habitual unhealthy eating behaviors with depressive symptoms: A prospective study. Journal of Epidemiology, 27(1), 4247. https://doi.org/10.1016/j.je.2016.08.005 CrossRefGoogle ScholarPubMed
Huang, D. Y. C., Lanza, H. I., & Anglin, M. D. (2013). Association between adolescent substance use and obesity in young adulthood: A group-based dual trajectory analysis. Addictive Behaviors, 38(11), 26532660. https://doi.org/10.1016/j.addbeh.2013.06.024 CrossRefGoogle ScholarPubMed
Jääskeläinen, A., Nevanperä, N., Remes, J., Rahkonen, F., Järvelin, M.-R., Laitinen, J. (2014). Stress-related eating, obesity and associated behavioural traits in adolescents: A prospective population-based cohort study. BMC Public Health, 14(1), 321321. https://doi.org/10.1186/1471-2458-14-321 CrossRefGoogle ScholarPubMed
Jafflin, K., Pfeiffer, C., Bergman, M. M. (2019). Effects of self-esteem and stress on self-assessed health: A Swiss study from adolescence to early adulthood. Quality of Life Research, 28(4), 915924. https://doi.org/10.1007/s11136-018-2059-1 CrossRefGoogle Scholar
Jamner, L. D., Shapiro, D., & Jarvik, M. E. (1999). Nicotine reduces the frequency of anger reports in smokers and nonsmokers with high but not low hostility: An ambulatory study. Experimental and Clinical Psychopharmacology, 7(4), 454463. https://doi.org/10.1037/1064-1297.7.4.454 CrossRefGoogle Scholar
Jensen, E. W., James, S. A., Boyce, W. T., & Hartnett, S. A. (1983). The family routines inventory: Development and validation. Social Science & Medicine, 17(4), 201211. https://doi.org/10.1016/0277-9536(83)90117-X CrossRefGoogle ScholarPubMed
Jessor, R., & Jessor, S. L. (1977). Problem behavior and psychosocial development: A longitudinal study of youth. Academic Press.Google Scholar
Jester, J. M., Glass, J. M., Bohnert, K. M., Nigg, J. T., Wong, M. M., & Zucker, R. A. (2019). Child and adolescent predictors of smoking involvement in emerging adulthood. Health Psychology, 38(2), 133142. https://doi.org/10.1037/hea0000703 CrossRefGoogle ScholarPubMed
Kaplan, H. B., Johnson, R. J., Bailey, C. A. (1987). Deviant peers and deviant behavior: Further elaboration of a model. Social Psychology Quarterly, 50(3), 277284. https://doi.org/10.2307/2786829 CrossRefGoogle Scholar
Keenan-Miller, D., Hammen, C. L., & Brennan, P. A. (2007). Health outcomes related to early adolescent depression. Journal of Adolescent Health, 41(3), 256262. https://doi.org/10.1016/j.jadohealth.2007.03.015 CrossRefGoogle ScholarPubMed
Khantzian, E. J. (1997). The self-medication hypothesis of substance use disorders: A reconsideration and recent applications. Harvard Review of Psychiatry, 4(5), 231244. https://doi.org/10.3109/10673229709030550 CrossRefGoogle ScholarPubMed
Kliewer, W., Sandler, I. N. (1992). Locus of control and self-esteem as moderators of stressor-symptom relations in children and adolescents. Journal of Abnormal Child Psychology, 20(4), 393413. https://doi.org/10.1007/BF00918984 CrossRefGoogle ScholarPubMed
Kovacs, M. (1981). Rating scales to assess depression in school-aged children. Cta Paedopsychiatrica: International Journal of Child & Adolescent Psychiatry, 46(5-6), 305315.Google ScholarPubMed
Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002). Mediators and moderators of treatment effects in randomized clinical trials. Archives of General Psychiatry, 59(10), 877883. https://doi.org/10.1001/archpsyc.59.10.877 CrossRefGoogle ScholarPubMed
Kyler, K. E., Hall, M., Halvorson, E. E., & Davis, A. M. (2021). Associations between obesity and adverse childhood experiences in the United States. Childhood Obesity, 17(5), 342348. https://doi.org/10.1089/chi.2020.0261 CrossRefGoogle ScholarPubMed
Lacey, R. E., Kumari, M., & McMunn, A. (2013). Parental separation in childhood and adult inflammation: The importance of material and psychosocial pathways. Psychoneuroendocrinology, 38(11), 24762484. https://doi.org/10.1016/j.psyneuen.2013.05.007 CrossRefGoogle ScholarPubMed
Lanier, P., Dunnigan, A., & Kohl, P. L. (2018). Impact of Pathways Triple P on pediatric health-related quality of life in maltreated children. Journal of Developmental & Behavioral Pediatrics, 39(9), 701708. https://doi.org/10.1097/DBP.0000000000000608 CrossRefGoogle ScholarPubMed
Larson, K., & Halfon, N. (2013). Parental divorce and adult longevity. International Journal of Public Health, 58(1), 8997. https://doi.org/10.1007/s00038-012-0373-x CrossRefGoogle ScholarPubMed
Lo (2002). A longitudinal study of perceived level of stress, coping and self-esteem of undergraduate nursing students: An Australian case study. Journal of Advanced Nursing, 39(2), 119126. https://doi.org/10.1046/j.1365-2648.2000.02251.x CrossRefGoogle Scholar
MacKinnon, D. P., Lockwood, C. M., Hoffman, J. M., West, S. G., & Sheets, V. (2002). A comparison of methods to test mediation and other intervening variable effects. Psychological Methods, 7(1), 83104. https://doi.org/10.1037/1082-989X.7.1.83 CrossRefGoogle ScholarPubMed
Maggs, J. L., Frome, P. M., Eccles, J. S., & Barber, B. L. (1997). Psychosocial resources, adolescent risk behavior and young adult adjustment: Is risk taking more dangerous for some than others? Journal of Adolescence, 20(1), 103119. https://doi.org/10.1006/jado.1996.0067 CrossRefGoogle Scholar
Maier, E. H., & Lachman, M. E. (2000). Consequences of early parental loss and separation for health and well-being in midlife. International Journal of Behavioral Development, 24(2), 183189. https://doi.org/10.1080/016502500383304 CrossRefGoogle Scholar
Martyn‐Nemeth, P., Penckofer, S., Gulanick, M., Velsor‐Friedrich, B., & Bryant, F. B. (2009). The relationships among self‐esteem, stress, coping, eating behavior, and depressive mood in adolescents. Research in Nursing & Health, 32(1), 96109. https://doi.org/10.1002/nur.20304 CrossRefGoogle ScholarPubMed
Masten, A. S. (2015). Pathways to integrated resilience science. Psychological Inquiry, 26(2), 187196. https://doi.org/10.1080/1047840X.2015.1012041 CrossRefGoogle Scholar
Masten, A. S., Burt, K. B., & Coatsworth, J. D. (2015). Competence and psychopathology in development. In Cicchetti, D., & Cohen, D. J. (Eds.), Developmental psychopathology (pp. 696738). John Wiley & Sons, Inc. https://doi.org/10.1002/9780470939406.ch19 CrossRefGoogle Scholar
Masten, A. S., Cicchetti, D. (2010). Developmental cascades. Development and Psychopathology, 22(3), 491495. https://doi.org/10.1017/S0954579410000222 CrossRefGoogle ScholarPubMed
Masten, A. S., & Cicchetti, D. (2016). Resilience in development: Progress and transformation. In Cicchetti, D. (Eds.), Developmental psychopathology (pp. 163). John Wiley & Sons, Inc. https://doi.org/10.1002/9781119125556.devpsy406 Google Scholar
Masten, A. S., & Palmer, A. R. (2019). Parenting to promote resilience in children. In Bornstein, M. H. (Eds.), Handbook of parenting (3rd ed. pp. 156188). Routledge. https://doi.org/10.4324/9780429401695-6 CrossRefGoogle Scholar
McClernon, F. J., & Kollins, S. H. (2008). ADHD and smoking. Annals of the New York Academy of Sciences, 1141(1), 131147. https://doi.org/10.1196/annals.1441.016 CrossRefGoogle ScholarPubMed
McKenzie, M., Olsson, C. A., Jorm, A. F., Romaniuk, H., Patton, G. C. (2010). Association of adolescent symptoms of depression and anxiety with daily smoking and nicotine dependence in young adulthood: Findings from a 10-year longitudinal study. Addiction (Abingdon, England), 105(9), 16521659. https://doi.org/10.1111/j.1360-0443.2010.03002.x CrossRefGoogle ScholarPubMed
Meier, M. H., Schriber, R. A., Beardslee, J., Hanson, J., & Pardini, D. (2019). Associations between adolescent cannabis use frequency and adult brain structure: A prospective study of boys followed to adulthood. Drug and Alcohol Dependence, 202, 191199. https://doi.org/10.1016/j.drugalcdep.2019.05.012 CrossRefGoogle ScholarPubMed
Mirowsky, J., Ross, C. E. (2005). Education, learned effectiveness and health. London Review of Education, 3(3), 205220. https://doi.org/10.1080/14748460500372366 CrossRefGoogle Scholar
Mirowsky, J., & Ross, C. E. (2007). Life course trajectories of perceived control and their relationship to education. American Journal of Sociology, 112(5), 13391382. https://doi.org/10.1086/511800 CrossRefGoogle Scholar
Monnat, S. M., & Chandler, R. F. (2015). Long-term physical health consequences of adverse childhood experiences. The Sociological Quarterly, 56(4), 723752. https://doi.org/10.1111/tsq.12107 CrossRefGoogle ScholarPubMed
Muris, P., Meesters, C., & Fijen, P. (2003). The Self-Perception Profile for Children: Further evidence for its factor structure, reliability, and validity. Personality and Individual Differences, 35(8), 17911802. https://doi.org/10.1016/S0191-8869(03)00004-7 CrossRefGoogle Scholar
Murry, B., Brody, C., G., H., Gibbons, M., & Gibbons, F. X. (2007). The strong African American families program: Longitudinal pathways to sexual risk reduction. Journal of Adolescent Health, 41(4), 333342. https://doi.org/10.1016/j.jadohealth.2007.04.003 CrossRefGoogle ScholarPubMed
Muthén, L. K., & Muthén, B. O. (1998). Mplus user’s guide (8th edn.). Muthén & Muthén.Google Scholar
Naicker, K., Galambos, N. L., Zeng, Y., Senthilselvan, A., & Colman, I. (2013). Social, demographic, and health outcomes in the 10 years following adolescent depression. Journal of Adolescent Health, 52(5), 533538. https://doi.org/10.1016/j.jadohealth.2012.12.016 CrossRefGoogle ScholarPubMed
National Academies of Sciences, Engineering, and Medicine (NASEM) (2019). Fostering healthy mental, emotional, and behavioral health in children and youth: A national agenda. The National Academies Press. https://doi.org/10.17226/25201 Google Scholar
O’Connell, M. E., Boat, F., & Warner, K. E. (2009). Preventing mental, emotional, and behavioral disorders among young people progress and possibilities. National Academies Press.Google Scholar
O’Connor, D. B., & Conner, M. (2011). Effects of stress on eating behavior. In The handbook of stress science: Biology, psychology, and health (pp. 275286). Springer Publishing Company.Google Scholar
O’Connor, D. B., Conner, M., Jones, F., McMillan, B., & Ferguson, E. (2009). Exploring the benefits of conscientiousness: An investigation of the role of daily stressors and health behaviors. Annals of Behavioral Medicine, 37(2), 184196. https://doi.org/10.1007/s12160-009-9087-6 CrossRefGoogle ScholarPubMed
O’Connor, T. G., Davies, L., Dunn, J., Golding, J., the ALSPAC Study Team (2000). Distribution of accidents, injuries, and illnesses by family type. Pediatrics, 106(5), e68e68. https://doi.org/10.1542/peds.106.5.e68 CrossRefGoogle ScholarPubMed
Oesterle, S., Hill, K. G., Hawkins, J. D., Guo, J., Catalano, R. F., & Abbott, R. D. (2004). Adolescent heavy episodic drinking trajectories and health in young adulthood. Journal of Studies on Alcohol, 65(2), 204212. https://doi.org/10.15288/jsa.2004.65.204 CrossRefGoogle ScholarPubMed
Oregon Social Learning Center 1991). LIFT parent interview. Unpublished manual.Google Scholar
Paavola, M., Vartiainen, E., Haukkala, A. (2004). Smoking, alcohol use, and physical activity: A 13-year longitudinal study ranging from adolescence into adulthood. Journal of Adolescent Health, 35(3), 238244. https://doi.org/10.1016/j.jadohealth.2003.12.004 CrossRefGoogle ScholarPubMed
Pajari, M., Pietilainen, K. H., Kaprio, J., Rose, R. J., & Saarni, S. E. (2010). The effect of alcohol consumption on later obesity in early adulthood—A population-based longitudinal study. Alcohol and Alcoholism, 45(2), 173179. https://doi.org/10.1093/alcalc/agp090 CrossRefGoogle ScholarPubMed
Park, C. L., Adler, N. E. (2003). Coping style as a predictor of health and well-being across the first year of medical school. Health Psychology, 22(6), 627631. https://doi.org/10.1037/0278-6133.22.6.627 CrossRefGoogle ScholarPubMed
Park, J. (2003). Adolescent self-concept and health into adulthood. Health Reports, 14(Supp), 4152.Google ScholarPubMed
Park, S.-Y., Wilkens, L. R., Murphy, S. P., Monroe, K. R., Henderson, B. E., & Kolonel, L. N. (2012). Body mass index and mortality in an ethnically diverse population: The Multiethnic Cohort Study. European Journal of Epidemiology, 27(7), 489497. https://doi.org/10.1007/s10654-012-9695-5 CrossRefGoogle Scholar
Pasch, K. E., Velazquez, C. E., Cance, J. D., Moe, S. G., Lytle, L. A. (2012). Youth substance use and body composition: Does risk in one area predict risk in the other? Journal of Youth and Adolescence, 41(1), 1426. https://doi.org/10.1007/s10964-011-9706-y CrossRefGoogle ScholarPubMed
Patton, G. C., Carlin, J. B., Coffey, C., Wolfe, R., Hibbert, M., Bowes, G. (1998). Depression, anxiety, and smoking initiation: A prospective study over 3 years. American Journal of Public Health, 88(10), 15181522. https://doi.org/10.2105/AJPH.88.10.1518 1971.CrossRefGoogle ScholarPubMed
Patton, G. C., Coffey, C., Carlin, J. B., Sawyer, S. M., Lynskey, M. (2005). Reverse gateways? Frequent cannabis use as a predictor of tobacco initiation and nicotine dependence. Addiction (Abingdon, England), 100(10), 15181525. https://doi.org/10.1111/j.1360-0443.2005.01220.x CrossRefGoogle ScholarPubMed
Pedro-Carroll, J. L., Sutton, S. E., & Wyman, P. A. (1999). A two-year follow-up evaluation of a preventive intervention for young children of divorce. School Psychology Review, 28(3), 467476. https://doi.org/10.1080/02796015.1999.12085978 CrossRefGoogle Scholar
Ramadhani, N., Mahmudiono, T. (2021). Academic stress is associated with emotion eating behavior among adolescent. Media Gizi Indonesia (Online), 16(1), 3847. https://doi.org/10.20473/mgi.v16i1.38-47 CrossRefGoogle Scholar
Reynolds, C. R., & Paget, K. D. (1981). Factor analysis of the revised children’s manifest anxiety scale for Blacks, Whites, males, and females with a national normative sample. Journal of Consulting and Clinical Psychology, 49(3), 352359. https://doi.org/10.1037/0022-006X.49.3.352 CrossRefGoogle ScholarPubMed
Reynolds, C. R., & Richmond, B. O. (1978). What i think and feel: A revised measure of children’s manifest anxiety. Journal of Abnormal Child Psychology, 6(2), 271280. https://doi.org/10.1007/BF00919131 CrossRefGoogle Scholar
Riala, K., Hakko, , Isohanni, M., Järvelin, M.-R., Räsänen, P. (2004). Teenage smoking and substance use as predictors of severe alcohol problems in late adolescence and in young adulthood. Journal of Adolescent Health, 35(3), 245254. https://doi.org/10.1016/j.jadohealth.2003.08.016 CrossRefGoogle ScholarPubMed
Roberts, R. E., Duong, H. T. (2013). Obese youths are not more likely to become depressed, but depressed youths are more likely to become obese. Psychological Medicine, 43(10), 21432151. https://doi.org/10.1017/S0033291712002991 CrossRefGoogle Scholar
Roisman, G. I., Masten, A. S., Coatsworth, J. D., & Tellegen, A. (2004). Salient and emerging developmental tasks in the transition to adulthood. Child Development, 75(1), 123133. https://doi.org/10.1111/j.1467-8624.2004.00658.x CrossRefGoogle ScholarPubMed
Roshanaei-Moghaddam, B., Katon, W. J., Russo, J. (2009). The longitudinal effects of depression on physical activity. General Hospital Psychiatry, 31(4), 306315. https://doi.org/10.1016/j.genhosppsych.2009.04.002 CrossRefGoogle ScholarPubMed
Ross, C. E., Wu, C.-L. (1996). Education, age, and the cumulative advantage in health. Journal of Health and Social Behavior, 37(1), 104120. https://doi.org/10.2307/2137234 CrossRefGoogle ScholarPubMed
Rozeboom 1969). Statistical theories of mental test scores [Review of statistical theories of mental test scores]. American Educational Research Journal, 6(1), 112116. https://doi.org/10.2307/1162101 CrossRefGoogle Scholar
Rutter, M., & Sroufe, L. A. (2000). Developmental psychopathology: Concepts and challenges. Development and Psychopathology, 12(3), 265296. https://doi.org/10.1017/S0954579400003023 CrossRefGoogle ScholarPubMed
Sameroff, A. J. (1975). Early influences on development: Fact or fancy? Merrill-Palmer Quarterly of Behavior and Development, 21, 267294. https://doi.org/10.2307/23083878 Google Scholar
Sameroff, A. J. (2000). Developmental systems and psychopathology. Development and Psychopathology, 12(3), 297312. https://doi.org/10.1017/S0954579400003035 CrossRefGoogle ScholarPubMed
Sandler, I., Gunn, H., Mazza, G., Tein, J.-Y., Wolchik, S., Kim, H., Ayers, T., & Porter, M. (2018). Three perspectives on mental health problems of young adults and their parents at a 15-year follow-up of the family bereavement program. Journal of Consulting and Clinical Psychology, 86(10), 845855. https://doi.org/10.1037/ccp0000327 CrossRefGoogle Scholar
Sandler, I., Ingram, A., Wolchik, S., Tein, J.-Y., & Winslow, E. (2015). Long-term effects of parenting-focused preventive interventions to promote resilience of children and adolescents. Child Development Perspectives, 9(3), 164171. https://doi.org/10.1111/cdep.12126 CrossRefGoogle ScholarPubMed
Sandler, I., Yun-Tien, J., Zhang, N., Wolchik, S., & Thieleman, K. (2021). Grief as a predictor of long-term risk for suicidal ideation and attempts of parentally bereaved children and adolescents. Journal of Traumatic Stress, 34(6), 11591170. https://doi.org/10.1002/jts.22759 CrossRefGoogle ScholarPubMed
Sandler, I. N., Tein, J.-Y., Mehta, P., Wolchik, S., & Ayers, T. (2000). Coping efficacy and psychological problems of children of divorce. Child Development, 71(4), 10991118. https://doi.org/10.1111/1467-8624.00212 CrossRefGoogle ScholarPubMed
Sandler, I. N., Tein, J.-Y., & West, S. G. (1994). Coping, stress, and the psychological symptoms of children of divorce: A cross-sectional and longitudinal study. Child Development, 65(6), 1744. https://doi.org/10.2307/1131291 CrossRefGoogle ScholarPubMed
Saylor, C. F., Finch, A. J., Spirito, A., & Bennett, B. (1984). The Children’s Depression Inventory: A systematic evaluation of psychometric properties. Journal of Consulting and Clinical Psychology, 52(6), 955967. https://doi.org/10.1037/0022-006X.52.6.955 CrossRefGoogle ScholarPubMed
Schaefer, E. S. (1965). A configurational analysis of children’s reports of parent behavior. Journal of Consulting Psychology, 29(6), 552557. https://doi.org/10.1037/h0022702 CrossRefGoogle ScholarPubMed
Schreuder, R., C.A., M., Groothoff, J. W., van der Klink, J. J. L., Magerøy, N., Pallesen, S., Bjorvatn, B., & Moen, B. E. (2012). Coping styles relate to health and work environment of Norwegian and Dutch hospital nurses: A comparative study. Nursing Outlook, 60(1), 3743. https://doi.org/10.1016/j.outlook.2011.05.005 CrossRefGoogle ScholarPubMed
Shaffer, D., Fisher, P., Lucas, C. P., Dulcan, M. K., & Schwab-Stone, M. E. (2000). NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child & Adolescent Psychiatry, 39(1), 2838. https://doi.org/10.1097/00004583-200001000-00014 CrossRefGoogle ScholarPubMed
Slane, J. D., Burt, S. A., Klump, K. L. (2010). The road less traveled: Associations between externalizing behaviors and eating pathology. The International Journal of Eating Disorders, 43(2), 149160. https://doi.org/10.1002/eat.20680 CrossRefGoogle ScholarPubMed
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), 408419. https://doi.org/10.1007/s11121-014-0505-z CrossRefGoogle ScholarPubMed
Smothers, B., Bertolucci, D. (2001). Alcohol consumption and health-promoting behavior in a U.S. Household sample: Leisure-time physical activity. Journal of Studies on Alcohol, 62(4), 467476. https://doi.org/10.15288/jsa.2001.62.467 CrossRefGoogle Scholar
Sobol-Goldberg, S., & Rabinowitz, J. (2016). Association of childhood and teen school performance and obesity in young adulthood in the US National Longitudinal Survey of Youth. Preventive Medicine, 89, 5763. https://doi.org/10.1016/j.ypmed.2016.05.008 CrossRefGoogle ScholarPubMed
Spoth, R., Randall, G., Trudeau, L., Shin, C., & Redmond, C. (2008). Substance use outcomes 51/2 years past baseline for partnership-based, family-school preventive interventions. Drug and Alcohol Dependence, 96(1-2), 5768. https://doi.org/10.1016/j.drugalcdep.2008.01.023 CrossRefGoogle ScholarPubMed
Spoth, R., Redmond, C., Shin, C., Trudeau, L., Greenberg, M. T., Feinberg, M. E., & Welsh, J. (2022). Applying the PROSPER prevention delivery system with middle schools: Emerging adulthood effects on substance misuse and conduct problem behaviors through 14 years past baseline. Child Development, 93(4), 925940. https://doi.org/10.1111/cdev.13746 CrossRefGoogle ScholarPubMed
Spoth, R., Shin, C., Greenberg, C., M., T., Feinberg, M. E., & Trudeau, L. (2017). PROSPER delivery of universal preventive interventions with young adolescents: Long-term effects on emerging adult substance misuse and associated risk behaviors. Psychological Medicine, 47(13), 22462259. https://doi.org/10.1017/S0033291717000691 CrossRefGoogle ScholarPubMed
Spoth, R., Trudeau, L., Redmond, C., & Shin, C. (2016). Replicating and extending a model of effects of universal preventive intervention during early adolescence on young adult substance misuse. Journal of Consulting and Clinical Psychology, 84(10), 913921. https://doi.org/10.1037/ccp0000131 CrossRefGoogle Scholar
Statista. U.S. children living in a single parent family 1970-2020 [Statistics]. 2022. https://www.statista.com/statistics/252847/number-of-children-living-with-a-single-mother-or-single-father/.Google Scholar
Steiner, H., Erickson, S. J., Hernandez, N. L., Pavelski, R. (2002). Coping styles as correlates of health in high school students. Journal of Adolescent Health, 30(5), 326335. https://doi.org/10.1016/S1054-139X(01)00326-3 CrossRefGoogle ScholarPubMed
Stinson, D. A., & Fisher, A. N. (2020). Self esteem and health. In The Wiley Encyclopedia of health psychology (pp. 615621).CrossRefGoogle Scholar
Tan, C. C., & Chow, C. M. (2014). Stress and emotional eating: The mediating role of eating dysregulation. Personality and Individual Differences, 66, 14. https://doi.org/10.1016/j.paid.2014.02.033 CrossRefGoogle Scholar
Taylor, A. B., MacKinnon, D. P., & Tein, J.-Y. (2008). Tests of the three-path mediated effect. Organizational Research Methods, 11(2), 241269. https://doi.org/10.1177/1094428107300344 CrossRefGoogle Scholar
Taylor, M., Collin, S. M., Munafò, M. R., MacLeod, J., Hickman, M., Heron, J. (2017). Patterns of cannabis use during adolescence and their association with harmful substance use behaviour: Findings from a UK birth cohort. Journal of Epidemiology and Community Health, 71(8), 764770. https://doi.org/10.1136/jech-2016-208503 1979.CrossRefGoogle ScholarPubMed
Tein, J.-Y., Mazza, G. L., Gunn, H. J., Kim, H., Stuart, E. A., Sandler, I. N., & Wolchik, S. A. (2018). Multigroup propensity score approach to evaluating an effectiveness trial of the new beginnings program. Evaluation & the Health Professions, 41(2), 290320. https://doi.org/10.1177/0163278718763499 CrossRefGoogle ScholarPubMed
Tein, J.-Y., Sandler, I. N., MacKinnon, D. P., & Wolchik, S. A. (2004). How did it work? Who did it work for? Mediation in the context of a moderated prevention effect for children of divorce. Journal of Consulting and Clinical Psychology, 72(4), 617624. https://doi.org/10.1037/0022-006X.72.4.617 CrossRefGoogle ScholarPubMed
Teleki, J. K., Powell, J. A., & Dodder, R. A. (1982). Factor analysis of reports of parental behavior by children living in divorced and married families. Journal of Psychology, 112(2), 295302. https://doi.org/10.1080/00223980.1982.9915387 CrossRefGoogle ScholarPubMed
Terry-McElrath, Y. M., O’Malley, P. M., Johnston, L. D., Bray, B. C., Patrick, M. E., Schulenberg, J. E. (2017). Longitudinal patterns of marijuana use across ages 18-50 in a US national sample: A descriptive examination of predictors and health correlates of repeated measures latent class membership. Drug and Alcohol Dependence, 171, 7083. https://doi.org/10.1016/j.drugalcdep.2016.11.021 CrossRefGoogle Scholar
Thomas, J., & Högnäs, R. S. (2015). The effect of parental divorce on the health of adult children. Longitudinal and Life Course Studies, 6(3). https://doi.org/10.14301/llcs.v6i3.267 CrossRefGoogle ScholarPubMed
Thompson, L. A., Filipp, S. L., Mack, J. A., Mercado, R. E., Barnes, A., Bright, M., Shenkman, E. A., & Gurka, M. J. (2020). Specific adverse childhood experiences and their association with other adverse childhood experiences, asthma and emotional, developmental and behavioral problems in childhood. Pediatric Research, 88(1), 100109. https://doi.org/10.1038/s41390-020-0784-y CrossRefGoogle ScholarPubMed
Thuen, F., Breivik, K., Wold, B., & Ulveseter, G. (2015). Growing up with one or both parents: The effects on physical health and health-related behavior through adolescence and into early adulthood. Journal of Divorce & Remarriage, 56(6), 451474. https://doi.org/10.1080/10502556.2015.1058659 CrossRefGoogle Scholar
Trzesniewski, K. H., Donnellan, M. B., Moffitt, T. E., Robins, R. W., Poulton, R., Caspi, A. (2006). Low self-esteem during adolescence predicts poor health, criminal behavior, and limited economic prospects during adulthood. Developmental Psychology, 42(2), 381390. https://doi.org/10.1037/0012-1649.42.2.381 CrossRefGoogle ScholarPubMed
US Department of Health and Human Services (2014). The health consequences of smoking—50 years of progress: a report of the Surgeon General, US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health.Google Scholar
van Amsterdam, J., van der Velde, B., Schulte, M., & van den Brink, W. (2018). Causal factors of increased smoking in ADHD: A systematic review. Substance Use & Misuse, 53(3), 432445. https://doi.org/10.1080/10826084.2017.1334066 CrossRefGoogle ScholarPubMed
van de Pavert, I., Sunderland, M., Luijten, M., Slade, T., & Teesson, M. (2017). The general relationship between internalizing psychopathology and chronic physical health conditions: A population-based study. Social Psychiatry and Psychiatric Epidemiology, 52(10), 12571265. https://doi.org/10.1007/s00127-017-1422-9 CrossRefGoogle ScholarPubMed
Van Ryzin, M. J., & Nowicka, P. (2013). Direct and indirect effects of a family-based intervention in early adolescence on parent−youth relationship quality, late adolescent health, and early adult obesity. Journal of Family Psychology, 27(1), 106116. https://doi.org/10.1037/a0031428 CrossRefGoogle ScholarPubMed
Varis, H., Hagnäs, M., Mikkola, I., Nordström, T., Puukka, K., Taanila, A., & Keinänen-Kiukaanniemi, S. (2022). Parental separation and offspring morbidity in adulthood: A descriptive study of the Northern Finland Birth Cohort 1966. Scandinavian Journal of Public Health, 50(5), 601612. https://doi.org/10.1177/14034948211014296 CrossRefGoogle ScholarPubMed
Vélez, C. E., Wolchik, S. A., Tein, J.Y., & Sandler, I. (2011). Protecting children from the consequences of divorce: A longitudinal study of the effects of parenting on children’s coping processes: Parenting and children’s coping processes. Child Development, 82(1), 244257. https://doi.org/10.1111/j.1467-8624.2010.01553.x CrossRefGoogle ScholarPubMed
Ware, J. E., & Sherbourne, C. D. (1992). The MOS 36-ltem short-form health survey (SF-36): I. Conceptual framework and item selection. Medical Care, 30(6), 473483. https://doi.org/10.1097/00005650-199206000-00002 CrossRefGoogle Scholar
Westrick, P. A., Le, H., Robbins, S. B., Radunzel, J. M. R., & Schmidt, F. L. (2015). College performance and retention: A meta-analysis of the predictive validities of ACT ® Scores, High School Grades, and SES. Educational Assessment, 20(1), 2345. https://doi.org/10.1080/10627197.2015.997614 CrossRefGoogle Scholar
White, H. R., Pandina, R. J., & Chen, P.-H. (2002). Developmental trajectories of cigarette use from early adolescence into young adulthood. Drug and Alcohol Dependence, 65(2), 167178. https://doi.org/10.1016/S0376-8716(01)00159-4 CrossRefGoogle ScholarPubMed
Wing, J. K. (1990). SCAN: Schedules fonr clinical assessment in neuropsychiatry. Archives of General Psychiatry, 47(6), 589. https://doi.org/10.1001/archpsyc.1990.01810180089012 CrossRefGoogle Scholar
Wolchik, S., Sandler, I., Weiss, L., & Winslow, E. (2007). New beginnings: An empirically-based program to help divorced mothers promote resilience in their children. In Handbook of parent training: Helping parents prevent and solve problem behaviors (3rd ed. pp. 2562). John Wiley & Sons Inc.Google Scholar
Wolchik, S. A., Sandler, I. N., Millsap, R. E., Plummer, B. A., Greene, S. M., Anderson, E. R., Dawson-McClure, S. R., Hipke, K., & Haine, R. A. (2002). Six-year follow-up of preventive interventions for children of divorce: A randomized controlled trial. JAMA, 288(15), 1874. https://doi.org/10.1001/jama.288.15.1874 CrossRefGoogle ScholarPubMed
Wolchik, S. A., Sandler, I. N., Tein, J.-Y., Mahrer, N. E., Millsap, R. E., Winslow, E., Vélez, C., Porter, M. M., Luecken, L. J., & Reed, A. (2013). Fifteen-year follow-up of a randomized trial of a preventive intervention for divorced families: Effects on mental health and substance use outcomes in young adulthood. Journal of Consulting and Clinical Psychology, 81(4), 660673. https://doi.org/10.1037/a0033235 CrossRefGoogle ScholarPubMed
Wolchik, S. A., Tein, J.-Y., Sandler, I. N., & Kim, H.-J. (2016). Developmental cascade models of a parenting-focused program for divorced families on mental health problems and substance use in emerging adulthood. Development and Psychopathology, 28(3), 869888. https://doi.org/10.1017/S0954579416000365 CrossRefGoogle ScholarPubMed
Wolchik, S. A., Tein, J.-Y., Winslow, E., Minney, J., Sandler, I. N., & Masten, A. S. (2021). Developmental cascade effects of a parenting-focused program for divorced families on competence in emerging adulthood. Development and Psychopathology, 33(1), 201215. https://doi.org/10.1017/S095457941900169X CrossRefGoogle ScholarPubMed
Wolchik, S. A., West, S. G., Sandler, I. N., Tein, J.-Y., Coatsworth, D., Lengua, L., Weiss, L., Anderson, E. R., Greene, S. M., & Griffin, W. A. (2000). An experimental evaluation of theory-based mother and mother-child programs for children of divorce. Journal of Consulting and Clinical Psychology, 68(5), 843856. https://doi.org/10.1037/0022-006X.68.5.843 CrossRefGoogle ScholarPubMed
Wolchik, S. A., West, S. G., Westover, S., Sandler, I. N., Martin, A., Lustig, J., Tein, J.-Y., & Fisher, J. (1993). The children of divorce parenting intervention: Outcome evaluation of an empirically based program. American Journal of Community Psychology, 21(3), 293331. https://doi.org/10.1007/BF00941505 CrossRefGoogle ScholarPubMed
Zhou, Q., Sandler, I. N., Millsap, R. E., Wolchik, S. A., & Dawson-McClure, S. R. (2008). Mother-child relationship quality and effective discipline as mediators of the 6-year effects of the New Beginnings Program for children from divorced families. Journal of Consulting and Clinical Psychology, 76(4), 579594. https://doi.org/10.1037/0022-006X.76.4.579 CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Correlations and descriptive statistics of study variables

Figure 1

Figure 1. Cascade effects of adolescent mental health problems, substance use, and competencies on perception of health problems in emerging adulthood.

Figure 2

Figure 2. Cascade effects of adolescent mental health problems, substance use, and competencies on BMI in emerging adulthood.

Figure 3

Figure 3. Cascade effects of adolescent mental health problems, substance use, and competencies on smoking cigarettes in emerging adulthood.

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